| I've only looked briefly at Kapita . It looks interesting, but I think what Helm gets right, and these other tools don't, is to have a real deployment story that developers can like. Helm doesn't excel here, but it's better than kubectl. In short, I think the winning tool has to be as easy to use as Heroku. That means: The ability to deploy an app from Git with a single command. It doesn't need to be by pushing to git. I built a small in-house tool that allows devs to deploy apps using a single command. Given some command line flags, it: * Checks out a cached copy of the app from Git * Finds the Git diff between what's deployed and current HEAD and pretty-prints it * Checks the CI server for status * Lints the Kubernetes config by building it with "helm template" plus a "kubectl apply --dry-run" * Builds the Helm values from a set of YAML files (values.yml, values-production.yml etc.), some of which can be encrypted with GPG (secrets.yml.gpg) and which will be decrypted to build the final values. * Calls "helm upgrade --install --chart <dir>" with the values to do the actual deploy. The upshot is that a command such as "deploytool app deploy --red mybranch" does everything a developer would want in one go. That's what we need. The tool also supports deploying from your own local tree, in which case it has to bypass the CI and build and push the app's Docker image itself. Our tool also has useful things like status and diff commands. They all rely on Helm to find the resources belonging to an app, and we did this because Helm looked like a good solution back when we first started. But we now see that we could just rely on kubectl behind the scenes, because Helm's release system just makes things more complicated. We only need the YAML templating part. I hate YAML templating, though, so I think something Kubecfg is the better choice there. |
That tool for us is a gitlab pipeline, and I guess the logic in your tool is in our case split between the pipeline and some scaffolding in a build repo. The pipelines run on commit, the image is built, tested, audited, then the yaml is patched and linted as you describe before being cached in a build artifact. The deploy step is manual and tags/pushes the image and kubectl applies the yaml resources in a single doc so we can make one call. We recently added a step to check for a minimal set of ready pods and fail the pipe after x secs if they don't come up, but haven't actually started using it yet.