nextjs6 min read
Next.js Data Fetching — fetch, cache, revalidate, and ISR
Master Next.js data fetching with fetch caching strategies, time-based and on-demand revalidation, ISR, and parallel fetching patterns for optimal performance.
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Caching
16 articles
scaling6 min read
Cache Stampede — How to Prevent Thundering Herd on Cache Expiry
Cache stampede occurs when a high-traffic cache key expires and hundreds of requests simultaneously hit your database. This guide covers probabilistic early expiry, mutex locking, and background refresh strategies to eliminate thundering herd problems.
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typescript7 min read
Redis with Node.js — Caching, Sessions, and Pub/Sub 2026
Master Redis in Node.js with TypeScript for caching, session management, rate limiting, and pub/sub messaging. Covers the official redis client, ioredis, and production patterns for 2026.
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redis5 min read
Redis Caching Guide 2026 — Improve API Performance 10x
Complete Redis caching guide for 2026 covering cache-aside, write-through, TTL strategies, session storage, and rate limiting patterns with Node.js and ioredis.
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backend6 min read
Cache Invalidation Hell — The Second Hardest Problem in Computer Science
Users see stale prices. Admins update settings but the old value is served for 10 minutes. You delete a record but it keeps appearing. Cache invalidation is famously hard — and most implementations have subtle bugs that serve wrong data long after the source changed.
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eventual-consistency9 min read
Eventual Consistency in Practice — Building UIs and APIs That Handle Stale Data
Master read-after-write consistency, version vectors, causal consistency tokens, and UI patterns for systems where data is temporarily stale.
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backend6 min read
Inconsistent Reads — The Eventual Consistency Shock
User updates their profile. Refreshes the page — old data shows. They update again. Still old data. They''re furious. Your system is eventually consistent — but nobody told the user (or the developer who designed the UI). Here''s how to manage consistency expectations in distributed systems.
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http8 min read
HTTP Caching in Production — Cache-Control, ETags, and CDN Integration
Master HTTP caching layers from browser to CDN. Learn Cache-Control directives, ETag validation, and production strategies for cache consistency.
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backend11 min read
LLM Response Caching — Semantic Caching to Cut Costs and Latency by 60%
Cut LLM costs and latency with exact match caching, semantic caching, embedding similarity, Redis implementation, cost savings, and TTL strategies.
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AI9 min read
LLM Output Caching — Semantic Caching to Cut Costs by 60 Percent
Implement exact-match and semantic caching with Redis to dramatically reduce LLM API calls, improving latency and cutting costs by 60% through intelligent cache invalidation.
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redis12 min read
Redis Cluster in Production — Sharding, Failover, and the Gotchas No One Warns You About
Understand Redis Cluster architecture, consistent hashing, CROSSSLOT errors, hot slot detection, replication, and monitoring for production deployments.
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backend6 min read
Redis Eviction Causing Chaos — When Your Cache Turns on You
Redis is full. Instead of failing gracefully, it starts silently evicting your most important cache keys — session tokens, rate limit counters, distributed locks. Your app behaves mysteriously until you realize Redis has been quietly deleting data. Here''s how to tame Redis eviction.
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redis9 min read
Redis in 2026 — Beyond Caching to the Multi-Model Database
Redis evolved from a cache into a multi-model database: vector storage, time series, JSON, full-text search. Learn when to use Redis and modern patterns for 2026.
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redis11 min read
Redis Patterns in Production — Caching, Sessions, Locks, and Rate Limiting Done Right
Master Redis patterns: cache-aside vs write-through caching, distributed locks with Lua, sliding window rate limiters, pub/sub, sorted sets for leaderboards, Redis Streams, and memory management.
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Caching7 min read
Semantic Caching for LLMs — Reducing API Costs With Similarity-Based Cache Hits
Implement semantic caching to reduce LLM API costs by 40-60%, handle similarity thresholds, TTLs, and cache invalidation in production.
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backend6 min read
Traffic Spike After Marketing Campaign — Surviving Your Own Success
Your marketing team runs a campaign. It goes viral. Traffic spikes 50x in 10 minutes. Your servers crash. This is the happiest disaster in tech — and it''s entirely preventable. Here''s how to build systems that survive sudden viral traffic spikes.
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