openstack/openstack-manuals
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Merge "Removing the ops-guide from openstack-manuals"

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Jenkins 2017-07-19 10:25:42 +00:00 committed by Gerrit Code Review
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3
doc-tools-check-languages.conf
View File

@ -8,7 +8,7 @@ declare -A BOOKS=(
["de"]="install-guide"
["fr"]="install-guide"
["id"]="image-guide install-guide"
["ja"]="ha-guide image-guide install-guide ops-guide"
["ja"]="ha-guide image-guide install-guide"
["ko_KR"]="install-guide"
["ru"]="install-guide"
["tr_TR"]="image-guide install-guide arch-design"
@ -47,7 +47,6 @@ declare -A SPECIAL_BOOKS=(
["image-guide"]="RST"
["install-guide"]="RST"
["networking-guide"]="RST"
["ops-guide"]="RST"
# Do not translate for now, we need to fix our scripts first to
# generate the content properly.
["install-guide-debconf"]="skip"

2
doc/common/app-support.rst
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@ -50,8 +50,6 @@ The following books explain how to configure and run an OpenStack cloud:
* `Configuration Reference <https://docs.openstack.org/ocata/config-reference/>`_
* `Operations Guide <https://docs.openstack.org/ops-guide/>`_
* `Networking Guide <https://docs.openstack.org/neutron/latest/admin/>`_
* `High Availability Guide <https://docs.openstack.org/ha-guide/>`_

27
doc/ops-guide/setup.cfg
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@ -1,27 +0,0 @@
[metadata]
name = openstackopsguide
summary = OpenStack Operations Guide
author = OpenStack
author-email = openstack-docs@lists.openstack.org
home-page = https://docs.openstack.org/
classifier =
Environment :: OpenStack
Intended Audience :: Information Technology
Intended Audience :: System Administrators
License :: OSI Approved :: Apache Software License
Operating System :: POSIX :: Linux
Topic :: Documentation
[global]
setup-hooks =
pbr.hooks.setup_hook
[files]
[build_sphinx]
warning-is-error = 1
build-dir = build
source-dir = source
[wheel]
universal = 1

30
doc/ops-guide/setup.py
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@ -1,30 +0,0 @@
#!/usr/bin/env python
# Copyright (c) 2013 Hewlett-Packard Development Company, L.P.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# THIS FILE IS MANAGED BY THE GLOBAL REQUIREMENTS REPO - DO NOT EDIT
import setuptools
# In python < 2.7.4, a lazy loading of package `pbr` will break
# setuptools if some other modules registered functions in `atexit`.
# solution from: http://bugs.python.org/issue15881#msg170215
try:
import multiprocessing # noqa
except ImportError:
pass
setuptools.setup(
setup_requires=['pbr'],
pbr=True)

51
doc/ops-guide/source/acknowledgements.rst
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@ -1,51 +0,0 @@
================
Acknowledgements
================
The OpenStack Foundation supported the creation of this book with plane
tickets to Austin, lodging (including one adventurous evening without
power after a windstorm), and delicious food. For about USD $10,000, we
could collaborate intensively for a week in the same room at the
Rackspace Austin office. The authors are all members of the OpenStack
Foundation, which you can join. Go to the `Foundation web
site <https://www.openstack.org/join>`_.
We want to acknowledge our excellent host Rackers at Rackspace in
Austin:
- Emma Richards of Rackspace Guest Relations took excellent care of our
lunch orders and even set aside a pile of sticky notes that had
fallen off the walls.
- Betsy Hagemeier, a Fanatical Executive Assistant, took care of a room
reshuffle and helped us settle in for the week.
- The Real Estate team at Rackspace in Austin, also known as "The
Victors," were super responsive.
- Adam Powell in Racker IT supplied us with bandwidth each day and
second monitors for those of us needing more screens.
- On Wednesday night we had a fun happy hour with the Austin OpenStack
Meetup group and Racker Katie Schmidt took great care of our group.
We also had some excellent input from outside of the room:
- Tim Bell from CERN gave us feedback on the outline before we started
and reviewed it mid-week.
- Sébastien Han has written excellent blogs and generously gave his
permission for re-use.
- Oisin Feeley read it, made some edits, and provided emailed feedback
right when we asked.
Inside the book sprint room with us each day was our book sprint
facilitator Adam Hyde. Without his tireless support and encouragement,
we would have thought a book of this scope was impossible in five days.
Adam has proven the book sprint method effectively again and again. He
creates both tools and faith in collaborative authoring at
`www.booksprints.net <http://www.booksprints.net/>`_.
We couldn't have pulled it off without so much supportive help and
encouragement.

536
doc/ops-guide/source/app-crypt.rst
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@ -1,536 +0,0 @@
=================================
Tales From the Cryp^H^H^H^H Cloud
=================================
Herein lies a selection of tales from OpenStack cloud operators. Read,
and learn from their wisdom.
Double VLAN
~~~~~~~~~~~
I was on-site in Kelowna, British Columbia, Canada setting up a new
OpenStack cloud. The deployment was fully automated: Cobbler deployed
the OS on the bare metal, bootstrapped it, and Puppet took over from
there. I had run the deployment scenario so many times in practice and
took for granted that everything was working.
On my last day in Kelowna, I was in a conference call from my hotel. In
the background, I was fooling around on the new cloud. I launched an
instance and logged in. Everything looked fine. Out of boredom, I ran
:command:`ps aux` and all of the sudden the instance locked up.
Thinking it was just a one-off issue, I terminated the instance and
launched a new one. By then, the conference call ended and I was off to
the data center.
At the data center, I was finishing up some tasks and remembered the
lock-up. I logged into the new instance and ran :command:`ps aux` again.
It worked. Phew. I decided to run it one more time. It locked up.
After reproducing the problem several times, I came to the unfortunate
conclusion that this cloud did indeed have a problem. Even worse, my
time was up in Kelowna and I had to return back to Calgary.
Where do you even begin troubleshooting something like this? An instance
that just randomly locks up when a command is issued. Is it the image?
Nope—it happens on all images. Is it the compute node? Nope—all nodes.
Is the instance locked up? No! New SSH connections work just fine!
We reached out for help. A networking engineer suggested it was an MTU
issue. Great! MTU! Something to go on! What's MTU and why would it cause
a problem?
MTU is maximum transmission unit. It specifies the maximum number of
bytes that the interface accepts for each packet. If two interfaces have
two different MTUs, bytes might get chopped off and weird things
happen—such as random session lockups.
.. note::
Not all packets have a size of 1500. Running the :command:`ls` command over
SSH might only create a single packets less than 1500 bytes.
However, running a command with heavy output, such as :command:`ps aux`
requires several packets of 1500 bytes.
OK, so where is the MTU issue coming from? Why haven't we seen this in
any other deployment? What's new in this situation? Well, new data
center, new uplink, new switches, new model of switches, new servers,
first time using this model of servers… so, basically everything was
new. Wonderful. We toyed around with raising the MTU at various areas:
the switches, the NICs on the compute nodes, the virtual NICs in the
instances, we even had the data center raise the MTU for our uplink
interface. Some changes worked, some didn't. This line of
troubleshooting didn't feel right, though. We shouldn't have to be
changing the MTU in these areas.
As a last resort, our network admin (Alvaro) and myself sat down with
four terminal windows, a pencil, and a piece of paper. In one window, we
ran ping. In the second window, we ran ``tcpdump`` on the cloud
controller. In the third, ``tcpdump`` on the compute node. And the forth
had ``tcpdump`` on the instance. For background, this cloud was a
multi-node, non-multi-host setup.
One cloud controller acted as a gateway to all compute nodes.
VlanManager was used for the network config. This means that the cloud
controller and all compute nodes had a different VLAN for each OpenStack
project. We used the ``-s`` option of ``ping`` to change the packet
size. We watched as sometimes packets would fully return, sometimes they'd
only make it out and never back in, and sometimes the packets would stop at a
random point. We changed ``tcpdump`` to start displaying the hex dump of
the packet. We pinged between every combination of outside, controller,
compute, and instance.
Finally, Alvaro noticed something. When a packet from the outside hits
the cloud controller, it should not be configured with a VLAN. We
verified this as true. When the packet went from the cloud controller to
the compute node, it should only have a VLAN if it was destined for an
instance. This was still true. When the ping reply was sent from the
instance, it should be in a VLAN. True. When it came back to the cloud
controller and on its way out to the Internet, it should no longer have
a VLAN. False. Uh oh. It looked as though the VLAN part of the packet
was not being removed.
That made no sense.
While bouncing this idea around in our heads, I was randomly typing
commands on the compute node:
.. code-block:: console
$ ip a
…
10: vlan100@vlan20: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue master br100 state UP
…
"Hey Alvaro, can you run a VLAN on top of a VLAN?"
"If you did, you'd add an extra 4 bytes to the packet…"
Then it all made sense…
.. code-block:: console
$ grep vlan_interface /etc/nova/nova.conf
vlan_interface=vlan20
In ``nova.conf``, ``vlan_interface`` specifies what interface OpenStack
should attach all VLANs to. The correct setting should have been:
.. code-block:: ini
vlan_interface=bond0
As this would be the server's bonded NIC.
vlan20 is the VLAN that the data center gave us for outgoing Internet
access. It's a correct VLAN and is also attached to bond0.
By mistake, I configured OpenStack to attach all tenant VLANs to vlan20
instead of bond0 thereby stacking one VLAN on top of another. This added
an extra 4 bytes to each packet and caused a packet of 1504 bytes to be
sent out which would cause problems when it arrived at an interface that
only accepted 1500.
As soon as this setting was fixed, everything worked.
"The Issue"
~~~~~~~~~~~
At the end of August 2012, a post-secondary school in Alberta, Canada
migrated its infrastructure to an OpenStack cloud. As luck would have
it, within the first day or two of it running, one of their servers just
disappeared from the network. Blip. Gone.
After restarting the instance, everything was back up and running. We
reviewed the logs and saw that at some point, network communication
stopped and then everything went idle. We chalked this up to a random
occurrence.
A few nights later, it happened again.
We reviewed both sets of logs. The one thing that stood out the most was
DHCP. At the time, OpenStack, by default, set DHCP leases for one minute
(it's now two minutes). This means that every instance contacts the
cloud controller (DHCP server) to renew its fixed IP. For some reason,
this instance could not renew its IP. We correlated the instance's logs
with the logs on the cloud controller and put together a conversation:
#. Instance tries to renew IP.
#. Cloud controller receives the renewal request and sends a response.
#. Instance "ignores" the response and re-sends the renewal request.
#. Cloud controller receives the second request and sends a new
response.
#. Instance begins sending a renewal request to ``255.255.255.255``
since it hasn't heard back from the cloud controller.
#. The cloud controller receives the ``255.255.255.255`` request and
sends a third response.
#. The instance finally gives up.
With this information in hand, we were sure that the problem had to do
with DHCP. We thought that for some reason, the instance wasn't getting
a new IP address and with no IP, it shut itself off from the network.
A quick Google search turned up this: `DHCP lease errors in VLAN
mode <https://lists.launchpad.net/openstack/msg11696.html>`_
which further supported our DHCP theory.
An initial idea was to just increase the lease time. If the instance
only renewed once every week, the chances of this problem happening
would be tremendously smaller than every minute. This didn't solve the
problem, though. It was just covering the problem up.
We decided to have ``tcpdump`` run on this instance and see if we could
catch it in action again. Sure enough, we did.
The ``tcpdump`` looked very, very weird. In short, it looked as though
network communication stopped before the instance tried to renew its IP.
Since there is so much DHCP chatter from a one minute lease, it's very
hard to confirm it, but even with only milliseconds difference between
packets, if one packet arrives first, it arrived first, and if that
packet reported network issues, then it had to have happened before
DHCP.
Additionally, this instance in question was responsible for a very, very
large backup job each night. While "The Issue" (as we were now calling
it) didn't happen exactly when the backup happened, it was close enough
(a few hours) that we couldn't ignore it.
Further days go by and we catch The Issue in action more and more. We
find that dhclient is not running after The Issue happens. Now we're
back to thinking it's a DHCP issue. Running ``/etc/init.d/networking``
restart brings everything back up and running.
Ever have one of those days where all of the sudden you get the Google
results you were looking for? Well, that's what happened here. I was
looking for information on dhclient and why it dies when it can't renew
its lease and all of the sudden I found a bunch of OpenStack and dnsmasq
discussions that were identical to the problem we were seeing!
`Problem with Heavy Network IO and
Dnsmasq <http://www.gossamer-threads.com/lists/openstack/operators/18197>`_.
`instances losing IP address while running, due to No
DHCPOFFER <http://www.gossamer-threads.com/lists/openstack/dev/14696>`_.
Seriously, Google.
This bug report was the key to everything: `KVM images lose connectivity
with bridged
network <https://bugs.launchpad.net/ubuntu/+source/qemu-kvm/+bug/997978>`_.
It was funny to read the report. It was full of people who had some
strange network problem but didn't quite explain it in the same way.
So it was a qemu/kvm bug.
At the same time of finding the bug report, a co-worker was able to
successfully reproduce The Issue! How? He used ``iperf`` to spew a ton
of bandwidth at an instance. Within 30 minutes, the instance just
disappeared from the network.
Armed with a patched qemu and a way to reproduce, we set out to see if
we've finally solved The Issue. After 48 hours straight of hammering the
instance with bandwidth, we were confident. The rest is history. You can
search the bug report for "joe" to find my comments and actual tests.
Disappearing Images
~~~~~~~~~~~~~~~~~~~
At the end of 2012, Cybera (a nonprofit with a mandate to oversee the
development of cyberinfrastructure in Alberta, Canada) deployed an
updated OpenStack cloud for their `DAIR
project <http://www.canarie.ca/cloud/>`_. A few days into
production, a compute node locks up. Upon rebooting the node, I checked
to see what instances were hosted on that node so I could boot them on
behalf of the customer. Luckily, only one instance.
The :command:`nova reboot` command wasn't working, so I used :command:`virsh`,
but it immediately came back with an error saying it was unable to find the
backing disk. In this case, the backing disk is the Glance image that is
copied to ``/var/lib/nova/instances/_base`` when the image is used for
the first time. Why couldn't it find it? I checked the directory and
sure enough it was gone.
I reviewed the ``nova`` database and saw the instance's entry in the
``nova.instances`` table. The image that the instance was using matched
what virsh was reporting, so no inconsistency there.
I checked Glance and noticed that this image was a snapshot that the
user created. At least that was good news—this user would have been the
only user affected.
Finally, I checked StackTach and reviewed the user's events. They had
created and deleted several snapshots—most likely experimenting.
Although the timestamps didn't match up, my conclusion was that they
launched their instance and then deleted the snapshot and it was somehow
removed from ``/var/lib/nova/instances/_base``. None of that made sense,
but it was the best I could come up with.
It turns out the reason that this compute node locked up was a hardware
issue. We removed it from the DAIR cloud and called Dell to have it
serviced. Dell arrived and began working. Somehow or another (or a fat
finger), a different compute node was bumped and rebooted. Great.
When this node fully booted, I ran through the same scenario of seeing
what instances were running so I could turn them back on. There were a
total of four. Three booted and one gave an error. It was the same error
as before: unable to find the backing disk. Seriously, what?
Again, it turns out that the image was a snapshot. The three other
instances that successfully started were standard cloud images. Was it a
problem with snapshots? That didn't make sense.
A note about DAIR's architecture: ``/var/lib/nova/instances`` is a
shared NFS mount. This means that all compute nodes have access to it,
which includes the ``_base`` directory. Another centralized area is
``/var/log/rsyslog`` on the cloud controller. This directory collects
all OpenStack logs from all compute nodes. I wondered if there were any
entries for the file that :command:`virsh` is reporting:
.. code-block:: console
dair-ua-c03/nova.log:Dec 19 12:10:59 dair-ua-c03
2012-12-19 12:10:59 INFO nova.virt.libvirt.imagecache
[-] Removing base file:
/var/lib/nova/instances/_base/7b4783508212f5d242cbf9ff56fb8d33b4ce6166_10
Ah-hah! So OpenStack was deleting it. But why?
A feature was introduced in Essex to periodically check and see if there
were any ``_base`` files not in use. If there were, OpenStack Compute
would delete them. This idea sounds innocent enough and has some good
qualities to it. But how did this feature end up turned on? It was
disabled by default in Essex. As it should be. It was `decided to be
turned on in Folsom <https://bugs.launchpad.net/nova/+bug/1029674>`_.
I cannot emphasize enough that:
*Actions which delete things should not be enabled by default.*
Disk space is cheap these days. Data recovery is not.
Secondly, DAIR's shared ``/var/lib/nova/instances`` directory
contributed to the problem. Since all compute nodes have access to this
directory, all compute nodes periodically review the \_base directory.
If there is only one instance using an image, and the node that the
instance is on is down for a few minutes, it won't be able to mark the
image as still in use. Therefore, the image seems like it's not in use
and is deleted. When the compute node comes back online, the instance
hosted on that node is unable to start.
The Valentine's Day Compute Node Massacre
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Although the title of this story is much more dramatic than the actual
event, I don't think, or hope, that I'll have the opportunity to use
"Valentine's Day Massacre" again in a title.
This past Valentine's Day, I received an alert that a compute node was
no longer available in the cloud—meaning,
.. code-block:: console
$ openstack compute service list
showed this particular node in a down state.
I logged into the cloud controller and was able to both ``ping`` and SSH
into the problematic compute node which seemed very odd. Usually if I
receive this type of alert, the compute node has totally locked up and
would be inaccessible.
After a few minutes of troubleshooting, I saw the following details:
- A user recently tried launching a CentOS instance on that node
- This user was the only user on the node (new node)
- The load shot up to 8 right before I received the alert
- The bonded 10gb network device (bond0) was in a DOWN state
- The 1gb NIC was still alive and active
I looked at the status of both NICs in the bonded pair and saw that
neither was able to communicate with the switch port. Seeing as how each
NIC in the bond is connected to a separate switch, I thought that the
chance of a switch port dying on each switch at the same time was quite
improbable. I concluded that the 10gb dual port NIC had died and needed
replaced. I created a ticket for the hardware support department at the
data center where the node was hosted. I felt lucky that this was a new
node and no one else was hosted on it yet.
An hour later I received the same alert, but for another compute node.
Crap. OK, now there's definitely a problem going on. Just like the
original node, I was able to log in by SSH. The bond0 NIC was DOWN but
the 1gb NIC was active.
And the best part: the same user had just tried creating a CentOS
instance. What?
I was totally confused at this point, so I texted our network admin to
see if he was available to help. He logged in to both switches and
immediately saw the problem: the switches detected spanning tree packets
coming from the two compute nodes and immediately shut the ports down to
prevent spanning tree loops:
.. code-block:: console
Feb 15 01:40:18 SW-1 Stp: %SPANTREE-4-BLOCK_BPDUGUARD: Received BPDU packet on Port-Channel35 with BPDU guard enabled. Disabling interface. (source mac fa:16:3e:24:e7:22)
Feb 15 01:40:18 SW-1 Ebra: %ETH-4-ERRDISABLE: bpduguard error detected on Port-Channel35.
Feb 15 01:40:18 SW-1 Mlag: %MLAG-4-INTF_INACTIVE_LOCAL: Local interface Port-Channel35 is link down. MLAG 35 is inactive.
Feb 15 01:40:18 SW-1 Ebra: %LINEPROTO-5-UPDOWN: Line protocol on Interface Port-Channel35 (Server35), changed state to down
Feb 15 01:40:19 SW-1 Stp: %SPANTREE-6-INTERFACE_DEL: Interface Port-Channel35 has been removed from instance MST0
Feb 15 01:40:19 SW-1 Ebra: %LINEPROTO-5-UPDOWN: Line protocol on Interface Ethernet35 (Server35), changed state to down
He re-enabled the switch ports and the two compute nodes immediately
came back to life.
Unfortunately, this story has an open ending... we're still looking into
why the CentOS image was sending out spanning tree packets. Further,
we're researching a proper way on how to mitigate this from happening.
It's a bigger issue than one might think. While it's extremely important
for switches to prevent spanning tree loops, it's very problematic to
have an entire compute node be cut from the network when this happens.
If a compute node is hosting 100 instances and one of them sends a
spanning tree packet, that instance has effectively DDOS'd the other 99
instances.
This is an ongoing and hot topic in networking circles —especially with
the raise of virtualization and virtual switches.
Down the Rabbit Hole
~~~~~~~~~~~~~~~~~~~~
Users being able to retrieve console logs from running instances is a
boon for support—many times they can figure out what's going on inside
their instance and fix what's going on without bothering you.
Unfortunately, sometimes overzealous logging of failures can cause
problems of its own.
A report came in: VMs were launching slowly, or not at all. Cue the
standard checks—nothing on the Nagios, but there was a spike in network
towards the current master of our RabbitMQ cluster. Investigation
started, but soon the other parts of the queue cluster were leaking
memory like a sieve. Then the alert came in—the master Rabbit server
went down and connections failed over to the slave.
At that time, our control services were hosted by another team and we
didn't have much debugging information to determine what was going on
with the master, and we could not reboot it. That team noted that it
failed without alert, but managed to reboot it. After an hour, the
cluster had returned to its normal state and we went home for the day.
Continuing the diagnosis the next morning was kick started by another
identical failure. We quickly got the message queue running again, and
tried to work out why Rabbit was suffering from so much network traffic.
Enabling debug logging on nova-api quickly brought understanding. A
``tail -f /var/log/nova/nova-api.log`` was scrolling by faster
than we'd ever seen before. CTRL+C on that and we could plainly see the
contents of a system log spewing failures over and over again - a system
log from one of our users' instances.
After finding the instance ID we headed over to
``/var/lib/nova/instances`` to find the ``console.log``:
.. code-block:: console
adm@cc12:/var/lib/nova/instances/instance-00000e05# wc -l console.log
92890453 console.log
adm@cc12:/var/lib/nova/instances/instance-00000e05# ls -sh console.log
5.5G console.log
Sure enough, the user had been periodically refreshing the console log
page on the dashboard and the 5G file was traversing the Rabbit cluster
to get to the dashboard.
We called them and asked them to stop for a while, and they were happy
to abandon the horribly broken VM. After that, we started monitoring the
size of console logs.
To this day, `the issue <https://bugs.launchpad.net/nova/+bug/832507>`__
doesn't have a permanent resolution, but we look forward to the discussion
at the next summit.
Havana Haunted by the Dead
~~~~~~~~~~~~~~~~~~~~~~~~~~
Felix Lee of Academia Sinica Grid Computing Centre in Taiwan contributed
this story.
I just upgraded OpenStack from Grizzly to Havana 2013.2-2 using the RDO
repository and everything was running pretty well—except the EC2 API.
I noticed that the API would suffer from a heavy load and respond slowly
to particular EC2 requests such as ``RunInstances``.
Output from ``/var/log/nova/nova-api.log`` on :term:`Havana`:
.. code-block:: console
2014-01-10 09:11:45.072 129745 INFO nova.ec2.wsgi.server
[req-84d16d16-3808-426b-b7af-3b90a11b83b0
0c6e7dba03c24c6a9bce299747499e8a 7052bd6714e7460caeb16242e68124f9]
117.103.103.29 "GET
/services/Cloud?AWSAccessKeyId=[something]&Action=RunInstances&ClientToken=[something]&ImageId=ami-00000001&InstanceInitiatedShutdownBehavior=terminate...
HTTP/1.1" status: 200 len: 1109 time: 138.5970151
This request took over two minutes to process, but executed quickly on
another co-existing Grizzly deployment using the same hardware and
system configuration.
Output from ``/var/log/nova/nova-api.log`` on :term:`Grizzly`:
.. code-block:: console
2014-01-08 11:15:15.704 INFO nova.ec2.wsgi.server
[req-ccac9790-3357-4aa8-84bd-cdaab1aa394e
ebbd729575cb404081a45c9ada0849b7 8175953c209044358ab5e0ec19d52c37]
117.103.103.29 "GET
/services/Cloud?AWSAccessKeyId=[something]&Action=RunInstances&ClientToken=[something]&ImageId=ami-00000007&InstanceInitiatedShutdownBehavior=terminate...
HTTP/1.1" status: 200 len: 931 time: 3.9426181
While monitoring system resources, I noticed a significant increase in
memory consumption while the EC2 API processed this request. I thought
it wasn't handling memory properly—possibly not releasing memory. If the
API received several of these requests, memory consumption quickly grew
until the system ran out of RAM and began using swap. Each node has 48
GB of RAM and the "nova-api" process would consume all of it within
minutes. Once this happened, the entire system would become unusably
slow until I restarted the nova-api service.
So, I found myself wondering what changed in the EC2 API on Havana that
might cause this to happen. Was it a bug or a normal behavior that I now
need to work around?
After digging into the nova (OpenStack Compute) code, I noticed two
areas in ``api/ec2/cloud.py`` potentially impacting my system:
.. code-block:: python
instances = self.compute_api.get_all(context,
search_opts=search_opts,
sort_dir='asc')
sys_metas = self.compute_api.get_all_system_metadata(
context, search_filts=[{'key': ['EC2_client_token']},
{'value': [client_token]}])
Since my database contained many records—over 1 million metadata records
and over 300,000 instance records in "deleted" or "errored" states—each
search took a long time. I decided to clean up the database by first
archiving a copy for backup and then performing some deletions using the
MySQL client. For example, I ran the following SQL command to remove
rows of instances deleted for over a year:
.. code-block:: console
mysql> delete from nova.instances where deleted=1 and terminated_at < (NOW() - INTERVAL 1 YEAR);
Performance increased greatly after deleting the old records and my new
deployment continues to behave well.

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=========
Resources
=========
OpenStack
~~~~~~~~~
- `OpenStack Installation Tutorial for openSUSE and SUSE Linux Enterprise
Server <https://docs.openstack.org/ocata/install-guide-obs/>`_
- `OpenStack Installation Tutorial for Red Hat Enterprise Linux and CentOS
<https://docs.openstack.org/ocata/install-guide-rdo/>`_
- `OpenStack Installation Tutorial for Ubuntu
Server <https://docs.openstack.org/ocata/install-guide-ubuntu/>`_
- `OpenStack Administrator Guide <https://docs.openstack.org/admin-guide/>`_
- `OpenStack Cloud Computing Cookbook (Packt
Publishing) <http://www.packtpub.com/openstack-cloud-computing-cookbook-second-edition/book>`_
Cloud (General)
~~~~~~~~~~~~~~~
- `The NIST Definition of Cloud
Computing <http://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-145.pdf>`_
Python
~~~~~~
- `Dive Into Python (Apress) <http://www.diveintopython.net/>`_
Networking
~~~~~~~~~~
- `TCP/IP Illustrated, Volume 1: The Protocols, 2/E
(Pearson) <http://www.pearsonhighered.com/educator/product/TCPIP-Illustrated-Volume-1-The-Protocols/9780321336316.page>`_
- `The TCP/IP Guide (No Starch
Press) <http://www.nostarch.com/tcpip.htm>`_
- `A tcpdump Tutorial and
Primer <http://danielmiessler.com/study/tcpdump/>`_
Systems Administration
~~~~~~~~~~~~~~~~~~~~~~
- `UNIX and Linux Systems Administration Handbook (Prentice
Hall) <http://www.admin.com/>`_
Virtualization
~~~~~~~~~~~~~~
- `The Book of Xen (No Starch
Press) <http://www.nostarch.com/xen.htm>`_
Configuration Management
~~~~~~~~~~~~~~~~~~~~~~~~
- `Puppet Labs Documentation <http://docs.puppetlabs.com/>`_
- `Pro Puppet (Apress) <http://www.apress.com/9781430230571>`_

