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Configuring the controller
The cloud controller runs on the management network and must talk to all other services.
intro-ha-arch-pacemaker.rst controller-ha-pacemaker.rst controller-ha-vip.rst controller-ha-haproxy.rst controller-ha-memcached.rst controller-ha-identity.rst controller-ha-telemetry.rst
Overview of highly available controllers
OpenStack is a set of services exposed to the end users as HTTP(s) APIs. Additionally, for your own internal usage, OpenStack requires an SQL database server and AMQP broker. The physical servers, where all the components are running, are called controllers. This modular OpenStack architecture allows you to duplicate all the components and run them on different controllers. By making all the components redundant, it is possible to make OpenStack highly available.
In general, we can divide all the OpenStack components into three categories:
- OpenStack APIs: APIs that are HTTP(s) stateless services written in python, easy to duplicate and mostly easy to load balance.
- The SQL relational database server provides stateful type consumed by other components. Supported databases are MySQL, MariaDB, and PostgreSQL. Making the SQL database redundant is complex.
Advanced Message Queuing Protocol (AMQP)provides OpenStack internal stateful communication service.
Common deployment architectures
We recommend two primary architectures for making OpenStack highly available.
The architectures differ in the sets of services managed by the cluster.
Both use a cluster manager, such as Pacemaker or Veritas, to orchestrate the actions of the various services across a set of machines. Because we are focused on FOSS, we refer to these as Pacemaker architectures.
Traditionally, Pacemaker has been positioned as an all-encompassing solution. However, as OpenStack services have matured, they are increasingly able to run in an active/active configuration and gracefully tolerate the disappearance of the APIs on which they depend.
With this in mind, some vendors are restricting Pacemaker's use to
services that must operate in an active/passive mode (such as
cinder-volume), those with multiple states (for example,
Galera), and those with complex bootstrapping procedures (such as
RabbitMQ).
The majority of services, needing no real orchestration, are handled by systemd on each node. This approach avoids the need to coordinate service upgrades or location changes with the cluster and has the added advantage of more easily scaling beyond Corosync's 16 node limit. However, it will generally require the addition of an enterprise monitoring solution such as Nagios or Sensu for those wanting centralized failure reporting.