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Caching Module
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Caching Module
Core details
Title
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Description
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A Caching Module stores frequently accessed data in fast-access layers like Redis or in-memory to reduce database load and improve response times. It implements strategies like LRU, TTL, and cache-aside patterns.
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Usage & Trade-offs
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When to use it
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Implement Caching when: - Experiencing high read traffic on databases. - Optimizing API latency for user-facing endpoints. - Handling expensive computations or external API calls. - Scaling read-heavy workloads horizontally.
Pros
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- Dramatically reduces latency for repeated queries. - Offloads pressure from primary data stores. - Supports invalidation for data consistency. - Cost-effective for volatile or computed data. - Integrates with ORMs for transparent caching.
Cons
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- Cache invalidation is notoriously hard (stale data risks). - Memory usage can balloon without eviction policies. - Adds complexity to deployment and monitoring. - Distributed caches introduce network latency. - Debugging cache hits/misses requires instrumentation.
Notes
Note: Use Redis for distributed caching in microservices. Implement cache warming for cold starts. Monitor hit ratios (>80% ideal) and tune accordingly.
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