openstack-manuals/doc/arch-design/multi_site/section_prescriptive_examples_multi_site.xml
Andreas Jaeger 3ca32b8434 s/Image Service/Image service/g
Change capitalization as discussed on openstack-docs mailing list.

Change-Id: I2ad81bffbd59bdd8b908664bb0a1ee16da1bf7ae
2015-04-15 15:16:59 +02:00

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE section [
<!ENTITY % openstack SYSTEM "../../common/entities/openstack.ent">
%openstack;
]>
<section xmlns="http://docbook.org/ns/docbook"
xmlns:xi="http://www.w3.org/2001/XInclude"
xmlns:xlink="http://www.w3.org/1999/xlink"
version="5.0"
xml:id="prescriptive-example-multisite">
<?dbhtml stop-chunking?>
<title>Prescriptive examples</title>
<para>There are multiple ways to build a multi-site OpenStack
installation, based on the needs of the intended workloads.
Below are example architectures based on different
requirements. These examples are meant as a reference, and not
a hard and fast rule for deployments. Use the previous
sections of this chapter to assist in selecting specific
components and implementations based on specific needs.</para>
<para>A large content provider needs to deliver content to
customers that are geographically dispersed. The workload is
very sensitive to latency and needs a rapid response to
end-users. After reviewing the user, technical and operational
considerations, it is determined beneficial to build a number
of regions local to the customer's edge. In this case rather
than build a few large, centralized data centers, the intent
of the architecture is to provide a pair of small data centers
in locations that are closer to the customer. In this use
case, spreading applications out allows for different
horizontal scaling than a traditional compute workload scale.
The intent is to scale by creating more copies of the
application in closer proximity to the users that need it
most, in order to ensure faster response time to user
requests. This provider deploys two datacenters at each of
the four chosen regions. The implications of this design are
based around the method of placing copies of resources in each
of the remote regions. Swift objects, Glance images, and block
storage need to be manually replicated into each region.
This may be beneficial for some systems, such as the case of
content service, where only some of the content needs to exist
in some but not all regions. A centralized Keystone is
recommended to ensure authentication and that access to the
API endpoints is easily manageable.</para>
<para>It is recommended that you install an automated DNS system such
as Designate. Application administrators need a way to
manage the mapping of which application copy exists in each
region and how to reach it, unless an external Dynamic DNS system
is available. Designate assists by making the process automatic
and by populating the records in the each region's zone.</para>
<para>Telemetry for each region is also deployed, as each region
may grow differently or be used at a different rate.
Ceilometer collects each region's meters from each
of the controllers and report them back to a central location.
This is useful both to the end user and the administrator of
the OpenStack environment. The end user will find this method
useful, as it makes possible to determine if certain
locations are experiencing higher load than others, and take
appropriate action. Administrators also benefit by
possibly being able to forecast growth per region, rather than
expanding the capacity of all regions simultaneously,
therefore maximizing the cost-effectiveness of the multi-site
design.</para>
<para>One of the key decisions of running this sort of
infrastructure is whether or not to provide a redundancy
model. Two types of redundancy and high availability models in
this configuration can be implemented. The first type
revolves around the availability of the central OpenStack
components. Keystone can be made highly available in three
central data centers that host the centralized OpenStack
components. This prevents a loss of any one of the regions
causing an outage in service. It also has the added benefit of
being able to run a central storage repository as a primary
cache for distributing content to each of the regions.</para>
<para>The second redundancy topic is that of the edge data center
itself. A second data center in each of the edge regional
locations house a second region near the first. This
ensures that the application does not suffer degraded
performance in terms of latency and availability.</para>
<para>This figure depicts the solution designed to have both a
centralized set of core data centers for OpenStack services
and paired edge data centers:</para>
<mediaobject>
<imageobject>
<imagedata contentwidth="4in"
fileref="../figures/Multi-Site_Customer_Edge.png"/>
</imageobject>
</mediaobject>
<section xml:id="geo-redundant-load-balancing">
<title>Geo-redundant load balancing</title>
<para>A large-scale web application has been designed with cloud
principles in mind. The application is designed provide
service to application store, on a 24/7 basis. The company has
typical 2-tier architecture with a web front-end servicing the
customer requests and a NoSQL database back end storing the
information.</para>
<para>As of late there has been several outages in number of major
public cloud providers&mdash;usually due to the fact these
applications were running out of a single geographical
location. The design therefore should mitigate the chance of a
single site causing an outage for their business.</para>
