SoFunction
Updated on 2025-04-22

Redis Sentinel and Cluster Split Brain Problem and Solutions

This article will explore in-depth the possible split brain problems that Redis may have in sentinel mode and cluster mode, including its occurrence scenarios, causes, and effective solutions. At the same time, we will also provide corresponding code examples and configuration solutions to help readers understand and implement.

1. Overview of split brain problems

Split-Brain refers to a distributed system where a system is divided into two or more subsets due to network partitioning or other factors, each subset thinks it is the only active part of the entire system and continues to operate independently. For Redis, whether it is Sentinel mode or cluster mode, once the brain split occurs, it may lead to data inconsistency or even unavailable services.

1.1 Redis Sentinel Schizorene

Redis Sentinel is a tool used to monitor the health of Redis instances and to automatically fail over when the master node fails. However, in some cases, such as network delays or brief interruptions, Sentinel may mistakenly assume that the master node has expired and initiates a new master node election process, resulting in a split brain.

1.2 Redis Cluster

Redis Cluster provides native data sharding support, allowing users to easily scale Redis to cope with larger data storage needs. However, when facing network partitions, if nodes in a certain area cannot communicate with other nodes, a split brain may occur, causing different cluster views to be held between different areas.

2. Solution to split brain problem

For the two split brain conditions mentioned above, we can take the following measures:

  • Improve network stability:Minimize network fluctuations caused by external factors as much as possible.
  • Optimized configuration parameters:Tolerate longer network latency by adjusting Redis's related configuration items, such as increasing the down-after-milliseconds value.
  • Use arbitration mechanism:Introduce additional arbitrator roles when designing system architectures to ensure that correct decisions can be made even in the case of network partitions.

3. Specific implementation

Here is a simple example to show how to reduce the probability of Redis Sentinel triggering failover by modifying the configuration file:

sentinel down-after-milliseconds mymaster 60000
sentinel failover-timeout mymaster 180000

The above settings mean that the master node will only be considered offline if it does not respond for 60 seconds in a row; and wait at least 3 minutes before attempting to failover.

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