The 'redis cluster error ttl exhausted' usually arises when your Redis Cluster nodes cannot agree on a consistent view of the cluster. One of the common causes is network partitioning, where some nodes are unable to communicate with others and therefore, assume those nodes are down.
Another cause could be related to memory limits. If the nodes in the Redis Cluster have exceeded their memory capacity due to data storage and TTL (Time To Live) settings, they may not be able to process new incoming requests or commands adequately.
Lastly, misconfigurations in your Redis settings can also lead to this issue. For instance, if the configuration for node timeout is set too low, it might cause frequent node failovers, leading to an inconsistent state within the cluster.
Firstly, to address potential network issues, ensure that all nodes within the Redis Cluster can communicate with each other without any restrictions. This can be confirmed by checking firewalls, security groups, or any network policies in place.
Next, regarding memory issues, consider optimizing your TTL settings. If you have keys that aren't expiring as expected, it could lead to memory exhaustion. Use the
EXPIRE command to set proper TTLs for your keys. Additionally, you could use memory-optimizing policies such as LRU (Least Recently Used) or LFU (Least Frequently Used) to manage key evictions when the memory limit is reached.
Finally, review the configuration of your Redis Cluster, especially regarding timeouts and failover settings. A good starting point is to increase the timeout value in your configuration or to enable the
cluster-require-full-coverage no option, which allows the cluster to serve queries even if part of the cluster is down.
In more complex scenarios, it might be necessary to take a closer look at the specific logs and error messages produced by your Redis Cluster in order to find more targeted solutions.