Fixing JavaScript Async Await Performance Bottlenecks

During a recent refactor of a data-fetching layer, I noticed our dashboard took about 1.5 seconds to load—roughly 800ms longer than it did a week prior. After digging into the trace, I realized I’d accidentally introduced a classic "deadlock" of logic: I was awaiting three independent API calls in a row instead of running them concurrently.

It’s an easy trap to fall into when writing clean-looking code. We get so used to the linear flow of async/await that we stop thinking about the underlying concurrency of the JavaScript event loop.

Why Unintended Serial Execution Happens

When you use await inside a loop or sequence, you tell the engine to pause execution of the current function until that specific promise resolves. If your operations don't depend on each other, you're essentially idling the CPU for no reason.

Here is the anti-pattern I found in my code:

JAVASCRIPT
async function loadDashboardData() {
  const user = await fetchUser(); // Takes 200ms
  const posts = await fetchPosts(); // Takes 300ms
  const settings = await fetchSettings(); // Takes 200ms
  return { user, posts, settings };
}

In this case, the total time is 700ms. If these calls are independent, there's no reason they can't be fetched simultaneously. The await keyword is powerful, but it’s a synchronization primitive. When you use it incorrectly, you create async performance bottlenecks that compound as your application grows.

Fixing Bottlenecks with Promise.all Patterns

The most common fix is to trigger the promises first, then await their collective resolution. This is where Promise.all patterns become essential for high-performance applications.

By invoking the functions without await, you create the promise objects immediately. The event loop then manages these requests in the background.

JAVASCRIPT
async function loadDashboardDataOptimized() {
  const userPromise = fetchUser();
  const postsPromise = fetchPosts();
  const settingsPromise = fetchSettings();

  const [user, posts, settings] = await Promise.all([
    userPromise,
    postsPromise,
    settingsPromise
  ]);
  
  return { user, posts, settings };
}

Now, the total time is roughly 300ms—the duration of the longest request. It’s a massive win for perceived performance. If you are struggling with similar issues in React, you might want to look at how you manage state updates during these fetches, as discussed in my guide on profiling with React DevTools: identifying performance bottlenecks.

Comparison: Serial vs. Concurrent Execution

Debugging the Event Loop

If your app still feels sluggish, you might be dealing with javascript event loop debugging issues. Sometimes, it's not the network calls—it's the synchronous work you're doing right after the await resolves.

If you perform heavy object manipulation or massive array sorting immediately after an await, you block the main thread. This leads to poor Core Web Vitals, specifically Interaction to Next Paint (INP). For more on keeping the main thread clear, check out my notes on Core Web Vitals: fixing hydration bottlenecks for faster INP.

When things go wrong, remember that Promise.all fails if any promise rejects. If you need a more resilient approach, consider using Promise.allSettled, which I covered in JavaScript Promise.allSettled: mastering async error handling.

What I'd Do Differently

Next time, I'm going to implement a concurrency limit for these fetches. If you have 50 requests to make, Promise.all will fire them all at once, which might trigger rate limiting on your API or exhaust local memory.

I’m still experimenting with custom utility functions to throttle these requests. It’s easy to get excited about performance and end up accidentally DDoSing your own backend. Always profile your changes—don't just assume that "parallel is better." Sometimes, a controlled queue is the most robust path forward.

FAQ

Q: Does using Promise.all make my code harder to debug? A: It can. Since all promises run concurrently, stack traces can sometimes be less clear. Use descriptive variable names and ensure you have global error boundaries or catch blocks to handle individual failures.

Q: When should I NOT use Promise.all? A: Don't use it if the second operation depends on the result of the first. If you need the userId from the first call to fetch userPosts in the second, you must keep them serial.

Q: Is there a performance penalty for creating too many promises? A: Yes, but it's usually negligible compared to network latency. The real risk is resource exhaustion on the server or hitting API rate limits.