Langfuse Operator
Self-host Langfuse on Kubernetes, properly
What it does
Langfuse Operator makes self-hosting Langfuse on Kubernetes actually production-ready. Deploy the full stack from one custom resource, automate upgrades and migrations, and avoid the usual self-hosting glue. Built for platform teams that want control, repeatability, and a cleaner path to running LLM observability in production.
Does the same job
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- LOLangfuse – Open-source observability and analytics for LLM apps2023 · github.com · ▲143
Hi HN! Langfuse is OSS observability and analytics for LLM applications (repo: https://github.com/langfuse/langfuse, 2 min demo: https://langfuse.com/video, try it yourself: https://langfuse.com/demo) Langfuse makes capturing and viewing LLM calls (execution traces) a breeze. On top of this data, you can analyze the quality, cost and latency of LLM apps. When GPT-4 dropped, we started building LLM apps – a lot of them! [1, 2] But they all suffered from the same issue: it’s hard to assure quality in 100% of cases and even to have a clear view…
- RTRenovate – The Kubernetes-Native WayFeb 2026 · github.com · ▲43
Hey folks, we built a Kubernetes operator for Renovate and wanted to share it. Instead of running Renovate as a cron job or relying on hosted services, this operator lets you manage it as a native Kubernetes resource with CRDs. You define your repos and config declaratively, and the operator handles scheduling and execution inside your cluster. No external dependencies, no SaaS lock-in, no webhook setup. The whole thing is open source and will stay that way – there's no paid tier or monetization plan behind it, we just needed this ourselves and figured others might too. Would love to hear…
- RGRun globally distributed full-stack apps on high-performance MicroVMs2023 · koyeb.com · ▲98
Hi HN! We’re Yann, Edouard, and Bastien from Koyeb (https://www.koyeb.com/). We’re building a platform to let you deploy full-stack apps on high-performance hardware around the world, with zero configuration. We provide a “global serverless feeling”, without the hassle of re-writing all your apps or managing k8s complexity [1]. We built Scaleway, a cloud service provider where we designed ARM servers and provided them as cloud servers. During our time there, we saw customers struggle with the same issues while trying to deploy full-stack applications and APIs resiliently. As…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Launched alongside, April 2026
the whole month →
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Thought the resources for GPU arch were lacking, so here we are
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Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
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Life & fun · Apr 2026 · sam-burns.com
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With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories. There are two versions: Minimal (HN-inspired, fast, static): https://text.blogosphere.app/ Non-minimal: https://blogosphere.app/ If you don't find your blog (or your favorite ones), please add them. I will review and approve it.
AI · Apr 2026 · text.blogosphere.app