spec VS community

I had a really (what I thought at the time) cool idea for a new Kubernetes storage driver, so I implemented the basic version in an evening. That's the first "rave-worthy" event - the architecture of these drivers is fairly complex and there are many ways to do it (see https://github.com/container-storage-interface/spec/blob/master/spec.md) so getting something working as I imagined it, knowing nothing beforehand, was the first moment of joy. The next day (after sharing in a few slacks) I got a DM from a tech lead at and he was really excited about the idea! That second affirmation that someone was excited about the project and wanted to brainstorm with me was my second moment of joy. And then for the third, last night and (some of today, still going to do more after dinner soon!) I've been doing detail work, and learning a ton, debugging, learning, making it slowly better... that flow state (often with music) is probably the closest thing to the idea of a rave. Anyway, that's my story! I love learning Kubernetes stuff, I'm so grateful I've been able to in my current role.

But if all of these are not an issue, then Containers and an orchestration system like Kubernetes can always take care of workload portability especially with OCI now in place for containers and CSI, CNI, CRI, SMI for storage, networking, runtime and service mesh respectively creating a healthy standards based ecosystem for all thereby enabling workload portability without lock-in since for a workload to be truly portable, all the underlying resources should be portable without any/very limited changes.

CSI (Container Storage Interface) is a standard which helps establish interoperability between multiple storage providers avoiding the need to have in-tree plugins within the core. So, any storage provider who supports CSI can work with Kubernetes without any issues. You can find a complete list of providers supporting CSI here

Multiple container runtimes are supported, like conatinerd, cri-o, or other CRI compliant runtimes.

More recently, the Kubernetes SIG Network has been evolving the Gateway API to support service meshes.

https://github.com/kubernetes/kubernetes https://www.kubernetes.dev/resources/calendar/ https://github.com/kubernetes/community/blob/master/governance.md https://github.com/kubernetes/steering https://github.com/kubernetes/community/blob/master/sig-list.md

According to this doc it takes the average of CPU utilization of a pod (average across the last 1 minute) divided by the CPU requested by the pod. Then it computes the arithmetic mean of all the pods' CPU.

metrics-server has not supported kubectl top Resource Metrics API

With the Gateway API being a superset of the Ingress API, it might make sense to consolidate both. Thanks to the SIG Network community, Gateway API is still growing and will soon be production ready.

Projects in/around Kubernetes and the CNCF are generally where I spend what little time I can these days. Most communities are incredibly welcoming and provide timely feedback. But the problem space of "managing a cloud platform" can take several years to really wrap ones head around, setting aside focused topics via SIGs like networking, storage, observability, API design, etc.

Krew is a plugin manager maintained by the Kubernetes Special Interest Group (SIG) CLI community. Krew makes it easy to use kubectl plugins and helps you discover, install, and manage them on your machine. It is similar to tools like apt, dnf, or brew. Today, over 200 kubectl plugins are available on Krew - and that number is only increasing. Some projects are actively used and some get deprecated over time, but are still accessible via Krew.

[1] https://k8s.devstats.cncf.io/d/9/companies-table?orgId=1&var-period_name=Last%20decade&var-metric=contributions [2] https://kubernetes.io/releases/release/ [3] https://github.com/kubernetes/community/blob/master/governance.md [4] https://github.com/kubernetes/community/blob/master/sig-list.md