Kapitan (https://kapitan.dev) is on my radar as a possible sweet spot between Kustomize and Helm.

Until now I've used Jinja2 templates for our Kubernetes definitions with a variables file for each environment, but this is awfully manual.

I'd love Kustomize to be sufficient for us as it's poised to become a standard thanks to now being part kubectl.

Unfortunately, in some ways its YAML patching philosophy is too limited, and coming from a templating system would be a step back even for relatively simple use cases : for example, you're very likely to need a few variables defined once and reused across k8s definitions (a host or domain name, project ID, etc). You can't really do that in a DRY way with Kustomize.

AFAIK, it also currently doesn't have a good story for managing special resources like encrypted secrets : it used to be able to run arbitrary helper tools for handling custom types (I use Sealed Secrets), but this has been removed recently for security reasons, prior to the Kubectl merge.

Kapitan seems to cover these grounds, and it doesn't carry the weight of those Helm features which are useless for releasing internal software, but I'm still a bit worried about the complexity and learning curve for dev teams.

Is there anything else out there that goes a little further than Kustomize, is simpler than Kapitan and Helm and fits well into a GitOps workflow ?

> for example, you're very likely to need a few variables defined once and reused across k8s definitions (a host or domain name, project ID, etc). You can't really do that in a DRY way with Kustomize.

I agree this is one of the areas where you feel the pinch of kustomize's rather puritan design philosophy. We've been able to work around those things in ways that aren't exactly elegant, but don't cause physical discomfort. For shared variables we keep a patch on disk and generate specialized copies of it during deployment. It's a hack, but it retains some of the benefits of a declarative approach. We also still use substitution in a couple of places. It's hard to use kustomize to update an image tag that changes with each build for example.

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.

> 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.

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.

That sounds similar, except you prepare some of the steps in the pipeline. Sounds like you still need some client-side tool to support the manual deploy, though. That's my point -- no matter what you do, it's not practical to reduce the client story to a single command without a wrapper around kubectl.

Interesting idea to pre-bake the YAML manifest. Our tool allows deploying directly from a local repo, which makes small incremental/experimental tweaks to the YAML very fast and easy. Moving that to the pipeline will make that harder.

Also, you still have to do the YAML magic in the CI. We have lots of small apps that follow exactly the same system in terms of deploying. That's why a single tool with all the scaffolding built in is nice. I don't know if Gitlab pipelines can be shared among many identical apps? If not, maybe you can "docker run" a shared tool inside the CI pipeline to do common things like linting?

> I've looked at Kustomize, and I don't think it's sufficient. For one, as far as I can see, it's not atomic.

Kustomize just applies structured edits to yaml. We run it to apply all the patches and output a single manifest file with all the resources, then send that to the master with kubectl apply. I suspect its as atomic as anything helm does, but I could be wrong.

The "atomicity" (a misleading term, I agree, but I couldn't think of a better one as I was writing the comment) I was referring to was its ability to do a destructive diff/patch. In other words, if you apply state (A+B+C), then (A+B), it will remove C.

With plain "kubectl apply", there's the "--prune" flag, which is supposed to be able to track upstream resources via annotations. But it's still considered experimental alpha functionality, as least according to the "kubectl --help" for Kubernetes 1.11.9.

Yeah I read your reply above and I do see your point. For our own services that we continuously deploy this really just doesn't come up. If we have an http or rpc service it's going to have a deployment, a service, and maybe an ingress for pretty much all of time. If we needed to remove a thing in that scenario it might be the ingress if we change architecture, but it would be a big enough deal that cleaning up manually wouldn't be an added burden.

Deletion is definitely less common, but we do this all the time. It keeps cruft from accumulating when people forget to delete resources.

It's also nice to be able to do "helm del myapp" and know that everything is wiped. You can do this with "kubectl delete -R -f", but I believe you need the original files. You can of course do something like "kubectl delete -l app=myapp", but this requires consistent use of a common label in all your resources.

You can also use kubectl patch locally to apply a label to a set of manifests locally before piping into kubectl apply, eg:

  kubectl patch -f input.yaml --type merge -p '{"metadata": { "labels": {"key": "value"} } }' --dry-run -o json | kubectl apply -f - --prune -l key=value

I might be misunderstanding something here bit is helm really atmoic?

Sure, it'll manage sets, but will it really flip versions in an atmoic way and does this really matter when it's doing 3 rolling upgrades, without anything to manage which traffic goes where?

It's possible it does more than I think it does, but I'm also wondering if atomic is the right word here?

> I might be misunderstanding something here bit is helm really atmoic?

No, the underlying Kubernetes API doesn't have multi-document transactions. What you're getting is closer to best-effort eventual consistency.

Sorry, "atomic" was not the best term here.

I don't know if there is a word for it — it comes up in a lot of situations — but given a set of resources, Helm will diff against Kubernetes and wipe out anything superfluous. So if I've deployed a chart that has (A, B, C) and then do a new deploy of (A, B), then C will be deleted. "Destructive diffing"? I don't know.

Kubernetes itself is not atomic right now. I believe Etcd supports multi-key transactions now, so it could be done.

Right.

But even if kubernetes and etcd supported multi-document transactions and thus gave you the ability to update data in an atomic way, you'd also need to be doing green/blue deploy and then atomically switching service calls, whilst maintaing old network traffic/service calls goes to old pods and new network traffic/service calls goes to new pods.

Pretty complicated and whilst it can be solved, I dont want us thinking that services will fully function during a helm or even a kubernetes update with major api changes between services. Likely your old service will call the new service and fail. This level of failure might be acceptable or you can work around it by having retries or keeping APIs backwards compatible for several versions.

Apologies for blabbering, I would consider the current default state of deploys with rolling upgades to be akin to eventual consistency, but it's possible it's more clever than that.

I believe Kubernetes itself supports that kind of a change - that is, re-applying a config and creating or deleting resources based on the update.

I would say that helm is batch, in that it's applying a bunch of stuff at once, but not doing it transactionally.

> I'd be interested in how Google does these things with Borg. My suspicion is that they're using BCL (which Jsonnet is based on, last I checked) to describe their resources.

Yes. Kubecfg is the closest equivalent for k8s. And it also works the best for me (but I might be biased).

A colleague (Dmitriy Kalinin) recently created this: https://get-kapp.io/

Which does the grouping-of-resources thing and explicitly leaves templating up to you.