Cloud Native Computing Foundation

[upbeat music] Quick lightning round.

First, Karmada has graduated from the CNCF.

The graduation itself is mostly a maturity signal.

The more interesting part is where multi-cluster orchestration is going, especially with distributed AI and GPU workloads.

That's it for this week of Ship It Weekly.

We covered Amazon Linux 2027, GitHub Actions cache permissions, pull request secret scanning enforcement, and the actively exploited N-able and central vulnerability.

Plus, Karmada graduating from the CNCF, Shield Crash, CodeQL on Linux ARM64, and simpler Dependabot access to private GitHub packages.

Follow or subscribe wherever you are watching or listening.

But I think it's $8 a month, so it's not the most expensive.

Then you have Podman Desktop, which is free and open source under Apache 2.0, and it's in CNCF.

And what that does, it's a little bit different.

So Podman is different comparing to Docker.

So I'm considering moving that.

And when it comes to the dominant engines, runtime, so you have Podman, which is daemonless, rootless by default engine, and that's backed by Red Hat.

Then you have ContainerD and NerdCTL, which is like a bundle, which is CNCF-graduated runtime.

And...

Now, obviously, there are many, many more elements.

Uh, uh, Kubeflow has just graduated from CNCF and so on.

I still, by the way, think that this declarative rollout of pipelines is still an unsolved problem in a lot of ways.

But it's obviously much further along, and Kubeflow has both achieved enormous success, of which I have very, very little to do.

'Cause we have somewhat common background, and I, I would love to hear your thoughts on some of these things that it's may not, may not be as related to the AI, AI infrastructure, but it's kind of related to everything we're talking about and doing in our day to days.

So first of all, what's your thoughts on like OSS models? And what I mean by that is today a lot of say, "Oh, this model's OSS," but it's really not.

It's open weights, right? And do you think there will ever be a truly OSS model like run by Linux Foundation or CNCF? Like what would it take and what is your thoughts on like something like that ever happening?

So that is an excellent, excellent question.

It was one of the challenges we saw in the data on Kubernetes community was the issue around standardization of practices, because like you said, there are so many different kinds of databases out there.

And it was even a challenge when speaking to the CNCF about, hey, could there be some kind of a certification for a certified Kubernetes database reliability engineer and say, well, which databases are we going to be testing here? Yeah, and we're also looking at things around storage.

One of the big projects that was talked about a lot in the data on Kubernetes community was OpenEDS and also all the things that were going on with SIG storage.

Sometimes I think a

And from a customer POV, what's great about our private AI services is that these are aligned to upstream open source.

So this is all Kubernetes and CNCF and Linux Foundation aligned.

So you're integrating with VCF without any fear of lock-in.

Now you're saying, well, okay, Chris, well, I can download these myself.

So we localize the control plane.

The second thing that we do is we're a highly modular stack.

We're highly standardized, and we still have CNCF conformant interfaces above our stack to remove the lock-in.

This is why this matters.

Software had one.

Apache, Linux Foundation, CNCF.

Neutral because the maintenance cost was donated human labor and stewardship was cheap enough that no patron was required.

That model doesn't port.

And it is established technology.

And it is the CNCF project.

It's a graduated CNCF project.

Well, recently I read the news.

So there's no reason to not use the buildpacks.

And the orchestration tooling landscape has gotten mature.

Karmada is a CNCF incubation project now.

It provides centralized multi-cloud Kubernetes management, speaking Kubernetes, native APIs, with advanced scheduling including cluster affinity and multi-dimension HA across regions, availability zones, and providers.

There's Cilium Cluster Mesh, which was used in a production case study for a regulated payments workload spanning AWS, GCP, and Azure.