1.Use opendev.org instead of git.openstack.org.
2.Use review.opendev.org instead of review.openstack.org.
You can see the discussion below:
http://lists.openstack.org/pipermail/openstack-discuss/2019-March/003603.html
Adapted for Stein to not change path to upper constraints already
modified by [1].
[1] https://review.opendev.org/650294
Change-Id: Ice4509204df788a1a44a06fb89fb44cfe6b54b94
(cherry picked from commit 41f3a817ac
)
13 KiB
Logging with Heka
https://blueprints.launchpad.net/kolla/+spec/heka
Kolla currently uses Rsyslog for logging. And Change Request
252968
[1] suggests to use ELK (Elasticsearch, Logstash,
Kibana) as a way to index all the logs, and visualize them.
This spec suggests using Heka [2] instead of Logstash, while still using Elasticsearch for indexing and Kibana for visualization. It also discusses the removal of Rsyslog along the way.
What is Heka? Heka is a open-source stream processing software created and maintained by Mozilla.
Using Heka will provide a lightweight and scalable log processing solution for Kolla.
Problem description
Change Request 252968
[1] adds an Ansible role named
"elk" that enables deploying ELK (Elasticsearch, Logstash, Kibana) on
nodes with that role. This spec builds on that work, proposing a
scalable log processing architecture based on the Heka [2] stream
processing software.
We think that Heka provides for a lightweight, flexible and powerful solution for processing data streams, including logs.
Using Heka our primary goal is distributing the logs processing load across the OpenStack nodes rather than using a centralized log processing engine that represents a bottleneck and a single-point-of-failure.
We also know from experience that Heka provides all the necessary flexibility for processing other types of data streams than log messages. For example, we already use Heka together with Elasticsearch for logs, but also with collectd and InfluxDB for statistics and metrics.
Proposed change
We propose to build on the ELK infrastructure brought by CR
252968
[1], and use Heka to collect and process logs in a
distributed and scalable way.
This is the proposed architecture:
In this architecture Heka runs on every node of the OpenStack cluster. It runs in a dedicated container, referred to as the Heka container in the rest of this document.
Each Heka instance reads and processes the logs local to the node it runs on, and sends these logs to Elasticsearch for indexing. Elasticsearch may be distributed on multiple nodes for resiliency and scalability, but that part is outside the scope of that specification.
Heka, written in Go, is fast and has a small footprint, making it possible to run it on every node of the cluster. In contrast, Logstash runs in a JVM and is known [3] to be too heavy to run on every node.
Another important aspect is flow control and avoiding the loss of log messages in case of overload. Heka's filter and output plugins, and the Elasticsearch output plugin in particular, support the use of a disk based message queue. This message queue allows plugins to reprocess messages from the queue when downstream servers (Elasticsearch) are down or cannot keep up with the data flow.
With Logstash it is often recommended [3] to use Redis as a centralized queue, which introduces some complexity and other points-of-failures.
Remove Rsyslog
Kolla currently uses Rsyslog. The Kolla services are configured to
write their logs to Syslog. Rsyslog gets the logs from the
/var/lib/kolla/dev/log
Unix socket and dispatches them to
log files on the local file system. Rsyslog running in a Docker
container, the log files are stored in a Docker volume (named
rsyslog
).
With Rsyslog already running on each cluster node, the question of
using two log processing daemons, namely rsyslogd
and
hekad
, has been raised on the mailing list. The spec
evaluates the possibility of using hekad
only, based on
some prototyping work we have conducted [4].
Note: Kolla doesn't currently collect logs from RabbitMQ, HAProxy and
Keepalived. For RabbitMQ the problem is related to RabbitMQ not having
the capability to write its logs to Syslog. HAProxy and Keepalived do
have that capability, but the /var/lib/kolla/dev/log
Unix
socket file is currently not mounted into the HAProxy and Keepalived
containers.
Use Heka's
DockerLogInput
plugin
To remove Rsyslog and only use Heka one option would be to make the
Kolla services write their logs to stdout
(or
stderr
) and rely on Heka's DockerLogInput
plugin [5] for reading the logs. Our experiments have revealed a number
of problems with this option:
- The
DockerLogInput
plugin doesn't currently work for containers that have atty
allocated. And Kolla currently allocates a tty for all containers (for good reasons). - When
DockerLogInput
is used there is no way to differentiate log messages for containers producing multiple log streams.neutron-agents
is an example of such a container. (Sam Yaple has raised that issue multiple times.) - If Heka is stopped and restarted later then log messages will be
lost, as the
DockerLogInput
plugin doesn't currently have a mechanism for tracking its positions in the log streams. This is in contrast to theLogstreamerInput
plugin [6] which does include that mechanism.
For these reasons we think that relying on the
DockerLogInput
plugin may not be a practical option.
For the note, our experiments have also shown that the OpenStack
containers logs written to stdout
are visible to neither
Heka nor docker logs
. This problem is not reproducible when
stderr
is used rather than stdout
. The cause
of this problem is currently unknown. And it looks like other people
have come across that issue [7].
Use local log files
Another option consists of configuring all the Kolla services to log
into local files, and using Heka's LogstreamerInput
plugin
[5].
This option involves using a Docker named volume, mounted both into
the service containers (in rw
mode) and into the Heka
container (in ro
mode). The services write logs into files
placed in that volume, and Heka reads logs from the files found in that
volume.
This option doesn't present the problems described in the previous
section. And it relies on Heka's LogstreamerInput
plugin,
which, based on our experience, is efficient and robust.
Keeping file logs locally on the nodes has been established as a requirement by the Kolla developers. With this option, and the Docker volume used, meeting that requirement necessitates no additional mechanism.
