July 15, 2026
Awaiting disaster
The Tokio/Rayon Trap and Why Async/Await Fails Concurrency
Coders are fighting over whether “easy” tools are secretly causing giant slowdowns
TLDR: The article says a popular way of writing app code can hide bottlenecks, force humans to manually separate “waiting” work from “heavy lifting,” and even let memory usage spiral into crashes. Commenters were split between “this is a real production trap” and “no, you’re just using the tools badly.”
A fresh tech essay basically kicked over the server room coffee table by arguing that async/await — the beloved coding shortcut that makes waiting for things look neat and simple — is actually a production nightmare when apps get busy. The author’s big claim: developers are being tricked into thinking they wrote calm, step-by-step code, when in reality they’ve built a hidden traffic jam. When one task suddenly does heavy number-crunching instead of just waiting on the internet, everything else can stall, memory can pile up, and apps can even crash.
But the real fireworks were in the comments. One camp yelled, essentially, “skill issue”: tools like Tokio and Rayon are fine, you’re just using them for jobs they were never meant to do. Another camp was far less charitable, calling the piece “AI slop” and mocking its use of Go creator Rob Pike as a role model, with one commenter sniping that Go has “the same problems, more magic, and worse observability.” Ouch.
Then came the analogies, because no internet fight is complete without those. One commenter compared the whole thing to Ethereum, saying only one thing happens at a time, which somehow made concurrency discourse sound like crypto group therapy. Another took the history-lesson route, reminding everyone that web servers have been reinventing this same mess since the Perl-and-CGI days. The vibe? Half support group, half roast battle, with a side of “most web stuff is a special case, stop pretending it solves everything.”
Key Points
- •The article argues that async/await makes asynchronous code easy to write while hiding structural concurrency complexity.
- •It says async/await conflates I/O asynchrony with true concurrency, which can mislead developers into placing CPU-heavy work inside async functions.
- •In cooperative runtimes such as Tokio and Node.js, the article says CPU-bound code can stall execution until the next await point, increasing latency for unrelated work.
- •The article states that teams often respond by splitting I/O and compute across different runtimes, such as Tokio and Rayon, and cites PostHog and Meilisearch postmortems as examples.
- •It also argues that low-friction task spawning and unbounded queues can allow in-flight work and memory usage to grow until an OOM event terminates the process.