kine VS rook

-- Kine (Kine is not etcd)

Looking at [1], is there any reason why this couldn’t run in something like DynamoDB? I feel like the operations required would fit

https://github.com/k3s-io/kine/blob/master/pkg/drivers/gener...

I don't like some of the decisions that k3s makes which is why I stay away from it, but it's a great project. I'm not using kine yet, but I fantasize about using it exclusively every time I deal with etcd-induced slowness/random CPU spikes on my group of controller nodes. k0s supports kine too of course but I just haven't switched it on yet.

Well in some situations you can also get away with CRDTs or Gossip (SWIM), but yeah in the general sense Paxos (Raft is a Paxos-family algo). There are lots of paxos family algos to choose from[0].

> I’m also currently building a distributed search engine using etcd for the service registry, broker peer announcements, and worker queue and it’s been a good experience so far.

As a random stranger on the internet, please build an abstraction layer around etcd. Even if there's only one implementation, I've found that so many distributed projects that just never reach the scale that etcd is built for would benefit from the option of writing their own drivers (you don't need a full plugin system just a regular abstraction layer).

One example is Kine[0] for k8s -- if k8s had a built in option for writing/reading from something like Postgres from the beginning it would have been a better project for it, IMO.

If you do build a plugin system though, you can pass off the work of maintaining the other implementations!

[0]: https://vadosware.io/post/paxosmon-gotta-concensus-them-all

[1]: https://github.com/k3s-io/kine

I could spent >0s looking into this, but I've been curious how kline implements Etcd's Watch API. For the matter, I don't have much idea in general how kline handles data. Kline would be a great candidate for a blog post or introductory technical article on.

I do quickly see one issue- evidently watches presently use polling. The issue requests use of postgres triggers: https://github.com/k3s-io/kine/issues/20

check out https://github.com/k3s-io/kine

Not to be mistaken for high-availability Dqlite[1], which is one of the options one can run the k3s kubernetes distribution on (instead of etcd), via the Kine etcd shim[2]. Ultimately though the K3s team replaced Dqlite with an embedded etcd to get high-availability[3].

[1] https://dqlite.io/

[2] https://github.com/k3s-io/kine

[3] https://rancher.com/docs/k3s/latest/en/installation/ha-embed...

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.