Posts About Performance Analysis and Optimization

I made a game with a friend in the same CS classes with me where any time we got our homework done early, we would see who could make theirs faster or take in larger inputs without crashing. When my first job after college had embarrassingly slow code, I parlayed that into my first specialization.

A lot of performance is a mental more than a technical challenge. And I hope that comes across in the linked articles.

Introducing Faceoff: Announcing Faceoff 1.1 and how it came to exist.

Part 3: Making the Most of Async in Node.js: In Part 2 we discussed how to use p-limit to handle common errors and chains of simple parent-child requests. Today we will discuss heterogenous use cases, such as complex graphs and high-variance task costs.

Part 2: Making the Most of Async in Node.js: In Part 1 we discussed how to use p-limit and how to avoid some common pitfalls. Today we are going to go over capacity planning, and cover one last common pitfall - retry logic.

Part 1: Making the Most of Async in Node.js: In the previous article, I very briefly described a bunch of concepts in distributed computing, but before we get to the meat of this series, there’s an elephant in the room that I have so far ignored.

Background: Making the Most of Async in Node.js: If you’re trying to get a lot of unrelated tasks done in Node.js or similar languages, the normal way to write async code is often close enough to best case that most people don’t bother doing more than a little bit of tuning. But as the workload increases, and particularly if you are attempting to do any sort of offline (batch) processing in Node.js, the gap between simple and fast can reach into orders of magnitude and can be worth digging a lot deeper.

You Should Make Your Build Agents Bigger: Someone once told me that a lot of blog posts are about arguments the author already lost. This is one.