How Khepri Approaches Failure Recovery

This section describes Khepri's Raft-based approach to failure handling and recovery.

Behavior in Cluster Minority

When Mnesia is used as the metadata store backend, RabbitMQ provides network partition recovery strategies.

Their role is to take care of conflicts resolution when a cluster is split, because nodes on both side will continue to write to the metadata store, based on an incomplete view of the cluster. Some strategies prevent the conflicts in the first place by stopping the service on the side of the split that has less cluster members, i.e., the minority.

Raft, the consensus algorithm implemented by the Ra library and used by quorum queues, stream queues and Khepri, only provides one recovery strategy, which most closely resembles the pause_minority strategy from the set of partition handling strategies developed for Mnesia.

When a Khepri member wants to update the metadata store, or needs to perform a query that spans all online cluster members, or even wants to change the cluster membership, the request goes through the elected leader replica in that Khepri cluster.

If the leader does not get an acknowledgement from the absolute majority of the members, the request blocks and may time out. Note that this is a very simplified description of how Raft approaches failure handling and recovery but also the most important aspect to understand.

Therefore, if a RabbitMQ node that is on the minority side of a network split wants to declare an exchange, a queue or a binding for instance, the request will time out if the split is not resolved in time.

Stopped RabbitMQ Nodes

This minority is also true if more than half of the RabbitMQ nodes are currently stopped or lost: the remaining running nodes cannot reach the other nodes and Raft cannot reach consensus.

Is the Behavior Configurable?

Unlike the network partition recovery strategies used with Mnesia, the strategy used with Khepri is not configurable: it is the design of the Raft algorithm.

Thanks to this, it is easier to reason about the behavior of RabbitMQ and understand what could happen.

Nodes Failing and Recovering

When a node that used to host a Khepri leader replica fails, a new leader will be selected using the Raft leader election semantics. When then the node hosting the previous leader rejoins, it will recognize that a new leader is present and it uses a new election term, and step down to become a follower.

The schema changes that were committed in the cluster while this node was down will be applied on it starting on the first common point in the log (change history) between it and the new leader. This happens completely transparently to applications and is not really different from how a newly added node catches up with the existing Khepri leader replica.