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=====================
Working with Roadmaps
=====================
The good news: OpenStack has unprecedented transparency when it comes to
providing information about what's coming up. The bad news: each release
moves very quickly. The purpose of this appendix is to highlight some of
the useful pages to track, and take an educated guess at what is coming
up in the next release and perhaps further afield.
OpenStack follows a six month release cycle, typically releasing in
April/May and October/November each year. At the start of each cycle,
the community gathers in a single location for a design summit. At the
summit, the features for the coming releases are discussed, prioritized,
and planned. The below figure shows an example release cycle, with dates
showing milestone releases, code freeze, and string freeze dates, along
with an example of when the summit occurs. Milestones are interim releases
within the cycle that are available as packages for download and
testing. Code freeze is putting a stop to adding new features to the
release. String freeze is putting a stop to changing any strings within
the source code.
.. image:: figures/osog_ac01.png
:width: 100%
Information Available to You
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
There are several good sources of information available that you can use
to track your OpenStack development desires.
Release notes are maintained on the OpenStack wiki, and also shown here:
.. list-table::
:widths: 25 25 25 25
:header-rows: 1
* - Series
- Status
- Releases
- Date
* - Liberty
- `Under Development
<https://wiki.openstack.org/wiki/Liberty_Release_Schedule>`_
- 2015.2
- Oct, 2015
* - Kilo
- `Current stable release, security-supported
<https://wiki.openstack.org/wiki/Kilo_Release_Schedule>`_
- `2015.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Kilo>`_
- Apr 30, 2015
* - Juno
- `Security-supported
<https://wiki.openstack.org/wiki/Juno_Release_Schedule>`_
- `2014.2 <https://wiki.openstack.org/wiki/ReleaseNotes/Juno>`_
- Oct 16, 2014
* - Icehouse
- `End-of-life
<https://wiki.openstack.org/wiki/Icehouse_Release_Schedule>`_
- `2014.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Icehouse>`_
- Apr 17, 2014
* -
-
- `2014.1.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2014.1.1>`_
- Jun 9, 2014
* -
-
- `2014.1.2 <https://wiki.openstack.org/wiki/ReleaseNotes/2014.1.2>`_
- Aug 8, 2014
* -
-
- `2014.1.3 <https://wiki.openstack.org/wiki/ReleaseNotes/2014.1.3>`_
- Oct 2, 2014
* - Havana
- End-of-life
- `2013.2 <https://wiki.openstack.org/wiki/ReleaseNotes/Havana>`_
- Apr 4, 2013
* -
-
- `2013.2.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.2.1>`_
- Dec 16, 2013
* -
-
- `2013.2.2 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.2.2>`_
- Feb 13, 2014
* -
-
- `2013.2.3 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.2.3>`_
- Apr 3, 2014
* -
-
- `2013.2.4 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.2.4>`_
- Sep 22, 2014
* -
-
- `2013.2.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.2.1>`_
- Dec 16, 2013
* - Grizzly
- End-of-life
- `2013.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Grizzly>`_
- Apr 4, 2013
* -
-
- `2013.1.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.1.1>`_
- May 9, 2013
* -
-
- `2013.1.2 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.1.2>`_
- Jun 6, 2013
* -
-
- `2013.1.3 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.1.3>`_
- Aug 8, 2013
* -
-
- `2013.1.4 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.1.4>`_
- Oct 17, 2013
* -
-
- `2013.1.5 <https://wiki.openstack.org/wiki/ReleaseNotes/2013.1.5>`_
- Mar 20, 2015
* - Folsom
- End-of-life
- `2012.2 <https://wiki.openstack.org/wiki/ReleaseNotes/Folsom>`_
- Sep 27, 2012
* -
-
- `2012.2.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.2.1>`_
- Nov 29, 2012
* -
-
- `2012.2.2 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.2.2>`_
- Dec 13, 2012
* -
-
- `2012.2.3 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.2.3>`_
- Jan 31, 2013
* -
-
- `2012.2.4 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.2.4>`_
- Apr 11, 2013
* - Essex
- End-of-life
- `2012.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Essex>`_
- Apr 5, 2012
* -
-
- `2012.1.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.1.1>`_
- Jun 22, 2012
* -
-
- `2012.1.2 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.1.2>`_
- Aug 10, 2012
* -
-
- `2012.1.3 <https://wiki.openstack.org/wiki/ReleaseNotes/2012.1.3>`_
- Oct 12, 2012
* - Diablo
- Deprecated
- `2011.3 <https://wiki.openstack.org/wiki/ReleaseNotes/Diablo>`_
- Sep 22, 2011
* -
-
- `2011.3.1 <https://wiki.openstack.org/wiki/ReleaseNotes/2011.3.1>`_
- Jan 19, 2012
* - Cactus
- Deprecated
- `2011.2 <https://wiki.openstack.org/wiki/ReleaseNotes/Cactus>`_
- Apr 15, 2011
* - Bexar
- Deprecated
- `2011.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Bexar>`_
- Feb 3, 2011
* - Austin
- Deprecated
- `2010.1 <https://wiki.openstack.org/wiki/ReleaseNotes/Austin>`_
- Oct 21, 2010
Here are some other resources:
- `A breakdown of current features under development, with their target
milestone <https://status.openstack.org/release/>`_
- `A list of all features, including those not yet under
development <https://blueprints.launchpad.net/openstack>`_
- `Rough-draft design discussions ("etherpads") from the last design
summit <https://wiki.openstack.org/wiki/Summit/Kilo/Etherpads>`_
- `List of individual code changes under
review <https://review.openstack.org/>`_
Influencing the Roadmap
~~~~~~~~~~~~~~~~~~~~~~~
OpenStack truly welcomes your ideas (and contributions) and highly
values feedback from real-world users of the software. By learning a
little about the process that drives feature development, you can
participate and perhaps get the additions you desire.
Feature requests typically start their life in Etherpad, a collaborative
editing tool, which is used to take coordinating notes at a design
summit session specific to the feature. This then leads to the creation
of a blueprint on the Launchpad site for the particular project, which
is used to describe the feature more formally. Blueprints are then
approved by project team members, and development can begin.
Therefore, the fastest way to get your feature request up for
consideration is to create an Etherpad with your ideas and propose a
session to the design summit. If the design summit has already passed,
you may also create a blueprint directly. Read this `blog post about how
to work with blueprints
<http://vmartinezdelacruz.com/how-to-work-with-blueprints-without-losing-your-mind/>`_
the perspective of Victoria Martínez, a developer intern.
The roadmap for the next release as it is developed can be seen at
`Releases <https://releases.openstack.org>`_.
To determine the potential features going in to future releases, or to
look at features implemented previously, take a look at the existing
blueprints such as `OpenStack Compute (nova)
Blueprints <https://blueprints.launchpad.net/nova>`_, `OpenStack
Identity (keystone)
Blueprints <https://blueprints.launchpad.net/keystone>`_, and release
notes.
Aside from the direct-to-blueprint pathway, there is another very
well-regarded mechanism to influence the development roadmap:
the user survey. Found at `OpenStack User Survey
<https://www.openstack.org/user-survey/>`_,
it allows you to provide details of your deployments and needs, anonymously by
default. Each cycle, the user committee analyzes the results and produces a
report, including providing specific information to the technical
committee and project team leads.
Aspects to Watch
~~~~~~~~~~~~~~~~
You want to keep an eye on the areas improving within OpenStack. The
best way to "watch" roadmaps for each project is to look at the
blueprints that are being approved for work on milestone releases. You
can also learn from PTL webinars that follow the OpenStack summits twice
a year.
Driver Quality Improvements
---------------------------
A major quality push has occurred across drivers and plug-ins in Block
Storage, Compute, and Networking. Particularly, developers of Compute
and Networking drivers that require proprietary or hardware products are
now required to provide an automated external testing system for use
during the development process.
Easier Upgrades
---------------
One of the most requested features since OpenStack began (for components
other than Object Storage, which tends to "just work"): easier upgrades.
In all recent releases internal messaging communication is versioned,
meaning services can theoretically drop back to backward-compatible
behavior. This allows you to run later versions of some components,
while keeping older versions of others.
In addition, database migrations are now tested with the Turbo Hipster
tool. This tool tests database migration performance on copies of
real-world user databases.
These changes have facilitated the first proper OpenStack upgrade guide,
found in :doc:`ops-upgrades`, and will continue to improve in the next
release.
Deprecation of Nova Network
---------------------------
With the introduction of the full software-defined networking stack
provided by OpenStack Networking (neutron) in the Folsom release,
development effort on the initial networking code that remains part of
the Compute component has gradually lessened. While many still use
``nova-network`` in production, there has been a long-term plan to
remove the code in favor of the more flexible and full-featured
OpenStack Networking.
An attempt was made to deprecate ``nova-network`` during the Havana
release, which was aborted due to the lack of equivalent functionality
(such as the FlatDHCP multi-host high-availability mode mentioned in
this guide), lack of a migration path between versions, insufficient
testing, and simplicity when used for the more straightforward use cases
``nova-network`` traditionally supported. Though significant effort has
been made to address these concerns, ``nova-network`` was not be
deprecated in the Juno release. In addition, to a limited degree,
patches to ``nova-network`` have again begin to be accepted, such as
adding a per-network settings feature and SR-IOV support in Juno.
This leaves you with an important point of decision when designing your
cloud. OpenStack Networking is robust enough to use with a small number
of limitations (performance issues in some scenarios, only basic high
availability of layer 3 systems) and provides many more features than
``nova-network``. However, if you do not have the more complex use cases
that can benefit from fuller software-defined networking capabilities,
or are uncomfortable with the new concepts introduced, ``nova-network``
may continue to be a viable option for the next 12 months.
Similarly, if you have an existing cloud and are looking to upgrade from
``nova-network`` to OpenStack Networking, you should have the option to
delay the upgrade for this period of time. However, each release of
OpenStack brings significant new innovation, and regardless of your use
of networking methodology, it is likely best to begin planning for an
upgrade within a reasonable timeframe of each release.
As mentioned, there's currently no way to cleanly migrate from
``nova-network`` to neutron. We recommend that you keep a migration in
mind and what that process might involve for when a proper migration
path is released.
Distributed Virtual Router
~~~~~~~~~~~~~~~~~~~~~~~~~~
One of the long-time complaints surrounding OpenStack Networking was the
lack of high availability for the layer 3 components. The Juno release
introduced Distributed Virtual Router (DVR), which aims to solve this
problem.
Early indications are that it does do this well for a base set of
scenarios, such as using the ML2 plug-in with Open vSwitch, one flat
external network and VXLAN tenant networks. However, it does appear that
there are problems with the use of VLANs, IPv6, Floating IPs, high
north-south traffic scenarios and large numbers of compute nodes. It is
expected these will improve significantly with the next release, but bug
reports on specific issues are highly desirable.
Replacement of Open vSwitch Plug-in with Modular Layer 2
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The Modular Layer 2 plug-in is a framework allowing OpenStack Networking
to simultaneously utilize the variety of layer-2 networking technologies
found in complex real-world data centers. It currently works with the
existing Open vSwitch, Linux Bridge, and Hyper-V L2 agents and is
intended to replace and deprecate the monolithic plug-ins associated
with those L2 agents.
New API Versions
~~~~~~~~~~~~~~~~
The third version of the Compute API was broadly discussed and worked on
during the Havana and Icehouse release cycles. Current discussions
indicate that the V2 API will remain for many releases, and the next
iteration of the API will be denoted v2.1 and have similar properties to
the existing v2.0, rather than an entirely new v3 API. This is a great
time to evaluate all API and provide comments while the next generation
APIs are being defined. A new working group was formed specifically to
`improve OpenStack APIs <https://wiki.openstack.org/wiki/API_Working_Group>`_
and create design guidelines, which you are welcome to join.
OpenStack on OpenStack (TripleO)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This project continues to improve and you may consider using it for
greenfield deployments, though according to the latest user survey
results it remains to see widespread uptake.
Data processing service for OpenStack (sahara)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A much-requested answer to big data problems, a dedicated team has been
making solid progress on a Hadoop-as-a-Service project.
Bare metal Deployment (ironic)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The bare-metal deployment has been widely lauded, and development
continues. The Juno release brought the OpenStack Bare metal drive into
the Compute project, and it was aimed to deprecate the existing
bare-metal driver in Kilo. If you are a current user of the bare metal
driver, a particular blueprint to follow is `Deprecate the bare metal
driver
<https://blueprints.launchpad.net/nova/+spec/deprecate-baremetal-driver>`_
Database as a Service (trove)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The OpenStack community has had a database-as-a-service tool in
development for some time, and we saw the first integrated release of it
in Icehouse. From its release it was able to deploy database servers out
of the box in a highly available way, initially supporting only MySQL.
Juno introduced support for Mongo (including clustering), PostgreSQL and
Couchbase, in addition to replication functionality for MySQL. In Kilo,
more advanced clustering capability was delivered, in addition to better
integration with other OpenStack components such as Networking.
Message Service (zaqar)
~~~~~~~~~~~~~~~~~~~~~~~
A service to provide queues of messages and notifications was released.
DNS service (designate)
~~~~~~~~~~~~~~~~~~~~~~~
A long requested service, to provide the ability to manipulate DNS
entries associated with OpenStack resources has gathered a following.
The designate project was also released.
Scheduler Improvements
~~~~~~~~~~~~~~~~~~~~~~
Both Compute and Block Storage rely on schedulers to determine where to
place virtual machines or volumes. In Havana, the Compute scheduler
underwent significant improvement, while in Icehouse it was the
scheduler in Block Storage that received a boost. Further down the
track, an effort started this cycle that aims to create a holistic
scheduler covering both will come to fruition. Some of the work that was
done in Kilo can be found under the `Gantt
project <https://wiki.openstack.org/wiki/Gantt/kilo>`_.
Block Storage Improvements
--------------------------
Block Storage is considered a stable project, with wide uptake and a
long track record of quality drivers. The team has discussed many areas
of work at the summits, including better error reporting, automated
discovery, and thin provisioning features.
Toward a Python SDK
-------------------
Though many successfully use the various python-\*client code as an
effective SDK for interacting with OpenStack, consistency between the
projects and documentation availability waxes and wanes. To combat this,
an `effort to improve the
experience <https://wiki.openstack.org/wiki/PythonOpenStackSDK>`_ has
started. Cross-project development efforts in OpenStack have a checkered
history, such as the `unified client
project <https://wiki.openstack.org/wiki/OpenStackClient>`_ having
several false starts. However, the early signs for the SDK project are
promising, and we expect to see results during the Juno cycle.

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=========
Use Cases
=========
This appendix contains a small selection of use cases from the
community, with more technical detail than usual. Further examples can
be found on the `OpenStack website <https://www.openstack.org/user-stories/>`_.
NeCTAR
~~~~~~
Who uses it: researchers from the Australian publicly funded research
sector. Use is across a wide variety of disciplines, with the purpose of
instances ranging from running simple web servers to using hundreds of
cores for high-throughput computing.
Deployment
----------
Using OpenStack Compute cells, the NeCTAR Research Cloud spans eight
sites with approximately 4,000 cores per site.
Each site runs a different configuration, as a resource cells in an
OpenStack Compute cells setup. Some sites span multiple data centers,
some use off compute node storage with a shared file system, and some
use on compute node storage with a non-shared file system. Each site
deploys the Image service with an Object Storage back end. A central
Identity, dashboard, and Compute API service are used. A login to the
dashboard triggers a SAML login with Shibboleth, which creates an
account in the Identity service with an SQL back end. An Object Storage
Global Cluster is used across several sites.
Compute nodes have 24 to 48 cores, with at least 4 GB of RAM per core
and approximately 40 GB of ephemeral storage per core.
All sites are based on Ubuntu 14.04, with KVM as the hypervisor. The
OpenStack version in use is typically the current stable version, with 5
to 10 percent back-ported code from trunk and modifications.
Resources
---------
- `OpenStack.org case
study <https://www.openstack.org/user-stories/nectar/>`_
- `NeCTAR-RC GitHub <https://github.com/NeCTAR-RC/>`_
- `NeCTAR website <https://www.nectar.org.au/>`_
MIT CSAIL
~~~~~~~~~
Who uses it: researchers from the MIT Computer Science and Artificial
Intelligence Lab.
Deployment
----------
The CSAIL cloud is currently 64 physical nodes with a total of 768
physical cores and 3,456 GB of RAM. Persistent data storage is largely
outside the cloud on NFS, with cloud resources focused on compute
resources. There are more than 130 users in more than 40 projects,
typically running 2,000–2,500 vCPUs in 300 to 400 instances.
We initially deployed on Ubuntu 12.04 with the Essex release of
OpenStack using FlatDHCP multi-host networking.
The software stack is still Ubuntu 12.04 LTS, but now with OpenStack
Havana from the Ubuntu Cloud Archive. KVM is the hypervisor, deployed
using `FAI <http://fai-project.org/>`_ and Puppet for configuration
management. The FAI and Puppet combination is used lab-wide, not only
for OpenStack. There is a single cloud controller node, which also acts
as network controller, with the remainder of the server hardware
dedicated to compute nodes.
Host aggregates and instance-type extra specs are used to provide two
different resource allocation ratios. The default resource allocation
ratios we use are 4:1 CPU and 1.5:1 RAM. Compute-intensive workloads use
instance types that require non-oversubscribed hosts where ``cpu_ratio``
and ``ram_ratio`` are both set to 1.0. Since we have hyper-threading
enabled on our compute nodes, this provides one vCPU per CPU thread, or
two vCPUs per physical core.
With our upgrade to Grizzly in August 2013, we moved to OpenStack
Networking, neutron (quantum at the time). Compute nodes have
two-gigabit network interfaces and a separate management card for IPMI
management. One network interface is used for node-to-node
communications. The other is used as a trunk port for OpenStack managed
VLANs. The controller node uses two bonded 10g network interfaces for
its public IP communications. Big pipes are used here because images are
served over this port, and it is also used to connect to iSCSI storage,
back-ending the image storage and database. The controller node also has
a gigabit interface that is used in trunk mode for OpenStack managed
VLAN traffic. This port handles traffic to the dhcp-agent and
metadata-proxy.
We approximate the older ``nova-network`` multi-host HA setup by using
"provider VLAN networks" that connect instances directly to existing
publicly addressable networks and use existing physical routers as their
default gateway. This means that if our network controller goes down,
running instances still have their network available, and no single
Linux host becomes a traffic bottleneck. We are able to do this because
we have a sufficient supply of IPv4 addresses to cover all of our
instances and thus don't need NAT and don't use floating IP addresses.
We provide a single generic public network to all projects and
additional existing VLANs on a project-by-project basis as needed.
Individual projects are also allowed to create their own private GRE
based networks.
Resources
---------
- `CSAIL homepage <http://www.csail.mit.edu/>`_
DAIR
~~~~
Who uses it: DAIR is an integrated virtual environment that leverages
the CANARIE network to develop and test new information communication
technology (ICT) and other digital technologies. It combines such
digital infrastructure as advanced networking and cloud computing and
storage to create an environment for developing and testing innovative
ICT applications, protocols, and services; performing at-scale
experimentation for deployment; and facilitating a faster time to
market.
Deployment
----------
DAIR is hosted at two different data centers across Canada: one in
Alberta and the other in Quebec. It consists of a cloud controller at
each location, although, one is designated the "master" controller that
is in charge of central authentication and quotas. This is done through
custom scripts and light modifications to OpenStack. DAIR is currently
running Havana.
For Object Storage, each region has a swift environment.
A NetApp appliance is used in each region for both block storage and
instance storage. There are future plans to move the instances off the
NetApp appliance and onto a distributed file system such as :term:`Ceph` or
GlusterFS.
VlanManager is used extensively for network management. All servers have
two bonded 10GbE NICs that are connected to two redundant switches. DAIR
is set up to use single-node networking where the cloud controller is
the gateway for all instances on all compute nodes. Internal OpenStack
traffic (for example, storage traffic) does not go through the cloud
controller.
Resources
---------
- `DAIR homepage <http://www.canarie.ca/cloud/>`__
CERN
~~~~
Who uses it: researchers at CERN (European Organization for Nuclear
Research) conducting high-energy physics research.
Deployment
----------
The environment is largely based on Scientific Linux 6, which is Red Hat
compatible. We use KVM as our primary hypervisor, although tests are
ongoing with Hyper-V on Windows Server 2008.
We use the Puppet Labs OpenStack modules to configure Compute, Image
service, Identity, and dashboard. Puppet is used widely for instance
configuration, and Foreman is used as a GUI for reporting and instance
provisioning.
Users and groups are managed through Active Directory and imported into
the Identity service using LDAP. CLIs are available for nova and
Euca2ools to do this.
There are three clouds currently running at CERN, totaling about 4,700
compute nodes, with approximately 120,000 cores. The CERN IT cloud aims
to expand to 300,000 cores by 2015.
Resources
---------
- `OpenStack in Production: A tale of 3 OpenStack
Clouds <http://openstack-in-production.blogspot.de/2013/09/a-tale-of-3-openstack-clouds-50000.html>`_
- `Review of CERN Data Centre
Infrastructure <http://cds.cern.ch/record/1457989/files/chep%202012%20CERN%20infrastructure%20final.pdf?version=1>`_
- `CERN Cloud Infrastructure User
Guide <http://information-technology.web.cern.ch/book/cern-private-cloud-user-guide>`_

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Appendix
~~~~~~~~
.. toctree::
:maxdepth: 1
app-usecases.rst
app-crypt.rst
app-roadmaps.rst
app-resources.rst
common/app-support.rst
common/glossary.rst

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../../common

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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import os
# import sys
import openstackdocstheme
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
# sys.path.insert(0, os.path.abspath('.'))
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
# needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['openstackdocstheme']
# Add any paths that contain templates here, relative to this directory.
# templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
# source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
repository_name = "openstack/openstack-manuals"
bug_project = 'openstack-manuals'
project = u'Operations Guide'
bug_tag = u'ops-guide'
copyright = u'2016-2017, OpenStack contributors'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = '15.0'
# The full version, including alpha/beta/rc tags.
release = '15.0.0'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
# language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
# today = ''
# Else, today_fmt is used as the format for a strftime call.
# today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['common/cli*', 'common/nova*',
'common/appendix.rst',
'common/get-started*', 'common/dashboard*']
# The reST default role (used for this markup: `text`) to use for all
# documents.
# default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
# add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
# add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
# show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
# modindex_common_prefix = []
# If true, keep warnings as "system message" paragraphs in the built documents.
# keep_warnings = False
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = 'openstackdocs'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
# html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
# html_theme_path = [openstackdocstheme.get_html_theme_path()]
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
# html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
# html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
# html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
# html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
# html_static_path = []
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
# html_extra_path = []
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
# So that we can enable "log-a-bug" links from each output HTML page, this
# variable must be set to a format that includes year, month, day, hours and
# minutes.
html_last_updated_fmt = '%Y-%m-%d %H:%M'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
# html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
# html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
# html_additional_pages = {}
# If false, no module index is generated.
# html_domain_indices = True
# If false, no index is generated.
html_use_index = False
# If true, the index is split into individual pages for each letter.
# html_split_index = False
# If true, links to the reST sources are added to the pages.
html_show_sourcelink = False
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
# html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
# html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
# html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
# html_file_suffix = None
# Output file base name for HTML help builder.
htmlhelp_basename = 'ops-guide'
# If true, publish source files
html_copy_source = False
# -- Options for LaTeX output ---------------------------------------------
pdf_theme_path = openstackdocstheme.get_pdf_theme_path()
openstack_logo = openstackdocstheme.get_openstack_logo_path()
latex_custom_template = r"""
\newcommand{\openstacklogo}{%s}
\usepackage{%s}
""" % (openstack_logo, pdf_theme_path)
latex_engine = 'xelatex'
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
'papersize': 'a4paper',
# The font size ('10pt', '11pt' or '12pt').
'pointsize': '11pt',
#Default figure align
'figure_align': 'H',
# Not to generate blank page after chapter
'classoptions': ',openany',
# Additional stuff for the LaTeX preamble.
'preamble': latex_custom_template,
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
('index', 'OpsGuide.tex', u'Operations Guide',
u'OpenStack contributors', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
# latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
# latex_use_parts = False
# If true, show page references after internal links.
# latex_show_pagerefs = False
# If true, show URL addresses after external links.
# latex_show_urls = False
# Documents to append as an appendix to all manuals.
# latex_appendices = []
# If false, no module index is generated.
# latex_domain_indices = True
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('index', 'opsguide', u'Operations Guide',
[u'OpenStack contributors'], 1)
]
# If true, show URL addresses after external links.
# man_show_urls = False
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'OpsGuide', u'Operations Guide',
u'OpenStack contributors', 'OpsGuide',
'This book provides information about designing and operating '
'OpenStack clouds.', 'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
# texinfo_appendices = []
# If false, no module index is generated.
# texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
# texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node's menu.
# texinfo_no_detailmenu = False
# -- Options for Internationalization output ------------------------------
locale_dirs = ['locale/']

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==========================
OpenStack Operations Guide
==========================
Abstract
~~~~~~~~
This guide provides information about operating OpenStack clouds.
We recommend that you turn to the `Installation Tutorials and Guides
<https://docs.openstack.org/project-install-guide/ocata/>`_,
which contains a step-by-step guide on how to manually install the
OpenStack packages and dependencies on your cloud.
While it is important for an operator to be familiar with the steps
involved in deploying OpenStack, we also strongly encourage you to
evaluate `OpenStack deployment tools
<https://docs.openstack.org/developer/openstack-projects.html>`_
and configuration-management tools, such as :term:`Puppet` or
:term:`Chef`, which can help automate this deployment process.
In this guide, we assume that you have successfully deployed an
OpenStack cloud and are able to perform basic operations
such as adding images, booting instances, and attaching volumes.
As your focus turns to stable operations, we recommend that you do skim
this guide to get a sense of the content. Some of this content is useful
to read in advance so that you can put best practices into effect to
simplify your life in the long run. Other content is more useful as a
reference that you might turn to when an unexpected event occurs (such
as a power failure), or to troubleshoot a particular problem.
Contents
~~~~~~~~
.. toctree::
:maxdepth: 2
acknowledgements.rst
preface.rst
common/conventions.rst
ops-deployment-factors.rst
ops-planning.rst
ops-capacity-planning-scaling.rst
ops-lay-of-the-land.rst
ops-projects-users.rst
ops-user-facing-operations.rst
ops-maintenance.rst
ops-network-troubleshooting.rst
ops-logging-monitoring.rst
ops-backup-recovery.rst
ops-customize.rst
ops-advanced-configuration.rst
ops-upgrades.rst
appendix.rst

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======================
Advanced Configuration
======================
OpenStack is intended to work well across a variety of installation
flavors, from very small private clouds to large public clouds. To
achieve this, the developers add configuration options to their code
that allow the behavior of the various components to be tweaked
depending on your needs. Unfortunately, it is not possible to cover all
possible deployments with the default configuration values.
At the time of writing, OpenStack has more than 3,000 configuration
options. You can see them documented at the
`OpenStack Configuration Reference
<https://docs.openstack.org/ocata/config-reference/config-overview.html>`_.
This chapter cannot hope to document all of these, but we do try to
introduce the important concepts so that you know where to go digging
for more information.
Differences Between Various Drivers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Many OpenStack projects implement a driver layer, and each of these
drivers will implement its own configuration options. For example, in
OpenStack Compute (nova), there are various hypervisor drivers
implemented—libvirt, xenserver, hyper-v, and vmware, for example. Not
all of these hypervisor drivers have the same features, and each has
different tuning requirements.
.. note::
The currently implemented hypervisors are listed on the `OpenStack
Configuration Reference
<https://docs.openstack.org/ocata/config-reference/compute/hypervisors.html>`__.
You can see a matrix of the various features in OpenStack Compute
(nova) hypervisor drivers at the `Hypervisor support matrix
page <https://docs.openstack.org/developer/nova/support-matrix.html>`_.
The point we are trying to make here is that just because an option
exists doesn't mean that option is relevant to your driver choices.
Normally, the documentation notes which drivers the configuration
applies to.
Implementing Periodic Tasks
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Another common concept across various OpenStack projects is that of
periodic tasks. Periodic tasks are much like cron jobs on traditional
Unix systems, but they are run inside an OpenStack process. For example,
when OpenStack Compute (nova) needs to work out what images it can
remove from its local cache, it runs a periodic task to do this.
Periodic tasks are important to understand because of limitations in the
threading model that OpenStack uses. OpenStack uses cooperative
threading in Python, which means that if something long and complicated
is running, it will block other tasks inside that process from running
unless it voluntarily yields execution to another cooperative thread.
A tangible example of this is the ``nova-compute`` process. In order to
manage the image cache with libvirt, ``nova-compute`` has a periodic
process that scans the contents of the image cache. Part of this scan is
calculating a checksum for each of the images and making sure that
checksum matches what ``nova-compute`` expects it to be. However, images
can be very large, and these checksums can take a long time to generate.
At one point, before it was reported as a bug and fixed,
``nova-compute`` would block on this task and stop responding to RPC
requests. This was visible to users as failure of operations such as
spawning or deleting instances.
The take away from this is if you observe an OpenStack process that
appears to "stop" for a while and then continue to process normally, you
should check that periodic tasks aren't the problem. One way to do this
is to disable the periodic tasks by setting their interval to zero.
Additionally, you can configure how often these periodic tasks run—in
some cases, it might make sense to run them at a different frequency
from the default.
The frequency is defined separately for each periodic task. Therefore,
to disable every periodic task in OpenStack Compute (nova), you would
need to set a number of configuration options to zero. The current list
of configuration options you would need to set to zero are:
* ``bandwidth_poll_interval``
* ``sync_power_state_interval``
* ``heal_instance_info_cache_interval``
* ``host_state_interval``
* ``image_cache_manager_interval``
* ``reclaim_instance_interval``
* ``volume_usage_poll_interval``
* ``shelved_poll_interval``
* ``shelved_offload_time``
* ``instance_delete_interval``
To set a configuration option to zero, include a line such as
``image_cache_manager_interval=0`` in your ``nova.conf`` file.
This list will change between releases, so please refer to your
configuration guide for up-to-date information.
Specific Configuration Topics
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This section covers specific examples of configuration options you might
consider tuning. It is by no means an exhaustive list.
Security Configuration for Compute, Networking, and Storage
-----------------------------------------------------------
The `OpenStack Security Guide <https://docs.openstack.org/security-guide/>`_
provides a deep dive into securing an OpenStack cloud, including
SSL/TLS, key management, PKI and certificate management, data transport
and privacy concerns, and compliance.
High Availability
-----------------
The `OpenStack High Availability
Guide <https://docs.openstack.org/ha-guide/index.html>`_ offers
suggestions for elimination of a single point of failure that could
cause system downtime. While it is not a completely prescriptive
document, it offers methods and techniques for avoiding downtime and
data loss.
Enabling IPv6 Support
---------------------
You can follow the progress being made on IPV6 support by watching the
`neutron IPv6 Subteam at
work <https://wiki.openstack.org/wiki/Meetings/Neutron-IPv6-Subteam>`_.
By modifying your configuration setup, you can set up IPv6 when using
``nova-network`` for networking, and a tested setup is documented for
FlatDHCP and a multi-host configuration. The key is to make
``nova-network`` think a ``radvd`` command ran successfully. The entire
configuration is detailed in a Cybera blog post, `“An IPv6 enabled
cloud” <http://www.cybera.ca/news-and-events/tech-radar/an-ipv6-enabled-cloud/>`_.
Geographical Considerations for Object Storage
----------------------------------------------
Support for global clustering of object storage servers is available for
all supported releases. You would implement these global clusters to
ensure replication across geographic areas in case of a natural disaster
and also to ensure that users can write or access their objects more
quickly based on the closest data center. You configure a default region
with one zone for each cluster, but be sure your network (WAN) can
handle the additional request and response load between zones as you add
more zones and build a ring that handles more zones. Refer to
`Geographically Distributed Clusters
<https://docs.openstack.org/developer/swift/admin_guide.html#geographically-distributed-clusters>`_
in the documentation for additional information.

