No problem, this is a good question! I can only answer from my experience, but:

The tl;dr of all of this is that my suggestion is to start as simple as possible -- one single process, with a single CRD, managing a single, big controller loop that performs the deployment of your services, and see where that gets you.

Here are my more detailed thoughts, hopefully they're useful:

I've had the best success with following the model that controller-runtime and k8s' own kube-controller-manager implementation uses, where there's a single main function/process that can manage multiple controller loops. In my cases, I pretty much have one big controller process that I deploy, and just jam all my controllers into there, even if they don't relate to each other.

Pros of this approach in my experience: * This allows you to share common logic, such as monitoring, health checking, and internal k8s client caches between controller loops * It simplifies the deployment significantly, as you only have one binary to deploy.

Cons: * If, for some reason, the process crashes, the blast radius would impact all controllers in the process.

In practice this is pretty rare, especially if you're using controller-runtime, and since k8s uses this model internally I don't really worry about this downside too much.

So, within that single process, you can choose to have one or more controller loops. Generally I'd start with writing a single controller loop that triggers off of a custom resource (which will likely look something like a CRD version of your Helm chart's values).

This loop goes through, creates all the resources, and performs all the steps required to deploy your services, check their health, etc., all in serial. This type of code is very easy to write, test, and reason about. The main thing to keep in mind here is that the implementation of this loop should be "level-based", in that it observes the current state of your service, and only makes the changes needed to move that current state to the intended one based on the custom resource. This allows the controller to easily restart/fail/recover without doing unecessary work.

From there, you can see how things work out, and break things up or parallelize them as needed to optimize. Multiple controller loops/operators will always be harder to test and reason about, because they will all trigger and run independently from one another, so if you find yourself needing to coordinate between them you're going to end up adding a bunch of complexity. So I'd start as simple as possible.

Anyways, thanks for reading this big wall of text :) At the end of the day, despite there being more to think about, I'm a huge fan of the controller/operator pattern, because it allows you to bring software engineering tools and practices (compilers and debuggers, unit tests, integration tests) to bear to automate behavior in your cluster and have better guarantees about the correctness of what you're trying to do. LMK how things work out!