Eviction Policies, Memory Management, Persistence, and Expiration Strategy
Operate Redis responsibly by understanding what happens when memory is constrained and how Redis can retain or discard data.
Inside this chapter
- Why Memory Strategy Matters
- Eviction Policies
- Persistence Options
- Expiration Strategy
- Business Example
Series navigation
Study the chapters in order for the clearest path from Redis basics to advanced cache architecture, operations, and distributed-system design. Use the navigation at the bottom to move smoothly through the full tutorial series.
Why Memory Strategy Matters
Redis keeps data in memory, so memory usage is a core operational concern. Teams must understand what happens when capacity fills up and which data should be retained, expired, or evicted.
Eviction Policies
Redis supports multiple eviction behaviors, such as removing least-recently used keys or evicting only keys with expiration settings. The right policy depends on how the application uses Redis.
Persistence Options
Although Redis is in-memory first, it can persist data through snapshots or append-only mechanisms depending on durability needs. This matters especially when Redis is used for more than disposable caching.
Expiration Strategy
Not every key should have the same TTL. Short-lived tokens, medium-lived cache entries, and nearly persistent coordination records may all need different treatment. Expiration should reflect business meaning, not just arbitrary defaults.
Business Example
A dashboard cache may safely evict stale analytical summaries, but a queue-like workflow key may require more careful persistence and memory planning. One Redis cluster may support multiple data classes, so policy choices must be intentional.