Add documentation for multi-engine
Describe how to set up Heat for a multi-engine deployment in the document on scaling Heat. blueprint multi-engine-docs Change-Id: I5db28b3bc8f5f5dda2d86d052223159adef5f5f0
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Jason Dunsmore
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@ -55,8 +55,10 @@ Developers Documentation
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Operations Documentation
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========================
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.. toctree::
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:maxdepth: 1
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scale_deployment
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scale_deployment
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Code Documentation
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==================
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@ -11,18 +11,20 @@
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License for the specific language governing permissions and limitations
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under the License.
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================
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Scaling Out APIs
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================
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====================
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Scaling a Deployment
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====================
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Working in an architecture where a large number of incoming requests need to be
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handled, the API services can be overloaded. In those scenarios, in order to
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increase the system performance, it can be helpful to run multiple APIs and use
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a load balancing mechanism.
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When deploying in an environment where a large number of incoming requests need
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to be handled, the API and engine services can be overloaded. In those
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scenarios, in order to increase the system performance, it can be helpful to run
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multiple load-balanced APIs and engines.
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This guide details how to scale out the ReST and CFN APIs, also known as the
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*heat-api* and *heat-api-cfn* services, respectively.
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This guide details how to scale out the ReST API, the CFN API, and the engine,
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also known as the *heat-api*, *heat-api-cfn*, and *heat-engine* services,
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respectively.
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.. _scale_deployment_assumptions:
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Assumptions
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===========
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@ -41,7 +43,7 @@ Architecture
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============
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This section shows the basic Heat architecture, the load balancing mechanism
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used and the target scaling out architecture.
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used and the target scaled out architecture.
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Basic Architecture
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------------------
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@ -52,9 +54,9 @@ diagram below, where we have a CLI that sends HTTP requests to the ReST and CFN
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APIs, which in turn make calls using AMQP to the Heat engine.
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::
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|- [ REST API ] -|
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[ CLI ] -- < HTTP > -- -- < AMQP > -- [ ENGINE ]
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|- [ CFN API ] -|
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|- [REST API] -|
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[CLI] -- <HTTP> -- -- <AMQP> -- [ENGINE]
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|- [CFN API] -|
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Load Balancing
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--------------
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@ -70,19 +72,23 @@ This way, the proxy will take the CLIs requests to the APIs and act on their
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behalf. Once the proxy receives a response, it will be redirected to the caller
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CLI.
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A round-robin distribution of messages from the AMQP queue will act as the load
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balancer for multiple engines. Check that your AMQP service is configured to
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distribute messages round-robin (RabbitMQ does this by default).
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Target Architecture
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-------------------
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A scaling out Heat architecture is represented in the diagram below:
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A scaled out Heat architecture is represented in the diagram below:
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::
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|- [ REST-API ] -|
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|- ... -|
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|- [ REST-API ] -|
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[ CLI ] -- < HTTP > -- [ PROXY ] -- -- < AMQP > -- [ ENGINE ]
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|- [ API-CFN ] -|
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|- ... -|
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|- [ API-CFN ] -|
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|- [REST-API] -|
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|- ... -|
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|- [REST-API] -| |- [ENGINE] -|
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[CLI] -- <HTTP> -- [PROXY] -- -- <AMQP> -- |- ... -|
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|- [API-CFN] -| |- [ENGINE] -|
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|- ... -|
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|- [API-CFN] -|
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Thus, a request sent from the CLI looks like:
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@ -90,8 +96,8 @@ Thus, a request sent from the CLI looks like:
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1. CLI contacts the proxy;
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2. The HAProxy server, acting as a load balancer, redirects the call to an
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API instance;
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3. The API server sends messages to RabbitMQ, and the engine server picks up
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messages from the RabbitMQ queue.
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3. The API server sends messages to the AMQP queue, and the engines pick up
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messages in round-robin fashion.
