Processing large amounts of data with Pandas can be difficult; it’s quite easy to run out of memory and either slow down or crash. The Polars dataframe library is a potential solution.
Source: Why Polars uses less memory than Pandas, an article by Itamar Turner-Trauring.
For a data format, yaml is extremely complicated. It aims to be a human-friendly format, but in striving for that it introduces so much complexity, that I would argue it achieves the opposite result. Yaml is full of footguns and its friendliness is deceptive. In this post I want to demonstrate this through an example.
Source: The yaml document from hell, an article by Ruud van Asseldonk.
One common question I see on Mastodon and Reddit is "I've inherited a cluster, how do I safely upgrade it". It's surprising that this still isn't a better understood process given the widespread adoption of k8s, but I've had to take over legacy clusters a few times and figured I would write up some of the tips and tricks I've found over the years to make the process easier.
Source: Upgrading Kubernetes - A Practical Guide, an article by Mathew Duggan.