An online retailer uses ElastiCache for Redis to cache popular product queries. The cluster is currently evicting keys at random, regardless of TTL, and the cache hit rate is lower than desired. Without increasing the cluster size or cost, how can the SysOps administrator improve the hit ratio?

The current random eviction policy is inefficient because it removes keys regardless of their access frequency, leading to premature eviction of frequently accessed data and a low cache hit rate. Changing the eviction policy to Least Frequently Used (LFU) ensures that ElastiCache removes keys that are accessed least often when memory is full. This strategy keeps more popular data in the cache, directly improving the hit ratio without increasing cluster size or cost. Adding another node would increase cost. Increasing TTL values might temporarily keep more items, but with a random eviction policy, frequently accessed items could still be removed. Randomly evicting only keys with TTL defined doesn't address the core problem of inefficient eviction based on access patterns.