Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

This is an awesome experiment and write up. I really appreciate the reproducibility.

I would like to see how moving to database that scales write throughput with replicas would behave, namely FoundationDB. I think this will require more than an intermediary like kine to be efficient, as the author illustrates the apisever does a fair bit of its own watching and keeping state. I also think there's benefit, at least for blast radius, to shard the server by api group or namespace.

I think years ago this would have been a non starter with the community, but given AWS has replaced etcd (or at least aspects) with their internal log service for their large cluster offering, I bet there's some appetite for making this interchangable and bringing and open source solution to market.

I share the authors viewpoint that for modern cloud based deployments, you're probably best avoiding it and relying on VMs being stable and recoverable. I think reliability does matter if you want to actually realize the "borg" value and run it on bare metal across a serious fleet. I haven't found the business justification to work on that though!



Here you go, Kine FoundationDB backend https://github.com/melgenek/f8n

To be honest, I was building it with the purpose of matching the Etcd scale, but making foundationdb a multitenant data store.

But with the recent craze of scalability , I'll be investing time into understanding how far foundationdb can be pushed as a K8s data store. Stay tuned.


Awesome, I will!

It would be great to see where the limits are with this approach.

I think at some point, you need to go deeper into the apiserver for scale than an API compatible shim, but this is just conjecture and not real data.




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: