kubernetes-mixin VS skycfg

I'd suggest looking at the queries used by the kubernetes mixin dashboards for inspiration.

Came across this lib, but realized the last update was 4 years ago.

Take a look at the kubernetes mixins to get an idea and/or starting point

The last step is to use the Mixin dashboard to visualize the usage of PV, you can get it from here

It's working good so far, except for the annoying CPUThrottlingHigh alert that is firing for many pods (including the own Prometheus' config-reloaders containers). This alert is currently under discussion, and I want to silence its notifications for now.

I think it might still have issues figuring out that it needs to apply CRDs first: https://github.com/grafana/tanka/issues/246 Besides that, I found it super-handy for deploying https://github.com/prometheus-operator/prometheus-operator and https://github.com/kubernetes-monitoring/kubernetes-mixin

These all standard dashboards are basically generated from the kubernetes-mixin project.

I would suggest looking at the Kubernetes Mixin: https://github.com/kubernetes-monitoring/kubernetes-mixin, it has both alerts and Grafana dashboards.

I can definitely sympathize here - in every context, just straight JSON/YAML configuration seems never expressive enough, but the tooling created in response always seems to come with sharp edges.

Here are some of the things I appreciate about Jsonnet:

- It evals to JSON, so even though the semantics of the language are confusing, it is reasonably easy to eval and iterate on some Jsonnet until it emits what one is expecting - and after that, it's easy to create some validation tests so that regressions don't occur.

- It takes advantage of the fact that JSON is a lowest-common-denominator for many data serialization formats. YAML is technically a superset of JSON, so valid JSON is also valid YAML. Proto3 messages have a canonical JSON representation, so JSON can also adhere to protobuf schemas. This covers most "serialized data structure" use-cases I typically encounter (TOML and HCL are outliers, but many tools that accept those also accept equivalent JSON). This means that with a little bit of build-tool duct-taping, Jsonnet can be used to generate configurations for a wide variety of tooling.

- Jsonnet is itself a superset of JSON - so those more willing to write verbose JSON than learn Jsonnet can still write JSON that someone else can import/use elsewhere. Using Jsonnet does not preclude falling back to JSON.

- The tooling works well - installing the Jsonnet VSCode plugin brings in a code formatter that does an excellent job, and rules_jsonnet[0] provides good bazel integration, if that's your thing.

I'm excited about Jsonnet because now as long as other tool authors decide to consume JSON, I can more easily abstract away their verbosity without writing a purpose-built tool (looking at you, Kubernetes) without resorting to text templating (ahem Helm). Jsonnet might just be my "one JSON-generation language to rule them all"!

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Though if Starlark is your thing, do checkout out skycfg[1]

[0] - https://github.com/bazelbuild/rules_jsonnet

[1] - https://github.com/stripe/skycfg

Can you say more about what GCL does better than all of the open source ones?

Anecdotally, I've heard a lot of GCL horror stories, and many Xooglers have chosen to create things like Jsonnet or Skycfg (https://github.com/stripe/skycfg) instead.

If you’re looking at other solutions check out https://github.com/stripe/skycfg It works with Envoy and lots of other things that support protobuf configs

This is good and there are several other options like https://github.com/stripe/skycfg#why-use-skycfg to add full language support (using Go or python for ex) to configurations.