buildkit VS kubernetes

> We are uding docker-in-docker at the moment

You can also run a "less privileged" container with all the features of Docker by using rootless buildkit in Kubernetes. Here are some examples:

https://github.com/moby/buildkit/tree/master/examples/kubern...

https://github.com/moby/buildkit/blob/master/examples/kubern...

It's also possible to run dedicated buildkitd workers and connect to them remotely.

- BuildOp evaluates its input as additional LLB operations to add to the graph to allow for dynamic build graphs (also unused in the Dockerfile frontend)

With the Dockerfile Explorer, we run the Dockerfile frontend[1] that BuildKit uses inside of WASM to parse and produce the LLB output locally in your browser. We then embed the Monaco Editor so that you can change your Dockerfile to see how it impacts the LLB output that BuildKit will use to build your Docker image.

You can see a quick video and read more details on how it all works here: https://depot.dev/blog/dockerfile-explorer.

We'd love any feedback or ideas folks would like around this type of tool!

[0] https://github.com/moby/buildkit#exploring-llb

Now since Kubernetes works off of containerd I'll be taking a different approach on handling container builds by using nerdctl and the buildkit that comes bundled with it. I'll do this on the amd64 control plane node since it's beefier than my Raspberry Pi workers for handling builds and build related services. Go ahead and download and unpack the latest nerdctl release as of writing (make sure to check the release page in case there's a new one):

There's a 2-year-old moby/buildkit GitHub issue about frequent build cache misses when using the BuildKit docker-container driver and multi-stage builds. Anyone else in this sub run into this problem and/or have reasonable workarounds? It seems like something that should come up pretty often.

A couple months ago I encountered a bug in buildkit - when enabling OpenTelemetry tracing, we got occasional panics. With a bit of investigation, we found the cause, fixed and tested in our fork and internal deployments, and pushed to upstream.

I do some search in the internet and there seems to be no good solution, so I just create a feature request: https://github.com/moby/buildkit/issues/3859

Yeah, only Linux containers at the moment, BuildKit is the way we are constructing pipelines and doing caching. Split on if we will support non-linux hosts, but definitely want to find a good solution to not doing Docker-in-Docker.

Relevant issues are https://github.com/moby/buildkit/issues/3011 and https://github.com/moby/buildkit/issues/1512.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.