kubeplus VS enhancements

We went through this migration/upgrade in our KubePlus project (https://github.com/cloud-ark/kubeplus). It has an embedded webhook in it, fyi.

You might want to check out - KubePlus (https://github.com/cloud-ark/kubeplus), which has already been referenced in the thread and is exactly designed for building managed application services. I am the originator and core contributor to this project. KubePlus is a Kubernetes Operator that takes an application Helm chart and represents it as a Kubernetes API (CRD) on the cluster. This API allows you to create instances of the application in separate namespaces automatically ensuring a secure perimeter around each instance using NetworkPolicy, Resource Quota, and RBAC. These soft multi-tenancy measures are already mentioned in the thread along with the namespace. KubePlus has automated all of them for you under an API. This API not only allows the creation of the application instances but also supports day-2 operations such as monitoring, troubleshooting, and upgrades to simplify the end-to-end functioning of any managed application service. We are currently seeing interest from teams that want to create managed services for different types of containerized applications, including open-source platforms such as WordPress, Moodle, Ozone/OpenMRS, AI/ML workloads, etc. KubePlus has been tested successfully with all (90+) Bitnami Helm charts. For anyone who wants to deliver a managed application with minimal / no Kubernetes access to their customers, KubePlus can help by accelerating the implementation of namespace-based multi-tenancy on Kubernetes. With the ability to set NetworkPolicy and Resource Quota per application instance, the blast radius is restricted, if something goes wrong in an application instance. KubePlus does not need admin permissions on your cluster. This makes it possible to use KubePlus to manage your application instances on your customer's cluster as well.

We have an FAQ about Operators here: https://github.com/cloud-ark/kubeplus/blob/master/Operator-F...

It should be helpful if you are new to the Operator concept.

Operators are generally useful for handling domain-specific actions - for example, performing database backups, installing plugins on Moodle/Wordpress, etc. If you are looking for application deployment then a Helm chart should be sufficient.

If you are currently delivering your SaaS as a separate instance of your application per customer, you might want to check out our open-source project KubePlus - https://github.com/cloud-ark/kubeplus

A more commerical offering is from Cloudark who have designed a specific solution for operating your Helm application as a SaaS offering. I have never used it (ArgoCD being my poison) but you might find it fits your usecase better

As part of your data platform are you planning to create a separate instance of the database for your end customer? If so, you might find our KubePlus Operator helpful. Check it out here: https://github.com/cloud-ark/kubeplus

We have been helping organizations build such multi-instance multi-tenant cloud-native applications. We start with an application Helm chart and create separate release of it per customer/user of that organization. We have an open source Kubernetes Operator that aids in this: https://github.com/cloud-ark/kubeplus

You might also want to checkout Operator guidelines and Operator FAQ: - Operator Maturity Model guidelines: https://github.com/cloud-ark/kubeplus/blob/master/Guidelines.md

The project that is getting some traction recently is our KubePlus Operator that delivers Helm charts as-a-service: https://github.com/cloud-ark/kubeplus

> 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