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===================
Backup and Recovery
===================
Standard backup best practices apply when creating your OpenStack backup
policy. For example, how often to back up your data is closely related
to how quickly you need to recover from data loss.
.. note::
If you cannot have any data loss at all, you should also focus on a
highly available deployment. The `OpenStack High Availability
Guide <https://docs.openstack.org/ha-guide/index.html>`_ offers
suggestions for elimination of a single point of failure that could
cause system downtime. While it is not a completely prescriptive
document, it offers methods and techniques for avoiding downtime and
data loss.
Other backup considerations include:
* How many backups to keep?
* Should backups be kept off-site?
* How often should backups be tested?
Just as important as a backup policy is a recovery policy (or at least
recovery testing).
What to Back Up
~~~~~~~~~~~~~~~
While OpenStack is composed of many components and moving parts, backing
up the critical data is quite simple.
This chapter describes only how to back up configuration files and
databases that the various OpenStack components need to run. This
chapter does not describe how to back up objects inside Object Storage
or data contained inside Block Storage. Generally these areas are left
for users to back up on their own.
Database Backups
~~~~~~~~~~~~~~~~
The example OpenStack architecture designates the cloud controller as
the MySQL server. This MySQL server hosts the databases for nova,
glance, cinder, and keystone. With all of these databases in one place,
it's very easy to create a database backup:
.. code-block:: console
# mysqldump --opt --all-databases > openstack.sql
If you only want to backup a single database, you can instead run:
.. code-block:: console
# mysqldump --opt nova > nova.sql
where ``nova`` is the database you want to back up.
You can easily automate this process by creating a cron job that runs
the following script once per day:
.. code-block:: bash
#!/bin/bash
backup_dir="/var/lib/backups/mysql"
filename="${backup_dir}/mysql-`hostname`-`eval date +%Y%m%d`.sql.gz"
# Dump the entire MySQL database
/usr/bin/mysqldump --opt --all-databases | gzip > $filename
# Delete backups older than 7 days
find $backup_dir -ctime +7 -type f -delete
This script dumps the entire MySQL database and deletes any backups
older than seven days.
File System Backups
~~~~~~~~~~~~~~~~~~~
This section discusses which files and directories should be backed up
regularly, organized by service.
Compute
-------
The ``/etc/nova`` directory on both the cloud controller and compute
nodes should be regularly backed up.
``/var/log/nova`` does not need to be backed up if you have all logs
going to a central area. It is highly recommended to use a central
logging server or back up the log directory.
``/var/lib/nova`` is another important directory to back up. The
exception to this is the ``/var/lib/nova/instances`` subdirectory on
compute nodes. This subdirectory contains the KVM images of running
instances. You would want to back up this directory only if you need to
maintain backup copies of all instances. Under most circumstances, you
do not need to do this, but this can vary from cloud to cloud and your
service levels. Also be aware that making a backup of a live KVM
instance can cause that instance to not boot properly if it is ever
restored from a backup.
Image Catalog and Delivery
--------------------------
``/etc/glance`` and ``/var/log/glance`` follow the same rules as their
nova counterparts.
``/var/lib/glance`` should also be backed up. Take special notice of
``/var/lib/glance/images``. If you are using a file-based back end of
glance, ``/var/lib/glance/images`` is where the images are stored and
care should be taken.
There are two ways to ensure stability with this directory. The first is
to make sure this directory is run on a RAID array. If a disk fails, the
directory is available. The second way is to use a tool such as rsync to
replicate the images to another server:
.. code-block:: console
# rsync -az --progress /var/lib/glance/images backup-server:/var/lib/glance/images/
Identity
--------
``/etc/keystone`` and ``/var/log/keystone`` follow the same rules as
other components.
``/var/lib/keystone``, although it should not contain any data being
used, can also be backed up just in case.
Block Storage
-------------
``/etc/cinder`` and ``/var/log/cinder`` follow the same rules as other
components.
``/var/lib/cinder`` should also be backed up.
Networking
----------
``/etc/neutron`` and ``/var/log/neutron`` follow the same rules as other
components.
``/var/lib/neutron`` should also be backed up.
Object Storage
--------------
``/etc/swift`` is very important to have backed up. This directory
contains the swift configuration files as well as the ring files and
ring :term:`builder files <builder file>`, which if lost, render the data
on your cluster inaccessible. A best practice is to copy the builder files
to all storage nodes along with the ring files. Multiple backup copies are
spread throughout your storage cluster.
Telemetry
---------
Back up the ``/etc/ceilometer`` directory containing Telemetry configuration
files.
Orchestration
-------------
Back up HOT template ``yaml`` files, and the ``/etc/heat/`` directory
containing Orchestration configuration files.
Recovering Backups
~~~~~~~~~~~~~~~~~~
Recovering backups is a fairly simple process. To begin, first ensure
that the service you are recovering is not running. For example, to do a
full recovery of ``nova`` on the cloud controller, first stop all
``nova`` services:
.. code-block:: console
# stop nova-api
# stop nova-consoleauth
# stop nova-novncproxy
# stop nova-objectstore
# stop nova-scheduler
Now you can import a previously backed-up database:
.. code-block:: console
# mysql nova < nova.sql
You can also restore backed-up nova directories:
.. code-block:: console
# mv /etc/nova{,.orig}
# cp -a /path/to/backup/nova /etc/
Once the files are restored, start everything back up:
.. code-block:: console
# start mysql
# for i in nova-api nova-consoleauth nova-novncproxy \
nova-objectstore nova-scheduler
> do
> start $i
> done
Other services follow the same process, with their respective
directories and databases.
Summary
~~~~~~~
Backup and subsequent recovery is one of the first tasks system
administrators learn. However, each system has different items that need
attention. By taking care of your database, image service, and
appropriate file system locations, you can be assured that you can
handle any event requiring recovery.

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.. _capacity-planning-scaling:
=============================
Capacity planning and scaling
=============================
Cloud-based applications typically request more discrete hardware (horizontal
scaling) as opposed to traditional applications, which require larger hardware
to scale (vertical scaling).
OpenStack is designed to be horizontally scalable. Rather than switching
to larger servers, you procure more servers and simply install identically
configured services. Ideally, you scale out and load balance among groups of
functionally identical services (for example, compute nodes or ``nova-api``
nodes), that communicate on a message bus.
Determining cloud scalability
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Determining the scalability of your cloud and how to improve it requires
balancing many variables. No one solution meets everyone's scalability goals.
However, it is helpful to track a number of metrics. You can define
virtual hardware templates called "flavors" in OpenStack, which will impact
your cloud scaling decisions. These templates define sizes for memory in RAM,
root disk size, amount of ephemeral data disk space available, and the number
of CPU cores.
The default OpenStack flavors are shown in :ref:`table_default_flavors`.
.. _table_default_flavors:
.. list-table:: Table. OpenStack default flavors
:widths: 20 20 20 20 20
:header-rows: 1
* - Name
- Virtual cores
- Memory
- Disk
- Ephemeral
* - m1.tiny
- 1
- 512 MB
- 1 GB
- 0 GB
* - m1.small
- 1
- 2 GB
- 10 GB
- 20 GB
* - m1.medium
- 2
- 4 GB
- 10 GB
- 40 GB
* - m1.large
- 4
- 8 GB
- 10 GB
- 80 GB
* - m1.xlarge
- 8
- 16 GB
- 10 GB
- 160 GB
The starting point is the core count of your cloud. By applying
some ratios, you can gather information about:
- The number of virtual machines (VMs) you expect to run,
``((overcommit fraction × cores) / virtual cores per instance)``
- How much storage is required ``(flavor disk size × number of instances)``
You can use these ratios to determine how much additional infrastructure
you need to support your cloud.
Here is an example using the ratios for gathering scalability
information for the number of VMs expected as well as the storage
needed. The following numbers support (200 / 2) × 16 = 1600 VM instances
and require 80 TB of storage for ``/var/lib/nova/instances``:
- 200 physical cores.
- Most instances are size m1.medium (two virtual cores, 50 GB of
storage).
- Default CPU overcommit ratio (``cpu_allocation_ratio`` in the ``nova.conf``
file) of 16:1.
.. note::
Regardless of the overcommit ratio, an instance can not be placed
on any physical node with fewer raw (pre-overcommit) resources than
instance flavor requires.
However, you need more than the core count alone to estimate the load
that the API services, database servers, and queue servers are likely to
encounter. You must also consider the usage patterns of your cloud.
As a specific example, compare a cloud that supports a managed
web-hosting platform with one running integration tests for a
development project that creates one VM per code commit. In the former,
the heavy work of creating a VM happens only every few months, whereas
the latter puts constant heavy load on the cloud controller. You must
consider your average VM lifetime, as a larger number generally means
less load on the cloud controller.
Aside from the creation and termination of VMs, you must consider the
impact of users accessing the service particularly on ``nova-api`` and
its associated database. Listing instances garners a great deal of
information and, given the frequency with which users run this
operation, a cloud with a large number of users can increase the load
significantly. This can occur even without their knowledge. For example,
leaving the OpenStack dashboard instances tab open in the browser
refreshes the list of VMs every 30 seconds.
After you consider these factors, you can determine how many cloud
controller cores you require. A typical eight core, 8 GB of RAM server
is sufficient for up to a rack of compute nodes — given the above
caveats.
You must also consider key hardware specifications for the performance
of user VMs, as well as budget and performance needs, including storage
performance (spindles/core), memory availability (RAM/core), network
bandwidth hardware specifications and (Gbps/core), and overall
CPU performance (CPU/core).
.. tip::
For a discussion of metric tracking, including how to extract
metrics from your cloud, see the `OpenStack Operations Guide
<https://docs.openstack.org/ops-guide/ops-logging-monitoring.html>`_.
Adding cloud controller nodes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can facilitate the horizontal expansion of your cloud by adding
nodes. Adding compute nodes is straightforward since they are easily picked up
by the existing installation. However, you must consider some important
points when you design your cluster to be highly available.
A cloud controller node runs several different services. You
can install services that communicate only using the message queue
internally— ``nova-scheduler`` and ``nova-console`` on a new server for
expansion. However, other integral parts require more care.
You should load balance user-facing services such as dashboard,
``nova-api``, or the Object Storage proxy. Use any standard HTTP
load-balancing method (DNS round robin, hardware load balancer, or
software such as Pound or HAProxy). One caveat with dashboard is the VNC
proxy, which uses the WebSocket protocol— something that an L7 load
balancer might struggle with. See also `Horizon session storage
<https://docs.openstack.org/developer/horizon/topics/deployment.html#session-storage>`_.
You can configure some services, such as ``nova-api`` and
``glance-api``, to use multiple processes by changing a flag in their
configuration file allowing them to share work between multiple cores on
the one machine.
.. tip::
Several options are available for MySQL load balancing, and the
supported AMQP brokers have built-in clustering support. Information
on how to configure these and many of the other services can be
found in the `Operations Guide
<https://docs.openstack.org/ops-guide/operations.html>`_.
Segregating your cloud
~~~~~~~~~~~~~~~~~~~~~~
Segregating your cloud is needed when users require different regions for legal
considerations for data storage, redundancy across earthquake fault lines, or
for low-latency API calls. It can be segregated by *cells*, *regions*,
*availability zones*, or *host aggregates*.
Each method provides different functionality and can be best divided
into two groups:
- Cells and regions, which segregate an entire cloud and result in
running separate Compute deployments.
- :term:`Availability zones <availability zone>` and host aggregates,
which merely divide a single Compute deployment.
:ref:`table_segregation_methods` provides a comparison view of each
segregation method currently provided by OpenStack Compute.
.. _table_segregation_methods:
.. list-table:: Table. OpenStack segregation methods
:widths: 20 20 20 20 20
:header-rows: 1
* -
- Cells
- Regions
- Availability zones
- Host aggregates
* - **Use**
- A single :term:`API endpoint` for compute, or you require a second
level of scheduling.
- Discrete regions with separate API endpoints and no coordination
between regions.
- Logical separation within your nova deployment for physical isolation
or redundancy.
- To schedule a group of hosts with common features.
* - **Example**
- A cloud with multiple sites where you can schedule VMs "anywhere" or on
a particular site.
- A cloud with multiple sites, where you schedule VMs to a particular
site and you want a shared infrastructure.
- A single-site cloud with equipment fed by separate power supplies.
- Scheduling to hosts with trusted hardware support.
* - **Overhead**
- Considered experimental. A new service, nova-cells. Each cell has a full
nova installation except nova-api.
- A different API endpoint for every region. Each region has a full nova
installation.
- Configuration changes to ``nova.conf``.
- Configuration changes to ``nova.conf``.
* - **Shared services**
- Keystone, ``nova-api``
- Keystone
- Keystone, All nova services
- Keystone, All nova services
Cells and regions
-----------------
OpenStack Compute cells are designed to allow running the cloud in a
distributed fashion without having to use more complicated technologies,
or be invasive to existing nova installations. Hosts in a cloud are
partitioned into groups called *cells*. Cells are configured in a tree.
The top-level cell ("API cell") has a host that runs the ``nova-api``
service, but no ``nova-compute`` services. Each child cell runs all of
the other typical ``nova-*`` services found in a regular installation,
except for the ``nova-api`` service. Each cell has its own message queue
and database service and also runs ``nova-cells``, which manages the
communication between the API cell and child cells.
This allows for a single API server being used to control access to
multiple cloud installations. Introducing a second level of scheduling
(the cell selection), in addition to the regular ``nova-scheduler``
selection of hosts, provides greater flexibility to control where
virtual machines are run.
Unlike having a single API endpoint, regions have a separate API
endpoint per installation, allowing for a more discrete separation.
Users wanting to run instances across sites have to explicitly select a
region. However, the additional complexity of a running a new service is
not required.
The OpenStack dashboard (horizon) can be configured to use multiple
regions. This can be configured through the ``AVAILABLE_REGIONS``
parameter.
Availability zones and host aggregates
--------------------------------------
You can use availability zones, host aggregates, or both to partition a
nova deployment. Both methods are configured and implemented in a similar
way.
Availability zone
^^^^^^^^^^^^^^^^^
This enables you to arrange OpenStack compute hosts into logical groups
and provides a form of physical isolation and redundancy from other
availability zones, such as by using a separate power supply or network
equipment.
You define the availability zone in which a specified compute host
resides locally on each server. An availability zone is commonly used to
identify a set of servers that have a common attribute. For instance, if
some of the racks in your data center are on a separate power source,
you can put servers in those racks in their own availability zone.
Availability zones can also help separate different classes of hardware.
When users provision resources, they can specify from which availability
zone they want their instance to be built. This allows cloud consumers
to ensure that their application resources are spread across disparate
machines to achieve high availability in the event of hardware failure.
Host aggregates zone
^^^^^^^^^^^^^^^^^^^^
This enables you to partition OpenStack Compute deployments into logical
groups for load balancing and instance distribution. You can use host
aggregates to further partition an availability zone. For example, you
might use host aggregates to partition an availability zone into groups
of hosts that either share common resources, such as storage and
network, or have a special property, such as trusted computing
hardware.
A common use of host aggregates is to provide information for use with
the ``nova-scheduler``. For example, you might use a host aggregate to
group a set of hosts that share specific flavors or images.
The general case for this is setting key-value pairs in the aggregate
metadata and matching key-value pairs in flavor's ``extra_specs``
metadata. The ``AggregateInstanceExtraSpecsFilter`` in the filter
scheduler will enforce that instances be scheduled only on hosts in
aggregates that define the same key to the same value.
An advanced use of this general concept allows different flavor types to
run with different CPU and RAM allocation ratios so that high-intensity
computing loads and low-intensity development and testing systems can
share the same cloud without either starving the high-use systems or
wasting resources on low-utilization systems. This works by setting
``metadata`` in your host aggregates and matching ``extra_specs`` in
your flavor types.
The first step is setting the aggregate metadata keys
``cpu_allocation_ratio`` and ``ram_allocation_ratio`` to a
floating-point value. The filter schedulers ``AggregateCoreFilter`` and
``AggregateRamFilter`` will use those values rather than the global
defaults in ``nova.conf`` when scheduling to hosts in the aggregate. Be
cautious when using this feature, since each host can be in multiple
aggregates, but should have only one allocation ratio for
each resources. It is up to you to avoid putting a host in multiple
aggregates that define different values for the same resource.
This is the first half of the equation. To get flavor types that are
guaranteed a particular ratio, you must set the ``extra_specs`` in the
flavor type to the key-value pair you want to match in the aggregate.
For example, if you define ``extra_specs`` ``cpu_allocation_ratio`` to
"1.0", then instances of that type will run in aggregates only where the
metadata key ``cpu_allocation_ratio`` is also defined as "1.0." In
practice, it is better to define an additional key-value pair in the
aggregate metadata to match on rather than match directly on
``cpu_allocation_ratio`` or ``core_allocation_ratio``. This allows
better abstraction. For example, by defining a key ``overcommit`` and
setting a value of "high," "medium," or "low," you could then tune the
numeric allocation ratios in the aggregates without also needing to
change all flavor types relating to them.
.. note::
Previously, all services had an availability zone. Currently, only
the ``nova-compute`` service has its own availability zone. Services
such as ``nova-scheduler``, ``nova-network``, and ``nova-conductor``
have always spanned all availability zones.
When you run any of the following operations, the services appear in
their own internal availability zone
(CONF.internal_service_availability_zone):
- :command:`openstack host list` (os-hosts)
- :command:`euca-describe-availability-zones verbose`
- :command:`openstack compute service list`
The internal availability zone is hidden in
euca-describe-availability_zones (nonverbose).
CONF.node_availability_zone has been renamed to
CONF.default_availability_zone and is used only by the
``nova-api`` and ``nova-scheduler`` services.
CONF.node_availability_zone still works but is deprecated.
Scalable Hardware
~~~~~~~~~~~~~~~~~
While several resources already exist to help with deploying and
installing OpenStack, it's very important to make sure that you have
your deployment planned out ahead of time. This guide presumes that you
have set aside a rack for the OpenStack cloud but also offers
suggestions for when and what to scale.
Hardware Procurement
--------------------
“The Cloud” has been described as a volatile environment where servers
can be created and terminated at will. While this may be true, it does
not mean that your servers must be volatile. Ensuring that your cloud's
hardware is stable and configured correctly means that your cloud
environment remains up and running.
OpenStack can be deployed on any hardware supported by an
OpenStack compatible Linux distribution.
Hardware does not have to be consistent, but it should at least have the
same type of CPU to support instance migration.
The typical hardware recommended for use with OpenStack is the standard
value-for-money offerings that most hardware vendors stock. It should be
straightforward to divide your procurement into building blocks such as
"compute," "object storage," and "cloud controller," and request as many
of these as you need. Alternatively, any existing servers you have that meet
performance requirements and virtualization technology are likely to support
OpenStack.
Capacity Planning
-----------------
OpenStack is designed to increase in size in a straightforward manner.
Taking into account the considerations previous mentioned, particularly on the
sizing of the cloud controller, it should be possible to procure additional
compute or object storage nodes as needed. New nodes do not need to be the same
specification or vendor as existing nodes.
For compute nodes, ``nova-scheduler`` will manage differences in
sizing with core count and RAM. However, you should consider that the user
experience changes with differing CPU speeds. When adding object storage
nodes, a :term:`weight` should be specified that reflects the
:term:`capability` of the node.
Monitoring the resource usage and user growth will enable you to know
when to procure. The `Logging and Monitoring
<https://docs.openstack.org/ops-guide/ops-logging-monitoring.html>`_
chapte in the Operations Guide details some useful metrics.
Burn-in Testing
---------------
The chances of failure for the server's hardware are high at the start
and the end of its life. As a result, dealing with hardware failures
while in production can be avoided by appropriate burn-in testing to
attempt to trigger the early-stage failures. The general principle is to
stress the hardware to its limits. Examples of burn-in tests include
running a CPU or disk benchmark for several days.

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==================================================
Customizing the OpenStack Compute (nova) Scheduler
==================================================
Many OpenStack projects allow for customization of specific features
using a driver architecture. You can write a driver that conforms to a
particular interface and plug it in through configuration. For example,
you can easily plug in a new scheduler for Compute. The existing
schedulers for Compute are feature full and well documented at `Scheduling
<https://docs.openstack.org/ocata/config-reference/compute/schedulers.html>`_.
However, depending on your user's use cases, the existing schedulers
might not meet your requirements. You might need to create a new scheduler.
To create a scheduler, you must inherit from the class
``nova.scheduler.driver.Scheduler``. Of the five methods that you can
override, you *must* override the two methods marked with an asterisk
(\*) below:
- ``update_service_capabilities``
- ``hosts_up``
- ``group_hosts``
- \* ``schedule_run_instance``
- \* ``select_destinations``
To demonstrate customizing OpenStack, we'll create an example of a
Compute scheduler that randomly places an instance on a subset of hosts,
depending on the originating IP address of the request and the prefix of
the hostname. Such an example could be useful when you have a group of
users on a subnet and you want all of their instances to start within
some subset of your hosts.
.. warning::
This example is for illustrative purposes only. It should not be
used as a scheduler for Compute without further development and
testing.
When you join the screen session that ``stack.sh`` starts with
``screen -r stack``, you are greeted with many screen windows:
.. code-block:: console
0$ shell*  1$ key  2$ horizon  ...  9$ n-api  ...  14$ n-sch ...
``shell``
A shell where you can get some work done
``key``
The keystone service
``horizon``
The horizon dashboard web application
``n-{name}``
The nova services
``n-sch``
The nova scheduler service
**To create the scheduler and plug it in through configuration**
#. The code for OpenStack lives in ``/opt/stack``, so go to the ``nova``
directory and edit your scheduler module. Change to the directory where
``nova`` is installed:
.. code-block:: console
$ cd /opt/stack/nova
#. Create the ``ip_scheduler.py`` Python source code file:
.. code-block:: console
$ vim nova/scheduler/ip_scheduler.py
#. The code shown below is a driver that will
schedule servers to hosts based on IP address as explained at the
beginning of the section. Copy the code into ``ip_scheduler.py``. When
you are done, save and close the file.
.. code-block:: python
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (c) 2014 OpenStack Foundation
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""
IP Scheduler implementation
"""
import random
from oslo_config import cfg
from nova.compute import rpcapi as compute_rpcapi
from nova import exception
from nova.openstack.common import log as logging
from nova.openstack.common.gettextutils import _
from nova.scheduler import driver
CONF = cfg.CONF
CONF.import_opt('compute_topic', 'nova.compute.rpcapi')
LOG = logging.getLogger(__name__)
class IPScheduler(driver.Scheduler):
"""
Implements Scheduler as a random node selector based on
IP address and hostname prefix.
"""
def __init__(self, *args, **kwargs):
super(IPScheduler, self).__init__(*args, **kwargs)
self.compute_rpcapi = compute_rpcapi.ComputeAPI()
def _filter_hosts(self, request_spec, hosts, filter_properties,
hostname_prefix):
"""Filter a list of hosts based on hostname prefix."""
hosts = [host for host in hosts if host.startswith(hostname_prefix)]
return hosts
def _schedule(self, context, topic, request_spec, filter_properties):
"""Picks a host that is up at random."""
elevated = context.elevated()
hosts = self.hosts_up(elevated, topic)
if not hosts:
msg = _("Is the appropriate service running?")
raise exception.NoValidHost(reason=msg)
remote_ip = context.remote_address
if remote_ip.startswith('10.1'):
hostname_prefix = 'doc'
elif remote_ip.startswith('10.2'):
hostname_prefix = 'ops'
else:
hostname_prefix = 'dev'
hosts = self._filter_hosts(request_spec, hosts, filter_properties,
hostname_prefix)
if not hosts:
msg = _("Could not find another compute")
raise exception.NoValidHost(reason=msg)
host = random.choice(hosts)
LOG.debug("Request from %(remote_ip)s scheduled to %(host)s" % locals())
return host
def select_destinations(self, context, request_spec, filter_properties):
"""Selects random destinations."""
num_instances = request_spec['num_instances']
# NOTE(timello): Returns a list of dicts with 'host', 'nodename' and
# 'limits' as keys for compatibility with filter_scheduler.
dests = []
for i in range(num_instances):
host = self._schedule(context, CONF.compute_topic,
request_spec, filter_properties)
host_state = dict(host=host, nodename=None, limits=None)
dests.append(host_state)
if len(dests) < num_instances:
raise exception.NoValidHost(reason='')
return dests
def schedule_run_instance(self, context, request_spec,
admin_password, injected_files,
requested_networks, is_first_time,
filter_properties, legacy_bdm_in_spec):
"""Create and run an instance or instances."""
instance_uuids = request_spec.get('instance_uuids')
for num, instance_uuid in enumerate(instance_uuids):
request_spec['instance_properties']['launch_index'] = num
try:
host = self._schedule(context, CONF.compute_topic,
request_spec, filter_properties)
updated_instance = driver.instance_update_db(context,
instance_uuid)
self.compute_rpcapi.run_instance(context,
instance=updated_instance, host=host,
requested_networks=requested_networks,
injected_files=injected_files,
admin_password=admin_password,
is_first_time=is_first_time,
request_spec=request_spec,
filter_properties=filter_properties,
legacy_bdm_in_spec=legacy_bdm_in_spec)
except Exception as ex:
# NOTE(vish): we don't reraise the exception here to make sure
# that all instances in the request get set to
# error properly
driver.handle_schedule_error(context, ex, instance_uuid,
request_spec)
There is a lot of useful information in ``context``, ``request_spec``,
and ``filter_properties`` that you can use to decide where to schedule
the instance. To find out more about what properties are available, you
can insert the following log statements into the
``schedule_run_instance`` method of the scheduler above:
.. code-block:: python
LOG.debug("context = %(context)s" % {'context': context.__dict__})
LOG.debug("request_spec = %(request_spec)s" % locals())
LOG.debug("filter_properties = %(filter_properties)s" % locals())
#. To plug this scheduler into nova, edit one configuration file,
``/etc/nova/nova.conf``:
.. code-block:: console
$ vim /etc/nova/nova.conf
#. Find the ``scheduler_driver`` config and change it like so:
.. code-block:: ini
scheduler_driver=nova.scheduler.ip_scheduler.IPScheduler
#. Restart the nova scheduler service to make nova use your scheduler.
Start by switching to the ``n-sch`` screen:
#. Press **Ctrl+A** followed by **9**.
#. Press **Ctrl+A** followed by **N** until you reach the ``n-sch`` screen.
#. Press **Ctrl+C** to kill the service.
#. Press **Up Arrow** to bring up the last command.
#. Press **Enter** to run it.
#. Test your scheduler with the nova CLI. Start by switching to the
``shell`` screen and finish by switching back to the ``n-sch`` screen to
check the log output:
#. Press  **Ctrl+A** followed by **0**.
#. Make sure you are in the ``devstack`` directory:
.. code-block:: console
$ cd /root/devstack
#. Source ``openrc`` to set up your environment variables for the CLI:
.. code-block:: console
$ . openrc
#. Put the image ID for the only installed image into an environment
variable:
.. code-block:: console
$ IMAGE_ID=`openstack image list | egrep cirros | egrep -v "kernel|ramdisk" | awk '{print $2}'`
#. Boot a test server:
.. code-block:: console
$ openstack server create --flavor 1 --image $IMAGE_ID scheduler-test
#. Switch back to the ``n-sch`` screen. Among the log statements, you'll
see the line:
.. code-block:: console
2014-01-23 19:57:47.262 DEBUG nova.scheduler.ip_scheduler
[req-... demo demo] Request from xx.xx.xx.xx scheduled to devstack-havana
_schedule /opt/stack/nova/nova/scheduler/ip_scheduler.py:76
.. warning::
Functional testing like this is not a replacement for proper unit
and integration testing, but it serves to get you started.
A similar pattern can be followed in other projects that use the driver
architecture. Simply create a module and class that conform to the
driver interface and plug it in through configuration. Your code runs
when that feature is used and can call out to other services as
necessary. No project core code is touched. Look for a "driver" value in
the project's ``.conf`` configuration files in ``/etc/<project>`` to
identify projects that use a driver architecture.
When your scheduler is done, we encourage you to open source it and let
the community know on the OpenStack mailing list. Perhaps others need
the same functionality. They can use your code, provide feedback, and
possibly contribute. If enough support exists for it, perhaps you can
propose that it be added to the official Compute
`schedulers <https://git.openstack.org/cgit/openstack/nova/tree/nova/scheduler>`_.

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==========
Conclusion
==========
When operating an OpenStack cloud, you may discover that your users can
be quite demanding. If OpenStack doesn't do what your users need, it may
be up to you to fulfill those requirements. This chapter provided you
with some options for customization and gave you the tools you need to
get started.

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===================================
Customizing the Dashboard (Horizon)
===================================
The dashboard is based on the Python
`Django <https://www.djangoproject.com/>`_ web application framework.
To know how to build your Dashboard, see `Building a Dashboard using Horizon
<https://docs.openstack.org/developer/horizon/tutorials/dashboard.html>`_.

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===========================================
Create an OpenStack Development Environment
===========================================
To create a development environment, you can use DevStack. DevStack is
essentially a collection of shell scripts and configuration files that
builds an OpenStack development environment for you. You use it to
create such an environment for developing a new feature.
For more information on installing DevStack, see the
`DevStack <https://docs.openstack.org/developer/devstack/>`_ website.

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=============================================
Customizing Object Storage (Swift) Middleware
=============================================
OpenStack Object Storage, known as swift when reading the code, is based
on the Python `Paste <http://pythonpaste.org/>`_ framework. The best
introduction to its architecture is `A Do-It-Yourself
Framework <http://pythonpaste.org/do-it-yourself-framework.html>`_.
Because of the swift project's use of this framework, you are able to
add features to a project by placing some custom code in a project's
pipeline without having to change any of the core code.
Imagine a scenario where you have public access to one of your
containers, but what you really want is to restrict access to that to a
set of IPs based on a whitelist. In this example, we'll create a piece
of middleware for swift that allows access to a container from only a
set of IP addresses, as determined by the container's metadata items.
Only those IP addresses that you explicitly whitelist using the
container's metadata will be able to access the container.
.. warning::
This example is for illustrative purposes only. It should not be
used as a container IP whitelist solution without further
development and extensive security testing.
When you join the screen session that ``stack.sh`` starts with
``screen -r stack``, you see a screen for each service running, which
can be a few or several, depending on how many services you configured
DevStack to run.
The asterisk * indicates which screen window you are viewing. This
example shows we are viewing the key (for keystone) screen window:
.. code-block:: console
0$ shell 1$ key* 2$ horizon 3$ s-proxy 4$ s-object 5$ s-container 6$ s-account
The purpose of the screen windows are as follows:
``shell``
A shell where you can get some work done
``key*``
The keystone service
``horizon``
The horizon dashboard web application
``s-{name}``
The swift services
**To create the middleware and plug it in through Paste configuration:**
All of the code for OpenStack lives in ``/opt/stack``. Go to the swift
directory in the ``shell`` screen and edit your middleware module.
#. Change to the directory where Object Storage is installed:
.. code-block:: console
$ cd /opt/stack/swift
#. Create the ``ip_whitelist.py`` Python source code file:
.. code-block:: console
$ vim swift/common/middleware/ip_whitelist.py
#. Copy the code as shown below into ``ip_whitelist.py``.
The following code is a middleware example that
restricts access to a container based on IP address as explained at the
beginning of the section. Middleware passes the request on to another
application. This example uses the swift "swob" library to wrap Web
Server Gateway Interface (WSGI) requests and responses into objects for
swift to interact with. When you're done, save and close the file.
.. code-block:: python
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (c) 2014 OpenStack Foundation
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import socket
from swift.common.utils import get_logger
from swift.proxy.controllers.base import get_container_info
from swift.common.swob import Request, Response
class IPWhitelistMiddleware(object):
"""
IP Whitelist Middleware
Middleware that allows access to a container from only a set of IP
addresses as determined by the container's metadata items that start
with the prefix 'allow'. E.G. allow-dev=192.168.0.20
"""
def __init__(self, app, conf, logger=None):
self.app = app
if logger:
self.logger = logger
else:
self.logger = get_logger(conf, log_route='ip_whitelist')
self.deny_message = conf.get('deny_message', "IP Denied")
self.local_ip = socket.gethostbyname(socket.gethostname())
def __call__(self, env, start_response):
"""
WSGI entry point.
Wraps env in swob.Request object and passes it down.
:param env: WSGI environment dictionary
:param start_response: WSGI callable
"""
req = Request(env)
try:
version, account, container, obj = req.split_path(1, 4, True)
except ValueError:
return self.app(env, start_response)
container_info = get_container_info(
req.environ, self.app, swift_source='IPWhitelistMiddleware')
remote_ip = env['REMOTE_ADDR']
self.logger.debug("Remote IP: %(remote_ip)s",
{'remote_ip': remote_ip})
meta = container_info['meta']
allow = {k:v for k,v in meta.iteritems() if k.startswith('allow')}
allow_ips = set(allow.values())
allow_ips.add(self.local_ip)
self.logger.debug("Allow IPs: %(allow_ips)s",
{'allow_ips': allow_ips})
if remote_ip in allow_ips:
return self.app(env, start_response)
else:
self.logger.debug(
"IP %(remote_ip)s denied access to Account=%(account)s "
"Container=%(container)s. Not in %(allow_ips)s", locals())
return Response(
status=403,
body=self.deny_message,
request=req)(env, start_response)
def filter_factory(global_conf, **local_conf):
"""
paste.deploy app factory for creating WSGI proxy apps.
"""
conf = global_conf.copy()
conf.update(local_conf)
def ip_whitelist(app):
return IPWhitelistMiddleware(app, conf)
return ip_whitelist
There is a lot of useful information in ``env`` and ``conf`` that you
can use to decide what to do with the request. To find out more about
what properties are available, you can insert the following log
statement into the ``__init__`` method:
.. code-block:: python
self.logger.debug("conf = %(conf)s", locals())
and the following log statement into the ``__call__`` method:
.. code-block:: python
self.logger.debug("env = %(env)s", locals())
#. To plug this middleware into the swift Paste pipeline, you edit one
configuration file, ``/etc/swift/proxy-server.conf``:
.. code-block:: console
$ vim /etc/swift/proxy-server.conf
#. Find the ``[filter:ratelimit]`` section in
``/etc/swift/proxy-server.conf``, and copy in the following
configuration section after it:
.. code-block:: ini
[filter:ip_whitelist]
paste.filter_factory = swift.common.middleware.ip_whitelist:filter_factory
# You can override the default log routing for this filter here:
# set log_name = ratelimit
# set log_facility = LOG_LOCAL0
# set log_level = INFO
# set log_headers = False
# set log_address = /dev/log
deny_message = You shall not pass!
#. Find the ``[pipeline:main]`` section in
``/etc/swift/proxy-server.conf``, and add ``ip_whitelist`` after
ratelimit to the list like so. When you're done, save and close the
file:
.. code-block:: ini
[pipeline:main]
pipeline = catch_errors gatekeeper healthcheck proxy-logging cache bulk tempurl ratelimit ip_whitelist ...
#. Restart the ``swift proxy`` service to make swift use your middleware.
Start by switching to the ``swift-proxy`` screen:
#. Press **Ctrl+A** followed by **3**.
#. Press **Ctrl+C** to kill the service.
#. Press **Up Arrow** to bring up the last command.
#. Press Enter to run it.
#. Test your middleware with the ``swift`` CLI. Start by switching to the
shell screen and finish by switching back to the ``swift-proxy`` screen
to check the log output:
#. Press  **Ctrl+A** followed by **0**.
#. Make sure you're in the ``devstack`` directory:
.. code-block:: console
$ cd /root/devstack
#. Source openrc to set up your environment variables for the CLI:
.. code-block:: console
$ . openrc
#. Create a container called ``middleware-test``:
.. code-block:: console
$ swift post middleware-test
#. Press **Ctrl+A** followed by **3** to check the log output.
#. Among the log statements you'll see the lines:
.. code-block:: none
proxy-server Remote IP: my.instance.ip.address (txn: ...)
proxy-server Allow IPs: set(['my.instance.ip.address']) (txn: ...)
These two statements are produced by our middleware and show that the
request was sent from our DevStack instance and was allowed.
#. Test the middleware from outside DevStack on a remote machine that has
access to your DevStack instance:
#. Install the ``keystone`` and ``swift`` clients on your local machine:
.. code-block:: console
# pip install python-keystoneclient python-swiftclient
#. Attempt to list the objects in the ``middleware-test`` container:
.. code-block:: console
$ swift --os-auth-url=http://my.instance.ip.address:5000/v2.0/ \
--os-region-name=RegionOne --os-username=demo:demo \
--os-password=devstack list middleware-test
Container GET failed: http://my.instance.ip.address:8080/v1/AUTH_.../
middleware-test?format=json 403 Forbidden   You shall not pass!
#. Press **Ctrl+A** followed by **3** to check the log output. Look at the
swift log statements again, and among the log statements, you'll see the
lines:
.. code-block:: console
proxy-server Authorizing from an overriding middleware (i.e: tempurl) (txn: ...)
proxy-server ... IPWhitelistMiddleware
proxy-server Remote IP: my.local.ip.address (txn: ...)
proxy-server Allow IPs: set(['my.instance.ip.address']) (txn: ...)
proxy-server IP my.local.ip.address denied access to Account=AUTH_... \
Container=None. Not in set(['my.instance.ip.address']) (txn: ...)
Here we can see that the request was denied because the remote IP
address wasn't in the set of allowed IPs.
#. Back in your DevStack instance on the shell screen, add some metadata to
your container to allow the request from the remote machine:
#. Press **Ctrl+A** followed by **0**.
#. Add metadata to the container to allow the IP:
.. code-block:: console
$ swift post --meta allow-dev:my.local.ip.address middleware-test
#. Now try the command from Step 10 again and it succeeds. There are no
objects in the container, so there is nothing to list; however, there is
also no error to report.
.. warning::
Functional testing like this is not a replacement for proper unit
and integration testing, but it serves to get you started.
You can follow a similar pattern in other projects that use the Python
Paste framework. Simply create a middleware module and plug it in
through configuration. The middleware runs in sequence as part of that
project's pipeline and can call out to other services as necessary. No
project core code is touched. Look for a ``pipeline`` value in the
project's ``conf`` or ``ini`` configuration files in ``/etc/<project>``
to identify projects that use Paste.
When your middleware is done, we encourage you to open source it and let
the community know on the OpenStack mailing list. Perhaps others need
the same functionality. They can use your code, provide feedback, and
possibly contribute. If enough support exists for it, perhaps you can
propose that it be added to the official swift
`middleware <https://git.openstack.org/cgit/openstack/swift/tree/swift/common/middleware>`_.

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=====================
Provision an instance
=====================
To help understand how OpenStack works, this section describes the
end-to-end process and interaction of components when provisioning an instance
on OpenStack.
**Provision an instance**
.. figure:: figures/provision-an-instance.png
:width: 100%

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=============
Customization
=============
.. toctree::
:maxdepth: 1
ops-customize-provision-instance.rst
ops-customize-development.rst
ops-customize-objectstorage.rst
ops-customize-compute.rst
ops-customize-dashboard.rst
ops-customize-conclusion.rst
OpenStack might not do everything you need it to do out of the box. To
add a new feature, you can follow different paths.
To take the first path, you can modify the OpenStack code directly.
Learn `how to contribute
<https://wiki.openstack.org/wiki/How_To_Contribute>`_,
follow the `Developer's Guide
<https://docs.openstack.org/infra/manual/developers.html>`_, make your
changes, and contribute them back to the upstream OpenStack project.
This path is recommended if the feature you need requires deep
integration with an existing project. The community is always open to
contributions and welcomes new functionality that follows the
feature-development guidelines. This path still requires you to use
DevStack for testing your feature additions, so this chapter walks you
through the DevStack environment.
For the second path, you can write new features and plug them in using
changes to a configuration file. If the project where your feature would
need to reside uses the Python Paste framework, you can create
middleware for it and plug it in through configuration. There may also
be specific ways of customizing a project, such as creating a new
scheduler driver for Compute or a custom tab for the dashboard.
This chapter focuses on the second path for customizing OpenStack by
providing two examples for writing new features.
The first example shows how to modify Object Storage service (swift)
middleware to add a new feature, and the second example provides a new
scheduler feature for Compute service (nova).
To customize OpenStack this way you need a development environment.
The best way to get an environment up and running quickly is to run
DevStack within your cloud.

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.. _legal-requirements:
======================================
Factors affecting OpenStack deployment
======================================
Security requirements
~~~~~~~~~~~~~~~~~~~~~
When deploying OpenStack in an enterprise as a private cloud, it is
usually behind the firewall and within the trusted network alongside
existing systems. Users are employees that are bound by the
company security requirements. This tends to drive most of the security
domains towards a more trusted model. However, when deploying OpenStack
in a public facing role, no assumptions can be made and the attack vectors
significantly increase.
Consider the following security implications and requirements:
* Managing the users for both public and private clouds. The Identity service
allows for LDAP to be part of the authentication process. This may ease user
management if integrating into existing systems.
* User authentication requests include sensitive information including
usernames, passwords, and authentication tokens. It is strongly recommended
to place API services behind hardware that performs SSL termination.
* Negative or hostile users who would attack or compromise the security
of your deployment regardless of firewalls or security agreements.
* Attack vectors increase further in a public facing OpenStack deployment.
For example, the API endpoints and the software behind it become
vulnerable to hostile entities attempting to gain unauthorized access
or prevent access to services. You should provide appropriate filtering and
periodic security auditing.
.. warning::
Be mindful of consistency when utilizing third party
clouds to explore authentication options.
For more information OpenStack Security, see the `OpenStack Security
Guide <https://docs.openstack.org/security-guide/>`_.
Security domains
----------------
A security domain comprises of users, applications, servers or networks
that share common trust requirements and expectations within a system.
Typically they have the same authentication and authorization
requirements and users.
Security domains include:
Public security domains
The public security domain can refer to the internet as a whole or
networks over which you have no authority. This domain is considered
untrusted. For example, in a hybrid cloud deployment, any information
traversing between and beyond the clouds is in the public domain and
untrustworthy.
Guest security domains
The guest security domain handles compute data generated by instances
on the cloud, but not services that support the operation of the
cloud, such as API calls. Public cloud providers and private cloud
providers who do not have stringent controls on instance use or who
allow unrestricted internet access to instances should consider this
domain to be untrusted. Private cloud providers may want to consider
this network as internal and therefore trusted only if they have
controls in place to assert that they trust instances and all their
tenants.
Management security domains
The management security domain is where services interact. Sometimes
referred to as the control plane, the networks in this domain
transport confidential data such as configuration parameters, user
names, and passwords. In most deployments this domain is considered
trusted when it is behind an organization's firewall.
Data security domains
The data security domain is primarily concerned with information
pertaining to the storage services within OpenStack. The data
that crosses this network has high integrity and confidentiality
requirements and, depending on the type of deployment, may also have
strong availability requirements. The trust level of this network is
heavily dependent on other deployment decisions.
These security domains can be individually or collectively mapped to an
OpenStack deployment. The cloud operator should be aware of the appropriate
security concerns. Security domains should be mapped out against your specific
OpenStack deployment topology. The domains and their trust requirements depend
upon whether the cloud instance is public, private, or hybrid.
Hypervisor security
-------------------
The hypervisor also requires a security assessment. In a
public cloud, organizations typically do not have control
over the choice of hypervisor. Properly securing your
hypervisor is important. Attacks made upon the
unsecured hypervisor are called a **hypervisor breakout**.
Hypervisor breakout describes the event of a
compromised or malicious instance breaking out of the resource
controls of the hypervisor and gaining access to the bare
metal operating system and hardware resources.
Hypervisor security is not an issue if the security of instances is not
important. However, enterprises can minimize vulnerability by avoiding
hardware sharing with others in a public cloud.
Baremetal security
------------------
There are other services worth considering that provide a
bare metal instance instead of a cloud. In other cases, it is
possible to replicate a second private cloud by integrating
with a private Cloud-as-a-Service deployment. The
organization does not buy the hardware, but also does not share
with other tenants. It is also possible to use a provider that
hosts a bare-metal public cloud instance for which the
hardware is dedicated only to one customer, or a provider that
offers private Cloud-as-a-Service.
.. important::
Each cloud implements services differently. Understand the security
requirements of every cloud that handles the organization's data or
workloads.
Networking security
-------------------
Consider security implications and requirements before designing the
physical and logical network topologies. Make sure that the networks are
properly segregated and traffic flows are going to the correct
destinations without crossing through locations that are undesirable.
Consider the following factors:
* Firewalls
* Overlay interconnects for joining separated tenant networks
* Routing through or avoiding specific networks
How networks attach to hypervisors can expose security
vulnerabilities. To mitigate hypervisor breakouts, separate networks
from other systems and schedule instances for the
network onto dedicated Compute nodes. This prevents attackers
from having access to the networks from a compromised instance.
Multi-site security
-------------------
Securing a multi-site OpenStack installation brings
several challenges. Tenants may expect a tenant-created network
to be secure. In a multi-site installation the use of a
non-private connection between sites may be required. This may
mean that traffic would be visible to third parties and, in
cases where an application requires security, this issue
requires mitigation. In these instances, install a VPN or
encrypted connection between sites to conceal sensitive traffic.
Identity is another security consideration. Authentication
centralization provides a single authentication point for
users across the deployment, and a single administration point
for traditional create, read, update, and delete operations.
Centralized authentication is also useful for auditing purposes because
all authentication tokens originate from the same source.
Tenants in multi-site installations need isolation
from each other. The main challenge is ensuring tenant networks
function across regions which is not currently supported in OpenStack
Networking (neutron). Therefore an external system may be required
to manage mapping. Tenant networks may contain sensitive information requiring
accurate and consistent mapping to ensure that a tenant in one site
does not connect to a different tenant in another site.
Legal requirements
~~~~~~~~~~~~~~~~~~
Using remote resources for collection, processing, storage,
and retrieval provides potential benefits to businesses.
With the rapid growth of data within organizations, businesses
need to be proactive about their data storage strategies from
a compliance point of view.
Most countries have legislative and regulatory requirements governing
the storage and management of data in cloud environments. This is
particularly relevant for public, community and hybrid cloud models,
to ensure data privacy and protection for organizations using a
third party cloud provider.
Common areas of regulation include:
* Data retention policies ensuring storage of persistent data
and records management to meet data archival requirements.
* Data ownership policies governing the possession and
responsibility for data.
* Data sovereignty policies governing the storage of data in
foreign countries or otherwise separate jurisdictions.
* Data compliance policies governing certain types of
information needing to reside in certain locations due to
regulatory issues - and more importantly, cannot reside in
other locations for the same reason.
* Data location policies ensuring that the services deployed
to the cloud are used according to laws and regulations in place
for the employees, foreign subsidiaries, or third parties.
* Disaster recovery policies ensuring regular data backups and
relocation of cloud applications to another supplier in scenarios
where a provider may go out of business, or their data center could
become inoperable.
* Security breach policies governing the ways to notify individuals
through cloud provider's systems or other means if their personal
data gets compromised in any way.
* Industry standards policy governing additional requirements on what
type of cardholder data may or may not be stored and how it is to
be protected.
This is an example of such legal frameworks:
Data storage regulations in Europe are currently driven by provisions of
the `Data protection framework <http://ec.europa.eu/justice/data-protection/>`_.
`Financial Industry Regulatory Authority
<http://www.finra.org/Industry/Regulation/FINRARules/>`_ works on this in
the United States.
Privacy and security are spread over different industry-specific laws and
regulations:
* Health Insurance Portability and Accountability Act (HIPAA)
* Gramm-Leach-Bliley Act (GLBA)
* Payment Card Industry Data Security Standard (PCI DSS)
* Family Educational Rights and Privacy Act (FERPA)
Cloud security architecture
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Cloud security architecture should recognize the issues
that arise with security management, which addresses these issues
with security controls. Cloud security controls are put in place to
safeguard any weaknesses in the system, and reduce the effect of an attack.
The following security controls are described below.
Deterrent controls:
Typically reduce the threat level by informing potential attackers
that there will be adverse consequences for them if they proceed.
Preventive controls:
Strengthen the system against incidents, generally by reducing
if not actually eliminating vulnerabilities.
Detective controls:
Intended to detect and react appropriately to any incidents
that occur. System and network security monitoring, including
intrusion detection and prevention arrangements, are typically
employed to detect attacks on cloud systems and the supporting
communications infrastructure.
Corrective controls:
Reduce the consequences of an incident, normally by limiting
the damage. They come into effect during or after an incident.
Restoring system backups in order to rebuild a compromised
system is an example of a corrective control.
For more information, see See also `NIST Special Publication 800-53
<https://web.nvd.nist.gov/view/800-53/home>`_.
Software licensing
~~~~~~~~~~~~~~~~~~
The many different forms of license agreements for software are often written
with the use of dedicated hardware in mind. This model is relevant for the
cloud platform itself, including the hypervisor operating system, supporting
software for items such as database, RPC, backup, and so on. Consideration
must be made when offering Compute service instances and applications to end
users of the cloud, since the license terms for that software may need some
adjustment to be able to operate economically in the cloud.
Multi-site OpenStack deployments present additional licensing
considerations over and above regular OpenStack clouds, particularly
where site licenses are in use to provide cost efficient access to
software licenses. The licensing for host operating systems, guest
operating systems, OpenStack distributions (if applicable),
software-defined infrastructure including network controllers and
storage systems, and even individual applications need to be evaluated.
Topics to consider include:
* The definition of what constitutes a site in the relevant licenses,
as the term does not necessarily denote a geographic or otherwise
physically isolated location.
* Differentiations between "hot" (active) and "cold" (inactive) sites,
where significant savings may be made in situations where one site is
a cold standby for disaster recovery purposes only.
* Certain locations might require local vendors to provide support and
services for each site which may vary with the licensing agreement in
place.

