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A distributed system, used authoritatively After writing about Git as universal storage, there is a question from the same line of thinking that kept coming back to me, and it is not a storage question but a collaboration question: why does contributing to

A general observation In the past months I started digging more and more into the self-hosting space.

When I first wrote about gguf-runner, it was exactly what the name suggested: a small binary that loaded a GGUF model and wrote the result to the terminal.

This is a guest post on jens.dev.

After I got building containers on Codeberg sorted out, the next thing that broke on me was much more boring on paper: the test job kept getting killed.

In an earlier post about gguf-runner I made a point that kept nagging at me afterwards.

A few days ago I ran into a surprisingly tricky TLS issue while setting up automated tests for a service running behind Let’s Encrypt certificates.

Everlock grew out of a simple frustration: handing your code, photos, mail, and calendars to someone else’s cloud means trusting that they will still be around — and still on your side — next year.

A more technical follow-up In the previous post I introduced gguf-runner, a small Rust CLI for running GGUF models locally on CPU.

I have been moving more and more of my smaller projects over to Codeberg lately.

A quick follow-up In the previous post I introduced gguf-runner, a small Rust CLI for running GGUF models locally with a focus on: CPU-only inference mmap-based model loading a small, scriptable command line interface If you haven’t read that one yet, it…

I’ve been playing with local LLMs again.

This post is a cross-post from Down to Zero.

I was recently on the lookout for a e-paper version of a picture frame that could be battery powered.

I recently purchased some IoT device based on a pre-built ESP32 firmaware.

Scaling our services in Kubernetes represented a multitude of problems.

The more engines we migrated, the more we reached the limits of our approach.

The “axum-server-timing” project on GitHub provides an Axum layer to inject the Server-Timing HTTP header into responses.

Recently I was wondering how I could track the timings of an API I wrote and was looking for ways to implement something to keep track of the individual stages of a request process.

This is a cross-posting from downtozero.cloud The more our little project progresses, the more code we produce.

We just started the migration and saw some impressive results very early on.

Containerizing BusinessWorks 5 comes with its own set of challenges.