Caching Strategy Designer
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Designs caching strategies across the stack to cut latency and load. Chooses cache layers (browser, CDN, application, database), picks patterns (cache-aside, read-through, write-through, write-behind), sets TTLs and eviction policies, and plans invalidation to avoid staleness and stampedes. Produces a layered plan with keys, TTLs, and invalidation rules.
Anwendungsfälle
- Designing a multi-layer caching plan for a read-heavy API
- Choosing between cache-aside and read-through patterns
- Planning invalidation to prevent stale data and stampedes
- Setting TTLs and eviction policies for a Redis cache
Beispiel-Prompt
Design a caching strategy for a product catalog API. Context: read-heavy, data updated a few times per hour, Redis + a CDN available. Deliver: 1. Which layers to cache at (CDN, app, DB) and why 2. Pattern per layer (cache-aside, read-through, etc.) with trade-offs 3. Key naming scheme, TTLs, and eviction policy 4. Invalidation approach on updates, including how to prevent cache stampedes 5. Metrics to track (hit ratio, staleness) to validate the design
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