garden VS kubernetes

Hey there! Have you tried garden.io for caching? We also cache tests. Pretty much anything that's possible to cache. We're open source at https://github.com/garden-io/garden

To add to what's already been said: If you think about it, CI pipelines are typically a complete description of how your system is built, tested, and deployed.

Which is pretty fantastic except for how walled off they are. You can't really re-use these descriptions for e.g. development, they're not vendor agnostic, and they only way to run them is by pushing your code.

Maybe it's a silly analogy but it's almost like being a web dev that doesn't have a browser and needs to send their code to a friend who can tell them if that font size looks good.

I think we're way over due for freeing these "blueprints" of our system from the confines of CI and making them portable and flexible. And containers are the technology that's enabling that.

Full disclaimer (as always): I work at Garden[0] where we're also solving that problem but taking a slightly different approach to Dagger (it's still a DAG). Garden config is declarative and the jobs (we call them actions) have a semantic meaning. You can e.g. have a Build action of type container or a Deploy action of type Helm and Garden will figure out what to do with it.

[0] https://github.com/garden-io/garden

Yes, there's us over at https://github.com/garden-io/garden! We're big believers in pipelines that run anywhere. I even made a short little video that should give you the gist. [1]

Some of the short-list of differences: we use YAML for our configuration language, Dagger can use full-fat languages to define its pipelines. Our feature scope is broader: you can use us to vend IDP-like stacks to your developers if you're a Platform Team; we make development with remote Kubernetes clusters very easy, including all the remote image builds; and we have a number of integrations so you can bring your IaC tool of choice (Pulumi, Terraform) into your pipeline and set up service -> infra dependencies.

[1] https://www.youtube.com/watch?v=JFnan6s2cDg

Me too. In fact Garden (dev tooling for the Kubernetes)[0] is a Berlin start-up with three Icelandic founders.

And if I'm not mistaken, two of us worked briefly with @halldorel (above commenter) at an earlier Icelandic start-up. It's a small world (if you're Icelandic).

[0] https://garden.io

There are dedicated tools just for that. Apart from skaffold check also tilt.dev, garden.io, devspace.sh, okteto.com

Would appreciate any insights on garden.io. Thanks.

Telepresence, tilt, garden.io, okteto, skaffold etc.

- https://garden.io/

haha, do my pictures give off a strong not-web-dev vibe? Either way your right, I'm focusing on devxp and automation for kubernetes. Because my work is open source you can see it here https://github.com/garden-io/garden (btw we're also hiring another open core dev like me)

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.