How do you handle failover and node restarts in an Akka Cluster to maintain high availability?
In an Akka Cluster, high availability is maintained during failover and node restarts through several strategies :
1. Cluster Sharding : Distributes actors across nodes, ensuring that a single actor instance exists in the cluster. In case of node failure, shards are automatically rebalanced to available nodes.
2. Persistent Actors : Store their state using Event Sourcing or other persistence mechanisms, allowing them to recover from failures by replaying stored events.
3. Cluster Singleton : Ensures only one instance of a specific actor runs within the cluster. If the node hosting the singleton fails, it’s automatically started on another node.
4. Split Brain Resolver (SBR) : Resolves network partition scenarios by monitoring unreachable nodes and taking appropriate actions like downing nodes or keeping majority side operational.
5. Rolling Updates : Deploy new versions without downtime by updating nodes sequentially, ensuring continuous service availability.
6. Circuit Breakers : Prevent cascading failures by isolating problematic services and giving them time to recover.
7. Monitoring and Supervision : Use tools like Lightbend Telemetry for monitoring cluster health and implement supervision strategies to handle actor failures.