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===============
Lay of the Land
===============
This chapter helps you set up your working environment and use it to
take a look around your cloud.
Using the OpenStack Dashboard for Administration
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
As a cloud administrative user, you can use the OpenStack dashboard to
create and manage projects, users, images, and flavors. Users are
allowed to create and manage images within specified projects and to
share images, depending on the Image service configuration. Typically,
the policy configuration allows admin users only to set quotas and
create and manage services. The dashboard provides an :guilabel:`Admin`
tab with a :guilabel:`System Panel` and an :guilabel:`Identity` tab.
These interfaces give you access to system information and usage as
well as to settings for configuring what
end users can do. Refer to the `OpenStack Administrator
Guide <https://docs.openstack.org/admin-guide/dashboard.html>`__ for
detailed how-to information about using the dashboard as an admin user.
Command-Line Tools
~~~~~~~~~~~~~~~~~~
We recommend using a combination of the OpenStack command-line interface
(CLI) tools and the OpenStack dashboard for administration. Some users
with a background in other cloud technologies may be using the EC2
Compatibility API, which uses naming conventions somewhat different from
the native API.
The pip utility is used to manage package installation from the PyPI
archive and is available in the python-pip package in most Linux
distributions. While each OpenStack project has its own client, they are
being deprecated in favour of a common OpenStack client. It is generally
recommended to install the OpenStack client.
.. tip::
To perform testing and orchestration, it is usually easier to install the
OpenStack CLI tools in a dedicated VM in the cloud. We recommend
that you keep the VM installation simple. All the tools should be installed
from a single OpenStack release version. If you need to run tools from
multiple OpenStack releases, then we recommend that you run with multiple
VMs that are each running a dedicated version.
Install OpenStack command-line clients
--------------------------------------
For instructions on installing, upgrading, or removing command-line clients,
see the `Install the OpenStack command-line clients
<https://docs.openstack.org/user-guide/common/cli-install-openstack-command-line-clients.html>`_
section in OpenStack End User Guide.
.. note::
If you support the EC2 API on your cloud, you should also install the
euca2ools package or some other EC2 API tool so that you can get the
same view your users have. Using EC2 API-based tools is mostly out of
the scope of this guide, though we discuss getting credentials for use
with it.
Administrative Command-Line Tools
---------------------------------
There are also several :command:`*-manage` command-line tools. These are
installed with the project's services on the cloud controller and do not
need to be installed separately:
* :command:`nova-manage`
* :command:`glance-manage`
* :command:`keystone-manage`
* :command:`cinder-manage`
Unlike the CLI tools mentioned above, the :command:`*-manage` tools must
be run from the cloud controller, as root, because they need read access
to the config files such as ``/etc/nova/nova.conf`` and to make queries
directly against the database rather than against the OpenStack
:term:`API endpoints <API endpoint>`.
.. warning::
The existence of the ``*-manage`` tools is a legacy issue. It is a
goal of the OpenStack project to eventually migrate all of the
remaining functionality in the ``*-manage`` tools into the API-based
tools. Until that day, you need to SSH into the
:term:`cloud controller node` to perform some maintenance operations
that require one of the ``*-manage`` tools.
Getting Credentials
-------------------
You must have the appropriate credentials if you want to use the
command-line tools to make queries against your OpenStack cloud. By far,
the easiest way to obtain :term:`authentication` credentials to use with
command-line clients is to use the OpenStack dashboard. Select
:guilabel:`Project`, click the :guilabel:`Project` tab, and click
:guilabel:`Access & Security` on the :guilabel:`Compute` category.
On the :guilabel:`Access & Security` page, click the :guilabel:`API Access`
tab to display two buttons, :guilabel:`Download OpenStack RC File` and
:guilabel:`Download EC2 Credentials`, which let you generate files that
you can source in your shell to populate the environment variables the
command-line tools require to know where your service endpoints and your
authentication information are. The user you logged in to the dashboard
dictates the filename for the openrc file, such as ``demo-openrc.sh``.
When logged in as admin, the file is named ``admin-openrc.sh``.
The generated file looks something like this:
.. code-block:: bash
#!/usr/bin/env bash
# To use an OpenStack cloud you need to authenticate against the Identity
# service named keystone, which returns a **Token** and **Service Catalog**.
# The catalog contains the endpoints for all services the user/tenant has
# access to - such as Compute, Image Service, Identity, Object Storage, Block
# Storage, and Networking (code-named nova, glance, keystone, swift,
# cinder, and neutron).
#
# *NOTE*: Using the 3 *Identity API* does not necessarily mean any other
# OpenStack API is version 3. For example, your cloud provider may implement
# Image API v1.1, Block Storage API v2, and Compute API v2.0. OS_AUTH_URL is
# only for the Identity API served through keystone.
export OS_AUTH_URL=http://203.0.113.10:5000/v3
# With the addition of Keystone we have standardized on the term **project**
# as the entity that owns the resources.
export OS_PROJECT_ID=98333aba48e756fa8f629c83a818ad57
export OS_PROJECT_NAME="test-project"
export OS_USER_DOMAIN_NAME="default"
if [ -z "$OS_USER_DOMAIN_NAME" ]; then unset OS_USER_DOMAIN_NAME; fi
# In addition to the owning entity (tenant), OpenStack stores the entity
# performing the action as the **user**.
export OS_USERNAME="demo"
# With Keystone you pass the keystone password.
echo "Please enter your OpenStack Password for project $OS_PROJECT_NAME as user $OS_USERNAME: "
read -sr OS_PASSWORD_INPUT
export OS_PASSWORD=$OS_PASSWORD_INPUT
# If your configuration has multiple regions, we set that information here.
# OS_REGION_NAME is optional and only valid in certain environments.
export OS_REGION_NAME="RegionOne"
# Don't leave a blank variable, unset it if it was empty
if [ -z "$OS_REGION_NAME" ]; then unset OS_REGION_NAME; fi
export OS_INTERFACE=public
export OS_IDENTITY_API_VERSION=3
.. warning::
This does not save your password in plain text, which is a good
thing. But when you source or run the script, it prompts you for
your password and then stores your response in the environment
variable ``OS_PASSWORD``. It is important to note that this does
require interactivity. It is possible to store a value directly in
the script if you require a noninteractive operation, but you then
need to be extremely cautious with the security and permissions of
this file.
EC2 compatibility credentials can be downloaded by selecting
:guilabel:`Project`, then :guilabel:`Compute`, then
:guilabel:`Access & Security`, then :guilabel:`API Access` to display the
:guilabel:`Download EC2 Credentials` button. Click the button to generate
a ZIP file with server x509 certificates and a shell script fragment.
Create a new directory in a secure location because these are live credentials
containing all the authentication information required to access your
cloud identity, unlike the default ``user-openrc``. Extract the ZIP file
here. You should have ``cacert.pem``, ``cert.pem``, ``ec2rc.sh``, and
``pk.pem``. The ``ec2rc.sh`` is similar to this:
.. code-block:: bash
#!/bin/bash
NOVARC=$(readlink -f "${BASH_SOURCE:-${0}}" 2>/dev/null) ||\
NOVARC=$(python -c 'import os,sys; \
print os.path.abspath(os.path.realpath(sys.argv[1]))' "${BASH_SOURCE:-${0}}")
NOVA_KEY_DIR=${NOVARC%/*}
export EC2_ACCESS_KEY=df7f93ec47e84ef8a347bbb3d598449a
export EC2_SECRET_KEY=ead2fff9f8a344e489956deacd47e818
export EC2_URL=http://203.0.113.10:8773/services/Cloud
export EC2_USER_ID=42 # nova does not use user id, but bundling requires it
export EC2_PRIVATE_KEY=${NOVA_KEY_DIR}/pk.pem
export EC2_CERT=${NOVA_KEY_DIR}/cert.pem
export NOVA_CERT=${NOVA_KEY_DIR}/cacert.pem
export EUCALYPTUS_CERT=${NOVA_CERT} # euca-bundle-image seems to require this
alias ec2-bundle-image="ec2-bundle-image --cert $EC2_CERT --privatekey \
$EC2_PRIVATE_KEY --user 42 --ec2cert $NOVA_CERT"
alias ec2-upload-bundle="ec2-upload-bundle -a $EC2_ACCESS_KEY -s \
$EC2_SECRET_KEY --url $S3_URL --ec2cert $NOVA_CERT"
To put the EC2 credentials into your environment, source the
``ec2rc.sh`` file.
Inspecting API Calls
--------------------
The command-line tools can be made to show the OpenStack API calls they
make by passing the ``--debug`` flag to them. For example:
.. code-block:: console
# openstack --debug server list
This example shows the HTTP requests from the client and the responses
from the endpoints, which can be helpful in creating custom tools
written to the OpenStack API.
Using cURL for further inspection
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Underlying the use of the command-line tools is the OpenStack API, which
is a RESTful API that runs over HTTP. There may be cases where you want
to interact with the API directly or need to use it because of a
suspected bug in one of the CLI tools. The best way to do this is to use
a combination of `cURL <http://curl.haxx.se/>`_ and another tool,
such as `jq <http://stedolan.github.io/jq/>`_, to parse the JSON from
the responses.
The first thing you must do is authenticate with the cloud using your
credentials to get an :term:`authentication token`.
Your credentials are a combination of username, password, and tenant
(project). You can extract these values from the ``openrc.sh`` discussed
above. The token allows you to interact with your other service
endpoints without needing to reauthenticate for every request. Tokens
are typically good for 24 hours, and when the token expires, you are
alerted with a 401 (Unauthorized) response and you can request another
token.
#. Look at your OpenStack service :term:`catalog`:
.. code-block:: console
$ curl -s -X POST http://203.0.113.10:35357/v2.0/tokens \
-d '{"auth": {"passwordCredentials": {"username":"test-user", "password":"test-password"}, "tenantName":"test-project"}}' \
-H "Content-type: application/json" | jq .
#. Read through the JSON response to get a feel for how the catalog is
laid out.
To make working with subsequent requests easier, store the token in
an environment variable:
.. code-block:: console
$ TOKEN=`curl -s -X POST http://203.0.113.10:35357/v2.0/tokens \
-d '{"auth": {"passwordCredentials": {"username":"test-user", "password":"test-password"}, "tenantName":"test-project"}}' \
-H "Content-type: application/json" |  jq -r .access.token.id`
Now you can refer to your token on the command line as ``$TOKEN``.
#. Pick a service endpoint from your service catalog, such as compute.
Try a request, for example, listing instances (servers):
.. code-block:: console
$ curl -s \
-H "X-Auth-Token: $TOKEN" \
http://203.0.113.10:8774/v2.0/98333aba48e756fa8f629c83a818ad57/servers | jq .
To discover how API requests should be structured, read the `OpenStack
API Reference <https://developer.openstack.org/api-guide/quick-start/index.html>`_. To chew
through the responses using jq, see the `jq
Manual <http://stedolan.github.io/jq/manual/>`_.
The ``-s flag`` used in the cURL commands above are used to prevent
the progress meter from being shown. If you are having trouble running
cURL commands, you'll want to remove it. Likewise, to help you
troubleshoot cURL commands, you can include the ``-v`` flag to show you
the verbose output. There are many more extremely useful features in
cURL; refer to the man page for all the options.
Servers and Services
--------------------
As an administrator, you have a few ways to discover what your OpenStack
cloud looks like simply by using the OpenStack tools available. This
section gives you an idea of how to get an overview of your cloud, its
shape, size, and current state.
First, you can discover what servers belong to your OpenStack cloud by
running:
.. code-block:: console
# openstack compute service list --long
The output looks like the following:
.. code-block:: console
+----+------------------+-------------------+------+---------+-------+----------------------------+-----------------+
| Id | Binary | Host | Zone | Status | State | Updated_at | Disabled Reason |
+----+------------------+-------------------+------+---------+-------+----------------------------+-----------------+
| 1 | nova-cert | cloud.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 2 | nova-compute | c01.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 3 | nova-compute | c01.example.com. | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 4 | nova-compute | c01.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 5 | nova-compute | c01.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 6 | nova-compute | c01.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 7 | nova-conductor | cloud.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 8 | nova-cert | cloud.example.com | nova | enabled | up | 2016-01-05T17:20:42.000000 | - |
| 9 | nova-scheduler | cloud.example.com | nova | enabled | up | 2016-01-05T17:20:38.000000 | - |
| 10 | nova-consoleauth | cloud.example.com | nova | enabled | up | 2016-01-05T17:20:35.000000 | - |
+----+------------------+-------------------+------+---------+-------+----------------------------+-----------------+
The output shows that there are five compute nodes and one cloud
controller. You see all the services in the up state, which indicates that
the services are up and running. If a service is in a down state, it is
no longer available. This is an indication that you
should troubleshoot why the service is down.
If you are using cinder, run the following command to see a similar
listing:
.. code-block:: console
# cinder-manage host list | sort
host zone
c01.example.com nova
c02.example.com nova
c03.example.com nova
c04.example.com nova
c05.example.com nova
cloud.example.com nova
With these two tables, you now have a good overview of what servers and
services make up your cloud.
You can also use the Identity service (keystone) to see what services
are available in your cloud as well as what endpoints have been
configured for the services.
The following command requires you to have your shell environment
configured with the proper administrative variables:
.. code-block:: console
$ openstack catalog list
+----------+------------+---------------------------------------------------------------------------------+
| Name | Type | Endpoints |
+----------+------------+---------------------------------------------------------------------------------+
| nova | compute | RegionOne |
| | | public: http://192.168.122.10:8774/v2/9faa845768224258808fc17a1bb27e5e |
| | | RegionOne |
| | | internal: http://192.168.122.10:8774/v2/9faa845768224258808fc17a1bb27e5e |
| | | RegionOne |
| | | admin: http://192.168.122.10:8774/v2/9faa845768224258808fc17a1bb27e5e |
| | | |
| cinderv2 | volumev2 | RegionOne |
| | | public: http://192.168.122.10:8776/v2/9faa845768224258808fc17a1bb27e5e |
| | | RegionOne |
| | | internal: http://192.168.122.10:8776/v2/9faa845768224258808fc17a1bb27e5e |
| | | RegionOne |
| | | admin: http://192.168.122.10:8776/v2/9faa845768224258808fc17a1bb27e5e |
| | | |
The preceding output has been truncated to show only two services. You
will see one service entry for each service that your cloud provides.
Note how the endpoint domain can be different depending on the endpoint
type. Different endpoint domains per type are not required, but this can
be done for different reasons, such as endpoint privacy or network
traffic segregation.
You can find the version of the Compute installation by using the
OpenStack command-line client:
.. code-block:: console
# openstack --version
Diagnose Your Compute Nodes
---------------------------
You can obtain extra information about virtual machines that are
running—their CPU usage, the memory, the disk I/O or network I/O—per
instance, by running the :command:`nova diagnostics` command with a server ID:
.. code-block:: console
$ nova diagnostics <serverID>
The output of this command varies depending on the hypervisor because
hypervisors support different attributes. The following demonstrates
the difference between the two most popular hypervisors.
Here is example output when the hypervisor is Xen:
.. code-block:: console
+----------------+-----------------+
| Property | Value |
+----------------+-----------------+
| cpu0 | 4.3627 |
| memory | 1171088064.0000 |
| memory_target | 1171088064.0000 |
| vbd_xvda_read | 0.0 |
| vbd_xvda_write | 0.0 |
| vif_0_rx | 3223.6870 |
| vif_0_tx | 0.0 |
| vif_1_rx | 104.4955 |
| vif_1_tx | 0.0 |
+----------------+-----------------+
While the command should work with any hypervisor that is controlled
through libvirt (KVM, QEMU, or LXC), it has been tested only with KVM.
Here is the example output when the hypervisor is KVM:
.. code-block:: console
+------------------+------------+
| Property | Value |
+------------------+------------+
| cpu0_time | 2870000000 |
| memory | 524288 |
| vda_errors | -1 |
| vda_read | 262144 |
| vda_read_req | 112 |
| vda_write | 5606400 |
| vda_write_req | 376 |
| vnet0_rx | 63343 |
| vnet0_rx_drop | 0 |
| vnet0_rx_errors | 0 |
| vnet0_rx_packets | 431 |
| vnet0_tx | 4905 |
| vnet0_tx_drop | 0 |
| vnet0_tx_errors | 0 |
| vnet0_tx_packets | 45 |
+------------------+------------+
Network Inspection
~~~~~~~~~~~~~~~~~~
To see which fixed IP networks are configured in your cloud, you can use
the :command:`openstack` command-line client to get the IP ranges:
.. code-block:: console
$ openstack subnet list
+--------------------------------------+----------------+--------------------------------------+-----------------+
| ID | Name | Network | Subnet |
+--------------------------------------+----------------+--------------------------------------+-----------------+
| 346806ee-a53e-44fd-968a-ddb2bcd2ba96 | public_subnet | 0bf90de6-fc0f-4dba-b80d-96670dfb331a | 172.24.4.224/28 |
| f939a1e4-3dc3-4540-a9f6-053e6f04918f | private_subnet | 1f7f429e-c38e-47ba-8acf-c44e3f5e8d71 | 10.0.0.0/24 |
+--------------------------------------+----------------+--------------------------------------+-----------------+
The OpenStack command-line client can provide some additional details:
.. code-block:: console
# openstack compute service list
+----+------------------+------------+----------+---------+-------+----------------------------+
| Id | Binary | Host | Zone | Status | State | Updated At |
+----+------------------+------------+----------+---------+-------+----------------------------+
| 1 | nova-consoleauth | controller | internal | enabled | up | 2016-08-18T12:16:53.000000 |
| 2 | nova-scheduler | controller | internal | enabled | up | 2016-08-18T12:16:59.000000 |
| 3 | nova-conductor | controller | internal | enabled | up | 2016-08-18T12:16:52.000000 |
| 7 | nova-compute | controller | nova | enabled | up | 2016-08-18T12:16:58.000000 |
+----+------------------+------------+----------+---------+-------+----------------------------+
This output shows that two networks are configured, each network
containing 255 IPs (a /24 subnet). The first network has been assigned
to a certain project, while the second network is still open for
assignment. You can assign this network manually; otherwise, it is
automatically assigned when a project launches its first instance.
To find out whether any floating IPs are available in your cloud, run:
.. code-block:: console
# openstack floating ip list
+--------------------------------------+---------------------+------------------+--------------------------------------+
| ID | Floating IP Address | Fixed IP Address | Port |
+--------------------------------------+---------------------+------------------+--------------------------------------+
| 340cb36d-6a52-4091-b256-97b6e61cbb20 | 172.24.4.227 | 10.2.1.8 | 1fec8fb8-7a8c-44c2-acd8-f10e2e6cd326 |
| 8b1bfc0c-7a91-4da0-b3cc-4acae26cbdec | 172.24.4.228 | None | None |
+--------------------------------------+---------------------+------------------+--------------------------------------+
Here, two floating IPs are available. The first has been allocated to a
project, while the other is unallocated.
Users and Projects
~~~~~~~~~~~~~~~~~~
To see a list of projects that have been added to the cloud, run:
.. code-block:: console
$ openstack project list
+----------------------------------+--------------------+
| ID | Name |
+----------------------------------+--------------------+
| 422c17c0b26f4fbe9449f37a5621a5e6 | alt_demo |
| 5dc65773519248f3a580cfe28ba7fa3f | demo |
| 9faa845768224258808fc17a1bb27e5e | admin |
| a733070a420c4b509784d7ea8f6884f7 | invisible_to_admin |
| aeb3e976e7794f3f89e4a7965db46c1e | service |
+----------------------------------+--------------------+
To see a list of users, run:
.. code-block:: console
$ openstack user list
+----------------------------------+----------+
| ID | Name |
+----------------------------------+----------+
| 5837063598694771aedd66aa4cddf0b8 | demo |
| 58efd9d852b74b87acc6efafaf31b30e | cinder |
| 6845d995a57a441f890abc8f55da8dfb | glance |
| ac2d15a1205f46d4837d5336cd4c5f5a | alt_demo |
| d8f593c3ae2b47289221f17a776a218b | admin |
| d959ec0a99e24df0b7cb106ff940df20 | nova |
+----------------------------------+----------+
.. note::
Sometimes a user and a group have a one-to-one mapping. This happens
for standard system accounts, such as cinder, glance, nova, and
swift, or when only one user is part of a group.
Running Instances
~~~~~~~~~~~~~~~~~
To see a list of running instances, run:
.. code-block:: console
$ openstack server list --all-projects
+--------------------------------------+------+--------+---------------------+------------+
| ID | Name | Status | Networks | Image Name |
+--------------------------------------+------+--------+---------------------+------------+
| 495b4f5e-0b12-4c5a-b4e0-4326dee17a5a | vm1 | ACTIVE | public=172.24.4.232 | cirros |
| e83686f9-16e8-45e6-911d-48f75cb8c0fb | vm2 | ACTIVE | private=10.0.0.7 | cirros |
+--------------------------------------+------+--------+---------------------+------------+
Unfortunately, this command does not tell you various details about the
running instances, such as what compute node the instance is running on,
what flavor the instance is, and so on. You can use the following
command to view details about individual instances:
.. code-block:: console
$ openstack server show <uuid>
For example:
.. code-block:: console
# openstack server show 81db556b-8aa5-427d-a95c-2a9a6972f630
+--------------------------------------+----------------------------------------------------------+
| Field | Value |
+--------------------------------------+----------------------------------------------------------+
| OS-DCF:diskConfig | AUTO |
| OS-EXT-AZ:availability_zone | nova |
| OS-EXT-SRV-ATTR:host | c02.example.com |
| OS-EXT-SRV-ATTR:hypervisor_hostname | c02.example.com |
| OS-EXT-SRV-ATTR:instance_name | instance-00000001 |
| OS-EXT-STS:power_state | Running |
| OS-EXT-STS:task_state | None |
| OS-EXT-STS:vm_state | active |
| OS-SRV-USG:launched_at | 2016-10-19T15:18:09.000000 |
| OS-SRV-USG:terminated_at | None |
| accessIPv4 | |
| accessIPv6 | |
| addresses | private=10.0.0.7 |
| config_drive | |
| created | 2016-10-19T15:17:46Z |
| flavor | m1.tiny (1) |
| hostId | 2b57e2b7a839508337fb55695b8f6e65aa881460a20449a76352040b |
| id | e83686f9-16e8-45e6-911d-48f75cb8c0fb |
| image | cirros (9fef3b2d-c35d-4b61-bea8-09cc6dc41829) |
| key_name | None |
| name | test |
| os-extended-volumes:volumes_attached | [] |
| progress | 0 |
| project_id | 1eaaf6ede7a24e78859591444abf314a |
| properties | |
| security_groups | [{u'name': u'default'}] |
| status | ACTIVE |
| updated | 2016-10-19T15:18:58Z |
| user_id | 7aaa9b5573ce441b98dae857a82ecc68 |
+--------------------------------------+----------------------------------------------------------+
This output shows that an instance named ``devstack`` was created from
an Ubuntu 12.04 image using a flavor of ``m1.small`` and is hosted on
the compute node ``c02.example.com``.
Summary
~~~~~~~
We hope you have enjoyed this quick tour of your working environment,
including how to interact with your cloud and extract useful
information. From here, you can use the `OpenStack Administrator
Guide <https://docs.openstack.org/admin-guide/>`_ as your
reference for all of the command-line functionality in your cloud.

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=======
Summary
=======
For stable operations, you want to detect failure promptly and determine
causes efficiently. With a distributed system, it's even more important
to track the right items to meet a service-level target. Learning where
these logs are located in the file system or API gives you an advantage.
This chapter also showed how to read, interpret, and manipulate
information from OpenStack services so that you can monitor effectively.

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======================
Logging and Monitoring
======================
.. toctree::
:maxdepth: 1
ops-logging.rst
ops-monitoring.rst
ops-logging-monitoring-summary.rst
As an OpenStack cloud is composed of so many different services, there
are a large number of log files. This chapter aims to assist you in
locating and working with them and describes other ways to track the
status of your deployment.

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=======
rsyslog
=======
A number of operating systems use rsyslog as the default logging service.
Since it is natively able to send logs to a remote location, you do not
have to install anything extra to enable this feature, just modify the
configuration file. In doing this, consider running your logging over a
management network or using an encrypted VPN to avoid interception.
rsyslog client configuration
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To begin, configure all OpenStack components to log to the syslog log
file in addition to their standard log file location. Also, configure each
component to log to a different syslog facility. This makes it easier to
split the logs into individual components on the central server:
``nova.conf``:
.. code-block:: ini
use_syslog=True
syslog_log_facility=LOG_LOCAL0
``glance-api.conf`` and ``glance-registry.conf``:
.. code-block:: ini
use_syslog=True
syslog_log_facility=LOG_LOCAL1
``cinder.conf``:
.. code-block:: ini
use_syslog=True
syslog_log_facility=LOG_LOCAL2
``keystone.conf``:
.. code-block:: ini
use_syslog=True
syslog_log_facility=LOG_LOCAL3
By default, Object Storage logs to syslog.
Next, create ``/etc/rsyslog.d/client.conf`` with the following line:
.. code-block:: none
*.* @192.168.1.10
This instructs rsyslog to send all logs to the IP listed. In this
example, the IP points to the cloud controller.
rsyslog server configuration
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Designate a server as the central logging server. The best practice is
to choose a server that is solely dedicated to this purpose. Create a
file called ``/etc/rsyslog.d/server.conf`` with the following contents:
.. code-block:: none
# Enable UDP
$ModLoad imudp
# Listen on 192.168.1.10 only
$UDPServerAddress 192.168.1.10
# Port 514
$UDPServerRun 514
# Create logging templates for nova
$template NovaFile,"/var/log/rsyslog/%HOSTNAME%/nova.log"
$template NovaAll,"/var/log/rsyslog/nova.log"
# Log everything else to syslog.log
$template DynFile,"/var/log/rsyslog/%HOSTNAME%/syslog.log"
*.* ?DynFile
# Log various openstack components to their own individual file
local0.* ?NovaFile
local0.* ?NovaAll
& ~
This example configuration handles the nova service only. It first
configures rsyslog to act as a server that runs on port 514. Next, it
creates a series of logging templates. Logging templates control where
received logs are stored. Using the last example, a nova log from
c01.example.com goes to the following locations:
- ``/var/log/rsyslog/c01.example.com/nova.log``
- ``/var/log/rsyslog/nova.log``
This is useful, as logs from c02.example.com go to:
- ``/var/log/rsyslog/c02.example.com/nova.log``
- ``/var/log/rsyslog/nova.log``
This configuration will result in a separate log file for each compute
node as well as an aggregated log file that contains nova logs from all
nodes.

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=======
Logging
=======
Where Are the Logs?
~~~~~~~~~~~~~~~~~~~
Most services use the convention of writing their log files to
subdirectories of the ``/var/log directory``, as listed in
:ref:`table_log_locations`.
.. _table_log_locations:
.. list-table:: Table OpenStack log locations
:widths: 25 25 50
:header-rows: 1
* - Node type
- Service
- Log location
* - Cloud controller
- ``nova-*``
- ``/var/log/nova``
* - Cloud controller
- ``glance-*``
- ``/var/log/glance``
* - Cloud controller
- ``cinder-*``
- ``/var/log/cinder``
* - Cloud controller
- ``keystone-*``
- ``/var/log/keystone``
* - Cloud controller
- ``neutron-*``
- ``/var/log/neutron``
* - Cloud controller
- horizon
- ``/var/log/apache2/``
* - All nodes
- misc (swift, dnsmasq)
- ``/var/log/syslog``
* - Compute nodes
- libvirt
- ``/var/log/libvirt/libvirtd.log``
* - Compute nodes
- Console (boot up messages) for VM instances:
- ``/var/lib/nova/instances/instance-<instance id>/console.log``
* - Block Storage nodes
- cinder-volume
- ``/var/log/cinder/cinder-volume.log``
Reading the Logs
~~~~~~~~~~~~~~~~
OpenStack services use the standard logging levels, at increasing
severity: TRACE, DEBUG, INFO, AUDIT, WARNING, ERROR, and CRITICAL. That
is, messages only appear in the logs if they are more "severe" than the
particular log level, with DEBUG allowing all log statements through.
For example, TRACE is logged only if the software has a stack trace,
while INFO is logged for every message including those that are only for
information.
To disable DEBUG-level logging, edit ``/etc/nova/nova.conf`` file as follows:
.. code-block:: ini
debug=false
Keystone is handled a little differently. To modify the logging level,
edit the ``/etc/keystone/logging.conf`` file and look at the
``logger_root`` and ``handler_file`` sections.
