intermediateRedis — Data Structures, Persistence & Pub/Sub

An API is being hammered: 10,000 requests/second are hitting the database for the same popular product page. How do you use Redis to fix this?

Cache-Aside Pattern with Redis: 1) Check Redis first: String key = 'product:' + productId; String cached = redis.get(key); if (cached != null) return deserialize(cached). 2) Cache miss: query database, set in Redis with TTL: redis.set(key, serialize(product), 'EX', 300). Cache Stampede Prevention (when TTL expires, all 10,000 requests miss simultaneously): Use probabilistic early expiration: check

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An API is being hammered: 10,000 requests/second are hitting the database for the same popular product page. How do you use Redis to fix this?

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