IDM in a cluster

To ensure that your identity management service remains available in the event of system failure, you can deploy multiple IDM instances in a cluster. In a clustered environment, each instance points to the same external repository.

If one instance in a cluster shuts down or fails to check in with the cluster management service, a second instance will detect the failure. For example, if an instance named instance1 loses connectivity while executing a scheduled task, the cluster manager notifies the scheduler service that instance1 is not available. The scheduler service then attempts to clean up any jobs that instance1 was running at that time. Note that clustered instances claim scheduled tasks in a random order. For more information, refer to Scheduled tasks across a cluster.

Consistency and concurrency across cluster instances is ensured using multi-version concurrency control (MVCC). MVCC provides consistency because each instance updates only the particular revision of the object that was specified in the update.

All instances in a cluster run simultaneously. When a clustered deployment is configured with a load balancer, the deployment works as an active-active high availability cluster. If the database is also clustered, IDM points to the database cluster as a single system.

IDM requires a single, consistent view of all the data it manages, including the user store, roles, schedules, and configuration. If you can guarantee this consistent view, the number and locations of IDM nodes in a cluster will be limited only by your network latency and other network factors that affect performance.

The following diagram shows an IDM deployment where both the IDM instances and the databases are clustered, and accessed through a load balancer:

This chapter describes the changes required to configure multiple IDM instances in a single cluster. It does not include instructions on configuring the various third-party load balancing options.