Logging for horizon is configured in
``/etc/openstack_dashboard/local_settings.py``. Because horizon is
a Django web application, it follows the `Django Logging framework
conventions <https://docs.djangoproject.com/en/dev/topics/logging/>`_.
The first step in finding the source of an error is typically to search
for a CRITICAL, or ERROR message in the log starting at the
bottom of the log file.
Here is an example of a log message with the corresponding
ERROR (Python traceback) immediately following:
.. code-block:: console
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server [req-c0b38ace-2586-48ce-9336-6233efa1f035 6c9808c2c5044e1388a83a74da9364d5 e07f5395c
2eb428cafc41679e7deeab1 - default default] Exception during message handling
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server Traceback (most recent call last):
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/oslo_messaging/rpc/server.py", line 133, in _process_incoming
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server res = self.dispatcher.dispatch(message)
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/oslo_messaging/rpc/dispatcher.py", line 150, in dispatch
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server return self._do_dispatch(endpoint, method, ctxt, args)
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/oslo_messaging/rpc/dispatcher.py", line 121, in _do_dispatch
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server result = func(ctxt, **new_args)
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/cinder/volume/manager.py", line 4366, in create_volume
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server allow_reschedule=allow_reschedule, volume=volume)
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/cinder/volume/manager.py", line 634, in create_volume
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server _run_flow()
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/cinder/volume/manager.py", line 626, in _run_flow
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server flow_engine.run()
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/taskflow/engines/action_engine/engine.py", line 247, in run
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server for _state in self.run_iter(timeout=timeout):
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/taskflow/engines/action_engine/engine.py", line 340, in run_iter
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server failure.Failure.reraise_if_any(er_failures)
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/taskflow/types/failure.py", line 336, in reraise_if_any
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server failures[0].reraise()
2017-01-18 15:54:00.467 32552 ERROR oslo_messaging.rpc.server File "/openstack/venvs/cinder-14.0.0/lib/python2.7/site-packages/taskflow/types/failure.py", line 343, in reraise
In this example, ``cinder-volumes`` failed to start and has provided a
stack trace, since its volume back end has been unable to set up the
storage volume—probably because the LVM volume that is expected from the
configuration does not exist.
Here is an example error log:
.. code-block:: console
2013-02-25 20:26:33 6619 ERROR nova.openstack.common.rpc.common [-] AMQP server on localhost:5672 is unreachable:
[Errno 111] ECONNREFUSED. Trying again in 23 seconds.
In this error, a nova service has failed to connect to the RabbitMQ
server because it got a connection refused error.
Tracing Instance Requests
~~~~~~~~~~~~~~~~~~~~~~~~~
When an instance fails to behave properly, you will often have to trace
activity associated with that instance across the log files of various
``nova-*`` services and across both the cloud controller and compute
nodes.
The typical way is to trace the UUID associated with an instance across
the service logs.
Consider the following example:
.. code-block:: console
$ openstack server list
+--------------------------------+--------+--------+--------------------------+------------+
| ID | Name | Status | Networks | Image Name |
+--------------------------------+--------+--------+--------------------------+------------+
| fafed8-4a46-413b-b113-f1959ffe | cirros | ACTIVE | novanetwork=192.168.100.3| cirros |
+--------------------------------------+--------+--------+--------------------+------------+
Here, the ID associated with the instance is
``faf7ded8-4a46-413b-b113-f19590746ffe``. If you search for this string
on the cloud controller in the ``/var/log/nova-*.log`` files, it appears
in ``nova-api.log`` and ``nova-scheduler.log``. If you search for this
on the compute nodes in ``/var/log/nova-*.log``, it appears in
``nova-compute.log``. If no ERROR or CRITICAL messages appear, the most
recent log entry that reports this may provide a hint about what has gone
wrong.
Adding Custom Logging Statements
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If there is not enough information in the existing logs, you may need to
add your own custom logging statements to the ``nova-*``
services.
The source files are located in
``/usr/lib/python2.7/dist-packages/nova``.
To add logging statements, the following line should be near the top of
the file. For most files, these should already be there:
.. code-block:: python
from nova.openstack.common import log as logging
LOG = logging.getLogger(__name__)
To add a DEBUG logging statement, you would do:
.. code-block:: python
LOG.debug("This is a custom debugging statement")
You may notice that all the existing logging messages are preceded by an
underscore and surrounded by parentheses, for example:
.. code-block:: python
LOG.debug(_("Logging statement appears here"))
This formatting is used to support translation of logging messages into
different languages using the
`gettext <https://docs.python.org/2/library/gettext.html>`_
internationalization library. You don't need to do this for your own
custom log messages. However, if you want to contribute the code back to
the OpenStack project that includes logging statements, you must
surround your log messages with underscores and parentheses.
RabbitMQ Web Management Interface or rabbitmqctl
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Aside from connection failures, RabbitMQ log files are generally not
useful for debugging OpenStack related issues. Instead, we recommend you
use the RabbitMQ web management interface. Enable it on your cloud
controller:
.. code-block:: console
# /usr/lib/rabbitmq/bin/rabbitmq-plugins enable rabbitmq_management
.. code-block:: console
# service rabbitmq-server restart
The RabbitMQ web management interface is accessible on your cloud
controller at *http://localhost:55672*.
.. note::
Ubuntu 12.04 installs RabbitMQ version 2.7.1, which uses port 55672.
RabbitMQ versions 3.0 and above use port 15672 instead. You can
check which version of RabbitMQ you have running on your local
Ubuntu machine by doing:
.. code-block:: console
$ dpkg -s rabbitmq-server | grep "Version:"
Version: 2.7.1-0ubuntu4
An alternative to enabling the RabbitMQ web management interface is to
use the ``rabbitmqctl`` commands. For example,
:command:`rabbitmqctl list_queues| grep cinder` displays any messages left in
the queue. If there are messages, it's a possible sign that cinder
services didn't connect properly to rabbitmq and might have to be
restarted.
Items to monitor for RabbitMQ include the number of items in each of the
queues and the processing time statistics for the server.
Centrally Managing Logs
~~~~~~~~~~~~~~~~~~~~~~~
Because your cloud is most likely composed of many servers, you must
check logs on each of those servers to properly piece an event together.
A better solution is to send the logs of all servers to a central
location so that they can all be accessed from the same
area.
The choice of central logging engine will be dependent on the operating
system in use as well as any organizational requirements for logging tools.
Syslog choices
--------------
There are a large number of syslogs engines available, each have differing
capabilities and configuration requirements.
.. toctree::
:maxdepth: 1
ops-logging-rsyslog.rst

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@ -1,50 +0,0 @@
===========================
Handling a Complete Failure
===========================
A common way of dealing with the recovery from a full system failure,
such as a power outage of a data center, is to assign each service a
priority, and restore in order.
:ref:`table_example_priority` shows an example.
.. _table_example_priority:
.. list-table:: Table. Example service restoration priority list
:header-rows: 1
* - Priority
- Services
* - 1
- Internal network connectivity
* - 2
- Backing storage services
* - 3
- Public network connectivity for user virtual machines
* - 4
- ``nova-compute``, cinder hosts
* - 5
- User virtual machines
* - 10
- Message queue and database services
* - 15
- Keystone services
* - 20
- ``cinder-scheduler``
* - 21
- Image Catalog and Delivery services
* - 22
- ``nova-scheduler`` services
* - 98
- ``cinder-api``
* - 99
- ``nova-api`` services
* - 100
- Dashboard node
Use this example priority list to ensure that user-affected services are
restored as soon as possible, but not before a stable environment is in
place. Of course, despite being listed as a single-line item, each step
requires significant work. For example, just after starting the
database, you should check its integrity, or, after starting the nova
services, you should verify that the hypervisor matches the database and
fix any mismatches.

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@ -1,638 +0,0 @@
=====================================
Compute Node Failures and Maintenance
=====================================
Sometimes a compute node either crashes unexpectedly or requires a
reboot for maintenance reasons.
Planned Maintenance
~~~~~~~~~~~~~~~~~~~
If you need to reboot a compute node due to planned maintenance, such as
a software or hardware upgrade, perform the following steps:
#. Disable scheduling of new VMs to the node, optionally providing a reason
comment:
.. code-block:: console
# openstack compute service set --disable --disable-reason \
maintenance c01.example.com nova-compute
#. Verify that all hosted instances have been moved off the node:
* If your cloud is using a shared storage:
#. Get a list of instances that need to be moved:
.. code-block:: console
# openstack server list --host c01.example.com --all-projects
#. Migrate all instances one by one:
.. code-block:: console
# openstack server migrate <uuid> --live c02.example.com
* If your cloud is not using a shared storage, run:
.. code-block:: console
# openstack server migrate <uuid> --live --block-migration c02.example.com
#. Stop the ``nova-compute`` service:
.. code-block:: console
# stop nova-compute
If you use a configuration-management system, such as Puppet, that
ensures the ``nova-compute`` service is always running, you can
temporarily move the ``init`` files:
.. code-block:: console
# mkdir /root/tmp
# mv /etc/init/nova-compute.conf /root/tmp
# mv /etc/init.d/nova-compute /root/tmp
#. Shut down your compute node, perform the maintenance, and turn
the node back on.
#. Start the ``nova-compute`` service:
.. code-block:: console
# start nova-compute
You can re-enable the ``nova-compute`` service by undoing the commands:
.. code-block:: console
# mv /root/tmp/nova-compute.conf /etc/init
# mv /root/tmp/nova-compute /etc/init.d/
#. Enable scheduling of VMs to the node:
.. code-block:: console
# openstack compute service set --enable c01.example.com nova-compute
#. Optionally, migrate the instances back to their original compute node.
After a Compute Node Reboots
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When you reboot a compute node, first verify that it booted
successfully. This includes ensuring that the ``nova-compute`` service
is running:
.. code-block:: console
# ps aux | grep nova-compute
# status nova-compute
Also ensure that it has successfully connected to the AMQP server:
.. code-block:: console
# grep AMQP /var/log/nova/nova-compute.log
2013-02-26 09:51:31 12427 INFO nova.openstack.common.rpc.common [-] Connected to AMQP server on 199.116.232.36:5672
After the compute node is successfully running, you must deal with the
instances that are hosted on that compute node because none of them are
running. Depending on your SLA with your users or customers, you might
have to start each instance and ensure that they start correctly.
Instances
~~~~~~~~~
You can create a list of instances that are hosted on the compute node
by performing the following command:
.. code-block:: console
# openstack server list --host c01.example.com --all-projects
After you have the list, you can use the :command:`openstack` command to
start each instance:
.. code-block:: console
# openstack server reboot <server>
.. note::
Any time an instance shuts down unexpectedly, it might have problems
on boot. For example, the instance might require an ``fsck`` on the
root partition. If this happens, the user can use the dashboard VNC
console to fix this.
If an instance does not boot, meaning ``virsh list`` never shows the
instance as even attempting to boot, do the following on the compute
node:
.. code-block:: console
# tail -f /var/log/nova/nova-compute.log
Try executing the :command:`openstack server reboot` command again. You should
see an error message about why the instance was not able to boot.
In most cases, the error is the result of something in libvirt's XML
file (``/etc/libvirt/qemu/instance-xxxxxxxx.xml``) that no longer
exists. You can enforce re-creation of the XML file as well as rebooting
the instance by running the following command:
.. code-block:: console
# openstack server reboot --hard <server>
Inspecting and Recovering Data from Failed Instances
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In some scenarios, instances are running but are inaccessible through
SSH and do not respond to any command. The VNC console could be
displaying a boot failure or kernel panic error messages. This could be
an indication of file system corruption on the VM itself. If you need to
recover files or inspect the content of the instance, qemu-nbd can be
used to mount the disk.
.. warning::
If you access or view the user's content and data, get approval first!
To access the instance's disk
(``/var/lib/nova/instances/instance-xxxxxx/disk``), use the following
steps:
#. Suspend the instance using the ``virsh`` command.
#. Connect the qemu-nbd device to the disk.
#. Mount the qemu-nbd device.
#. Unmount the device after inspecting.
#. Disconnect the qemu-nbd device.
#. Resume the instance.
If you do not follow last three steps, OpenStack Compute cannot manage
the instance any longer. It fails to respond to any command issued by
OpenStack Compute, and it is marked as shut down.
Once you mount the disk file, you should be able to access it and treat
it as a collection of normal directories with files and a directory
structure. However, we do not recommend that you edit or touch any files
because this could change the
:term:`access control lists (ACLs) <access control list (ACL)>` that are used
to determine which accounts can perform what operations on files and
directories. Changing ACLs can make the instance unbootable if it is not
already.
#. Suspend the instance using the :command:`virsh` command, taking note of the
internal ID:
.. code-block:: console
# virsh list
Id Name State
----------------------------------
1 instance-00000981 running
2 instance-000009f5 running
30 instance-0000274a running
# virsh suspend 30
Domain 30 suspended
#. Find the ID for each instance by listing the server IDs using the
following command:
.. code-block:: console
# openstack server list
+--------------------------------------+-------+---------+-----------------------------+------------+
| ID | Name | Status | Networks | Image Name |
+--------------------------------------+-------+---------+-----------------------------+------------+
| 2da14c5c-de6d-407d-a7d2-2dd0862b9967 | try3 | ACTIVE | finance-internal=10.10.0.4 | |
| 223f4860-722a-44a0-bac7-f73f58beec7b | try2 | ACTIVE | finance-internal=10.10.0.13 | |
+--------------------------------------+-------+---------+-----------------------------+------------+
#. Connect the qemu-nbd device to the disk:
.. code-block:: console
# cd /var/lib/nova/instances/instance-0000274a
# ls -lh
total 33M
-rw-rw---- 1 libvirt-qemu kvm 6.3K Oct 15 11:31 console.log
-rw-r--r-- 1 libvirt-qemu kvm 33M Oct 15 22:06 disk
-rw-r--r-- 1 libvirt-qemu kvm 384K Oct 15 22:06 disk.local
-rw-rw-r-- 1 nova nova 1.7K Oct 15 11:30 libvirt.xml
# qemu-nbd -c /dev/nbd0 `pwd`/disk
#. Mount the qemu-nbd device.
The qemu-nbd device tries to export the instance disk's different
partitions as separate devices. For example, if vda is the disk and
vda1 is the root partition, qemu-nbd exports the device as
``/dev/nbd0`` and ``/dev/nbd0p1``, respectively:
.. code-block:: console
# mount /dev/nbd0p1 /mnt/
You can now access the contents of ``/mnt``, which correspond to the
first partition of the instance's disk.
To examine the secondary or ephemeral disk, use an alternate mount
point if you want both primary and secondary drives mounted at the
same time:
.. code-block:: console
# umount /mnt
# qemu-nbd -c /dev/nbd1 `pwd`/disk.local
# mount /dev/nbd1 /mnt/
# ls -lh /mnt/
total 76K
lrwxrwxrwx. 1 root root 7 Oct 15 00:44 bin -> usr/bin
dr-xr-xr-x. 4 root root 4.0K Oct 15 01:07 boot
drwxr-xr-x. 2 root root 4.0K Oct 15 00:42 dev
drwxr-xr-x. 70 root root 4.0K Oct 15 11:31 etc
drwxr-xr-x. 3 root root 4.0K Oct 15 01:07 home
lrwxrwxrwx. 1 root root 7 Oct 15 00:44 lib -> usr/lib
lrwxrwxrwx. 1 root root 9 Oct 15 00:44 lib64 -> usr/lib64
drwx------. 2 root root 16K Oct 15 00:42 lost+found
drwxr-xr-x. 2 root root 4.0K Feb 3 2012 media
drwxr-xr-x. 2 root root 4.0K Feb 3 2012 mnt
drwxr-xr-x. 2 root root 4.0K Feb 3 2012 opt
drwxr-xr-x. 2 root root 4.0K Oct 15 00:42 proc
dr-xr-x---. 3 root root 4.0K Oct 15 21:56 root
drwxr-xr-x. 14 root root 4.0K Oct 15 01:07 run
lrwxrwxrwx. 1 root root 8 Oct 15 00:44 sbin -> usr/sbin
drwxr-xr-x. 2 root root 4.0K Feb 3 2012 srv
drwxr-xr-x. 2 root root 4.0K Oct 15 00:42 sys
drwxrwxrwt. 9 root root 4.0K Oct 15 16:29 tmp
drwxr-xr-x. 13 root root 4.0K Oct 15 00:44 usr
drwxr-xr-x. 17 root root 4.0K Oct 15 00:44 var
#. Once you have completed the inspection, unmount the mount point and
release the qemu-nbd device:
.. code-block:: console
# umount /mnt
# qemu-nbd -d /dev/nbd0
/dev/nbd0 disconnected
#. Resume the instance using :command:`virsh`:
.. code-block:: console
# virsh list
Id Name State
----------------------------------
1 instance-00000981 running
2 instance-000009f5 running
30 instance-0000274a paused
# virsh resume 30
Domain 30 resumed
Managing floating IP addresses between instances
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In an elastic cloud environment using the ``Public_AGILE`` network, each
instance has a publicly accessible IPv4 & IPv6 address. It does not support
the concept of OpenStack floating IP addresses that can easily be attached,
removed, and transferred between instances. However, there is a workaround
using neutron ports which contain the IPv4 & IPv6 address.
**Create a port that can be reused**
#. Create a port on the ``Public_AGILE`` network:
.. code-block:: console
$ openstack port create port1 --network Public_AGILE
Created a new port:
+-----------------------+------------------------------------------------------+
| Field | Value |
+-----------------------+------------------------------------------------------+
| admin_state_up | UP |
| allowed_address_pairs | |
| binding_host_id | None |
| binding_profile | None |
| binding_vif_details | None |
| binding_vif_type | None |
| binding_vnic_type | normal |
| created_at | 2017-02-26T14:23:18Z |
| description | |
| device_id | |
| device_owner | |
| dns_assignment | None |
| dns_name | None |
| extra_dhcp_opts | |
| fixed_ips | ip_address='96.118.182.106', |
| | subnet_id='4279c70a-7218-4c7e-94e5-7bd4c045644e' |
| | ip_address='2001:558:fc0b:100:f816:3eff:fefb:45fb', |
| | subnet_id='11d8087b-6288-4129-95ff-42c3df0c1df0' |
| id | 3871bf29-e963-4701-a7dd-8888dbaab375 |
| ip_address | None |
| mac_address | fa:16:3e:e2:09:e0 |
| name | port1 |
| network_id | f41bd921-3a59-49c4-aa95-c2e4496a4b56 |
| option_name | None |
| option_value | None |
| port_security_enabled | True |
| project_id | 52f0574689f14c8a99e7ca22c4eb572 |
| qos_policy_id | None |
| revision_number | 6 |
| security_groups | 20d96891-0055-428a-8fa6-d5aed25f0dc6 |
| status | DOWN |
| subnet_id | None |
| updated_at | 2017-02-26T14:23:19Z |
+-----------------------+------------------------------------------------------+
#. If you know the fully qualified domain name (FQDN) that will be assigned to
the IP address, assign the port with the same name:
.. code-block:: console
$ openstack port create "example-fqdn-01.sys.example.com" --network Public_AGILE
Created a new port:
+-----------------------+------------------------------------------------------+
| Field | Value |
+-----------------------+------------------------------------------------------+
| admin_state_up | UP |
| allowed_address_pairs | |
| binding_host_id | None |
| binding_profile | None |
| binding_vif_details | None |
| binding_vif_type | None |
| binding_vnic_type | normal |
| created_at | 2017-02-26T14:24:16Z |
| description | |
| device_id | |
| device_owner | |
| dns_assignment | None |
| dns_name | None |
| extra_dhcp_opts | |
| fixed_ips | ip_address='96.118.182.107', |
| | subnet_id='4279c70a-7218-4c7e-94e5-7bd4c045644e' |
| | ip_address='2001:558:fc0b:100:f816:3eff:fefb:65fc', |
| | subnet_id='11d8087b-6288-4129-95ff-42c3df0c1df0' |
| id | 731c3b28-3753-4e63-bae3-b58a52d6ccca |
| ip_address | None |
| mac_address | fa:16:3e:fb:65:fc |
| name | example-fqdn-01.sys.example.com |
| network_id | f41bd921-3a59-49c4-aa95-c2e4496a4b56 |
| option_name | None |
| option_value | None |
| port_security_enabled | True |
| project_id | 52f0574689f14c8a99e7ca22c4eb5720 |
| qos_policy_id | None |
| revision_number | 6 |
| security_groups | 20d96891-0055-428a-8fa6-d5aed25f0dc6 |
| status | DOWN |
| subnet_id | None |
| updated_at | 2017-02-26T14:24:17Z |
+-----------------------+------------------------------------------------------+
#. Use the port when creating an instance:
.. code-block:: console
$ openstack server create --flavor m1.medium --image ubuntu.qcow2 \
--key-name team_key --nic port-id=PORT_ID \
"example-fqdn-01.sys.example.com"
#. Verify the instance has the correct IP address:
.. code-block:: console
+--------------------------------------+----------------------------------------------------------+
| Field | Value |
+--------------------------------------+----------------------------------------------------------+
| OS-DCF:diskConfig | MANUAL |
| OS-EXT-AZ:availability_zone | nova |
| OS-EXT-SRV-ATTR:host | os_compute-1 |
| OS-EXT-SRV-ATTR:hypervisor_hostname | os_compute.ece.example.com |
| OS-EXT-SRV-ATTR:instance_name | instance-00012b82 |
| OS-EXT-STS:power_state | Running |
| OS-EXT-STS:task_state | None |
| OS-EXT-STS:vm_state | active |
| OS-SRV-USG:launched_at | 2016-11-30T08:55:27.000000 |
| OS-SRV-USG:terminated_at | None |
| accessIPv4 | |
| accessIPv6 | |
| addresses | public=172.24.4.236 |
| config_drive | |
| created | 2016-11-30T08:55:14Z |
| flavor | m1.medium (103) |
| hostId | aca973d5b7981faaf8c713a0130713bbc1e64151be65c8dfb53039f7 |
| id | f91bd761-6407-46a6-b5fd-11a8a46e4983 |
| image | Example Cloud Ubuntu 14.04 x86_64 v2.5 (fb49d7e1-273b-...|
| key_name | team_key |
| name | example-fqdn-01.sys.example.com |
| os-extended-volumes:volumes_attached | [] |
| progress | 0 |
| project_id | 2daf82a578e9437cab396c888ff0ca57 |
| properties | |
| security_groups | [{u'name': u'default'}] |
| status | ACTIVE |
| updated | 2016-11-30T08:55:27Z |
| user_id | 8cbea24666ae49bbb8c1641f9b12d2d2 |
+--------------------------------------+----------------------------------------------------------+
#. Check the port connection using the netcat utility:
.. code-block:: console
$ nc -v -w 2 96.118.182.107 22
Ncat: Version 7.00 ( https://nmap.org/ncat )
Ncat: Connected to 96.118.182.107:22.
SSH-2.0-OpenSSH_6.6.1p1 Ubuntu-2ubuntu2.6
**Detach a port from an instance**
#. Find the port corresponding to the instance. For example:
.. code-block:: console
$ openstack port list | grep -B1 96.118.182.107
| 731c3b28-3753-4e63-bae3-b58a52d6ccca | example-fqdn-01.sys.example.com | fa:16:3e:fb:65:fc | ip_address='96.118.182.107', subnet_id='4279c70a-7218-4c7e-94e5-7bd4c045644e' |
#. Run the :command:`openstack port set` command to remove the port from
the instance:
.. code-block:: console
$ openstack port set 731c3b28-3753-4e63-bae3-b58a52d6ccca \
--device "" --device-owner "" --no-binding-profile
#. Delete the instance and create a new instance using the
``--nic port-id`` option.
**Retrieve an IP address when an instance is deleted before detaching
a port**
The following procedure is a possible workaround to retrieve an IP address
when an instance has been deleted with the port still attached:
#. Launch several neutron ports:
.. code-block:: console
$ for i in {0..10}; do openstack port create --network Public_AGILE \
ip-recovery; done
#. Check the ports for the lost IP address and update the name:
.. code-block:: console
$ openstack port set 731c3b28-3753-4e63-bae3-b58a52d6ccca \
--name "don't delete"
#. Delete the ports that are not needed:
.. code-block:: console
$ for port in $(openstack port list | grep -i ip-recovery | \
awk '{print $2}'); do openstack port delete $port; done
#. If you still cannot find the lost IP address, repeat these steps
again.
.. _volumes:
Volumes
~~~~~~~
If the affected instances also had attached volumes, first generate a
list of instance and volume UUIDs:
.. code-block:: mysql
mysql> select nova.instances.uuid as instance_uuid,
cinder.volumes.id as volume_uuid, cinder.volumes.status,
cinder.volumes.attach_status, cinder.volumes.mountpoint,
cinder.volumes.display_name from cinder.volumes
inner join nova.instances on cinder.volumes.instance_uuid=nova.instances.uuid
where nova.instances.host = 'c01.example.com';
You should see a result similar to the following:
.. code-block:: mysql
+--------------+------------+-------+--------------+-----------+--------------+
|instance_uuid |volume_uuid |status |attach_status |mountpoint | display_name |
+--------------+------------+-------+--------------+-----------+--------------+
|9b969a05 |1f0fbf36 |in-use |attached |/dev/vdc | test |
+--------------+------------+-------+--------------+-----------+--------------+
1 row in set (0.00 sec)
Next, manually detach and reattach the volumes, where X is the proper
mount point:
.. code-block:: console
# openstack server remove volume <instance_uuid> <volume_uuid>
# openstack server add volume <instance_uuid> <volume_uuid> --device /dev/vdX
Be sure that the instance has successfully booted and is at a login
screen before doing the above.
Total Compute Node Failure
~~~~~~~~~~~~~~~~~~~~~~~~~~
Compute nodes can fail the same way a cloud controller can fail. A
motherboard failure or some other type of hardware failure can cause an
entire compute node to go offline. When this happens, all instances
running on that compute node will not be available. Just like with a
cloud controller failure, if your infrastructure monitoring does not
detect a failed compute node, your users will notify you because of
their lost instances.
If a compute node fails and won't be fixed for a few hours (or at all),
you can relaunch all instances that are hosted on the failed node if you
use shared storage for ``/var/lib/nova/instances``.
To do this, generate a list of instance UUIDs that are hosted on the
failed node by running the following query on the nova database:
.. code-block:: mysql
mysql> select uuid from instances
where host = 'c01.example.com' and deleted = 0;
Next, update the nova database to indicate that all instances that used
to be hosted on c01.example.com are now hosted on c02.example.com:
.. code-block:: mysql
mysql> update instances set host = 'c02.example.com'
where host = 'c01.example.com' and deleted = 0;
If you're using the Networking service ML2 plug-in, update the
Networking service database to indicate that all ports that used to be
hosted on c01.example.com are now hosted on c02.example.com:
.. code-block:: mysql
mysql> update ml2_port_bindings set host = 'c02.example.com'
where host = 'c01.example.com';
mysql> update ml2_port_binding_levels set host = 'c02.example.com'
where host = 'c01.example.com';
After that, use the :command:`openstack` command to reboot all instances
that were on c01.example.com while regenerating their XML files at the same
time:
.. code-block:: console
# openstack server reboot --hard <server>
Finally, reattach volumes using the same method described in the section
:ref:`volumes`.
/var/lib/nova/instances
~~~~~~~~~~~~~~~~~~~~~~~
It's worth mentioning this directory in the context of failed compute
nodes. This directory contains the libvirt KVM file-based disk images
for the instances that are hosted on that compute node. If you are not
running your cloud in a shared storage environment, this directory is
unique across all compute nodes.
``/var/lib/nova/instances`` contains two types of directories.
The first is the ``_base`` directory. This contains all the cached base
images from glance for each unique image that has been launched on that
compute node. Files ending in ``_20`` (or a different number) are the
ephemeral base images.
The other directories are titled ``instance-xxxxxxxx``. These
directories correspond to instances running on that compute node. The
files inside are related to one of the files in the ``_base`` directory.
They're essentially differential-based files containing only the changes
made from the original ``_base`` directory.
All files and directories in ``/var/lib/nova/instances`` are uniquely
named. The files in \_base are uniquely titled for the glance image that
they are based on, and the directory names ``instance-xxxxxxxx`` are
uniquely titled for that particular instance. For example, if you copy
all data from ``/var/lib/nova/instances`` on one compute node to
another, you do not overwrite any files or cause any damage to images
that have the same unique name, because they are essentially the same
file.
Although this method is not documented or supported, you can use it when
your compute node is permanently offline but you have instances locally
stored on it.