<para>The solution would consist of the following OpenStack
components:</para>
<itemizedlist>
<listitem>
<para>A firewall, switches and load balancers on the
public facing network connections.</para>
</listitem>
<listitem>
<para>OpenStack Controller services running, Networking,
dashboard, Block Storage and Compute running locally in
each of the three regions. The other services,
Identity, Orchestration, Telemetry, Image service and
Object Storage can be
installed centrally&mdash;with nodes in each of the region
providing a redundant OpenStack Controller plane
throughout the globe.</para>
</listitem>
<listitem>
<para>OpenStack Compute nodes running the KVM
hypervisor.</para>
</listitem>
<listitem>
<para>OpenStack Object Storage for serving static objects
such as images can be used to ensure that all images
are standardized across all the regions, and
replicated on a regular basis.</para>
</listitem>
<listitem>
<para>A Distributed DNS service available to all
regions&mdash;that allows for dynamic update of DNS records of
deployed instances.</para>
</listitem>
<listitem>
<para>A geo-redundant load balancing service can be used
to service the requests from the customers based on
their origin.</para>
</listitem>
</itemizedlist>
<para>An autoscaling heat template can be used to deploy the
application in the three regions. This template includes:</para>
<itemizedlist>
<listitem>
<para>Web Servers, running Apache.</para>
</listitem>
<listitem>
<para>Appropriate <literal>user_data</literal> to populate the central DNS
servers upon instance launch.</para>
</listitem>
<listitem>
<para>Appropriate Telemetry alarms that maintain state of
the application and allow for handling of region or
instance failure.</para>
</listitem>
</itemizedlist>
<para>Another autoscaling Heat template can be used to deploy a
distributed MongoDB shard over the three locations&mdash;with the
option of storing required data on a globally available swift
container. According to the usage and load on the database
server&mdash;additional shards can be provisioned according to
the thresholds defined in Telemetry.</para>
<!-- <para>The reason that three regions were selected here was because of
the fear of having abnormal load on a single region in the
event of a failure. Two data center would have been sufficient
had the requirements been met.</para>-->
<para>Two data centers would have been sufficient had the requirements
been met. But three regions are selected here to avoid abnormal
load on a single region in the event of a failure.</para>
<para>Orchestration is used because of the built-in functionality of
autoscaling and auto healing in the event of increased load.
Additional configuration management tools, such as Puppet or
Chef could also have been used in this scenario, but were not
chosen due to the fact that Orchestration had the appropriate built-in
hooks into the OpenStack cloud&mdash;whereas the other tools were
external and not native to OpenStack. In addition&mdash;since this
deployment scenario was relatively straight forward&mdash;the
external tools were not needed.</para>
<para>
OpenStack Object Storage is used here to serve as a back end for
the Image service since it is the most suitable solution for a
globally distributed storage solution&mdash;with its own
replication mechanism. Home grown solutions could also have
been used including the handling of replication&mdash;but were not
chosen, because Object Storage is already an intricate part of the
infrastructure&mdash;and proven solution.</para>
<para>An external load balancing service was used and not the
LBaaS in OpenStack because the solution in OpenStack is not
redundant and does not have any awareness of geo location.</para>
<mediaobject>
<imageobject>
<imagedata contentwidth="4in"
fileref="../figures/Multi-site_Geo_Redundant_LB.png"/>
</imageobject>
</mediaobject></section>
<section xml:id="location-local-services"><title>Location-local service</title>
<para>A common use for a multi-site deployment of OpenStack, is
for creating a Content Delivery Network. An application that
uses a location-local architecture requires low network
latency and proximity to the user, in order to provide an
optimal user experience, in addition to reducing the cost of
bandwidth and transit, since the content resides on sites
closer to the customer, instead of a centralized content store
that requires utilizing higher cost cross-country links.</para>
<para>This architecture usually includes a geo-location component
that places user requests at the closest possible node. In
this scenario, 100% redundancy of content across every site is
a goal rather than a requirement, with the intent being to
maximize the amount of content available that is within a
minimum number of network hops for any given end user. Despite
these differences, the storage replication configuration has
significant overlap with that of a geo-redundant load
balancing use case.</para>
<para>In this example, the application utilizing this multi-site
OpenStack install that is location aware would launch web
server or content serving instances on the compute cluster in
each site. Requests from clients are first sent to a
global services load balancer that determines the location of
the client, then routes the request to the closest OpenStack
site where the application completes the request.</para>
<mediaobject>
<imageobject>
<imagedata contentwidth="4in"
fileref="../figures/Multi-Site_shared_keystone1.png"/>
</imageobject>
</mediaobject></section>
</section>