Understanding Event Loops Beyond the Basics

tl;dr: The event loop isn’t just about async and setTimeout, it’s a layered system of queues, priorities, and runtime quirks. This post digs into the subtle mechanics of microtasks vs macrotasks, how await really behaves, and why understanding the loop matters for performance and correctness in production-grade systems.

If you’ve been around long enough to have scars from callback hell or debugging race conditions at 3 AM, chances are you’re already familiar with the event loop. It’s the core of how many modern runtimes manage concurrency without threads, e.g. Node.js, Python’s asyncio, browser JavaScript, etc. But there’s a surprising amount of nuance lurking just beneath the surface of the textbook diagrams. This post goes past the usual high-level explanation and digs into where event loops get both tricky and interesting.

A Quick Recap (Just to Sync Terms)

The event loop is fundamentally a coordination mechanism. It waits for tasks, events, or messages and dispatches them one at a time. This lets a single-threaded environment appear asynchronous and non-blocking. Great. But that’s the part we all know.

Where things get more subtle is in how these tasks are scheduled, prioritized, and even what qualifies as a “task” depending on the runtime and its architecture.

Microtasks, Macrotasks, and Prioritization

Let’s talk about microtasks (aka “jobs” in ECMAScript) and macrotasks (a term not actually used in the spec, but widely adopted). In Node.js and modern browsers, these two categories have different queues and behaviors.

  • Macrotasks include I/O events, setTimeout, setInterval, setImmediate (Node), etc.
  • Microtasks include promises (.then, async/await), queueMicrotask, and MutationObservers.

After a macrotask is executed, the event loop runs all microtasks in the queue before proceeding to the next macrotask. This often trips people up when debugging async timing issues. It’s not just “promise comes later”, it’s “promise comes before nearly everything else.”

Example:

setTimeout(() => console.log("macro"), 0);
Promise.resolve().then(() => console.log("micro"));
// Output:
// micro
// macro

In other words: microtasks can starve the event loop if not used carefully.

The Hidden Cost of Await

In Python’s asyncio, a similar model exists, though it’s abstracted away a bit differently. Each await yields control back to the event loop, but every yield is not free. The event loop has to schedule your coroutine, switch context, and jump through a few internal hoops.

That becomes particularly relevant in performance-sensitive paths. Senior devs often instinctively factor out blocking calls into async equivalents, but beware of granular awaits in tight loops—they add overhead you may not notice until scale hits. Profiling tools rarely surface this clearly.

Ordering Isn’t Always What You Expect

Let’s say you’re using Node and you queue a setImmediate and a process.nextTick. Which fires first?

setImmediate(() => console.log("setImmediate"));
process.nextTick(() => console.log("nextTick"));

This logs:

nextTick
setImmediate

Why? Because process.nextTick() is part of the next tick queue, which is run before the event loop continues, even before microtasks. It’s special. And potentially dangerous. Abuse this and you can delay I/O indefinitely.

Also worth noting: timers (setTimeout) don’t guarantee exact timing. The delay is minimum delay, not an exact schedule. The actual execution time is affected by the call stack, OS scheduling, and other queued tasks.

Real-World Pitfalls

  1. Async race conditions – You have three services calling into a shared cache. All use await, none use locks. Everything works fine until a real user load hits. Debugging this often reveals stale reads or duplicate writes due to improper assumptions about when tasks actually run.

  2. CPU-bound blocking in an event loop – It’s still a single thread. Run anything CPU-bound (JSON parsing at large scale, crypto, etc.) and you’ll freeze your event loop. Use workers or offload to native code if you need serious performance.

  3. Unbounded microtasks – A recursive async function can starve the rest of your program:

function loop() {
  Promise.resolve().then(loop);
}
loop(); // Everything else is frozen.

The Bigger Picture: Event Loop as an API Contract

Understanding the event loop isn’t just about debugging, it’s also about designing APIs that play nicely with async runtimes. Consider:

  • Does your async function yield often enough under load?
  • Are you leaking memory by holding onto promises that never resolve?
  • Is your library safe to use in the middle of other people’s event loops?

As developers building abstractions on top of the loop, we’re entering into a contract with the runtime. Break the unwritten rules, and performance (or correctness) suffers.

Final Thoughts

The event loop is deceptively simple at first glance, but as with most core primitives, the real learning happens at the edge cases. If you’re designing high-throughput services, working in low-latency environments, or just debugging mysteriously delayed tasks, go beyond the surface-level understanding.

You don’t need to memorize every phase of every loop, but it’s worth knowing how your code is actually being scheduled. That’s where you’ll find the really subtle bugs and maybe save yourself a few 3 AM incident calls.