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========================
Configuration Management
========================
Maintaining an OpenStack cloud requires that you manage multiple
physical servers, and this number might grow over time. Because managing
nodes manually is error prone, we strongly recommend that you use a
configuration-management tool. These tools automate the process of
ensuring that all your nodes are configured properly and encourage you
to maintain your configuration information (such as packages and
configuration options) in a version-controlled repository.
.. note::
Several configuration-management tools are available, and this guide does
not recommend a specific one. The most popular ones in the OpenStack
community are:
* `Puppet <https://puppetlabs.com/>`_, with available `OpenStack
Puppet modules <https://github.com/puppetlabs/puppetlabs-openstack>`_
* `Ansible <https://www.ansible.com/>`_, with `OpenStack Ansible
<https://github.com/openstack/openstack-ansible>`_
* `Chef <http://www.getchef.com/chef/>`_, with available `OpenStack Chef
recipes <https://github.com/openstack/openstack-chef-repo>`_
Other newer configuration tools include `Juju <https://juju.ubuntu.com/>`_
and `Salt <http://www.saltstack.com/>`_; and more mature configuration
management tools include `CFEngine <http://cfengine.com/>`_ and `Bcfg2
<http://bcfg2.org/>`_.

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===========================================================
Cloud Controller and Storage Proxy Failures and Maintenance
===========================================================
The cloud controller and storage proxy are very similar to each other
when it comes to expected and unexpected downtime. One of each server
type typically runs in the cloud, which makes them very noticeable when
they are not running.
For the cloud controller, the good news is if your cloud is using the
FlatDHCP multi-host HA network mode, existing instances and volumes
continue to operate while the cloud controller is offline. For the
storage proxy, however, no storage traffic is possible until it is back
up and running.
Planned Maintenance
~~~~~~~~~~~~~~~~~~~
One way to plan for cloud controller or storage proxy maintenance is to
simply do it off-hours, such as at 1 a.m. or 2 a.m. This strategy
affects fewer users. If your cloud controller or storage proxy is too
important to have unavailable at any point in time, you must look into
high-availability options.
Rebooting a Cloud Controller or Storage Proxy
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
All in all, just issue the :command:`reboot` command. The operating system
cleanly shuts down services and then automatically reboots. If you want
to be very thorough, run your backup jobs just before you
reboot.
After a cloud controller reboots, ensure that all required services were
successfully started. The following commands use :command:`ps` and
:command:`grep` to determine if nova, glance, and keystone are currently
running:
.. code-block:: console
# ps aux | grep nova-
# ps aux | grep glance-
# ps aux | grep keystone
# ps aux | grep cinder
Also check that all services are functioning. The following set of
commands sources the ``openrc`` file, then runs some basic glance, nova,
and openstack commands. If the commands work as expected, you can be
confident that those services are in working condition:
.. code-block:: console
# . openrc
# openstack image list
# openstack server list
# openstack project list
For the storage proxy, ensure that the :term:`Object Storage service <Object
Storage service (swift)>` has resumed:
.. code-block:: console
# ps aux | grep swift
Also check that it is functioning:
.. code-block:: console
# swift stat
Total Cloud Controller Failure
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The cloud controller could completely fail if, for example, its
motherboard goes bad. Users will immediately notice the loss of a cloud
controller since it provides core functionality to your cloud
environment. If your infrastructure monitoring does not alert you that
your cloud controller has failed, your users definitely will.
Unfortunately, this is a rough situation. The cloud controller is an
integral part of your cloud. If you have only one controller, you will
have many missing services if it goes down.
To avoid this situation, create a highly available cloud controller
cluster. This is outside the scope of this document, but you can read
more in the `OpenStack High Availability
Guide <https://docs.openstack.org/ha-guide/index.html>`_.
The next best approach is to use a configuration-management tool, such
as Puppet, to automatically build a cloud controller. This should not
take more than 15 minutes if you have a spare server available. After
the controller rebuilds, restore any backups taken
(see :doc:`ops-backup-recovery`).
Also, in practice, the ``nova-compute`` services on the compute nodes do
not always reconnect cleanly to rabbitmq hosted on the controller when
it comes back up after a long reboot; a restart on the nova services on
the compute nodes is required.

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=========
Databases
=========
Almost all OpenStack components have an underlying database to store
persistent information. Usually this database is MySQL. Normal MySQL
administration is applicable to these databases. OpenStack does not
configure the databases out of the ordinary. Basic administration
includes performance tweaking, high availability, backup, recovery, and
repairing. For more information, see a standard MySQL administration guide.
You can perform a couple of tricks with the database to either more
quickly retrieve information or fix a data inconsistency error—for
example, an instance was terminated, but the status was not updated in
the database. These tricks are discussed throughout this book.
Database Connectivity
~~~~~~~~~~~~~~~~~~~~~
Review the component's configuration file to see how each OpenStack component
accesses its corresponding database. Look for a ``connection`` option. The
following command uses ``grep`` to display the SQL connection string for nova,
glance, cinder, and keystone:
.. code-block:: console
# grep -hE "connection ?=" \
/etc/nova/nova.conf /etc/glance/glance-*.conf \
/etc/cinder/cinder.conf /etc/keystone/keystone.conf \
/etc/neutron/neutron.conf
connection = mysql+pymysql://nova:password@cloud.example.com/nova
connection = mysql+pymysql://glance:password@cloud.example.com/glance
connection = mysql+pymysql://glance:password@cloud.example.com/glance
connection = mysql+pymysql://cinder:password@cloud.example.com/cinder
connection = mysql+pymysql://keystone:password@cloud.example.com/keystone
connection = mysql+pymysql://neutron:password@cloud.example.com/neutron
The connection strings take this format:
.. code-block:: console
mysql+pymysql:// <username> : <password> @ <hostname> / <database name>
Performance and Optimizing
~~~~~~~~~~~~~~~~~~~~~~~~~~
As your cloud grows, MySQL is utilized more and more. If you suspect
that MySQL might be becoming a bottleneck, you should start researching
MySQL optimization. The MySQL manual has an entire section dedicated to
this topic: `Optimization Overview
<http://dev.mysql.com/doc/refman/5.5/en/optimize-overview.html>`_.

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=====================================
Determining Which Component Is Broken
=====================================
OpenStack's collection of different components interact with each other
strongly. For example, uploading an image requires interaction from
``nova-api``, ``glance-api``, ``glance-registry``, keystone, and
potentially ``swift-proxy``. As a result, it is sometimes difficult to
determine exactly where problems lie. Assisting in this is the purpose
of this section.
Tailing Logs
~~~~~~~~~~~~
The first place to look is the log file related to the command you are
trying to run. For example, if ``openstack server list`` is failing, try
tailing a nova log file and running the command again:
Terminal 1:
.. code-block:: console
# tail -f /var/log/nova/nova-api.log
Terminal 2:
.. code-block:: console
# openstack server list
Look for any errors or traces in the log file. For more information, see
:doc:`ops-logging-monitoring`.
If the error indicates that the problem is with another component,
switch to tailing that component's log file. For example, if nova cannot
access glance, look at the ``glance-api`` log:
Terminal 1:
.. code-block:: console
# tail -f /var/log/glance/api.log
Terminal 2:
.. code-block:: console
# openstack server list
Wash, rinse, and repeat until you find the core cause of the problem.
Running Daemons on the CLI
~~~~~~~~~~~~~~~~~~~~~~~~~~
Unfortunately, sometimes the error is not apparent from the log files.
In this case, switch tactics and use a different command; maybe run the
service directly on the command line. For example, if the ``glance-api``
service refuses to start and stay running, try launching the daemon from
the command line:
.. code-block:: console
# sudo -u glance -H glance-api
This might print the error and cause of the problem.
.. note::
The ``-H`` flag is required when running the daemons with sudo
because some daemons will write files relative to the user's home
directory, and this write may fail if ``-H`` is left off.
.. Tip::
**Example of Complexity**
One morning, a compute node failed to run any instances. The log files
were a bit vague, claiming that a certain instance was unable to be
started. This ended up being a red herring because the instance was
simply the first instance in alphabetical order, so it was the first
instance that ``nova-compute`` would touch.
Further troubleshooting showed that libvirt was not running at all. This
made more sense. If libvirt wasn't running, then no instance could be
virtualized through KVM. Upon trying to start libvirt, it would silently
die immediately. The libvirt logs did not explain why.
Next, the ``libvirtd`` daemon was run on the command line. Finally a
helpful error message: it could not connect to d-bus. As ridiculous as
it sounds, libvirt, and thus ``nova-compute``, relies on d-bus and
somehow d-bus crashed. Simply starting d-bus set the entire chain back
on track, and soon everything was back up and running.

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=====================
Working with Hardware
=====================
As for your initial deployment, you should ensure that all hardware is
appropriately burned in before adding it to production. Run software
that uses the hardware to its limits—maxing out RAM, CPU, disk, and
network. Many options are available, and normally double as benchmark
software, so you also get a good idea of the performance of your
system.
Adding a Compute Node
~~~~~~~~~~~~~~~~~~~~~
If you find that you have reached or are reaching the capacity limit of
your computing resources, you should plan to add additional compute
nodes. Adding more nodes is quite easy. The process for adding compute
nodes is the same as when the initial compute nodes were deployed to
your cloud: use an automated deployment system to bootstrap the
bare-metal server with the operating system and then have a
configuration-management system install and configure OpenStack Compute.
Once the Compute service has been installed and configured in the same
way as the other compute nodes, it automatically attaches itself to the
cloud. The cloud controller notices the new node(s) and begins
scheduling instances to launch there.
If your OpenStack Block Storage nodes are separate from your compute
nodes, the same procedure still applies because the same queuing and
polling system is used in both services.
We recommend that you use the same hardware for new compute and block
storage nodes. At the very least, ensure that the CPUs are similar in
the compute nodes to not break live migration.
Adding an Object Storage Node
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Adding a new object storage node is different from adding compute or
block storage nodes. You still want to initially configure the server by
using your automated deployment and configuration-management systems.
After that is done, you need to add the local disks of the object
storage node into the object storage ring. The exact command to do this
is the same command that was used to add the initial disks to the ring.
Simply rerun this command on the object storage proxy server for all
disks on the new object storage node. Once this has been done, rebalance
the ring and copy the resulting ring files to the other storage nodes.
.. note::
If your new object storage node has a different number of disks than
the original nodes have, the command to add the new node is
different from the original commands. These parameters vary from
environment to environment.
Replacing Components
~~~~~~~~~~~~~~~~~~~~
Failures of hardware are common in large-scale deployments such as an
infrastructure cloud. Consider your processes and balance time saving
against availability. For example, an Object Storage cluster can easily
live with dead disks in it for some period of time if it has sufficient
capacity. Or, if your compute installation is not full, you could
consider live migrating instances off a host with a RAM failure until
you have time to deal with the problem.

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=====
HDWMY
=====
Here's a quick list of various to-do items for each hour, day, week,
month, and year. Please note that these tasks are neither required nor
definitive but helpful ideas:
Hourly
~~~~~~
* Check your monitoring system for alerts and act on them.
* Check your ticket queue for new tickets.
Daily
~~~~~
* Check for instances in a failed or weird state and investigate why.
* Check for security patches and apply them as needed.
Weekly
~~~~~~
* Check cloud usage:
* User quotas
* Disk space
* Image usage
* Large instances
* Network usage (bandwidth and IP usage)
* Verify your alert mechanisms are still working.
Monthly
~~~~~~~
* Check usage and trends over the past month.
* Check for user accounts that should be removed.
* Check for operator accounts that should be removed.
Quarterly
~~~~~~~~~
* Review usage and trends over the past quarter.
* Prepare any quarterly reports on usage and statistics.
* Review and plan any necessary cloud additions.
* Review and plan any major OpenStack upgrades.
Semiannually
~~~~~~~~~~~~
* Upgrade OpenStack.
* Clean up after an OpenStack upgrade (any unused or new services to be
aware of?).

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========================
RabbitMQ troubleshooting
========================
This section provides tips on resolving common RabbitMQ issues.
RabbitMQ service hangs
~~~~~~~~~~~~~~~~~~~~~~
It is quite common for the RabbitMQ service to hang when it is
restarted or stopped. Therefore, it is highly recommended that
you manually restart RabbitMQ on each controller node.
.. note::
The RabbitMQ service name may vary depending on your operating
system or vendor who supplies your RabbitMQ service.
#. Restart the RabbitMQ service on the first controller node. The
:command:`service rabbitmq-server restart` command may not work
in certain situations, so it is best to use:
.. code-block:: console
# service rabbitmq-server stop
# service rabbitmq-server start
#. If the service refuses to stop, then run the :command:`pkill` command
to stop the service, then restart the service:
.. code-block:: console
# pkill -KILL -u rabbitmq
# service rabbitmq-server start
#. Verify RabbitMQ processes are running:
.. code-block:: console
# ps -ef | grep rabbitmq
# rabbitmqctl list_queues
# rabbitmqctl list_queues 2>&1 | grep -i error
#. If there are errors, run the :command:`cluster_status` command to make sure
there are no partitions:
.. code-block:: console
# rabbitmqctl cluster_status
For more information, see `RabbitMQ documentation
<https://www.rabbitmq.com/partitions.html>`_.
#. Go back to the first step and try restarting the RabbitMQ service again. If
you still have errors, remove the contents in the
``/var/lib/rabbitmq/mnesia/`` directory between stopping and starting the
RabbitMQ service.
#. If there are no errors, restart the RabbitMQ service on the next controller
node.
Since the Liberty release, OpenStack services will automatically recover from
a RabbitMQ outage. You should only consider restarting OpenStack services
after checking if RabbitMQ heartbeat functionality is enabled, and if
OpenStack services are not picking up messages from RabbitMQ queues.
RabbitMQ alerts
~~~~~~~~~~~~~~~
If you receive alerts for RabbitMQ, take the following steps to troubleshoot
and resolve the issue:
#. Determine which servers the RabbitMQ alarms are coming from.
#. Attempt to boot a nova instance in the affected environment.
#. If you cannot launch an instance, continue to troubleshoot the issue.
#. Log in to each of the controller nodes for the affected environment, and
check the ``/var/log/rabbitmq`` log files for any reported issues.
#. Look for connection issues identified in the log files.
#. For each controller node in your environment, view the ``/etc/init.d``
directory to check it contains nova*, cinder*, neutron*, or
glance*. Also check RabbitMQ message queues that are growing without being
consumed which will indicate which OpenStack service is affected. Restart
the affected OpenStack service.
#. For each compute node your environment, view the ``/etc/init.d`` directory
and check if it contains nova*, cinder*, neutron*, or glance*, Also check
RabbitMQ message queues that are growing without being consumed which will
indicate which OpenStack services are affected. Restart the affected
OpenStack services.
#. Open OpenStack Dashboard and launch an instance. If the instance launches,
the issue is resolved.
#. If you cannot launch an instance, check the ``/var/log/rabbitmq`` log
files for reported connection issues.
#. Restart the RabbitMQ service on all of the controller nodes:
.. code-block:: console
# service rabbitmq-server stop
# service rabbitmq-server start
.. note::
This step applies if you have already restarted only the OpenStack components, and
cannot connect to the RabbitMQ service.
#. Repeat steps 7-8.
Excessive database management memory consumption
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Since the Liberty release, OpenStack with RabbitMQ 3.4.x or 3.6.x has an issue
with the management database consuming the memory allocated to RabbitMQ.
This is caused by statistics collection and processing. When a single node
with RabbitMQ reaches its memory threshold, all exchange and queue processing
is halted until the memory alarm recovers.
To address this issue:
#. Check memory consumption:
.. code-block:: console
# rabbitmqctl status
#. Edit the ``/etc/rabbitmq/rabbitmq.config`` configuration file, and change
the ``collect_statistics_interval`` parameter between 30000-60000
milliseconds. Alternatively you can turn off statistics collection by
setting ``collect_statistics`` parameter to "none".
File descriptor limits when scaling a cloud environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A cloud environment that is scaled to a certain size will require the file
descriptor limits to be adjusted.
Run the :command:`rabbitmqctl status` to view the current file descriptor
limits:
.. code-block:: console
"{file_descriptors,
[{total_limit,3996},
{total_used,135},
{sockets_limit,3594},
{sockets_used,133}]},"
Adjust the appropriate limits in the
``/etc/security/limits.conf`` configuration file.

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=========================================
What to do when things are running slowly
=========================================
When you are getting slow responses from various services, it can be
hard to know where to start looking. The first thing to check is the
extent of the slowness: is it specific to a single service, or varied
among different services? If your problem is isolated to a specific
service, it can temporarily be fixed by restarting the service, but that
is often only a fix for the symptom and not the actual problem.
This is a collection of ideas from experienced operators on common
things to look at that may be the cause of slowness. It is not, however,
designed to be an exhaustive list.
OpenStack Identity service
~~~~~~~~~~~~~~~~~~~~~~~~~~
If OpenStack :term:`Identity service <Identity service (keystone)>` is
responding slowly, it could be due to the token table getting large.
This can be fixed by running the :command:`keystone-manage token_flush`
command.
Additionally, for Identity-related issues, try the tips
in :ref:`sql_backend`.
OpenStack Image service
~~~~~~~~~~~~~~~~~~~~~~~
OpenStack :term:`Image service <Image service (glance)>` can be slowed down
by things related to the Identity service, but the Image service itself can be
slowed down if connectivity to the back-end storage in use is slow or otherwise
problematic. For example, your back-end NFS server might have gone down.
OpenStack Block Storage service
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
OpenStack :term:`Block Storage service <Block Storage service (cinder)>` is
similar to the Image service, so start by checking Identity-related services,
and the back-end storage.
Additionally, both the Block Storage and Image services rely on AMQP and
SQL functionality, so consider these when debugging.
OpenStack Compute service
~~~~~~~~~~~~~~~~~~~~~~~~~
Services related to OpenStack Compute are normally fairly fast and rely
on a couple of backend services: Identity for authentication and
authorization), and AMQP for interoperability. Any slowness related to
services is normally related to one of these. Also, as with all other
services, SQL is used extensively.
OpenStack Networking service
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Slowness in the OpenStack :term:`Networking service <Networking service
(neutron)>` can be caused by services that it relies upon, but it can
also be related to either physical or virtual networking. For example:
network namespaces that do not exist or are not tied to interfaces correctly;
DHCP daemons that have hung or are not running; a cable being physically
disconnected; a switch not being configured correctly. When debugging
Networking service problems, begin by verifying all physical networking
functionality (switch configuration, physical cabling, etc.). After the
physical networking is verified, check to be sure all of the Networking
services are running (neutron-server, neutron-dhcp-agent, etc.), then check
on AMQP and SQL back ends.
AMQP broker
~~~~~~~~~~~
Regardless of which AMQP broker you use, such as RabbitMQ, there are
common issues which not only slow down operations, but can also cause
real problems. Sometimes messages queued for services stay on the queues
and are not consumed. This can be due to dead or stagnant services and
can be commonly cleared up by either restarting the AMQP-related
services or the OpenStack service in question.
.. _sql_backend:
SQL back end
~~~~~~~~~~~~
Whether you use SQLite or an RDBMS (such as MySQL), SQL interoperability
is essential to a functioning OpenStack environment. A large or
fragmented SQLite file can cause slowness when using files as a back
end. A locked or long-running query can cause delays for most RDBMS
services. In this case, do not kill the query immediately, but look into
it to see if it is a problem with something that is hung, or something
that is just taking a long time to run and needs to finish on its own.
The administration of an RDBMS is outside the scope of this document,
but it should be noted that a properly functioning RDBMS is essential to
most OpenStack services.

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=====================================
Storage Node Failures and Maintenance
=====================================
Because of the high redundancy of Object Storage, dealing with object
storage node issues is a lot easier than dealing with compute node
issues.
Rebooting a Storage Node
~~~~~~~~~~~~~~~~~~~~~~~~
If a storage node requires a reboot, simply reboot it. Requests for data
hosted on that node are redirected to other copies while the server is
rebooting.
Shutting Down a Storage Node
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If you need to shut down a storage node for an extended period of time
(one or more days), consider removing the node from the storage ring.
For example:
.. code-block:: console
# swift-ring-builder account.builder remove <ip address of storage node>
# swift-ring-builder container.builder remove <ip address of storage node>
# swift-ring-builder object.builder remove <ip address of storage node>
# swift-ring-builder account.builder rebalance
# swift-ring-builder container.builder rebalance
# swift-ring-builder object.builder rebalance
Next, redistribute the ring files to the other nodes:
.. code-block:: console
# for i in s01.example.com s02.example.com s03.example.com
> do
> scp *.ring.gz $i:/etc/swift
> done
These actions effectively take the storage node out of the storage
cluster.
When the node is able to rejoin the cluster, just add it back to the
ring. The exact syntax you use to add a node to your swift cluster with
``swift-ring-builder`` heavily depends on the original options used when
you originally created your cluster. Please refer back to those
commands.
Replacing a Swift Disk
~~~~~~~~~~~~~~~~~~~~~~
If a hard drive fails in an Object Storage node, replacing it is
relatively easy. This assumes that your Object Storage environment is
configured correctly, where the data that is stored on the failed drive
is also replicated to other drives in the Object Storage environment.
This example assumes that ``/dev/sdb`` has failed.
First, unmount the disk:
.. code-block:: console
# umount /dev/sdb
Next, physically remove the disk from the server and replace it with a
working disk.
Ensure that the operating system has recognized the new disk:
.. code-block:: console
# dmesg | tail
You should see a message about ``/dev/sdb``.
Because it is recommended to not use partitions on a swift disk, simply
format the disk as a whole:
.. code-block:: console
# mkfs.xfs /dev/sdb
Finally, mount the disk:
.. code-block:: console
# mount -a
Swift should notice the new disk and that no data exists. It then begins
replicating the data to the disk from the other existing replicas.

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====================================
Maintenance, Failures, and Debugging
====================================
.. toctree::
:maxdepth: 2
ops-maintenance-controller.rst
ops-maintenance-compute.rst
ops-maintenance-storage.rst
ops-maintenance-complete.rst
ops-maintenance-configuration.rst
ops-maintenance-hardware.rst
ops-maintenance-database.rst
ops-maintenance-rabbitmq.rst
ops-maintenance-hdmwy.rst
ops-maintenance-determine.rst
ops-maintenance-slow.rst
ops-uninstall.rst
Downtime, whether planned or unscheduled, is a certainty when running a
cloud. This chapter aims to provide useful information for dealing
proactively, or reactively, with these occurrences.

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==========
Monitoring
==========
There are two types of monitoring: watching for problems and watching
usage trends. The former ensures that all services are up and running,
creating a functional cloud. The latter involves monitoring resource
usage over time in order to make informed decisions about potential
bottlenecks and upgrades.
Process Monitoring
~~~~~~~~~~~~~~~~~~
A basic type of alert monitoring is to simply check and see whether a
required process is running. For example, ensure that
the ``nova-api`` service is running on the cloud controller:
.. code-block:: console
# ps aux | grep nova-api
nova 12786 0.0 0.0 37952 1312 ? Ss Feb11 0:00 su -s /bin/sh -c exec nova-api
--config-file=/etc/nova/nova.conf nova
nova 12787 0.0 0.1 135764 57400 ? S Feb11 0:01 /usr/bin/python
/usr/bin/nova-api --config-file=/etc/nova/nova.conf
nova 12792 0.0 0.0 96052 22856 ? S Feb11 0:01 /usr/bin/python
/usr/bin/nova-api --config-file=/etc/nova/nova.conf
nova 12793 0.0 0.3 290688 115516 ? S Feb11 1:23 /usr/bin/python
/usr/bin/nova-api --config-file=/etc/nova/nova.conf
nova 12794 0.0 0.2 248636 77068 ? S Feb11 0:04 /usr/bin/python
/usr/bin/nova-api --config-file=/etc/nova/nova.conf
root 24121 0.0 0.0 11688 912 pts/5 S+ 13:07 0:00 grep nova-api
The OpenStack processes that should be monitored depend on the specific
configuration of the environment, but can include:
**Compute service (nova)**
* nova-api
* nova-scheduler
* nova-conductor
* nova-novncproxy
* nova-compute
**Block Storage service (cinder)**
* cinder-volume
* cinder-api
* cinder-scheduler
**Networking service (neutron)**
* neutron-api
* neutron-server
* neutron-openvswitch-agent
* neutron-dhcp-agent
* neutron-l3-agent
* neutron-metadata-agent
**Image service (glance)**
* glance-api
* glance-registry
**Identity service (keystone)**
The keystone processes are run within Apache as WSGI applications.
Resource Alerting
~~~~~~~~~~~~~~~~~
Resource alerting provides notifications when one or more resources are
critically low. While the monitoring thresholds should be tuned to your
specific OpenStack environment, monitoring resource usage is not
specific to OpenStack at all—any generic type of alert will work
fine.
Some of the resources that you want to monitor include:
* Disk usage
* Server load
* Memory usage
* Network I/O
* Available vCPUs
Telemetry Service
~~~~~~~~~~~~~~~~~
The Telemetry service (:term:`ceilometer`) collects
metering and event data relating to OpenStack services. Data collected
by the Telemetry service could be used for billing. Depending on
deployment configuration, collected data may be accessible to users
based on the deployment configuration. The Telemetry service provides a
REST API documented at `ceilometer V2 Web API
<https://docs.openstack.org/developer/ceilometer/webapi/v2.html>`_. You can
read more about the module in the `OpenStack Administrator
Guide <https://docs.openstack.org/admin-guide/telemetry.html>`_ or
in the `developer
documentation <https://docs.openstack.org/developer/ceilometer>`_.
OpenStack Specific Resources
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Resources such as memory, disk, and CPU are generic resources that all
servers (even non-OpenStack servers) have and are important to the
overall health of the server. When dealing with OpenStack specifically,
these resources are important for a second reason: ensuring that enough
are available to launch instances. There are a few ways you can see
OpenStack resource usage.
The first is through the :command:`nova` command:
.. code-block:: console
# openstack usage list
This command displays a list of how many instances a tenant has running
and some light usage statistics about the combined instances. This
command is useful for a quick overview of your cloud, but it doesn't
really get into a lot of details.
Next, the ``nova`` database contains three tables that store usage
information.
The ``nova.quotas`` and ``nova.quota_usages`` tables store quota
information. If a tenant's quota is different from the default quota
settings, its quota is stored in the ``nova.quotas`` table. For example:
.. code-block:: mysql
mysql> select project_id, resource, hard_limit from quotas;
+----------------------------------+-----------------------------+------------+
| project_id | resource | hard_limit |
+----------------------------------+-----------------------------+------------+
| 628df59f091142399e0689a2696f5baa | metadata_items | 128 |
| 628df59f091142399e0689a2696f5baa | injected_file_content_bytes | 10240 |
| 628df59f091142399e0689a2696f5baa | injected_files | 5 |
| 628df59f091142399e0689a2696f5baa | gigabytes | 1000 |
| 628df59f091142399e0689a2696f5baa | ram | 51200 |
| 628df59f091142399e0689a2696f5baa | floating_ips | 10 |
| 628df59f091142399e0689a2696f5baa | instances | 10 |
| 628df59f091142399e0689a2696f5baa | volumes | 10 |
| 628df59f091142399e0689a2696f5baa | cores | 20 |
+----------------------------------+-----------------------------+------------+
The ``nova.quota_usages`` table keeps track of how many resources the
tenant currently has in use:
.. code-block:: mysql
mysql> select project_id, resource, in_use from quota_usages where project_id like '628%';
+----------------------------------+--------------+--------+
| project_id | resource | in_use |
+----------------------------------+--------------+--------+
| 628df59f091142399e0689a2696f5baa | instances | 1 |
| 628df59f091142399e0689a2696f5baa | ram | 512 |
| 628df59f091142399e0689a2696f5baa | cores | 1 |
| 628df59f091142399e0689a2696f5baa | floating_ips | 1 |
| 628df59f091142399e0689a2696f5baa | volumes | 2 |
| 628df59f091142399e0689a2696f5baa | gigabytes | 12 |
| 628df59f091142399e0689a2696f5baa | images | 1 |
+----------------------------------+--------------+--------+
By comparing a tenant's hard limit with their current resource usage,
you can see their usage percentage. For example, if this tenant is using
1 floating IP out of 10, then they are using 10 percent of their
floating IP quota. Rather than doing the calculation manually, you can
use SQL or the scripting language of your choice and create a formatted
report:
.. code-block:: mysql
+----------------------------------+------------+-------------+---------------+
| some_tenant |
+-----------------------------------+------------+------------+---------------+
| Resource | Used | Limit | |
+-----------------------------------+------------+------------+---------------+
| cores | 1 | 20 | 5 % |
| floating_ips | 1 | 10 | 10 % |
| gigabytes | 12 | 1000 | 1 % |
| images | 1 | 4 | 25 % |
| injected_file_content_bytes | 0 | 10240 | 0 % |
| injected_file_path_bytes | 0 | 255 | 0 % |
| injected_files | 0 | 5 | 0 % |
| instances | 1 | 10 | 10 % |
| key_pairs | 0 | 100 | 0 % |
| metadata_items | 0 | 128 | 0 % |
| ram | 512 | 51200 | 1 % |
| reservation_expire | 0 | 86400 | 0 % |
| security_group_rules | 0 | 20 | 0 % |
| security_groups | 0 | 10 | 0 % |
| volumes | 2 | 10 | 20 % |
+-----------------------------------+------------+------------+---------------+
The preceding information was generated by using a custom script that
can be found on
`GitHub <https://github.com/cybera/novac/blob/dev/libexec/novac-quota-report>`_.
.. note::
This script is specific to a certain OpenStack installation and must
be modified to fit your environment. However, the logic should
easily be transferable.
Intelligent Alerting
~~~~~~~~~~~~~~~~~~~~
Intelligent alerting can be thought of as a form of continuous
integration for operations. For example, you can easily check to see
whether the Image service is up and running by ensuring that
the ``glance-api`` and ``glance-registry`` processes are running or by
seeing whether ``glance-api`` is responding on port 9292.
But how can you tell whether images are being successfully uploaded to
the Image service? Maybe the disk that Image service is storing the
images on is full or the S3 back end is down. You could naturally check
this by doing a quick image upload:
.. code-block:: bash
#!/bin/bash
#
# assumes that reasonable credentials have been stored at
# /root/auth
. /root/openrc
wget http://download.cirros-cloud.net/0.3.5/cirros-0.3.5-x86_64-disk.img
openstack image create --name='cirros image' --public \
--container-format=bare --disk-format=qcow2 \
--file cirros-0.3.5-x86_64-disk.img
By taking this script and rolling it into an alert for your monitoring
system (such as Nagios), you now have an automated way of ensuring that
image uploads to the Image Catalog are working.
.. note::
You must remove the image after each test. Even better, test whether
you can successfully delete an image from the Image service.
Intelligent alerting takes considerably more time to plan and implement
than the other alerts described in this chapter. A good outline to
implement intelligent alerting is:
- Review common actions in your cloud.
- Create ways to automatically test these actions.
- Roll these tests into an alerting system.
Some other examples for Intelligent Alerting include:
- Can instances launch and be destroyed?
- Can users be created?
- Can objects be stored and deleted?
- Can volumes be created and destroyed?
Trending
~~~~~~~~
Trending can give you great insight into how your cloud is performing
day to day. You can learn, for example, if a busy day was simply a rare
occurrence or if you should start adding new compute nodes.
Trending takes a slightly different approach than alerting. While
alerting is interested in a binary result (whether a check succeeds or
fails), trending records the current state of something at a certain
point in time. Once enough points in time have been recorded, you can
see how the value has changed over time.
All of the alert types mentioned earlier can also be used for trend
reporting. Some other trend examples include:
* The number of instances on each compute node
* The types of flavors in use
* The number of volumes in use
* The number of Object Storage requests each hour
* The number of ``nova-api`` requests each hour
* The I/O statistics of your storage services
As an example, recording ``nova-api`` usage can allow you to track the
need to scale your cloud controller. By keeping an eye on ``nova-api``
requests, you can determine whether you need to spawn more ``nova-api``
processes or go as far as introducing an entirely new server to run
``nova-api``. To get an approximate count of the requests, look for
standard INFO messages in ``/var/log/nova/nova-api.log``:
.. code-block:: console
# grep INFO /var/log/nova/nova-api.log | wc
You can obtain further statistics by looking for the number of
successful requests:
.. code-block:: console
# grep " 200 " /var/log/nova/nova-api.log | wc
By running this command periodically and keeping a record of the result,
you can create a trending report over time that shows whether your
``nova-api`` usage is increasing, decreasing, or keeping steady.
A tool such as **collectd** can be used to store this information. While
collectd is out of the scope of this book, a good starting point would
be to use collectd to store the result as a COUNTER data type. More
information can be found in `collectd's
documentation <https://collectd.org/wiki/index.php/Data_source>`_.
Monitoring Tools
~~~~~~~~~~~~~~~~
Nagios
------
Nagios is an open source monitoring service. It is capable of executing
arbitrary commands to check the status of server and network services,
remotely executing arbitrary commands directly on servers, and allowing
servers to push notifications back in the form of passive monitoring.
Nagios has been around since 1999. Although newer monitoring services
are available, Nagios is a tried-and-true systems administration
staple.
You can create automated alerts for critical processes by using Nagios
and NRPE. For example, to ensure that the ``nova-compute`` process is
running on the compute nodes, create an alert on your Nagios server:
.. code-block:: none
define service {
host_name c01.example.com
check_command check_nrpe_1arg!check_nova-compute
use generic-service
notification_period 24x7
contact_groups sysadmins
service_description nova-compute
}
On the Compute node, create the following NRPE
configuration:
.. code-block:: ini
command[check_nova-compute]=/usr/lib/nagios/plugins/check_procs -c 1: -a nova-compute
Nagios checks that at least one ``nova-compute`` service is running at
all times.
For resource alerting, for example, monitor disk capacity on a compute node
with Nagios, add the following to your Nagios configuration:
.. code-block:: none
define service {
host_name c01.example.com
check_command check_nrpe!check_all_disks!20% 10%
use generic-service
contact_groups sysadmins
service_description Disk
}
On the compute node, add the following to your NRPE configuration:
.. code-block:: none
command[check_all_disks]=/usr/lib/nagios/plugins/check_disk -w $ARG1$ -c $ARG2$ -e
Nagios alerts you with a `WARNING` when any disk on the compute node is 80
percent full and `CRITICAL` when 90 percent is full.
StackTach
---------
StackTach is a tool that collects and reports the notifications sent by
nova. Notifications are essentially the same as logs but can be much
more detailed. Nearly all OpenStack components are capable of generating
notifications when significant events occur. Notifications are messages
placed on the OpenStack queue (generally RabbitMQ) for consumption by
downstream systems. An overview of notifications can be found at `System
Usage
Data <https://wiki.openstack.org/wiki/SystemUsageData>`_.
To enable nova to send notifications, add the following to the
``nova.conf`` configuration file:
.. code-block:: ini
notification_topics=monitor
notification_driver=messagingv2
Once nova is sending notifications, install and configure StackTach.
StackTach works for queue consumption and pipeline processing are
configured to read these notifications from RabbitMQ servers and store
them in a database. Users can inquire on instances, requests, and servers
by using the browser interface or command-line tool,
`Stacky <https://github.com/rackerlabs/stacky>`_. Since StackTach is
relatively new and constantly changing, installation instructions
quickly become outdated. Refer to the `StackTach Git
repository <https://git.openstack.org/cgit/openstack/stacktach>`_ for
instructions as well as a demostration video. Additional details on the latest
developments can be discovered at the `official
page <http://stacktach.com/>`_
Logstash
~~~~~~~~
Logstash is a high performance indexing and search engine for logs. Logs
from Jenkins test runs are sent to logstash where they are indexed and
stored. Logstash facilitates reviewing logs from multiple sources in a
single test run, searching for errors or particular events within a test
run, and searching for log event trends across test runs.
There are four major layers in Logstash setup which are:
* Log Pusher
* Log Indexer
* ElasticSearch
* Kibana
Each layer scales horizontally. As the number of logs grows you can add
more log pushers, more Logstash indexers, and more ElasticSearch nodes.
Logpusher is a pair of Python scripts that first listens to Jenkins
build events, then converts them into Gearman jobs. Gearman provides a
generic application framework to farm out work to other machines or
processes that are better suited to do the work. It allows you to do
work in parallel, to load balance processing, and to call functions
between languages. Later, Logpusher performs Gearman jobs to push log
files into logstash. Logstash indexer reads these log events, filters
them to remove unwanted lines, collapse multiple events together, and
parses useful information before shipping them to ElasticSearch for
storage and indexing. Kibana is a logstash oriented web client for
ElasticSearch.

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=================================================
Planning for deploying and provisioning OpenStack
=================================================
The decisions you make with respect to provisioning and deployment will
affect your maintenance of the cloud. Your configuration management will be
able to evolve over time. However, more thought and design need to be done
for upfront choices about deployment, disk partitioning, and network
configuration.
A critical part of a cloud's scalability is the amount of effort that it
takes to run your cloud. To minimize the operational cost of running
your cloud, set up and use an automated deployment and configuration
infrastructure with a configuration management system, such as :term:`Puppet`
or :term:`Chef`. Combined, these systems greatly reduce manual effort and the
chance for operator error.
This infrastructure includes systems to automatically install the
operating system's initial configuration and later coordinate the
configuration of all services automatically and centrally, which reduces
both manual effort and the chance for error. Examples include Ansible,
CFEngine, Chef, Puppet, and Salt. You can even use OpenStack to deploy
OpenStack, named TripleO (OpenStack On OpenStack).
Automated deployment
~~~~~~~~~~~~~~~~~~~~
An automated deployment system installs and configures operating systems
on new servers, without intervention, after the absolute minimum amount
of manual work, including physical racking, MAC-to-IP assignment, and
power configuration. Typically, solutions rely on wrappers around PXE
boot and TFTP servers for the basic operating system install and then
hand off to an automated configuration management system.
Both Ubuntu and Red Hat Enterprise Linux include mechanisms for
configuring the operating system, including preseed and kickstart, that
you can use after a network boot. Typically, these are used to bootstrap
an automated configuration system. Alternatively, you can use an
image-based approach for deploying the operating system, such as
systemimager. You can use both approaches with a virtualized
infrastructure, such as when you run VMs to separate your control
services and physical infrastructure.
When you create a deployment plan, focus on a few vital areas because
they are very hard to modify post deployment. The next two sections talk
about configurations for:
- Disk partitioning and disk array setup for scalability
- Networking configuration just for PXE booting
Disk partitioning and RAID
--------------------------
At the very base of any operating system are the hard drives on which
the operating system (OS) is installed.
You must complete the following configurations on the server's hard
drives:
- Partitioning, which provides greater flexibility for layout of
operating system and swap space, as described below.
- Adding to a RAID array (RAID stands for redundant array of
independent disks), based on the number of disks you have available,
so that you can add capacity as your cloud grows. Some options are
described in more detail below.
The simplest option to get started is to use one hard drive with two
partitions:
- File system to store files and directories, where all the data lives,
including the root partition that starts and runs the system.
- Swap space to free up memory for processes, as an independent area of
the physical disk used only for swapping and nothing else.
RAID is not used in this simplistic one-drive setup because generally
for production clouds, you want to ensure that if one disk fails,
another can take its place. Instead, for production, use more than one
disk. The number of disks determine what types of RAID arrays to build.
We recommend that you choose one of the following multiple disk options:
Option 1
Partition all drives in the same way in a horizontal fashion, as
shown in :ref:`partition_setup`.
With this option, you can assign different partitions to different
RAID arrays. You can allocate partition 1 of disk one and two to the
``/boot`` partition mirror. You can make partition 2 of all disks
the root partition mirror. You can use partition 3 of all disks for
a ``cinder-volumes`` LVM partition running on a RAID 10 array.
.. _partition_setup:
.. figure:: figures/osog_0201.png
Partition setup of drives
While you might end up with unused partitions, such as partition 1
in disk three and four of this example, this option allows for
maximum utilization of disk space. I/O performance might be an issue
as a result of all disks being used for all tasks.
Option 2
Add all raw disks to one large RAID array, either hardware or
software based. You can partition this large array with the boot,
root, swap, and LVM areas. This option is simple to implement and
uses all partitions. However, disk I/O might suffer.
Option 3
Dedicate entire disks to certain partitions. For example, you could
allocate disk one and two entirely to the boot, root, and swap
partitions under a RAID 1 mirror. Then, allocate disk three and four
entirely to the LVM partition, also under a RAID 1 mirror. Disk I/O
should be better because I/O is focused on dedicated tasks. However,
the LVM partition is much smaller.
.. tip::
You may find that you can automate the partitioning itself. For
example, MIT uses `Fully Automatic Installation
(FAI) <http://fai-project.org/>`_ to do the initial PXE-based
partition and then install using a combination of min/max and
percentage-based partitioning.
As with most architecture choices, the right answer depends on your
environment. If you are using existing hardware, you know the disk
density of your servers and can determine some decisions based on the
options above. If you are going through a procurement process, your
user's requirements also help you determine hardware purchases. Here are
some examples from a private cloud providing web developers custom
environments at AT&T. This example is from a specific deployment, so
your existing hardware or procurement opportunity may vary from this.
AT&T uses three types of hardware in its deployment:
- Hardware for controller nodes, used for all stateless OpenStack API
services. About 32–64 GB memory, small attached disk, one processor,
varied number of cores, such as 6–12.
- Hardware for compute nodes. Typically 256 or 144 GB memory, two
processors, 24 cores. 4–6 TB direct attached storage, typically in a
RAID 5 configuration.
- Hardware for storage nodes. Typically for these, the disk space is
optimized for the lowest cost per GB of storage while maintaining
rack-space efficiency.
Again, the right answer depends on your environment. You have to make
your decision based on the trade-offs between space utilization,
simplicity, and I/O performance.
Network configuration
---------------------
.. TODO Reference to networking sections in the following paragraph.
Network configuration is a very large topic that spans multiple areas of
this book. For now, make sure that your servers can PXE boot and
successfully communicate with the deployment server.
For example, you usually cannot configure NICs for VLANs when PXE
booting. Additionally, you usually cannot PXE boot with bonded NICs. If
you run into this scenario, consider using a simple 1 GB switch in a
private network on which only your cloud communicates.
Automated configuration
~~~~~~~~~~~~~~~~~~~~~~~
The purpose of automatic configuration management is to establish and
maintain the consistency of a system without using human intervention.
You want to maintain consistency in your deployments so that you can
have the same cloud every time, repeatably. Proper use of automatic
configuration-management tools ensures that components of the cloud
systems are in particular states, in addition to simplifying deployment,
and configuration change propagation.
These tools also make it possible to test and roll back changes, as they
are fully repeatable. Conveniently, a large body of work has been done
by the OpenStack community in this space. Puppet, a configuration
management tool, even provides official modules for OpenStack projects
in an OpenStack infrastructure system known as `Puppet
OpenStack <https://wiki.openstack.org/wiki/Puppet>`_. Chef
configuration management is provided within
https://git.openstack.org/cgit/openstack/openstack-chef-repo. Additional
configuration management systems include Juju, Ansible, and Salt. Also,
PackStack is a command-line utility for Red Hat Enterprise Linux and
derivatives that uses Puppet modules to support rapid deployment of
OpenStack on existing servers over an SSH connection.
An integral part of a configuration-management system is the item that
it controls. You should carefully consider all of the items that you
want, or do not want, to be automatically managed. For example, you may
not want to automatically format hard drives with user data.
Remote management
~~~~~~~~~~~~~~~~~
In our experience, most operators don't sit right next to the servers
running the cloud, and many don't necessarily enjoy visiting the data
center. OpenStack should be entirely remotely configurable, but
sometimes not everything goes according to plan.
In this instance, having an out-of-band access into nodes running
OpenStack components is a boon. The IPMI protocol is the de facto
standard here, and acquiring hardware that supports it is highly
recommended to achieve that lights-out data center aim.
In addition, consider remote power control as well. While IPMI usually
controls the server's power state, having remote access to the PDU that
the server is plugged into can really be useful for situations when
everything seems wedged.
Other considerations
~~~~~~~~~~~~~~~~~~~~
.. TODO In the first paragraph, reference to use case sections.
You can save time by understanding the use cases for the cloud you want
to create. Use cases for OpenStack are varied. Some include object
storage only; others require preconfigured compute resources to speed
development-environment set up; and others need fast provisioning of
compute resources that are already secured per tenant with private
networks. Your users may have need for highly redundant servers to make
sure their legacy applications continue to run. Perhaps a goal would be
to architect these legacy applications so that they run on multiple
instances in a cloudy, fault-tolerant way, but not make it a goal to add
to those clusters over time. Your users may indicate that they need
scaling considerations because of heavy Windows server use.
You can save resources by looking at the best fit for the hardware you
have in place already. You might have some high-density storage hardware
available. You could format and repurpose those servers for OpenStack
Object Storage. All of these considerations and input from users help
you build your use case and your deployment plan.
.. tip::
For further research about OpenStack deployment, investigate the
supported and documented preconfigured, prepackaged installers for
OpenStack from companies such as
`Canonical <https://www.ubuntu.com/cloud/openstack>`_,
`Cisco <http://www.cisco.com/c/en/us/solutions/data-center-virtualization/openstack-at-cisco/index.html>`_,
`Cloudscaling <http://www.cloudscaling.com>`_,
`IBM <http://www-03.ibm.com/software/products/en/ibm-cloud-orchestrator>`_,
`Metacloud <http://www.cisco.com/c/en/us/products/cloud-systems-management/metacloud/index.html>`_,
`Mirantis <https://www.mirantis.com>`_,
`Rackspace <https://www.rackspace.com/cloud/private>`_,
`Red Hat <https://www.redhat.com/openstack>`_,
`SUSE <https://www.suse.com/products/suse-openstack-cloud>`_,
and `SwiftStack <https://www.swiftstack.com>`_.

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=======
Summary
=======
One key element of systems administration that is often overlooked is
that end users are the reason systems administrators exist. Don't go the
BOFH route and terminate every user who causes an alert to go off. Work
with users to understand what they're trying to accomplish and see how
your environment can better assist them in achieving their goals. Meet
your users needs by organizing your users into projects, applying
policies, managing quotas, and working with them.

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===========================
Managing Projects and Users
===========================
.. toctree::
ops-projects.rst
ops-quotas.rst
ops-users.rst
ops-projects-users-summary.rst
An OpenStack cloud does not have much value without users. This chapter
covers topics that relate to managing users, projects, and quotas. This
chapter describes users and projects as described by version 2 of the
OpenStack Identity API.
Projects or Tenants?
~~~~~~~~~~~~~~~~~~~~
In OpenStack user interfaces and documentation, a group of users is
referred to as a :term:`project` or :term:`tenant`.
These terms are interchangeable.
The initial implementation of OpenStack Compute had its own
authentication system and used the term ``project``. When authentication
moved into the OpenStack Identity (keystone) project, it used the term
``tenant`` to refer to a group of users. Because of this legacy, some of
the OpenStack tools refer to projects and some refer to tenants.
.. tip::
This guide uses the term ``project``, unless an example shows
interaction with a tool that uses the term ``tenant``.