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Deploying Multiple APIs
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=======================
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@ -107,9 +113,6 @@ new ReST and CFN API services, you must run:
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python bin/heat-api --config-file=/etc/heat/heat.conf
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python bin/heat-api-cfn --config-file=/etc/heat/heat.conf
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Running multiple APIs require that you create as many copies of this file as the
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number of instances you want to deploy.
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Each API service must have a unique address to listen. This address have to be
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defined in the configuration file. For ReST and CFN APIs, modify the
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*[heat_api]* and *[heat_api_cfn]* blocks, respectively.
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@ -125,11 +128,35 @@ defined in the configuration file. For ReST and CFN APIs, modify the
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bind_port = {API_CFN_PORT}
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bind_host = {API_CFN_HOST}
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If you wish to run multiple API processes on the same machine, you must create
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multiple copies of the heat.conf file, each containing a unique port number.
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In addition, if you want to run some API services in different machines than
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the devstack server, you have to update the loopback addresses found at the
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*sql_connection* and *rabbit_host* properties to the devstack server's IP,
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which must be reachable from the remote machine.
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Deploying Multiple Engines
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==========================
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All engines must be configured to use the same AMQP service. Ensure that all of
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the *rabbit_*\* and *kombu_*\* configuration options in the *[DEFAULT]* section
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of */etc/heat/heat.conf* match across each machine that will be running an
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engine. By using the same AMQP configuration, each engine will subscribe to the
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same AMQP *engine* queue and pick up work in round-robin fashion with the other
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engines.
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One or more engines can be deployed per host. Depending on the host's CPU
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architecture, it may be beneficial to deploy several engines on a single
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machine.
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To start multiple engines on the same machine, simply start multiple
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*heat-engine* processes:
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::
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python bin/heat-engine --config-file=/etc/heat/heat.conf &
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python bin/heat-engine --config-file=/etc/heat/heat.conf &
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Deploying the Proxy
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===================
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@ -201,8 +228,8 @@ as to show more details of the configuration by describing a concrete sample.
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Architecture
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------------
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This subsection shows a basic OpenStack architecture and the target one that
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will be meet.
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This section shows a basic OpenStack architecture and the target one
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that will be used for testing of the scaled-out heat services.
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Basic Architecture
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^^^^^^^^^^^^^^^^^^
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@ -212,7 +239,8 @@ For this sample, consider that:
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1. We have an architecture composed by 3 machines configured in a LAN, with
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the addresses A: 10.0.0.1; B: 10.0.0.2; and C: 10.0.0.3;
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2. The OpenStack devstack installation, including the Heat module, has been
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done in the machine A, as shown in the Assumptions section.
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done in the machine A, as shown in the
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:ref:`scale_deployment_assumptions` section.
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Target Architecture
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^^^^^^^^^^^^^^^^^^^
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@ -223,8 +251,8 @@ subsections show how to deploy a scaling out Heat architecture by:
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1. Running one ReST and one CFN API on the machines B and C;
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2. Setting up the HAProxy server on the machine A.
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Running API Services
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--------------------
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Running the API and Engine Services
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-----------------------------------
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For each machine, B and C, you must do the following steps:
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@ -234,10 +262,19 @@ For each machine, B and C, you must do the following steps:
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3. Make required changes on the configuration file;
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4. Enter the Heat local repository and run:
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::
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::
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python bin/heat-api --config-file=/etc/heat/heat.conf
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python bin/heat-api-cfn --config-file=/etc/heat/heat.conf
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python bin/heat-api --config-file=/etc/heat/heat.conf
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python bin/heat-api-cfn --config-file=/etc/heat/heat.conf
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5. Start as many *heat-engine* processes as you want running on that
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machine:
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::
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python bin/heat-engine --config-file=/etc/heat/heat.conf &
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python bin/heat-engine --config-file=/etc/heat/heat.conf &
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...
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Changes On Configuration
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^^^^^^^^^^^^^^^^^^^^^^^^
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