Redis is powerful when it has a clear job. The hard part is not putting data into a cache. It is knowing when cached data becomes wrong.
Cache-aside
Cache-aside keeps the application in control: read from Redis first, fall back to the database, then populate the cache.
Expiration and invalidation
Every cached value should have an expiration policy. For data that changes often, invalidation needs to be part of the write path.
Hot keys
Popular keys can become pressure points. Watch access patterns and design keys so a single value does not quietly become a bottleneck.