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=================
Managing Projects
=================
Users must be associated with at least one project, though they may
belong to many. Therefore, you should add at least one project before
adding users.
Adding Projects
~~~~~~~~~~~~~~~
To create a project through the OpenStack dashboard:
#. Log in as an administrative user.
#. Select the :guilabel:`Identity` tab in the left navigation bar.
#. Under Identity tab, click :guilabel:`Projects`.
#. Click the :guilabel:`Create Project` button.
You are prompted for a project name and an optional, but recommended,
description. Select the check box at the bottom of the form to enable
this project. By default, it is enabled, as shown below:
.. figure:: figures/create_project.png
:alt: Create Project form
It is also possible to add project members and adjust the project
quotas. We'll discuss those actions later, but in practice, it can be
quite convenient to deal with all these operations at one time.
To add a project through the command line, you must use the OpenStack
command line client.
.. code-block:: console
# openstack project create demo --domain default
This command creates a project named ``demo``. Optionally, you can add a
description string by appending ``--description PROJECT_DESCRIPTION``,
which can be very useful. You can also
create a project in a disabled state by appending ``--disable`` to the
command. By default, projects are created in an enabled state.

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======
Quotas
======
To prevent system capacities from being exhausted without notification,
you can set up :term:`quotas <quota>`. Quotas are operational limits. For example,
the number of gigabytes allowed per tenant can be controlled to ensure that
a single tenant cannot consume all of the disk space. Quotas are
currently enforced at the tenant (or project) level, rather than the
user level.
.. warning::
Because without sensible quotas a single tenant could use up all the
available resources, default quotas are shipped with OpenStack. You
should pay attention to which quota settings make sense for your
hardware capabilities.
Using the command-line interface, you can manage quotas for the
OpenStack Compute service and the Block Storage service.
Typically, default values are changed because a tenant requires more
than the OpenStack default of 10 volumes per tenant, or more than the
OpenStack default of 1 TB of disk space on a compute node.
.. note::
To view all tenants, run:
.. code-block:: console
$ openstack project list
+---------------------------------+----------+
| ID | Name |
+---------------------------------+----------+
| a981642d22c94e159a4a6540f70f9f8 | admin |
| 934b662357674c7b9f5e4ec6ded4d0e | tenant01 |
| 7bc1dbfd7d284ec4a856ea1eb82dca8 | tenant02 |
| 9c554aaef7804ba49e1b21cbd97d218 | services |
+---------------------------------+----------+
Set Image Quotas
~~~~~~~~~~~~~~~~
You can restrict a project's image storage by total number of bytes.
Currently, this quota is applied cloud-wide, so if you were to set an
Image quota limit of 5 GB, then all projects in your cloud will be able
to store only 5 GB of images and snapshots.
To enable this feature, edit the ``/etc/glance/glance-api.conf`` file,
and under the ``[DEFAULT]`` section, add:
.. code-block:: ini
user_storage_quota = <bytes>
For example, to restrict a project's image storage to 5 GB, do this:
.. code-block:: ini
user_storage_quota = 5368709120
.. note::
There is a configuration option in ``/etc/glance/glance-api.conf`` that limits
the number of members allowed per image, called
``image_member_quota``, set to 128 by default. That setting is a
different quota from the storage quota.
Set Compute Service Quotas
~~~~~~~~~~~~~~~~~~~~~~~~~~
As an administrative user, you can update the Compute service quotas for
an existing tenant, as well as update the quota defaults for a new
tenant. See :ref:`table_compute_quota`.
.. _table_compute_quota:
.. list-table:: Compute quota descriptions
:widths: 30 40 30
:header-rows: 1
* - Quota
- Description
- Property name
* - Fixed IPs
- Number of fixed IP addresses allowed per project.
This number must be equal to or greater than the number
of allowed instances.
- ``fixed-ips``
* - Floating IPs
- Number of floating IP addresses allowed per project.
- ``floating-ips``
* - Injected file content bytes
- Number of content bytes allowed per injected file.
- ``injected-file-content-bytes``
* - Injected file path bytes
- Number of bytes allowed per injected file path.
- ``injected-file-path-bytes``
* - Injected files
- Number of injected files allowed per project.
- ``injected-files``
* - Instances
- Number of instances allowed per project.
- ``instances``
* - Key pairs
- Number of key pairs allowed per user.
- ``key-pairs``
* - Metadata items
- Number of metadata items allowed per instance.
- ``metadata-items``
* - RAM
- Megabytes of instance RAM allowed per project.
- ``ram``
* - Security group rules
- Number of security group rules per project.
- ``security-group-rules``
* - Security groups
- Number of security groups per project.
- ``security-groups``
* - VCPUs
- Number of instance cores allowed per project.
- ``cores``
* - Server Groups
- Number of server groups per project.
- ``server_groups``
* - Server Group Members
- Number of servers per server group.
- ``server_group_members``
View and update compute quotas for a tenant (project)
-----------------------------------------------------
As an administrative user, you can use the :command:`nova quota-*`
commands, which are provided by the
``python-novaclient`` package, to view and update tenant quotas.
**To view and update default quota values**
#. List all default quotas for all tenants, as follows:
.. code-block:: console
$ nova quota-defaults
For example:
.. code-block:: console
$ nova quota-defaults
+-----------------------------+-------+
| Quota | Limit |
+-----------------------------+-------+
| instances | 10 |
| cores | 20 |
| ram | 51200 |
| floating_ips | 10 |
| fixed_ips | -1 |
| metadata_items | 128 |
| injected_files | 5 |
| injected_file_content_bytes | 10240 |
| injected_file_path_bytes | 255 |
| key_pairs | 100 |
| security_groups | 10 |
| security_group_rules | 20 |
| server_groups | 10 |
| server_group_members | 10 |
+-----------------------------+-------+
#. Update a default value for a new tenant, as follows:
.. code-block:: console
$ nova quota-class-update default key value
For example:
.. code-block:: console
$ nova quota-class-update default --instances 15
**To view quota values for a tenant (project)**
#. Place the tenant ID in a variable:
.. code-block:: console
$ tenant=$(openstack project list | awk '/tenantName/ {print $2}')
#. List the currently set quota values for a tenant, as follows:
.. code-block:: console
$ nova quota-show --tenant $tenant
For example:
.. code-block:: console
$ nova quota-show --tenant $tenant
+-----------------------------+-------+
| Quota | Limit |
+-----------------------------+-------+
| instances | 10 |
| cores | 20 |
| ram | 51200 |
| floating_ips | 10 |
| fixed_ips | -1 |
| metadata_items | 128 |
| injected_files | 5 |
| injected_file_content_bytes | 10240 |
| injected_file_path_bytes | 255 |
| key_pairs | 100 |
| security_groups | 10 |
| security_group_rules | 20 |
| server_groups | 10 |
| server_group_members | 10 |
+-----------------------------+-------+
**To update quota values for a tenant (project)**
#. Obtain the tenant ID, as follows:
.. code-block:: console
$ tenant=$(openstack project list | awk '/tenantName/ {print $2}')
#. Update a particular quota value, as follows:
.. code-block:: console
# nova quota-update --quotaName quotaValue tenantID
For example:
.. code-block:: console
# nova quota-update --floating-ips 20 $tenant
# nova quota-show --tenant $tenant
+-----------------------------+-------+
| Quota | Limit |
+-----------------------------+-------+
| instances | 10 |
| cores | 20 |
| ram | 51200 |
| floating_ips | 20 |
| fixed_ips | -1 |
| metadata_items | 128 |
| injected_files | 5 |
| injected_file_content_bytes | 10240 |
| injected_file_path_bytes | 255 |
| key_pairs | 100 |
| security_groups | 10 |
| security_group_rules | 20 |
| server_groups | 10 |
| server_group_members | 10 |
+-----------------------------+-------+
.. note::
To view a list of options for the ``nova quota-update`` command, run:
.. code-block:: console
$ nova help quota-update
Set Object Storage Quotas
~~~~~~~~~~~~~~~~~~~~~~~~~
There are currently two categories of quotas for Object Storage:
Container quotas
Limit the total size (in bytes) or number of objects that can be
stored in a single container.
Account quotas
Limit the total size (in bytes) that a user has available in the
Object Storage service.
To take advantage of either container quotas or account quotas, your
Object Storage proxy server must have ``container_quotas`` or
``account_quotas`` (or both) added to the ``[pipeline:main]`` pipeline.
Each quota type also requires its own section in the
``proxy-server.conf`` file:
.. code-block:: ini
[pipeline:main]
pipeline = catch_errors [...] slo dlo account_quotas proxy-server
[filter:account_quotas]
use = egg:swift#account_quotas
[filter:container_quotas]
use = egg:swift#container_quotas
To view and update Object Storage quotas, use the :command:`swift` command
provided by the ``python-swiftclient`` package. Any user included in the
project can view the quotas placed on their project. To update Object
Storage quotas on a project, you must have the role of ResellerAdmin in
the project that the quota is being applied to.
To view account quotas placed on a project:
.. code-block:: console
$ swift stat
Account: AUTH_b36ed2d326034beba0a9dd1fb19b70f9
Containers: 0
Objects: 0
Bytes: 0
Meta Quota-Bytes: 214748364800
X-Timestamp: 1351050521.29419
Content-Type: text/plain; charset=utf-8
Accept-Ranges: bytes
To apply or update account quotas on a project:
.. code-block:: console
$ swift post -m quota-bytes:
<bytes>
For example, to place a 5 GB quota on an account:
.. code-block:: console
$ swift post -m quota-bytes:
5368709120
To verify the quota, run the :command:`swift stat` command again:
.. code-block:: console
$ swift stat
Account: AUTH_b36ed2d326034beba0a9dd1fb19b70f9
Containers: 0
Objects: 0
Bytes: 0
Meta Quota-Bytes: 5368709120
X-Timestamp: 1351541410.38328
Content-Type: text/plain; charset=utf-8
Accept-Ranges: bytes
Set Block Storage Quotas
~~~~~~~~~~~~~~~~~~~~~~~~
As an administrative user, you can update the Block Storage service
quotas for a tenant, as well as update the quota defaults for a new
tenant. See :ref:`table_block_storage_quota`.
.. _table_block_storage_quota:
.. list-table:: Table: Block Storage quota descriptions
:widths: 50 50
:header-rows: 1
* - Property name
- Description
* - gigabytes
- Number of volume gigabytes allowed per tenant
* - snapshots
- Number of Block Storage snapshots allowed per tenant.
* - volumes
- Number of Block Storage volumes allowed per tenant
View and update Block Storage quotas for a tenant (project)
-----------------------------------------------------------
As an administrative user, you can use the :command:`cinder quota-*`
commands, which are provided by the
``python-cinderclient`` package, to view and update tenant quotas.
**To view and update default Block Storage quota values**
#. List all default quotas for all tenants, as follows:
.. code-block:: console
$ cinder quota-defaults tenantID
#. Obtain the tenant ID, as follows:
.. code-block:: console
$ tenant=$(openstack project list | awk '/tenantName/ {print $2}')
For example:
.. code-block:: console
$ cinder quota-defaults $tenant
+-----------+-------+
| Property | Value |
+-----------+-------+
| gigabytes | 1000 |
| snapshots | 10 |
| volumes | 10 |
+-----------+-------+
#. To update a default value for a new tenant, update the property in the
``/etc/cinder/cinder.conf`` file.
**To view Block Storage quotas for a tenant (project)**
#. View quotas for the tenant, as follows:
.. code-block:: console
# cinder quota-show tenantID
For example:
.. code-block:: console
# cinder quota-show $tenant
+-----------+-------+
| Property | Value |
+-----------+-------+
| gigabytes | 1000 |
| snapshots | 10 |
| volumes | 10 |
+-----------+-------+
**To update Block Storage quotas for a tenant (project)**
#. Place the tenant ID in a variable:
.. code-block:: console
$ tenant=$(openstack project list | awk '/tenantName/ {print $2}')
#. Update a particular quota value, as follows:
.. code-block:: console
# cinder quota-update --quotaName NewValue tenantID
For example:
.. code-block:: console
# cinder quota-update --volumes 15 $tenant
# cinder quota-show $tenant
+-----------+-------+
| Property | Value |
+-----------+-------+
| gigabytes | 1000 |
| snapshots | 10 |
| volumes | 15 |
+-----------+-------+

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============
Uninstalling
============
While we'd always recommend using your automated deployment system to
reinstall systems from scratch, sometimes you do need to remove
OpenStack from a system the hard way. Here's how:
* Remove all packages.
* Remove remaining files.
* Remove databases.
These steps depend on your underlying distribution, but in general you
should be looking for :command:`purge` commands in your package manager, like
:command:`aptitude purge ~c $package`. Following this, you can look for
orphaned files in the directories referenced throughout this guide. To
uninstall the database properly, refer to the manual appropriate for the
product in use.

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========
Upgrades
========
With the exception of Object Storage, upgrading from one version of
OpenStack to another can take a great deal of effort. This chapter
provides some guidance on the operational aspects that you should
consider for performing an upgrade for an OpenStack environment.
Pre-upgrade considerations
~~~~~~~~~~~~~~~~~~~~~~~~~~
Upgrade planning
----------------
- Thoroughly review the `release
notes <https://releases.openstack.org/>`_ to learn
about new, updated, and deprecated features. Find incompatibilities
between versions.
- Consider the impact of an upgrade to users. The upgrade process
interrupts management of your environment including the dashboard. If
you properly prepare for the upgrade, existing instances, networking,
and storage should continue to operate. However, instances might
experience intermittent network interruptions.
- Consider the approach to upgrading your environment. You can perform
an upgrade with operational instances, but this is a dangerous
approach. You might consider using live migration to temporarily
relocate instances to other compute nodes while performing upgrades.
However, you must ensure database consistency throughout the process;
otherwise your environment might become unstable. Also, don't forget
to provide sufficient notice to your users, including giving them
plenty of time to perform their own backups.
- Consider adopting structure and options from the service
configuration files and merging them with existing configuration
files. The `OpenStack Configuration
Reference <https://docs.openstack.org/ocata/config-reference/>`_
contains new, updated, and deprecated options for most services.
- Like all major system upgrades, your upgrade could fail for one or
more reasons. You can prepare for this situation by having the
ability to roll back your environment to the previous release,
including databases, configuration files, and packages. We provide an
example process for rolling back your environment in
:ref:`rolling_back_a_failed_upgrade`.
- Develop an upgrade procedure and assess it thoroughly by using a test
environment similar to your production environment.
Pre-upgrade testing environment
-------------------------------
The most important step is the pre-upgrade testing. If you are upgrading
immediately after release of a new version, undiscovered bugs might
hinder your progress. Some deployers prefer to wait until the first
point release is announced. However, if you have a significant
deployment, you might follow the development and testing of the release
to ensure that bugs for your use cases are fixed.
Each OpenStack cloud is different even if you have a near-identical
architecture as described in this guide. As a result, you must still
test upgrades between versions in your environment using an approximate
clone of your environment.
However, that is not to say that it needs to be the same size or use
identical hardware as the production environment. It is important to
consider the hardware and scale of the cloud that you are upgrading. The
following tips can help you minimise the cost:
Use your own cloud
The simplest place to start testing the next version of OpenStack is
by setting up a new environment inside your own cloud. This might
seem odd, especially the double virtualization used in running
compute nodes. But it is a sure way to very quickly test your
configuration.
Use a public cloud
Consider using a public cloud to test the scalability limits of your
cloud controller configuration. Most public clouds bill by the hour,
which means it can be inexpensive to perform even a test with many
nodes.
Make another storage endpoint on the same system
If you use an external storage plug-in or shared file system with
your cloud, you can test whether it works by creating a second share
or endpoint. This allows you to test the system before entrusting
the new version on to your storage.
Watch the network
Even at smaller-scale testing, look for excess network packets to
determine whether something is going horribly wrong in
inter-component communication.
To set up the test environment, you can use one of several methods:
- Do a full manual install by using the `Installation Tutorials and Guides
<https://docs.openstack.org/project-install-guide/ocata/>`_ for
your platform. Review the final configuration files and installed
packages.
- Create a clone of your automated configuration infrastructure with
changed package repository URLs.
Alter the configuration until it works.
Either approach is valid. Use the approach that matches your experience.
An upgrade pre-testing system is excellent for getting the configuration
to work. However, it is important to note that the historical use of the
system and differences in user interaction can affect the success of
upgrades.
If possible, we highly recommend that you dump your production database
tables and test the upgrade in your development environment using this
data. Several MySQL bugs have been uncovered during database migrations
because of slight table differences between a fresh installation and
tables that migrated from one version to another. This will have impact
on large real datasets, which you do not want to encounter during a
production outage.
Artificial scale testing can go only so far. After your cloud is
upgraded, you must pay careful attention to the performance aspects of
your cloud.
Upgrade Levels
--------------
Upgrade levels are a feature added to OpenStack Compute since the
Grizzly release to provide version locking on the RPC (Message Queue)
communications between the various Compute services.
This functionality is an important piece of the puzzle when it comes to
live upgrades and is conceptually similar to the existing API versioning
that allows OpenStack services of different versions to communicate
without issue.
Without upgrade levels, an X+1 version Compute service can receive and
understand X version RPC messages, but it can only send out X+1 version
RPC messages. For example, if a nova-conductor process has been upgraded
to X+1 version, then the conductor service will be able to understand
messages from X version nova-compute processes, but those compute
services will not be able to understand messages sent by the conductor
service.
During an upgrade, operators can add configuration options to
``nova.conf`` which lock the version of RPC messages and allow live
upgrading of the services without interruption caused by version
mismatch. The configuration options allow the specification of RPC
version numbers if desired, but release name alias are also supported.
For example:
.. code-block:: ini
[upgrade_levels]
compute=X+1
conductor=X+1
scheduler=X+1
will keep the RPC version locked across the specified services to the
RPC version used in X+1. As all instances of a particular service are
upgraded to the newer version, the corresponding line can be removed
from ``nova.conf``.
Using this functionality, ideally one would lock the RPC version to the
OpenStack version being upgraded from on nova-compute nodes, to ensure
that, for example X+1 version nova-compute processes will continue to
work with X version nova-conductor processes while the upgrade
completes. Once the upgrade of nova-compute processes is complete, the
operator can move onto upgrading nova-conductor and remove the version
locking for nova-compute in ``nova.conf``.
Upgrade process
~~~~~~~~~~~~~~~
This section describes the process to upgrade a basic OpenStack
deployment based on the basic two-node architecture in the `Installation
Tutorials and Guides
<https://docs.openstack.org/project-install-guide/ocata/>`_. All
nodes must run a supported distribution of Linux with a recent kernel
and the current release packages.
Service specific upgrade instructions
-------------------------------------
Refer to the following upgrade notes for information on upgrading specific
OpenStack services:
* `Networking service (neutron) upgrades
<https://docs.openstack.org/developer/neutron/devref/upgrade.html>`_
* `Compute service (nova) upgrades
<https://docs.openstack.org/developer/nova/upgrade.html>`_
* `Identity service (keystone) upgrades
<https://docs.openstack.org/developer/keystone/upgrading.html>`_
* `Block Storage service (cinder) upgrades
<https://docs.openstack.org/developer/cinder/upgrade.html>`_
* `Image service (glance) zero downtime database upgrades
<https://docs.openstack.org/developer/glance/db.html#zero-downtime-database-upgrades>`_
* `Image service (glance) rolling upgrades
<https://docs.openstack.org/developer/glance/rollingupgrades.html>`_
* `Bare Metal service (ironic) upgrades
<https://docs.openstack.org/developer/ironic/deploy/upgrade-guide.html>`_
* `Object Storage service (swift) upgrades
<https://docs.openstack.org/developer/swift/overview_policies.html#upgrade-policy>`_
* `Telemetry service (ceilometer) upgrades
<https://docs.openstack.org/developer/ceilometer/install/upgrade.html>`_
Prerequisites
-------------
- Perform some cleaning of the environment prior to starting the
upgrade process to ensure a consistent state. For example, instances
not fully purged from the system after deletion might cause
indeterminate behavior.
- For environments using the OpenStack Networking service (neutron),
verify the release version of the database. For example:
.. code-block:: console
# su -s /bin/sh -c "neutron-db-manage --config-file /etc/neutron/neutron.conf \
--config-file /etc/neutron/plugins/ml2/ml2_conf.ini current" neutron
Perform a backup
----------------
#. Save the configuration files on all nodes. For example:
.. code-block:: console
# for i in keystone glance nova neutron openstack-dashboard cinder heat ceilometer; \
do mkdir $i-RELEASE_NAME; \
done
# for i in keystone glance nova neutron openstack-dashboard cinder heat ceilometer; \
do cp -r /etc/$i/* $i-RELEASE_NAME/; \
done
.. note::
You can modify this example script on each node to handle different
services.
#. Make a full database backup of your production data. Since the Kilo release,
database downgrades are not supported, and restoring from backup is the only
method available to retrieve a previous database version.
.. code-block:: console
# mysqldump -u root -p --opt --add-drop-database --all-databases > RELEASE_NAME-db-backup.sql
.. note::
Consider updating your SQL server configuration as described in the
`Installation Tutorials and Guides
<https://docs.openstack.org/project-install-guide/ocata/>`_.
Manage repositories
-------------------
On all nodes:
#. Remove the repository for the previous release packages.
#. Add the repository for the new release packages.
#. Update the repository database.
Upgrade packages on each node
-----------------------------
Depending on your specific configuration, upgrading all packages might
restart or break services supplemental to your OpenStack environment.
For example, if you use the TGT iSCSI framework for Block Storage
volumes and the upgrade includes new packages for it, the package
manager might restart the TGT iSCSI services and impact connectivity to
volumes.
If the package manager prompts you to update configuration files, reject
the changes. The package manager appends a suffix to newer versions of
configuration files. Consider reviewing and adopting content from these
files.
.. note::
You may need to explicitly install the ``ipset`` package if your
distribution does not install it as a dependency.
Update services
---------------
To update a service on each node, you generally modify one or more
configuration files, stop the service, synchronize the database schema,
and start the service. Some services require different steps. We
recommend verifying operation of each service before proceeding to the
next service.
The order you should upgrade services, and any changes from the general
upgrade process is described below:
**Controller node**
#. Identity service - Clear any expired tokens before synchronizing
the database.
#. Image service
#. Compute service, including networking components.
#. Networking service
#. Block Storage service
#. Dashboard - In typical environments, updating Dashboard only
requires restarting the Apache HTTP service.
#. Orchestration service
#. Telemetry service - In typical environments, updating the
Telemetry service only requires restarting the service.
#. Compute service - Edit the configuration file and restart the service.
#. Networking service - Edit the configuration file and restart the service.
**Storage nodes**
* Block Storage service - Updating the Block Storage service only requires
restarting the service.
**Compute nodes**
* Networking service - Edit the configuration file and restart the service.
Final steps
-----------
On all distributions, you must perform some final tasks to complete the
upgrade process.
#. Decrease DHCP timeouts by modifying the :file:`/etc/nova/nova.conf` file on
the compute nodes back to the original value for your environment.
#. Update all ``.ini`` files to match passwords and pipelines as required
for the OpenStack release in your environment.
#. After migration, users see different results from
:command:`openstack image list` and :command:`glance image-list`. To ensure
users see the same images in the list commands, edit the
:file:`/etc/glance/policy.json` file and :file:`/etc/nova/policy.json` file
to contain ``"context_is_admin": "role:admin"``, which limits access to
private images for projects.
#. Verify proper operation of your environment. Then, notify your users
that their cloud is operating normally again.
.. _rolling_back_a_failed_upgrade:
Rolling back a failed upgrade
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This section provides guidance for rolling back to a previous release of
OpenStack. All distributions follow a similar procedure.
.. warning::
Rolling back your environment should be the final course of action
since you are likely to lose any data added since the backup.
A common scenario is to take down production management services in
preparation for an upgrade, completed part of the upgrade process, and
discovered one or more problems not encountered during testing. As a
consequence, you must roll back your environment to the original "known
good" state. You also made sure that you did not make any state changes
after attempting the upgrade process; no new instances, networks,
storage volumes, and so on. Any of these new resources will be in a
frozen state after the databases are restored from backup.
Within this scope, you must complete these steps to successfully roll
back your environment:
#. Roll back configuration files.
#. Restore databases from backup.
#. Roll back packages.
You should verify that you have the requisite backups to restore.
Rolling back upgrades is a tricky process because distributions tend to
put much more effort into testing upgrades than downgrades. Broken
downgrades take significantly more effort to troubleshoot and, resolve
than broken upgrades. Only you can weigh the risks of trying to push a
failed upgrade forward versus rolling it back. Generally, consider
rolling back as the very last option.
The following steps described for Ubuntu have worked on at least one
production environment, but they might not work for all environments.
**To perform a rollback**
#. Stop all OpenStack services.
#. Copy contents of configuration backup directories that you created
during the upgrade process back to ``/etc/<service>`` directory.
#. Restore databases from the ``RELEASE_NAME-db-backup.sql`` backup file
that you created with the :command:`mysqldump` command during the upgrade
process:
.. code-block:: console
# mysql -u root -p < RELEASE_NAME-db-backup.sql
#. Downgrade OpenStack packages.
.. warning::
Downgrading packages is by far the most complicated step; it is
highly dependent on the distribution and the overall administration
of the system.
#. Determine which OpenStack packages are installed on your system. Use the
:command:`dpkg --get-selections` command. Filter for OpenStack
packages, filter again to omit packages explicitly marked in the
``deinstall`` state, and save the final output to a file. For example,
the following command covers a controller node with keystone, glance,
nova, neutron, and cinder:
.. code-block:: console
# dpkg --get-selections | grep -e keystone -e glance -e nova -e neutron \
-e cinder | grep -v deinstall | tee openstack-selections
cinder-api install
cinder-common install
cinder-scheduler install
cinder-volume install
glance install
glance-api install
glance-common install
glance-registry install
neutron-common install
neutron-dhcp-agent install
neutron-l3-agent install
neutron-lbaas-agent install
neutron-metadata-agent install
neutron-plugin-openvswitch install
neutron-plugin-openvswitch-agent install
neutron-server install
nova-api install
nova-common install
nova-conductor install
nova-consoleauth install
nova-novncproxy install
nova-objectstore install
nova-scheduler install
python-cinder install
python-cinderclient install
python-glance install
python-glanceclient install
python-keystone install
python-keystoneclient install
python-neutron install
python-neutronclient install
python-nova install
python-novaclient install
.. note::
Depending on the type of server, the contents and order of your
package list might vary from this example.
#. You can determine the package versions available for reversion by using
the ``apt-cache policy`` command. For example:
.. code-block:: console
# apt-cache policy nova-common
nova-common:
Installed: 2:14.0.1-0ubuntu1~cloud0
Candidate: 2:14.0.1-0ubuntu1~cloud0
Version table:
*** 2:14.0.1-0ubuntu1~cloud0 500
500 http://ubuntu-cloud.archive.canonical.com/ubuntu xenial-updates/newton/main amd64 Packages
100 /var/lib/dpkg/status
2:13.1.2-0ubuntu2 500
500 http://archive.ubuntu.com/ubuntu xenial-updates/main amd64 Packages
2:13.0.0-0ubuntu2 500
500 http://archive.ubuntu.com/ubuntu xenial/main amd64 Packages
.. note::
If you removed the release repositories, you must first reinstall
them and run the :command:`apt-get update` command.
The command output lists the currently installed version of the package,
newest candidate version, and all versions along with the repository that
contains each version. Look for the appropriate release
version— ``2:14.0.1-0ubuntu1~cloud0`` in this case. The process of
manually picking through this list of packages is rather tedious and
prone to errors. You should consider using a script to help
with this process. For example:
.. code-block:: console
# for i in `cut -f 1 openstack-selections | sed 's/neutron/;'`;
do echo -n $i ;apt-cache policy $i | grep -B 1 RELEASE_NAME |
grep -v Packages | awk '{print "="$1}';done | tr '\n' ' ' |
tee openstack-RELEASE_NAME-versions
cinder-api=2:9.0.0-0ubuntu1~cloud0
cinder-common=2:9.0.0-0ubuntu1~cloud0
cinder-scheduler=2:9.0.0-0ubuntu1~cloud0
cinder-volume=2:9.0.0-0ubuntu1~cloud0
glance=2:13.0.0-0ubuntu1~cloud0
glance-api=2:13.0.0-0ubuntu1~cloud0 500
glance-common=2:13.0.0-0ubuntu1~cloud0 500
glance-registry=2:13.0.0-0ubuntu1~cloud0 500
neutron-common=2:9.0.0-0ubuntu1~cloud0
neutron-dhcp-agent=2:9.0.0-0ubuntu1~cloud0
neutron-l3-agent=2:9.0.0-0ubuntu1~cloud0
neutron-lbaas-agent=2:9.0.0-0ubuntu1~cloud0
neutron-metadata-agent=2:9.0.0-0ubuntu1~cloud0
neutron-server=2:9.0.0-0ubuntu1~cloud0
nova-api=2:14.0.1-0ubuntu1~cloud0
nova-common=2:14.0.1-0ubuntu1~cloud0
nova-conductor=2:14.0.1-0ubuntu1~cloud0
nova-consoleauth=2:14.0.1-0ubuntu1~cloud0
nova-novncproxy=2:14.0.1-0ubuntu1~cloud0
nova-objectstore=2:14.0.1-0ubuntu1~cloud0
nova-scheduler=2:14.0.1-0ubuntu1~cloud0
python-cinder=2:9.0.0-0ubuntu1~cloud0
python-cinderclient=1:1.9.0-0ubuntu1~cloud0
python-glance=2:13.0.0-0ubuntu1~cloud0
python-glanceclient=1:2.5.0-0ubuntu1~cloud0
python-neutron=2:9.0.0-0ubuntu1~cloud0
python-neutronclient=1:6.0.0-0ubuntu1~cloud0
python-nova=2:14.0.1-0ubuntu1~cloud0
python-novaclient=2:6.0.0-0ubuntu1~cloud0
python-openstackclient=3.2.0-0ubuntu2~cloud0
#. Use the :command:`apt-get install` command to install specific versions
of each package by specifying ``<package-name>=<version>``. The script in
the previous step conveniently created a list of ``package=version``
pairs for you:
.. code-block:: console
# apt-get install `cat openstack-RELEASE_NAME-versions`
This step completes the rollback procedure. You should remove the
upgrade release repository and run :command:`apt-get update` to prevent
accidental upgrades until you solve whatever issue caused you to roll
back your environment.

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===============
User Management
===============
The OpenStack Dashboard provides a graphical interface to manage users.
This section describes user management with the Dashboard.
You can also `manage projects, users, and roles
<https://docs.openstack.org/admin-guide/cli-manage-projects-users-and-roles.html>`_
from the command-line clients.
In addition, many sites write custom tools for local needs to enforce
local policies and provide levels of self-service to users that are not
currently available with packaged tools.
Creating New Users
~~~~~~~~~~~~~~~~~~
To create a user, you need the following information:
* Username
* Description
* Email address
* Password
* Primary project
* Role
* Enabled
Username and email address are self-explanatory, though your site may
have local conventions you should observe. The primary project is simply
the first project the user is associated with and must exist prior to
creating the user. Role is almost always going to be "member." Out of
the box, OpenStack comes with two roles defined:
member
A typical user
admin
An administrative super user, which has full permissions across all
projects and should be used with great care
It is possible to define other roles, but doing so is uncommon.
Once you've gathered this information, creating the user in the
dashboard is just another web form similar to what we've seen before and
can be found by clicking the :guilabel:`Users` link in the
:guilabel:`Identity` navigation bar and then clicking the
:guilabel:`Create User` button at the top right.
Modifying users is also done from this :guilabel:`Users` page. If you have a
large number of users, this page can get quite crowded. The :guilabel:`Filter`
search box at the top of the page can be used to limit the users listing. A
form very similar to the user creation dialog can be pulled up by selecting
:guilabel:`Edit` from the actions drop-down menu at the end of the line for
the user you are modifying.
Associating Users with Projects
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Many sites run with users being associated with only one project. This
is a more conservative and simpler choice both for administration and
for users. Administratively, if a user reports a problem with an
instance or quota, it is obvious which project this relates to. Users
needn't worry about what project they are acting in if they are only in
one project. However, note that, by default, any user can affect the
resources of any other user within their project. It is also possible to
associate users with multiple projects if that makes sense for your
organization.
Associating existing users with an additional project or removing them
from an older project is done from the :guilabel:`Projects` page of the
dashboard by selecting :guilabel:`Manage Members` from the
:guilabel:`Actions` column, as shown in the screenshot below.
From this view, you can do a number of useful things, as well as a few
dangerous ones.
The first column of this form, named :guilabel:`All Users`, includes a list of
all the users in your cloud who are not already associated with this
project. The second column shows all the users who are. These lists can
be quite long, but they can be limited by typing a substring of the
username you are looking for in the filter field at the top of the
column.
From here, click the :guilabel:`+` icon to add users to the project.
Click the :guilabel:`-` to remove them.
.. figure:: figures/edit_project_member.png
:alt: Edit Project Members tab
The dangerous possibility comes with the ability to change member roles.
This is the dropdown list below the username in the
:guilabel:`Project Members` list. In virtually all cases,
this value should be set to :guilabel:`Member`. This example purposefully
shows an administrative user where this value is ``admin``.
.. warning::
The admin is global, not per project, so granting a user the ``admin``
role in any project gives the user administrative rights across the
whole cloud.
Typical use is to only create administrative users in a single project,
by convention the admin project, which is created by default during
cloud setup. If your administrative users also use the cloud to launch
and manage instances, it is strongly recommended that you use separate
user accounts for administrative access and normal operations and that
they be in distinct projects.
Customizing Authorization
-------------------------
The default :term:`authorization` settings allow administrative users
only to create resources on behalf of a different project.
OpenStack handles two kinds of authorization policies:
Operation based
Policies specify access criteria for specific operations, possibly
with fine-grained control over specific attributes.
Resource based
Whether access to a specific resource might be granted or not
according to the permissions configured for the resource (currently
available only for the network resource). The actual authorization
policies enforced in an OpenStack service vary from deployment to
deployment.
The policy engine reads entries from the ``policy.json`` file. The
actual location of this file might vary from distribution to
distribution: for nova, it is typically in ``/etc/nova/policy.json``.
You can update entries while the system is running, and you do not have
to restart services. Currently, the only way to update such policies is
to edit the policy file.
The OpenStack service's policy engine matches a policy directly. A rule
indicates evaluation of the elements of such policies. For instance, in
a ``compute:create: "rule:admin_or_owner"`` statement, the policy is
``compute:create``, and the rule is ``admin_or_owner``.
Policies are triggered by an OpenStack policy engine whenever one of
them matches an OpenStack API operation or a specific attribute being
used in a given operation. For instance, the engine tests the
``create:compute`` policy every time a user sends a
``POST /v2/{tenant_id}/servers`` request to the OpenStack Compute API
server. Policies can be also related to specific :term:`API extensions
<API extension>`. For instance, if a user needs an extension like
``compute_extension:rescue``, the attributes defined by the provider
extensions trigger the rule test for that operation.
An authorization policy can be composed by one or more rules. If more
rules are specified, evaluation policy is successful if any of the rules
evaluates successfully; if an API operation matches multiple policies,
then all the policies must evaluate successfully. Also, authorization
rules are recursive. Once a rule is matched, the rule(s) can be resolved
to another rule, until a terminal rule is reached. These are the rules
defined:
Role-based rules
Evaluate successfully if the user submitting the request has the
specified role. For instance, ``"role:admin"`` is successful if the
user submitting the request is an administrator.
Field-based rules
Evaluate successfully if a field of the resource specified in the
current request matches a specific value. For instance,
``"field:networks:shared=True"`` is successful if the attribute
shared of the network resource is set to ``true``.
Generic rules
Compare an attribute in the resource with an attribute extracted
from the user's security credentials and evaluates successfully if
the comparison is successful. For instance,
``"tenant_id:%(tenant_id)s"`` is successful if the tenant identifier
in the resource is equal to the tenant identifier of the user
submitting the request.
Here are snippets of the default nova ``policy.json`` file:
.. code-block:: none
{
"context_is_admin": "role:admin",
"admin_or_owner": "is_admin:True", "project_id:%(project_id)s", ~~~~(1)~~~~
"default": "rule:admin_or_owner", ~~~~(2)~~~~
"compute:create": "",
"compute:create:attach_network": "",
"compute:create:attach_volume": "",
"compute:get_all": "",
"admin_api": "is_admin:True",
"compute_extension:accounts": "rule:admin_api",
"compute_extension:admin_actions": "rule:admin_api",
"compute_extension:admin_actions:pause": "rule:admin_or_owner",
"compute_extension:admin_actions:unpause": "rule:admin_or_owner",
...
"compute_extension:admin_actions:migrate": "rule:admin_api",
"compute_extension:aggregates": "rule:admin_api",
"compute_extension:certificates": "",
...
"compute_extension:flavorextraspecs": "",
"compute_extension:flavormanage": "rule:admin_api", ~~~~(3)~~~~
}
1. Shows a rule that evaluates successfully if the current user is an
administrator or the owner of the resource specified in the request
(tenant identifier is equal).
2. Shows the default policy, which is always evaluated if an API
operation does not match any of the policies in ``policy.json``.
3. Shows a policy restricting the ability to manipulate flavors to
administrators using the Admin API only.
In some cases, some operations should be restricted to administrators
only. Therefore, as a further example, let us consider how this sample
policy file could be modified in a scenario where we enable users to
create their own flavors:
.. code-block:: none
"compute_extension:flavormanage": "",
Users Who Disrupt Other Users
-----------------------------
Users on your cloud can disrupt other users, sometimes intentionally and
maliciously and other times by accident. Understanding the situation
allows you to make a better decision on how to handle the
disruption.
For example, a group of users have instances that are utilizing a large
amount of compute resources for very compute-intensive tasks. This is
driving the load up on compute nodes and affecting other users. In this
situation, review your user use cases. You may find that high compute
scenarios are common, and should then plan for proper segregation in
your cloud, such as host aggregation or regions.
Another example is a user consuming a very large amount of bandwidth.
Again, the key is to understand what the user is doing.
If she naturally needs a high amount of bandwidth,
you might have to limit her transmission rate as to not
affect other users or move her to an area with more bandwidth available.
On the other hand, maybe her instance has been hacked and is part of a
botnet launching DDOS attacks. Resolution of this issue is the same as
though any other server on your network has been hacked. Contact the
user and give her time to respond. If she doesn't respond, shut down the
instance.
A final example is if a user is hammering cloud resources repeatedly.
Contact the user and learn what he is trying to do. Maybe he doesn't
understand that what he's doing is inappropriate, or maybe there is an
issue with the resource he is trying to access that is causing his
requests to queue or lag.

