Awesome-CloudOps-Automation

Hey HN! I run a small k8s cluster and found myself running the same set of `kubectl` commands frequently to execute my troubleshooting decision tree! That's why I created the Kubernetes Runtime Scanner (KRS) - a pro-active, rule-based health assessment. Why KRS? - Automated Health Checks: Quick assessments of nodes, pods, and services (and others) - Log Aggregation: Extracts and organizes relevant error logs. - Resource Snapshots: View resource states at a glance. - Open-Source & Extensible: let me know your troubleshooting workflow and I can try to incorporate it as pro-active checks! I'm eager for feedback and collaboration. Try KRS, suggest features, or dive into the code. Your insights will make KRS an invaluable tool for every k8s user! Here is a quick start guide on how to run a scan and get a report with about ~150 checks in a few

It's a good thing they called themselves "CloudOps" and not "DevOps" because I struggle to think of any sane reason to write code like this https://github.com/unskript/Awesome-CloudOps-Automation/blob... (setting aside the lack of try:finally: to close those cursors or why one needs a commit for a SELECT statement)

Confusingly, there is a Apache licensed repo you can find linked at the bottom of the site, except the files are individually relicensed, eg, https://github.com/unskript/Awesome-CloudOps-Automation/blob... The concept is interesting. In our experience with regular and top teams trying to do notebooks for runbooks.. there are a lot of gaps around the Jupyter UI specifically and the concept in general. It's a fascinating problem to work on.

The github repo: https://github.com/unskript/Awesome-CloudOps-Automation

A really cool project about automating the mundane using a notebook approach! I loved the use case they highlighted here in the blog :-) (no office Mariah!) The open source project is here: https://github.com/unskript/Awesome-CloudOps-Automation