One of the solutions is to stop the ai hype, as the excessive electrical needs it creates are obviously not helping with the climate.

Excuse me, fossils?

It's only offensive if you're being carried around.

I think they're referring to the artifacts (like foo) rather than people.

Petroleum is used by everyone right? And it's a literal fossil. I wouldn't call it a fossil because all terminology has lore, but the idea as I understand it is that it's an artifact that outlived the context it was originally relevant in.

I think foo never outlived what it was from the beginning - a way to harmlessly goof around while describing complex systems & patterns. So, really dunno why the commenter above wanted to atribute all the fooness to something "ancient".

PS. Unsure why to mix petroleum into this discussion..

Not the usage, the context.

The idea is very noble.

In am just thinking about the number of 5, who these times has really five trustable friends not just acquaintances or people bound by some specific activity perishing over time. I am afraid, for most people in the digital era this number is much lower (and I am certainly not speaking for myself now).

"who has five friends?" has been the number one comment I've received on this, by far. a bubble just popped for me

You should add a feature where you can select the shares/threshold, with 3/5 being the default.

edit: d'oh! you do, I didn't get that far into using it yet cause I was on mobile.

Looks nice.

What is the memory consumption under a significant load? That seems to be as much important as the throughput & latency.

Very relevant question! The memory profile in minikv depends on usage scenario and storage backend.

- With the in-memory backend: Every value lives in RAM (with HashMap index, WAL ring buffer, TTL map, and Bloom filters). For a cluster with a few million objects, you’ll typically see a node use as little as 50–200 MB, scaling up with active dataset size and batch inflight writes;

- With RocksDB or Sled: Persistent storage keeps RAM use lower for huge sets but still caches hot keys/metadata and maintains Bloom + index snapshots (both configurable). The minimum stays light, but DB block cache, WAL write buffering, and active transaction state all add some baseline RAM (tens to a few hundreds of MB/node in practice);

- Heavy load (many concurrent clients, transactions, or CDC enabled): Buffers, Raft logs, and transaction queues scale up, but you can cap these in config (batch size, CDC buffer, WAL fsync policy, etc);

- Prometheus /metrics and admin API expose live stats, so you can observe resource use per node in production.

If you have a specific workload or dataset in mind, feel free to share it and I can benchmark or provide more precise figures!

Thanks for the thorough reply!

Isn't it also how timeshift [1] backups are working?

[1] https://github.com/linuxmint/timeshift

Very honest warning there :)

Btw, Hetzner seems to have slightly cheaper offer for such small VPSs, and their disk i/o is much better than at OVH. (My own tests; I always compare the storage speed)

May I ask all the unsatisfied programmers from the Java ecosystem to avoid Go - or to radically change the approach and programming habits when going there.

There are far too many javaisms in the overall Go codebase. Please, respect that the language was created with completely different mindset than what you already are used to.

Thanks

Yeah, but you know, they needed to save extra bytes in the Rust implementation of their services, so wherever Rust pops up it apparently justifies any such action. ;)

What about: tech managers can no longer hide their poor or nonexistent management skills.