NOTE
Designing a Cache Middleware Layer
A cache abstraction layer for routing, serialization, TTL policy, observability, stampede protection, multi-level caching, and graceful fallback.
This is a historical learning note and may contain outdated or incomplete understanding.
1. Why Add Middleware?
A cache client layer can centralize behavior repeated across services:
- key construction;
- serialization;
- TTL/jitter;
- routing/sharding;
- retries/timeouts;
- metrics/tracing;
- local + remote cache policy.
The abstraction should make correctness visible rather than turning every cache read into an opaque magic call.
2. API Shape
Expose typed get/set/delete/batch primitives and distinguish:
- cache miss;
- backend error;
- decode/schema error.
These outcomes should not collapse into the same nil value.
3. Stampede Protection
Support request coalescing/singleflight and TTL jitter so many simultaneous misses do not hammer the source of truth.
4. Multi-Level Cache
Local memory can reduce remote Redis QPS, but invalidation and per-process staleness become more complex.
Use explicit versioning/events/short TTLs according to the required freshness.
5. Failure Behavior
A cache is often optional. On timeout, fail open to the source of truth when safe—but protect the source with concurrency limits so a cache outage does not become a database outage.
6. Observability
Track hit/miss, stale hits, backend latency/errors, key size/cardinality, coalesced requests, and fallback load.