kubefed VS rook

The project is similar (in spirit) to kubefed.

What Is KubeFed? KubeFed (Kubernetes Cluster Federation) allows you to use a single Kubernetes cluster to coordinate multiple Kubernetes clusters. It can deploy multiple-cluster applications in different regions and design for disaster recovery. To learn more about KubeFed: https://github.com/kubernetes-sigs/kubefed

There's active work on a standard called kubefed [0] that is being worked on.

> I want a scale-to-zero node-pool in every region, and one kube master api for the world.

Personally, I'd generalize this to: "I want to describe the reliability requirements and configuration for my software and have an automated system solve for where, how many, when, and how to route to it"

I want to have something where I can say "I need to have high availability, lowest latency, and X GB of RAM and Y cores" and have a system automatically schedule me wherever compute is cheapest while also intelligently routing traffic to my servers based on client origins.

[0] - https://github.com/kubernetes-sigs/kubefed

Two of the more common approaches to deploying Kubernetes in hybrid environments are from cloud-to-cloud and cloud to on-prem. Whether this is from using a single control plane like Rancher, Platform9, or Gardener to create multiple clusters that are managed from a single location, or utilizing Kubernetes federation to create a cluster that spans different regions, this model has become a key feature offered by Kubernetes that has helped drive adoption.

This is made possible by the very nature of Kubernetes being a standard portable platform across cloud providers, ability to manage infrastructure as code, ability to setup networking between them whenever needed with the help of multi-cluster service meshes and also due to the ability to orchestrate the deployments using Kubefed and Crossplane.

And the interesting thing about networking in cloud is that it need not be just be limited to the cloud provider within your region but can span across multiple providers across multiple regions as needed and this is where projects like Kubefed, Crossplane definitely does help.

Projects like Kubefed and Crossplane are especially useful here since they help you to manage and orchestrate clusters and the requests you send across different cloud providers even if its going to be across regions.

I have some experience with Ceph, both for work, and with homelab-y stuff.

First, bear in mind that Ceph is a distributed storage system - so the idea is that you will have multiple nodes.

For learning, you can definitely virtualise it all on a single box - but you'll have a better time with discrete physical machines.

Also, Ceph does prefer physical access to disks (similar to ZFS).

And you do need decent networking connectivity - I think that's the main thing people think of, when they think of high hardware requirements for Ceph. Ideally 10Gbe at the minimum - although more if you want higher performance - there can be a lot of network traffic, particularly with things like backfill. (25Gbps if you can find that gear cheap for homelab - 50Gbps is a technological dead-end. 100Gbps works well).

But honestly, for a homelab, a cheap mini PC or NUC with 10Gbe will work fine, and you should get acceptable performance, and it'll be good for learning.

You can install Ceph directly on bare-metal, or if you want to do the homelab k8s route, you can use Rook (https://rook.io/).

Hope this helps, and good luck! Let me know if you have any other questions.

Another option is to leverage a Kubernetes-native distributed storage solution such as Rook Ceph as the storage backend for stateful components running on Kubernetes. This has the benefit of simplifying application configuration while addressing business requirements for data backup and recovery such as the ability to take volume snapshots at a regular interval and perform application-level data recovery in case of a disaster.

This is beyond your question but might help someone else: I switch from docker-compose to kubernetes for my home lab a while ago. The storage solution I've settled on is Rook. It was a bit of up-front work learning how to get it up but now that it's done my storage is automatically managed by Ceph. I can swap out drives and Ceph basically takes care of everything itself.

The stumbling point I am at is I want to use rook.io(Ceph) as my storage solution for the cluster. The Ceph prerequisites are one of the following:

Have you looked at Rook?

I've briefly run ceph in an external mode, you can actually use a rook deployment to manage it (sort of). Here is the documentation for doing that. For me it didn't pass my testing phase because I need better networking equipment before I can try that.

This article explains the data corruption issue happened in Rook in 2021. The root cause lies in an unexpected place and can also occurs in all Ceph environment. It's interesting that Rook had started to encounter this problem recently even though this problem has existed for a long time. It's due to a series of coincidences. I wrote this article because the word "Atari" used in a non-historical context in 2021.

Rook (this is a nice article for Rook NFS)

Storage: Favor any distributed storage you know to start with for Persistent Volumes: Ceph maybe via rook.io, Longhorn if you go rancher etc

I've dealt with a lot of issues that are very close to just unplugging a node. Unfortunately on node lost, my stateful workloads using rook-ceph block storage won't migrate over to another node automatically due to an issue with rook. Stateless apps (ingress nginx, etc..) not using rook-ceph block failover to another node just fine. I've kind of accepted this for now and I know Longhorn has a feature that makes this work but I find rook-ceph to be more stable for my workloads.