For this option to be applicable the services must have the capability of logging into files. Most of the Kolla services have this capability. The exceptions are HAProxy and Keepalived, for which a different mechanism should be used (described further down in the document). Note that this will make it possible to collect logs from RabbitMQ, which does not support logging to Syslog but does support logging to a file.
Also, this option requires that the services have the permission to
create files into the Docker volume, and that Heka has the permission to
read these files. This means that the Docker named volume will have to
have appropriate owner, group and permission bits. With the Heka
container running under a specific user (see below) this will mean using
an extend_start.sh
script including sudo chown
and possibly sudo chmod
commands. Our prototype [4] already
includes this.
As mentioned already the LogstreamerInput
plugin
includes a mechanism for tracking positions in log streams. This works
with journal files stored on the file system (in
/var/cache/hekad
). A specific volume, private to Heka, will
be used for these journal files. In this way no logs will be lost if the
Heka container is removed and a new one is created.
Handling HAProxy and Keepalived
As already mentioned HAProxy and Keepalived do not support logging to files. This means that some other mechanism should be used for these two services (and any other services that only suppport logging to Syslog).
Our prototype has demonstrated that we can make Heka act as a Syslog
server. This works by using Heka's UdpInput
plugin with its
net
option set to unixgram
.
This also requires that a Unix socket is created by Heka, and that
socket is mounted into the HAProxy and Keepalived containers. For that
we will use the same technique as the one currently used in Kolla with
Rsyslog, that is mounting /var/lib/kolla/dev
into the Heka
container and mounting /var/lib/kolla/dev/log
into the
service containers.
Our prototype already includes some code demonstrating this. See [4].
Also, to be able to store a copy of the HAProxy and Keepalived logs
locally on the node, we will use Heka's FileOutput
plugin.
We will possibly create two instances of that plugin, one for HAProxy
and one for Keepalived, with specific filters
(message_matcher
).
Read Python Tracebacks
In case of exceptions the OpenStack services log Python Tracebacks as multiple log messages. If no special care is taken then the Python Tracebacks will be indexed as separate documents in Elasticsearch, and displayed as distinct log entries in Kibana, making them hard to read. To address that issue we will use a custom Heka decoder, which will be responsible for coalescing the log lines making up a Python Traceback into one message. Our prototype includes that decoder [4].
Collect system logs
In addition to container logs we think it is important to collect
system logs as well. For that we propose to mount the host's
/var/log
directory into the Heka container, and configure
Heka to get logs from standard log files located in that directory (e.g.
kern.log
, auth.log
, messages
).
The list of system log files will be determined at development time.
Log rotation
Log rotation is an important aspect of the logging system. Currently
Kolla doesn't rotate logs. Logs just accumulate in the
rsyslog
Docker volume. The work on Heka proposed in this
spec isn't directly related to log rotation, but we are suggesting to
address this issue for Mitaka. This will mean creating a new container
that uses logrotate
to manage the log files created by the
Kolla containers.
Create an heka
user
For security reasons an heka
user will be created in the
Heka container and the hekad
daemon will run under that
user. The heka
user will be added to the kolla
group, to make sure that Heka can read the log files created by the
services.
Security impact
Heka is a mature product maintained and used in production by Mozilla. So we trust Heka as being secure. We also trust the Heka developers as being serious should security vulnerabilities be found in the Heka code.
As described above we are proposing to use a Docker volume between
the service containers and the Heka container. The group of the volume
directory and the log files will be kolla
. And the owner of
the log files will be the user that executes the service producing logs.
But the gid
of the kolla
group and the
uid
's of the users executing the services may correspond to
a different group and different users on the host system. This means
that the permissions may not be right on the host system. This problem
is not specific to this specification, and it already exists in Kolla
(for the mariadb data volume for example).
Performance Impact
The hekad
daemon will run in a container on each cluster
node. But the rsyslogd
will be removed. And we have
assessed that Heka is lightweight enough to run on every node. Also, a
possible option would be to constrain the Heka container to only use a
defined amount of resources.
Alternatives
An alternative to this proposal involves using Logstash in a centralized way as done in [1].
Another alternative would be to execute Logstash on each cluster node, as this spec proposes with Heka. But this would mean running a JVM on each cluster node, and using Redis as a centralized queue.
Also, as described above, we initially considered relying on services
writing their logs to stdout
and use Heka's
DockerLogInput
plugin. But our prototyping work has
demonstrated the limits of that approach. See the
DockerLogInput
section above for more information.
Implementation
Assignee(s)
Éric Lemoine (elemoine)
Milestones
Target Milestone for completion: Mitaka 3 (March 4th, 2016).
Work Items
- Create an Heka Docker image
- Create an Heka configuration for Kolla
- Develop the necessary Heka decoders (with support for Python Tracebacks)
- Create Ansible deployment files for Heka
- Modify the services' logging configuration when required
- Correctly handle RabbitMQ, HAProxy and Keepalived
- Integrate with Elastichsearch and Kibana
- Assess logs from all the Kolla services are collected
- Make the Heka container upgradable
- Integrate with kolla-mesos (will be done after Mitaka)
Testing
We will rely on the existing gate checks.
Documentation Impact
The location of log files on the host will be mentioned in the documentation.
References
[1] <https://review.opendev.org/#/c/252968/> [2] <http://hekad.readthedocs.org> [3] <http://blog.sematext.com/2015/09/28/recipe-rsyslog-redis-logstash/> [4] <https://review.opendev.org/#/c/269745/> [5] <http://hekad.readthedocs.org/en/latest/config/inputs/docker_log.html> [6] <http://hekad.readthedocs.org/en/latest/config/inputs/logstreamer.html> [7] <https://review.opendev.org/#/c/269952/>