Async Isn't Free: Performance Lessons from Real-World Node.js

If you're building in Node.js, you've probably embraced async/await like the rest of us. Cleaner syntax, non-blocking I/O — what's not to love? But here's the thing: async code isn't always faster. In fact, we hit a point where it made things slower.

The Myth: Async = Fast

Async code means non-blocking, not instantaneous. We made the mistake of parallelizing everything — dozens of concurrent API calls, database hits, and file reads — all launched with Promise.all(). And guess what? The system crashed under memory pressure and latency increased across the board.

Where It Broke

• 📈 High concurrency overloaded downstream APIs
• 🧠 Uncontrolled async loops triggered over 1000 open DB connections
• ⛔ Memory leaks from unresolved promises in edge cases

Real Fixes We Applied

After days of profiling and head-scratching, we rolled out these changes:

• 🔒 Added concurrency limits using p-limit to control how many async ops run in parallel
• 🧹 Used AbortController to cancel long-running fetches
• 💾 Implemented LRU caching to avoid duplicate async reads
• 📉 Measured per-function async cost using clinic.js and 0x

The Hidden Costs of Async

Async code introduces:

• Call stack fragmentation — async breaks stack traces unless handled properly
• Error swallowing — unhandled promises vanish silently in production
• Timing bugs — race conditions and double-handlers from careless awaits

Performance Tips for Node.js Devs

• ✅ Limit concurrency — not everything should run at once
• ✅ Use timeouts and abort signals on every async operation
• ✅ Monitor event loop lag and active handles with tools like clinic doctor
• ✅ Use pools (e.g. for DB) — avoid raw socket floods

Final Thought

Async is powerful — but uncontrolled async is chaos. If you treat concurrency as a lever (not a cheat code), you'll build faster, stabler systems. Remember: just because it's non-blocking doesn't mean it's free.