tilt-extensions VS Bazel

The first is the load function which loads Tilt extensions. It's a way to expand the tool's features, and several are available. Here we are using docker_build_with_restart, which will update the container running inside our Kubernetes cluster.

This is the central viewport into manual resource control and environment enhancement through the open-source extensions for Tilt.

argocd for cd Tilt

Recently, I found Tilt [0] to be a good partner of mine to run "all services locally". It can be compared to "webpack (live-reloading, a lot of configuration possibilities) for backend". You want to run a bunch of services directly? Use local_resource()/local(). You have Procfile? There is procfile() function. You have docker-compose.yml with databases? You can run it too with docker_compose(). You want have Tiltfile and include them all-together? There is load(). You need some web-ui for frontend devs and a nice log browser? It is there too. You need to do some extra steps before running a service? You want to update your local cluster with newly built image on file save? No problem, tilt will do that with k8s_yaml() function. Tilt uses Titlfiles for configuration, which are written Pythonish Starlark language and you use them to run any specific logic there.

Also, I am not very lucky in having resemble 1:1 k8s cluster locally. You could be close but as long as you don't run already in cloud you will have different configuration (additional annotations, various quirks that do not exist in kind/k3s but they are on GCP). However, making dedicated dev environments in the cloud might be very costly and incur a lot of additional tinkering.

[0]: https://tilt.dev/

If `host` means your production/staging hosts or whatever, you should get out of that habit now. Look into something like tilt.dev or telepresence.io or any number of other solutions that help solve this issue. Doing it directly on any host is just a recipe for bad habits and disaster.

The article doesn't mention k3d (https://k3d.io/) which is a variant of k3s that runs in docker (rather than a VM) - very nice for k8s dev/test on developer workstations.

It integrates very nicely with https://tilt.dev/ also (another very useful tool for k8s related dev/test).

If this is an issue during development then you can use something like tilt with docker-compose to directly copy modified source inside container and incrementally build it. https://tilt.dev/

I'd add Tilt

Tilt

Along similar lines, how about comparing Devspace to [Tilt](https://tilt.dev/)?

Wow, if you curl it, there's a lot of boilerplate code there.

Maybe built using Bazel?

https://bazel.build

Bazel by Google

Luckily a feature to limit the disk cache size is in development: https://github.com/bazelbuild/bazel/issues/5139

This is a problem that Bazel (https://bazel.build) solves in a very convenient way. You can just keep using the paths relative to the repository root, and as long as you properly declare your test needs that file it will access it without problems. Or you can use the runfile libraries to access them too.

When doing research for this lab exercise I looked at both vcpkg and conan. Both are package managers that would automate the installation and configuration of my program with its dependencies. However, when it came to releasing and sharing my program my options were limited. For example, the central public registry for conan packages is conan-center, but these packages are curated and the process is very involved. There was no way conan-center would accept a class project like mine. Alternatively, I could host a conan package on a public Artifactory repository, but accessing the package requires users to add the repository to their conan remote. This already sounded like too many steps to expect regular users to follow - I already haven't setup any conan remotes, there's no way I could expect regular users to know about conan remotes, let alone have conan installed on their system. After discussing with people online and consulting my instructor, I ultimately decided to do a GitHub release. However, in the future I was encouraged to look into using CMake or bazel.

NOTE: I won’t mention SBT and Leiningen here because, with all due respect, they are niche build tools. I also won’t discuss Kobalt for the same reason (besides, it’s no longer actively maintained). Additionally, I won’t touch upon Bazel and Buck in this context, mainly because I’m not very familiar with them. If you have insights or comments about these tools, please feel free to share them in the comments 👇

> None of this solves C's only REAL problem (in my opinion) which is the lack of dependency management.

Bazel solves this really nicely, I know some people have strong opinions on it but I cannot recommend it enough

https://bazel.build/