cloud-custodian VS enhancements

> The best optimization is simply shutting things off

This is the way.

A similar idea has been bouncing around in my mind for a while now. An ideal, turnkey system would do the following:

- Execute via Lambda (serverless).

- Support automated startup and shutdown of various AWS resources on a schedule influenced by specially formatted tags.

- Enable resources to be brought back up out of schedule when demand dictates.

- Operate as a TCP/HTTP proxy that can delay clients so that a given service can be started when it is dormant or, even better, the service isn't serverless but you want it to be. This can't work for everything, but perhaps enough things such that the need to run always on services is reduced.

Cloud Custodian [1] can purportedly do some of this, but I've been reluctant to learn yet another YAML-based DSL to use it.

So this is my "make things designed to be always-on serverless instead" project and the work AWS has done to make Java apps function on Lambda keeps me thinking about the potential to take things that 1) have a relatively long startup time and 2) are designed to be long running service loops, and find a way to force them into the serverless execution model.

[1] https://cloudcustodian.io/

Goal was to clear up anything old and set us up to rotate keys in use. Why did I do it in the end of December? It was a quarterly goal and I learned to push those across the line if I wanted a good review. Great incentive, that one. I used Cloud Custodian for this. It has a terrible bug where the code says you'll be acting on days since the key was used but actually is reading days since it was created.

What is wrong with https://github.com/cloud-custodian/cloud-custodian?

You can start reading about it here.

Use a tool like this https://cloudcustodian.io/ to manage instance on/off hours or go fargate.

Certs aside, there are some great compliance tools out there that you might want to become familiar with. Here is one that comes to mind (is open-source): https://cloudcustodian.io/

I'd use a combination of Cloudcustodian for start/stop scheduling and Apprise for notifications.

Cloud custodian is a good utility if config rules doesn’t satisfy your needs. It’s also cross platform.

AWS Security with open source – Cloud Custodian is a Cloud Security Posture Management (CSPM) tool. CSPM tools evaluate your cloud configuration and identify common configuration mistakes. They also monitor cloud logs to detect threats and configuration changes.

> was always told early on that although they supported vault on kubernetes via a helm chart, they did not recommend using it on anything but EC2 instances (because of "security" which never really made sense their reasoning).

The reasoning is basically that there are some security and isolation guarantees you don't get in Kubernetes that you do get on bare metal or (to a somewhat lesser extent) in VMs.

In particular for Kubernetes, Vault wants to run as a non-root user and set the IPC_LOCK capability when it starts to prevent its memory from being swapped to disk. While in Docker you can directly enable this by adding capabilities when you launch the container, Kubernetes has an issue because of the way it handles non-root container users specified in a pod manifest, detailed in a (long-dormant) KEP: https://github.com/kubernetes/enhancements/blob/master/keps/... (tl;dr: Kubernetes runs the container process as root, with the specified capabilities added, but then switches it to the non-root UID, which causes the explicitly-added capabilities to be dropped).

You can work around this by rebuilding the container and setting the capability directly on the binary, but the upstream build of the binary and the one in the container image don't come with that set (because the user should set it at runtime if running the container image directly, and the systemd unit sets it via systemd if running as a systemd service, so there's no need to do that except for working around Kubernetes' ambient-capability issue).

> It always surprised me how these conversations went. "Well we don't really recommend kubernetes so we won't support (feature)."

0 is not the request we've defined. And that makes sense. Memory QoS has been in alpha since Kubernetes 1.22 (August 2021) and according to the KEP data was still in alpha as of 1.27.

Note: There's actually a Structured Authentication Config established via KEP-3331. It's in v1.28 as a feature flag gated option and removes the limitation of only having one OIDC provider. I may look into doing an article on it, but for now I'll deal with the issue in a manner that should work even with a bit older versions versions of Kubernetes.

Kubernetes supports a skew policy of n+2 between API server and kubelet. This means if your CP and DP are both on 1.20, you could upgrade your control plane twice (1.20 -> 1.21 -> 1.22) before you need to upgrade your data plane. And when it comes time to upgrade your data plane you can jump from 1.20 to 1.22 to minimize update churn. In the future, this skew will be opened to n+3 https://github.com/kubernetes/enhancements/tree/master/keps/sig-architecture/3935-oldest-node-newest-control-plane

The KEP (Kubernetes Enhancement Proposal) is linked to in the PR [1]. From the summary:

> Sidecar containers are a new type of containers that start among the Init containers, run through the lifecycle of the Pod and don’t block pod termination. Kubelet makes a best effort to keep them alive and running while other containers are running.

[1] https://github.com/kubernetes/enhancements/tree/master/keps/...

This is where the new feature of mutable scheduling directives for jobs comes into play. This feature enables the updating of a job's scheduling directives before it begins. Essentially, it allows custom queue controllers to influence pod placement without needing to directly handle the assignment of pods to nodes themselves. To learn more about this check out the Kubernetes Enhancement Proposal 2926.

What your asking is a (vanilla) Kubernetes non-goal, others have mentioned fluxcd and other add ons that provide primitives for dependency aware deployments. The problem space is so large, that it's unreasonable to to address these concerns in Kubernetes itself, instead, make it extensible... Look at this KEP for example: https://github.com/kubernetes/enhancements/issues/753 Sidecar containers have existed, and been named as such since WAY before that KEP's inception, defining what these things should and shouldn't do is largely arbitrary. Aka: your use-case is niche, if you don't like the behavior, use flux or argo, or write something yourself.

If further interested, I may recommend checking out the KEP. I love how they document the decision making, and all these edge cases :).

See https://kubernetes.io/docs/reference/kubectl/conventions/#subresources and https://github.com/kubernetes/enhancements/issues/2590