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=======
Preface
=======
OpenStack is an open source platform that lets you build an
:term:`Infrastructure-as-a-Service (IaaS)` cloud that runs on commodity
hardware.
Introduction to OpenStack
~~~~~~~~~~~~~~~~~~~~~~~~~
OpenStack believes in open source, open design, and open development,
all in an open community that encourages participation by anyone. The
long-term vision for OpenStack is to produce a ubiquitous open source
cloud computing platform that meets the needs of public and private
cloud providers regardless of size. OpenStack services control large
pools of compute, storage, and networking resources throughout a data
center.
The technology behind OpenStack consists of a series of interrelated
projects delivering various components for a cloud infrastructure
solution. Each service provides an open API so that all of these
resources can be managed through a dashboard that gives administrators
control while empowering users to provision resources through a web
interface, a command-line client, or software development kits that
support the API. Many OpenStack APIs are extensible, meaning you can
keep compatibility with a core set of calls while providing access to
more resources and innovating through API extensions. The OpenStack
project is a global collaboration of developers and cloud computing
technologists. The project produces an open standard cloud computing
platform for both public and private clouds. By focusing on ease of
implementation, massive scalability, a variety of rich features, and
tremendous extensibility, the project aims to deliver a practical and
reliable cloud solution for all types of organizations.
Getting Started with OpenStack
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
As an open source project, one of the unique aspects of OpenStack is
that it has many different levels at which you can begin to engage with
it—you don't have to do everything yourself.
Using OpenStack
---------------
You could ask, "Do I even need to build a cloud?" If you want to start
using a compute or storage service by just swiping your credit card, you
can go to eNovance, HP, Rackspace, or other organizations to start using
their public OpenStack clouds. Using their OpenStack cloud resources is
similar to accessing the publicly available Amazon Web Services Elastic
Compute Cloud (EC2) or Simple Storage Solution (S3).
Plug and Play OpenStack
-----------------------
However, the enticing part of OpenStack might be to build your own
private cloud, and there are several ways to accomplish this goal.
Perhaps the simplest of all is an appliance-style solution. You purchase
an appliance, unpack it, plug in the power and the network, and watch it
transform into an OpenStack cloud with minimal additional configuration.
However, hardware choice is important for many applications, so if that
applies to you, consider that there are several software distributions
available that you can run on servers, storage, and network products of
your choosing. Canonical (where OpenStack replaced Eucalyptus as the
default cloud option in 2011), Red Hat, and SUSE offer enterprise
OpenStack solutions and support. You may also want to take a look at
some of the specialized distributions, such as those from Rackspace,
Piston, SwiftStack, or Cloudscaling.
Alternatively, if you want someone to help guide you through the
decisions about the underlying hardware or your applications, perhaps
adding in a few features or integrating components along the way,
consider contacting one of the system integrators with OpenStack
experience, such as Mirantis or Metacloud.
If your preference is to build your own OpenStack expertise internally,
a good way to kick-start that might be to attend or arrange a training
session. The OpenStack Foundation has a `Training
Marketplace <https://www.openstack.org/marketplace/training>`_ where you
can look for nearby events. Also, the OpenStack community is `working to
produce <https://wiki.openstack.org/wiki/Training-guides>`_ open source
training materials.
Roll Your Own OpenStack
-----------------------
However, this guide has a different audience—those seeking flexibility
from the OpenStack framework by deploying do-it-yourself solutions.
OpenStack is designed for horizontal scalability, so you can easily add
new compute, network, and storage resources to grow your cloud over
time. In addition to the pervasiveness of massive OpenStack public
clouds, many organizations, such as PayPal, Intel, and Comcast, build
large-scale private clouds. OpenStack offers much more than a typical
software package because it lets you integrate a number of different
technologies to construct a cloud. This approach provides great
flexibility, but the number of options might be daunting at first.
Who This Book Is For
~~~~~~~~~~~~~~~~~~~~
This book is for those of you starting to run OpenStack clouds as well
as those of you who were handed an operational one and want to keep it
running well. Perhaps you're on a DevOps team, perhaps you are a system
administrator starting to dabble in the cloud, or maybe you want to get
on the OpenStack cloud team at your company. This book is for all of
you.
This guide assumes that you are familiar with a Linux distribution that
supports OpenStack, SQL databases, and virtualization. You must be
comfortable administering and configuring multiple Linux machines for
networking. You must install and maintain an SQL database and
occasionally run queries against it.
One of the most complex aspects of an OpenStack cloud is the networking
configuration. You should be familiar with concepts such as DHCP, Linux
bridges, VLANs, and iptables. You must also have access to a network
hardware expert who can configure the switches and routers required in
your OpenStack cloud.
.. note::
Cloud computing is quite an advanced topic, and this book requires a
lot of background knowledge. However, if you are fairly new to cloud
computing, we recommend that you make use of the :doc:`common/glossary`
at the back of the book, as well as the online documentation for OpenStack
and additional resources mentioned in this book in :doc:`app-resources`.
Further Reading
---------------
There are other books on the `OpenStack documentation
website <https://docs.openstack.org>`_ that can help you get the job
done.
Installation Tutorials and Guides
Describes a manual installation process, as in, by hand, without
automation, for multiple distributions based on a packaging system:
- `OpenStack Installation Tutorial for openSUSE and SUSE Linux Enterprise
<https://docs.openstack.org/ocata/install-guide-obs/>`_
- `OpenStack Installation Tutorial for Red Hat Enterprise Linux and CentOS
<https://docs.openstack.org/ocata/install-guide-rdo/>`_
- `OpenStack Installation Tutorial for Ubuntu
<https://docs.openstack.org/ocata/install-guide-ubuntu/>`_
`OpenStack Configuration Reference <https://docs.openstack.org/ocata/config-reference/>`_
Contains a reference listing of all configuration options for core
and integrated OpenStack services by release version
`OpenStack Architecture Design Guide <https://docs.openstack.org/arch-design/>`_
Contains guidelines for designing an OpenStack cloud
`OpenStack Administrator Guide <https://docs.openstack.org/admin-guide/>`_
Contains how-to information for managing an OpenStack cloud as
needed for your use cases, such as storage, computing, or
software-defined-networking
`OpenStack High Availability Guide <https://docs.openstack.org/ha-guide/index.html>`_
Describes potential strategies for making your OpenStack services
and related controllers and data stores highly available
`OpenStack Security Guide <https://docs.openstack.org/security-guide/>`_
Provides best practices and conceptual information about securing an
OpenStack cloud
`Virtual Machine Image Guide <https://docs.openstack.org/image-guide/>`_
Shows you how to obtain, create, and modify virtual machine images
that are compatible with OpenStack
`OpenStack End User Guide <https://docs.openstack.org/user-guide/>`_
Shows OpenStack end users how to create and manage resources in an
OpenStack cloud with the OpenStack dashboard and OpenStack client
commands
`OpenStack Networking Guide <https://docs.openstack.org/ocata/networking-guide/>`_
This guide targets OpenStack administrators seeking to deploy and
manage OpenStack Networking (neutron).
`OpenStack API Guide <https://developer.openstack.org/api-guide/quick-start/>`_
A brief overview of how to send REST API requests to endpoints for
OpenStack services
How This Book Is Organized
~~~~~~~~~~~~~~~~~~~~~~~~~~
This book contains several parts to show best practices and tips for
the repeated operations for running OpenStack clouds.
:doc:`ops-lay-of-the-land`
This chapter is written to let you get your hands wrapped around
your OpenStack cloud through command-line tools and understanding
what is already set up in your cloud.
:doc:`ops-projects-users`
This chapter walks through user-enabling processes that all admins
must face to manage users, give them quotas to parcel out resources,
and so on.
:doc:`ops-user-facing-operations`
This chapter shows you how to use OpenStack cloud resources and how
to train your users.
:doc:`ops-maintenance`
This chapter goes into the common failures that the authors have
seen while running clouds in production, including troubleshooting.
:doc:`ops-network-troubleshooting`
Because network troubleshooting is especially difficult with virtual
resources, this chapter is chock-full of helpful tips and tricks for
tracing network traffic, finding the root cause of networking
failures, and debugging related services, such as DHCP and DNS.
:doc:`ops-logging-monitoring`
This chapter shows you where OpenStack places logs and how to best
read and manage logs for monitoring purposes.
:doc:`ops-backup-recovery`
This chapter describes what you need to back up within OpenStack as
well as best practices for recovering backups.
:doc:`ops-customize`
For readers who need to get a specialized feature into OpenStack,
this chapter describes how to use DevStack to write custom
middleware or a custom scheduler to rebalance your resources.
:doc:`ops-advanced-configuration`
Much of OpenStack is driver-oriented, so you can plug in different
solutions to the base set of services. This chapter describes some
advanced configuration topics.
:doc:`ops-upgrades`
This chapter provides upgrade information based on the architectures
used in this book.
**Back matter:**
:doc:`app-usecases`
You can read a small selection of use cases from the OpenStack
community with some technical details and further resources.
:doc:`app-crypt`
These are shared legendary tales of image disappearances, VM
massacres, and crazy troubleshooting techniques that result in
hard-learned lessons and wisdom.
:doc:`app-roadmaps`
Read about how to track the OpenStack roadmap through the open and
transparent development processes.
:doc:`app-resources`
So many OpenStack resources are available online because of the
fast-moving nature of the project, but there are also resources
listed here that the authors found helpful while learning
themselves.
:doc:`common/glossary`
A list of terms used in this book is included, which is a subset of
the larger OpenStack glossary available online.
Why and How We Wrote This Book
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We wrote this book because we have deployed and maintained OpenStack
clouds for at least a year and we wanted to share this knowledge with
others. After months of being the point people for an OpenStack cloud,
we also wanted to have a document to hand to our system administrators
so that they'd know how to operate the cloud on a daily basis—both
reactively and pro-actively. We wanted to provide more detailed
technical information about the decisions that deployers make along the
way.
We wrote this book to help you:
- Design and create an architecture for your first nontrivial OpenStack
cloud. After you read this guide, you'll know which questions to ask
and how to organize your compute, networking, and storage resources
and the associated software packages.
- Perform the day-to-day tasks required to administer a cloud.
We wrote this book in a book sprint, which is a facilitated, rapid
development production method for books. For more information, see the
`BookSprints site <http://www.booksprints.net/>`_. Your authors cobbled
this book together in five days during February 2013, fueled by caffeine
and the best takeout food that Austin, Texas, could offer.
On the first day, we filled white boards with colorful sticky notes to
start to shape this nebulous book about how to architect and operate
clouds:
.. figure:: figures/osog_00in01.png
:figwidth: 100%
We wrote furiously from our own experiences and bounced ideas between
each other. At regular intervals we reviewed the shape and organization
of the book and further molded it, leading to what you see today.
The team includes:
Tom Fifield
After learning about scalability in computing from particle physics
experiments, such as ATLAS at the Large Hadron Collider (LHC) at
CERN, Tom worked on OpenStack clouds in production to support the
Australian public research sector. Tom currently serves as an
OpenStack community manager and works on OpenStack documentation in
his spare time.
Diane Fleming
Diane works on the OpenStack API documentation tirelessly. She
helped out wherever she could on this project.
Anne Gentle
Anne is the documentation coordinator for OpenStack and also served
as an individual contributor to the Google Documentation Summit in
2011, working with the Open Street Maps team. She has worked on book
sprints in the past, with FLOSS Manuals’ Adam Hyde facilitating.
Anne lives in Austin, Texas.
Lorin Hochstein
An academic turned software-developer-slash-operator, Lorin worked
as the lead architect for Cloud Services at Nimbis Services, where
he deploys OpenStack for technical computing applications. He has
been working with OpenStack since the Cactus release. Previously, he
worked on high-performance computing extensions for OpenStack at
University of Southern California's Information Sciences Institute
(USC-ISI).
Adam Hyde
Adam facilitated this book sprint. He also founded the book sprint
methodology and is the most experienced book-sprint facilitator
around. See `BookSprints <http://www.booksprints.net>`_ for more
information. Adam founded FLOSS Manuals—a community of some 3,000
individuals developing Free Manuals about Free Software. He is also the
founder and project manager for Booktype, an open source project for
writing, editing, and publishing books online and in print.
Jonathan Proulx
Jon has been piloting an OpenStack cloud as a senior technical
architect at the MIT Computer Science and Artificial Intelligence
Lab for his researchers to have as much computing power as they
need. He started contributing to OpenStack documentation and
reviewing the documentation so that he could accelerate his
learning.
Everett Toews
Everett is a developer advocate at Rackspace making OpenStack and
the Rackspace Cloud easy to use. Sometimes developer, sometimes
advocate, and sometimes operator, he's built web applications,
taught workshops, given presentations around the world, and deployed
OpenStack for production use by academia and business.
Joe Topjian
Joe has designed and deployed several clouds at Cybera, a nonprofit
where they are building e-infrastructure to support entrepreneurs
and local researchers in Alberta, Canada. He also actively maintains
and operates these clouds as a systems architect, and his
experiences have generated a wealth of troubleshooting skills for
cloud environments.
OpenStack community members
Many individual efforts keep a community book alive. Our community
members updated content for this book year-round. Also, a year after
the first sprint, Jon Proulx hosted a second two-day mini-sprint at
MIT with the goal of updating the book for the latest release. Since
the book's inception, more than 30 contributors have supported this
book. We have a tool chain for reviews, continuous builds, and
translations. Writers and developers continuously review patches,
enter doc bugs, edit content, and fix doc bugs. We want to recognize
their efforts!
The following people have contributed to this book: Akihiro Motoki,
Alejandro Avella, Alexandra Settle, Andreas Jaeger, Andy McCallum,
Benjamin Stassart, Chandan Kumar, Chris Ricker, David Cramer, David
Wittman, Denny Zhang, Emilien Macchi, Gauvain Pocentek, Ignacio
Barrio, James E. Blair, Jay Clark, Jeff White, Jeremy Stanley, K
Jonathan Harker, KATO Tomoyuki, Lana Brindley, Laura Alves, Lee Li,
Lukasz Jernas, Mario B. Codeniera, Matthew Kassawara, Michael Still,
Monty Taylor, Nermina Miller, Nigel Williams, Phil Hopkins, Russell
Bryant, Sahid Orentino Ferdjaoui, Sandy Walsh, Sascha Peilicke, Sean
M. Collins, Sergey Lukjanov, Shilla Saebi, Stephen Gordon, Summer
Long, Uwe Stuehler, Vaibhav Bhatkar, Veronica Musso, Ying Chun
"Daisy" Guo, Zhengguang Ou, and ZhiQiang Fan.
How to Contribute to This Book
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The genesis of this book was an in-person event, but now that the book
is in your hands, we want you to contribute to it. OpenStack
documentation follows the coding principles of iterative work, with bug
logging, investigating, and fixing. We also store the source content on
GitHub and invite collaborators through the OpenStack Gerrit
installation, which offers reviews. For the O'Reilly edition of this
book, we are using the company's Atlas system, which also stores source
content on GitHub and enables collaboration among contributors.
Learn more about how to contribute to the OpenStack docs at `OpenStack
Documentation Contributor
Guide <https://docs.openstack.org/contributor-guide/>`_.
If you find a bug and can't fix it or aren't sure it's really a doc bug,
log a bug at `OpenStack
Manuals <https://bugs.launchpad.net/openstack-manuals>`_. Tag the bug
under Extra options with the ``ops-guide`` tag to indicate that the bug
is in this guide. You can assign the bug to yourself if you know how to
fix it. Also, a member of the OpenStack doc-core team can triage the doc
bug.

7
tools/build-all-rst.sh
View File

@ -29,12 +29,11 @@ done
# PDF targets for Install guides are dealt in build-install-guides-rst.sh
PDF_TARGETS=( 'arch-design'\
'ha-guide' \
'image-guide'\
'ops-guide' )
'image-guide')
# Note that these guides are only build for master branch
for guide in admin-guide arch-design contributor-guide \
ha-guide image-guide ops-guide; do
for guide in arch-design contributor-guide \
ha-guide image-guide; do
if [[ ${PDF_TARGETS[*]} =~ $guide ]]; then
tools/build-rst.sh doc/$guide --build build \
--target $guide $LINKCHECK $PDF_OPTION

1
tools/publishdocs.sh
View File

@ -33,7 +33,6 @@ function copy_to_branch {
rm -f publish-docs/$BRANCH/draft-index.html
# We don't need these draft guides on the branch
rm -rf publish-docs/$BRANCH/arch-design-to-archive
rm -rf publish-docs/$BRANCH/ops-guide
for f in $(find publish-docs/$BRANCH -name "atom.xml"); do
sed -i -e "s|/draft/|/$BRANCH/|g" $f

3
www/.htaccess
View File

@ -46,6 +46,9 @@ redirectmatch 301 "^/releases.*$" http://releases.openstack.org$1
# Redirect removed user guide
redirectmatch 301 /user-guide/.*$ /user/
# Redirect removed ops guide
redirectmatch 301 /ops-guide/.*$ /admin/
# Redirect changed directory name in the Contributor Guide
redirect 301 /contributor-guide/ui-text-guidelines.html /contributor-guide/ux-ui-guidelines/ui-text-guidelines.html
redirect 301 /contributor-guide/ui-text-guidelines /contributor-guide/ux-ui-guidelines