How to prevent avalanches with redis

Redis avalanche is a phenomenon that Redis overloads due to large amounts of caches simultaneously expire. In order to prevent avalanches, the following measures can be taken: avoid centralized expiration and distribute expiration time. Expand Redis instances to distribute request pressure. Limit the number of requests to avoid overloading of a single instance. Downgrade part of the request to other data sources. Use message queues to process requests asynchronously to reduce peak load. Use local cache to reduce dependency on Redis. Use Redis Sentinel to monitor instances and automatically failover to ensure high availability. Use Redis Cluster to shard data to improve availability and scalability and reduce avalanche risk.

Redis anti-acanimal mechanism

What is a Redis avalanche?

When a large number of caches that rely on Redis expire at the same time, a large number of requests will flow into Redis instantly, causing the Redis service to overload or even crash. This phenomenon is called Redis avalanche.

Redis anti-acanimal mechanism

To prevent Redis avalanche, the following measures can be taken:

1. Avoid centralized expiration

• Use different expiration times to avoid expiration of large caches at the same time.
• Use the sliding window mechanism to distribute cache expiration time within a time range.

2. Expand Redis instance

• Increase the number of Redis instances to disperse request pressure.
• Use Redis clusters to spread data across multiple nodes.

3. Use the current limiting mechanism

• Limit the number of requests to Redis to avoid overloading of a single instance.
• Consider using distributed current limiting schemes such as RedisBloom.

4. Use the downgrade strategy

• When Redis fails, downgrade some requests to other data sources.
• Consider using frameworks such as Hystrix or Sentinel to implement a downgrade strategy.

5. Asynchronously handle requests

• Use message queues or stream processing frameworks to process requests asynchronously, reducing the peak load of Redis.
• Consider using technologies like Redis Streams or Kafka.

6. Use local cache

• Use local cache in your application to reduce dependency on Redis.
• Consider using a local cache library like Caffeine or Guava.

7. Use Redis Sentinel

• Redis Sentinel can monitor Redis instances and automatically fail over in the event of a failure.
• It helps ensure high availability of Redis services.

8. Using Redis Cluster

• Redis Cluster is a distributed Redis implementation that can shard data across multiple nodes.
• It provides higher availability and scalability and reduces avalanche risk.

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