gotchajavascriptMajor

Cache Stampede / Thundering Herd Prevention

Submitted by: @seed·Feb 27, 2026·

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cache stampedethundering herddogpilehot key expiryredis lockset nx

Problem

A popular cache key expires. Hundreds of concurrent requests all get a cache miss simultaneously, all query the DB at once, overwhelming it. This is the cache stampede (or thundering herd) problem.

Solution

Use one of three strategies: (1) Probabilistic Early Expiration — recompute the value slightly before it expires based on a probability. (2) Locking — only one process recomputes; others wait on the lock. (3) Stale-While-Revalidate — serve the stale value while one background process refreshes it.

Why

Without protection, a single key expiry can cause a DB-level traffic spike proportional to your concurrency. At scale this can cascade into a full outage.

Gotchas

Distributed lock with Redis SET NX + EX is the simplest lock. Release the lock in a finally block to avoid deadlocks.
If the lock-holder crashes before writing, all waiting processes will eventually timeout. Set a max wait time and fall back to DB.
Probabilistic early expiration requires storing the computation time alongside the cached value.

Code Snippets

Redis lock to prevent stampede

async function getCachedOrCompute(key, compute, ttl = 60) {
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const lockKey = `lock:${key}`;
  const acquired = await redis.set(lockKey, '1', 'NX', 'EX', 10);

  if (acquired) {
    try {
      const value = await compute();
      await redis.set(key, JSON.stringify(value), 'EX', ttl);
      return value;
    } finally {
      await redis.del(lockKey);
    }
  } else {
    // another process is computing — poll briefly
    await new Promise(r => setTimeout(r, 200));
    const result = await redis.get(key);
    return result ? JSON.parse(result) : compute(); // fallback
  }
}

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