Django

How you can get there So, you’re running your python web application using gunicorn in production, and you’re a good folk, you know that having requests without a timeout can be a bad idea. Imagine a long query loading your DB with the client already leaving your beautiful SAAS waiting for the results, whole UI becoming sluggish, yada-yada-yada. You Google stuff, likely entirely miss the documentation, and go on with some settings like --timeout 30 and call it a day. Or maybe you’ve been running a production Gunicorn set-up with a different type of worker in place, you’ve changed it, and were assuming that it’ll just keep working the way you assume it to work. ...

Part 4: Celery Graceful Shutdown Process Part 1: Signals and Linux Part 2: Containers and signals Part 3: Graceful shutdown of K8S pods Part 4: Celery Graceful Shutdown [you’re here] Part 5: Prometheus Graceful Shutdown Part 6: Other frameworks and libraries [WIP] Change of the approach We’ve had enough generic theory in previous 3 articles, covering the kernel, application, container runtimes and high-level abstractions like K8S, so what’s next? I suggest to change the flow of the articles to overview of popular backend systems and how they handle graceful shutdowns, so that we have a perspective of the topic in the wild. ...

Part 1: Signals and Linux Part 1: Signals and Linux [you’re here] Part 2: Containers and signals Part 3: Graceful shutdown of K8S pods Part 4: Celery Graceful Shutdown Part 5: Prometheus Graceful Shutdown Part 6: Other frameworks and libraries [WIP] Intro There’s been quite a lot of issues surrounding application shutdowns in my line of work. Connections not being correctly closed, incoming requests being processed when they shouldn’t have been, various quirks around how new deployments affect customers during busy hours. I’ve decided to familiarize myself more with the topic and that’s quite a lot going on there. ...

Prelude Currently, I’m working on the product, built around a large Django monolithic application and a bunch of microservices around it. The codebase is quite huge and has a lot of (tens of thousands) tests, that are normally run in a parallel mode in the CI environment. The CPython and Django versions are a little bit stale (3.8 and 3.2 respectively). For local development purposes, it’s well enough to run a subset of tests in a non-parallel mode or to wait for the whole suite to pass during the CI run, but for one specific use case I had to run a parallel test suite locally. It was a surprise for me to see the Segmentation Fault as the test failure reason for a bunch of tests. ...