Database Cache Layer

Overview

Implement multi-tier caching strategies using Redis, application-level in-memory caches, and query result caching to reduce database load and improve read latency. This skill covers cache-aside, write-through, and write-behind patterns with proper invalidation strategies, TTL configuration, and cache stampede prevention.

Prerequisites

• Redis server (6.x+) available or Docker for running docker run redis:7-alpine
• redis-cli installed for cache inspection and debugging
• Application framework with Redis client library (ioredis, redis-py, Jedis, go-redis)
• Database query profiling data identifying read-heavy and slow queries
• Understanding of data freshness requirements (how stale can cached data be)
• Monitoring tools for cache hit rate and Redis memory usage

Instructions

1. Profile database queries to identify caching candidates. Focus on queries that: execute more than 100 times per minute, take longer than 50ms, return data that changes less frequently than every 5 minutes, and produce results smaller than 1MB. Use pg_stat_statements or MySQL slow query log.

2. Design the cache key schema with a consistent naming convention: service:entity:identifier:variant. Examples: app:user:12345:profile, app:products:category:electronics:page:1. Include a version prefix to enable bulk invalidation: v2:app:user:12345.