Cache Stampede Prevention in Go — 1k req/s load test + full monitoring stack

🚀 What I built

A production-ready cache stampede prevention library in Go with 3 strategies,

full Prometheus metrics, and a live Grafana dashboard.

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🔥 The problem

When a hot cache key expires, thousands of concurrent requests all miss at the same

time and hammer the database. This is a cache stampede — and it can take down your DB.

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🛡️ 3 strategies implemented

1. Hard Lock + Stale-While-Revalidate

Only one process fetches the new value (Redis SETNX + Lua atomic script)

Everyone else gets served the stale value immediately — zero wait time

2, XFetch (probabilistic early refresh)

Formula: P = exp(-β × timeRemaining / δ)

Starts refreshing in the background before the key expires

No thundering herd because refreshes are spread out probabilistically

1. Request Coalescing (singleflight)

In-process deduplication: 50 concurrent goroutines → 1 real DB call

~13:1 dedup ratio visible in Grafana

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📊 Monitoring stack

Prometheus metrics for every decision point (hit/miss/stale/lock_contention)

Grafana dashboard with 9 panels auto-provisioned via docker-compose

Circuit Breaker state transitions (Closed → Open → Half-Open) tracked as gauges

Load test drives 1 000 req/s of sustained traffic

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🧱 Tech stack

Go 1.2x· Redis 7 · Prometheus · Grafana · Docker Compose

Please give me a star for my repository if it is useful for you. Thanks

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🔗 GitHub: [https://github.com/0x48core/go-latency/tree/main/cache-stampede]