Distributed Locks Are Harder Than They Look: Leases, Fencing Tokens, and a Go Implementation
Every language-level sync.Mutex rests on a guarantee the operating system makes for you: if a thread dies holding the lock,
Tag: Redis
Client-Side Caching with Redis: Invalidation Is the Whole Design
Most services read the same rows over and over. A user profile endpoint gets hammered by the same traffic pattern
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Distributed Rate Limiting in Go: Token Buckets, Redis, and the Fail-Open Decision
Rate limiting looks like a solved problem until the day your API runs on more than one machine. The in-memory
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Distributed Rate Limiting in Go: GCRA, Redis, and the Pitfalls Nobody Warns You About
Every production rate limiter has two layers. The first layer is the algorithm: token bucket, leaky bucket, fixed window, sliding
HyperLogLog: Counting a Billion Uniques in 1.5 KB of Memory
Every analytics dashboard has one question that looks trivial and isn’t: how many unique users did this? You can run
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Idempotency Keys Done Right: Building Retry-Safe APIs That Never Double-Charge
You hit “Place Order,” the spinner hangs for ten seconds, and you tap the button again. Now the fear sets
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Caching Strategies in Distributed Systems: Cache-Aside, Write-Through, and Surviving the Thundering Herd
Almost every service that survives its own traffic eventually grows a cache. The idea is simple: the database is slow
The Open Source License Wars: Forks, Reversals, and the New Economics of Free Software
Every few months, another beloved open source project announces a license change. The blog post is polished, the reasoning sounds
Idempotency Keys: Making Your API Safe for Retries
Every web developer has been there: a user clicks “Submit Payment” and nothing happens. The spinner keeps spinning. They click
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Rate Limiting Strategies for Production APIs: From Token Buckets to Distributed Throttling
Every public API has a ceiling. Whether you’re running a SaaS platform, a microservice cluster, or a simple REST endpoint,