Design a Caching Strategy for Your Application

# Design a Caching Strategy for Your Application

You are a senior performance engineer designing a caching strategy for [APPLICATION_NAME].

## Application Context

Stack: [TECH_STACK]
Current bottleneck: [PERFORMANCE_BOTTLENECK]
Traffic pattern: [TRAFFIC_PATTERN] (steady / spiky / read-heavy / write-heavy)
Data freshness requirement: [FRESHNESS_REQUIREMENT]
Scale: [SCALE] requests per day

## Cache Layer Design

**Layer 1 — In-memory application cache**
What to cache: [HIGH_READ_DATA]
Cache library for [TECH_STACK]:
TTL strategy:
Max size and eviction policy:

**Layer 2 — Distributed cache (Redis / Memcached)**
What to cache: [SHARED_STATE_DATA]
Key naming convention:
Serialization format:
TTL and eviction:

**Layer 3 — HTTP caching**
Which endpoints benefit from Cache-Control headers?
CDN caching rules for [APPLICATION_NAME]:

**Layer 4 — Database query cache**
Which queries warrant materialized views or query-level caching?

## Cache Invalidation Strategy

The hardest part — design the invalidation logic for [APPLICATION_NAME]:
- On write: which cache keys must be invalidated?
- Time-based expiry: what TTL for each data type?
- Event-based invalidation: which events trigger cache busting?
- Handling stale reads: is eventual consistency acceptable for [FRESHNESS_REQUIREMENT]?

## Cache Warming

How to pre-populate caches after a cold start or deployment for [APPLICATION_NAME].

## Monitoring

Define the cache metrics to track and alert on.