Issue #4 - Documenting failures

We don’t document failure as much as we document success. At least, that’s the perception I had, until I discovered a curated, ever-growing list of Kubernetes failure stories in the wild. I particularly liked this.

and this.

If you are still skeptic about AI taking over our jobs, I suggest you read this. It draws parallels between the evolution of AI, it’s implication on jobs and how photography, daguerreotypes in particular, impacted painting in the 19th century. The good news is, this changed the entire painting landscape(no pun intended). Painters started to improvise by capturing their subjective perception of things, rather that capturing it as is(like in photography).

Typical Kubernetes cluster scaling happens on CPU and memory triggers. But what if you could define your custom scaling triggers? That’s exactly what KEDA does. This article shows how to build a KEDA autoscaler based on Kafka consumer lag. This not all, their site has a compendium of autoscalers for every possible use case, and you can roll out your own too! How cool is that?

Also, I’ve been thinking that I read a lot more interesting articles than I can pack in a weekly newsletter. So much that I want to do a daily edition. Reply and let me know what you think. Cheers and a happy Friday!