102 lines
5.1 KiB
XML
102 lines
5.1 KiB
XML
<?xml version="1.0" encoding="UTF-8"?>
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<section xmlns="http://docbook.org/ns/docbook"
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xmlns:xi="http://www.w3.org/2001/XInclude"
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xmlns:xlink="http://www.w3.org/1999/xlink"
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version="5.0"
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xml:id="prescriptive-example-online-classifieds">
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<?dbhtml stop-chunking?>
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<title>Prescriptive example</title>
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<para>An online classified advertising company wants to run web applications
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consisting of Tomcat, Nginx and MariaDB in a private cloud. To be able
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to meet policy requirements, the cloud infrastructure will run in their
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own data center. The company has predictable load requirements, but requires
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scaling to cope with nightly increases in demand. Their current environment
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does not have the flexibility to align with their goal of running an open
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source API environment. The current environment consists of the following:</para>
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<itemizedlist>
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<listitem>
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<para>Between 120 and 140 installations of Nginx and
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Tomcat, each with 2 vCPUs and 4 GB of RAM</para>
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</listitem>
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<listitem>
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<para>A three-node MariaDB and Galera cluster, each with 4
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vCPUs and 8 GB RAM</para>
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</listitem>
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</itemizedlist>
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<para>The company runs hardware load balancers and multiple web
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applications serving their websites, and orchestrates environments
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using combinations of scripts and Puppet. The website generates large amounts of
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log data daily that requires archiving.</para>
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<para>The solution would consist of the following OpenStack
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components:</para>
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<itemizedlist>
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<listitem>
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<para>A firewall, switches and load balancers on the
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public facing network connections.</para>
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</listitem>
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<listitem>
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<para>OpenStack Controller service running Image,
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Identity, Networking, combined with support services such as
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MariaDB and RabbitMQ, configured for high availability on at
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least three controller nodes.</para>
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</listitem>
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<listitem>
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<para>OpenStack Compute nodes running the KVM
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hypervisor.</para>
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</listitem>
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<listitem>
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<para>OpenStack Block Storage for use by compute instances,
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requiring persistent storage (such as databases for
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dynamic sites).</para>
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</listitem>
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<listitem>
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<para>OpenStack Object Storage for serving static objects
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(such as images).</para>
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</listitem>
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</itemizedlist>
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<mediaobject><imageobject><imagedata contentwidth="4in"
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fileref="../figures/General_Architecture3.png"
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/></imageobject></mediaobject>
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<para>Running up to 140
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web instances and the small number of MariaDB instances
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requires 292 vCPUs available, as well as 584 GB RAM. On a
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typical 1U server using dual-socket hex-core Intel CPUs with
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Hyperthreading, and assuming 2:1 CPU overcommit ratio, this
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would require 8 OpenStack Compute nodes.</para>
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<para>The web application instances run from local storage on each
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of the OpenStack Compute nodes. The web application instances
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are stateless, meaning that any of the instances can fail and
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the application will continue to function.</para>
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<para>MariaDB server instances store their data on shared
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enterprise storage, such as NetApp or Solidfire devices. If a
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MariaDB instance fails, storage would be expected to be
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re-attached to another instance and rejoined to the Galera
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cluster.</para>
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<para>Logs from the web application servers are shipped to
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OpenStack Object Storage for processing and
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archiving.</para>
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<para>Additional capabilities can be realized by
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moving static web content to be served from OpenStack Object
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Storage containers, and backing the OpenStack Image service
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with OpenStack Object Storage.</para>
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<note>
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<para>
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Increasing OpenStack Object Storage means network bandwidth
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needs to be taken into consideration. Running OpenStack Object
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Storage with network connections offering 10 GbE or better connectivity
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is advised.
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</para>
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</note>
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<para>Leveraging Orchestration and Telemetry services is also a potential issue when
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providing auto-scaling, orchestrated web application environments.
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Defining the web applications in <glossterm
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baseform="Heat Orchestration Template (HOT)">Heat Orchestration Templates (HOT)</glossterm>
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negates the reliance on the current scripted Puppet solution.</para>
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<para>OpenStack Networking can be used to control hardware load
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balancers through the use of plug-ins and the Networking API.
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This allows users to control hardware load balance pools
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and instances as members in these pools, but their use in
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production environments must be carefully weighed against
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current stability.</para>
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</section>
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