Show HN: Gitkube – Deploy to Kubernetes Using Git Push

Does Keel include any ability to rollback to a previously deployed version? How to you recommend handling that use case?

Keel looks similar to Weave Flux (https://github.com/weaveworks/flux). Have you looked at Flux, are you able to compare them? At first glance it looks like Keel is probably easier to setup, but Flux is more feature rich (edits k8s .yaml files in git with updated image tags, has CLI that supports listing deployments and images, can release an old image).

The best alternative would be to have Travis CI SSH into a box with kubectl. In any case it’s bit more complicated than the setup with Keel we currently have.

RBAC isn't too complicated though:

- get on specific app namespaces

- get, list, watch, patch, update on deployments

I planned to add Docker Swarm support from the beginning but a lot of people said that it's unnecessary. It's quite simple to add new providers, they need to implement this interface:

  // Provider - generic provider interface
  type Provider interface {
 	Submit(event types.Event) error  // <- this is where new image event comes in
	TrackedImages() ([]*types.TrackedImage, error) // <- provider needs to tell some triggers which images to track (registry watcher)
	GetName() string
	Stop()
  }

Like one of the commenters said, we also do some pre-push magic right now (esp. for client-side kubernetes templating) for a more complete and opionionated CI/CD workflow.

As far as upgrading OpenShift itself, you already wrote the Ansible inventory to deploy it (unless you're a masochist and deployed it manually) - just run the upgrade playbook against your existing inventory to upgrade to the latest point or major release.

I run OpenShift Origin 3.7 on CentOS Atomic at work, in production, it's basically been set and forget - I have an ansible playbook I run once a month to do OS upgrades (have to drain pods, upgrade atomic, reboot and then allow pods back on the node and do it across all of them in sequence) and then I just run the upgrade playbook periodically as new point releases come out.

Devs should be able to merge a PR, and have it safely rollout to production (e.g., canary), possibly with a staging step and manual promotion if desired. They should have a simple ability to rollback to a previous version.

Terraform typically would involve editing TF files to update a version, committing that TF change, opening and merge a PR for the change. The running plan, reading the output of plan, then applying the plan. If you have staging and stable environments, repeat the steps. If you want to rollback, repeat the steps.

And it gets oh so much more complex. TF binary versions need to be globally consistent, because the version is stored in the state file. You basically need to only run TF from the CI/CD system, people can't be allowed to run apply locally because they might use a newer version of TF which would then break CI/CD which has the older version. So then you wrap TF commands with a Makefile that checks TF version, or you pin the TF version within the TF code.

How many resources are you managing? Hundreds? Thousands? How many apps? Are they all deployed using the same state file?

How long does it take to run a plan and apply? 10 minutes? 20 minutes? Same for a rollback...

What if Bob want to deploy version 13 of app 'foo', but when he runs plan it says it will also update app 'bar' to version 27. But Bob doesn't know anything about bar, his team only works on foo.

So you break up the TF files so every app has its own state file. Cool. But now you need to upgrade TF itself. And it is a major upgrade. Now you need to update the TF version pinned in the source files, and update the build servers to have the new TF, and run a TF command to upgrade on every state file.

Then you start adding symlinks into the TF source tree, because TF doesn't have any sane way to reuse code. But there are slight changes that need to be made for each app, and TF doesn't allow variables in some parts of the code, and modules are OK be still too verbose, and you still end up with places you can't use variables. So no you start using templates to write you TF code, so you can reuse code, because 99% is the same for each app.

Ugh.

Terraform is great for defining infrastructure that rarely changes, and is managed by an infrastructure team. When you are trying to use it for app deployments, which happen multiple times a day, and are handles by app devs, it is a royal PITA.

What would be even better: a begin-commit model where you tell AWS (or $PROVIDER) that you're beginning a transactional change, you issue a bunch of API commands, and along the way the provider is modeling what that would cause the deployment to look like, and it's also checking subsequent actions' invariants / constraints against the "running total" of all the changes (the model) instead of the snapshot of how the deployment was before the "begin".

I ended up having to create a "staging environment" at $WORK that's just another AWS account. The deploy flow for this one terraform project is:

1. run 'terraform plan' against production; this shows you syntax errors and _some_ semantic errors.

2. run 'terraform apply' against the staging AWS account; this will shake out more semantic errors, like an ec2 security group having too many rules. this step helps prevent you partially applying whatever change you're working on to production, since the production deploy would have failed when it gets to the ec2 security group change.

3. finally, run 'terraform apply' on production. I've yet to find an error that made it to this step that didn't get caught in one of the previous two steps.

None of this would be necessary if AWS had some way of modeling deployments and checking invariants/conditions against models instead of checking them in situ.

edit: something like:

  aws change create-changeset
  aws ec2 authorize-security-group-ingress --changeset-id c-12345abc ...
  aws ... --changeset-id c-12345abc
  aws change commit-changeset --changeset-id c-12345abc

This always comes and bites us back isn't it? The whole promise of Docker was that we would be freed form these pains... But yet here we stand :(

Wondering what kind of issues you're running into. The first one that comes to mind for me is Kernel version mismatches. Though those shouldn't always cause that much trouble due to the "Dont break userspace mantra" that Linus has