Stop Parallelizing Everything: A Practical Guide to Parallel.ForEach
Parallel.ForEach feels like a free speed boost, until it slows your app to a crawl. This post explains when parallel loops shine, when they backfire, and how to avoid the classic traps. You will see small runnable C# examples for CPU bound work, shared state pitfalls, and I/O scenarios. We will also cover safer async alternatives, thread local aggregation, and simple tuning with ParallelOptions. By the end, you will know how to pick the right approach and measure the impact with confidence.
I once replaced a sleepy foreach with Parallel.ForEach expecting fireworks. The only thing that lit up was my laptop fan. The app got slower. Plot twist. If you have felt that sting, this post is your friendly tour through when parallel loops rock and when they troll you.
A tiny mental model
Think of moving couches with the Fellowship. One hobbit can move a cushion fine. Ten hobbits in a narrow hallway spend more time coordinating than lifting. Parallelism buys speed only when the work per worker is chunky and independent.
This article will be available on April 27, 2026 at 8 AM Central Time US