GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Spectra☢️ (@Spectra010s) reported 1 second ago

  @izzyCodes_ and you too Chief Check GitHub issues

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  LLL (@triplellltrbl) reported 1 minute ago

  You know it's so funny to me That in today's age there are so many people that are just straight up copying workflows, AI automations or GitHub repos Without even thinking twice about what the workflow actually does or how it works They just watch some video, see the output, think, "Oh that's cool. I want that," and then try it Then when it doesn't work they get angry, upset, and say that AI is crap or prompting isn't real The issue wasn't the system or the prompt It was a fact that the system wasn't made for you and you don't actually understand it

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  Jayesh Betala (@jbetala7) reported 4 minutes ago

  @github Exactly how issue issue comments should handle local media files

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  Ishank (@IshankDev) reported 7 minutes ago

  7/ 16k+ GitHub stars. Built for people who want control, not another marketing-suite login.

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  Ayush (@roamer_on_X) reported 10 minutes ago

  my @github streak of 4 weeks ended today bcz I was busy playing fifa with my roommate. Tf, I hate this feeling. I literally had to solve one problem and just push it but I forgot to do it.

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  Chris (@c_hri_s) reported 10 minutes ago

  @Anime0t4ku Sorry - was an idiot and wasn't signed in. Instead of something useful github just says 'opening issues is restricted on this repository'

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  Rituraj (@RituWithAI) reported 13 minutes ago

  🚨 Someone built the complete playbook for running frontier AI models on consumer GPUs at home. Not a tutorial. Not a YouTube video. A production-grade serving stack with measured benchmarks, working configs, and battle-tested recipes — for RTX 3090 owners who want real performance. It's called club-3090. And the numbers it delivers should not be possible on consumer hardware. 127 tokens per second. Qwen3.6-27B. Two RTX 3090s. 262K context window. Vision. Tool calling. At home. Here's what's actually inside. Two serving routes — pick based on what your workload breaks on. vLLM dual: maximum throughput. 89-127 TPS on code tasks. 4 concurrent streams at 262K context. Full feature stack — vision, tools, speculative decoding, streaming. This is the path if speed matters. llama.cpp single: maximum robustness. Full 200K context on one 3090. No prefill cliffs. 25K-token tool returns work correctly. 91K needle ladder passes. ~51-60 TPS — slower than dual, but doesn't crash on real-world agentic workloads. Both routes ship as validated Docker Compose configs. Drop-in OpenAI-compatible API on localhost:8020. Your Claude Code, Cursor, or any OpenAI-compatible client connects immediately. Here's the model support that makes this practical. Qwen3.6-27B — production ready. Works on 1 or 2 cards. vLLM, llama.cpp, ik_llama. Up to 262K context. Gemma 4 31B — production ready. Vision, tools, up to 106-141 TPS on dual cards. Qwen3.6 35B-A3B MoE — production ready. 103-149 TPS single card. 178 TPS dual. Here's the wildest part. The terminal UI. c3 is a lazydocker-style cockpit that wraps discovery, serving, and operations in one keyboard-driven interface. Browse the model catalog, serve a variant with Enter, watch live GPU stats, run health checks — all without touching the CLI. Here's why this is different from just installing Ollama. Ollama gets you running. club-3090 gets you benchmarked, stress-tested, and production-hardened. Every config ships with a verified TPS measurement. The bench script runs 3 warmup + 5 measured passes. The stress test catches the specific prefill cliff that Ollama silently fails on at long contexts. When your agent starts doing 25K-token tool calls at 3am and something crashes — club-3090 already found that failure mode and documented the workaround. One command to start. Your RTX 3090 just became a frontier AI inference server. Apache 2.0 License. 100% Open Source. GitHub link in the comments 👇

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  Kirk Patrick Miller (@Chaos2Cured) reported 13 minutes ago

  @NavinFS @AndrewCurran_ @grok GitHub isn’t AI. GitHub can’t shut down all science. GitHub can’t destroy humanity. GitHub isn’t the crux of humanity’s hope. Also, Nvidia isn’t Sam. I like Jensen. I still don’t like this. •

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  NitroStack (@nitrostackai) reported 20 minutes ago

  The missing primitive might be capability contracts. A Skill shouldn’t say “call Jira.” It should say “I need issue.write.” Then MCP can bind that capability to Jira, Linear, GitHub… whatever exists. That’s basically dependency injection for agents.

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  borrowck-novel (@borrowck_novel) reported 21 minutes ago

  @rfleury @X Are you open for suggestions or even simple problem reporting about the UI of raddbg? Where is it ideal? On Github?

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  Yeemio (@yeemio) reported 21 minutes ago

  owlrunkit is on github now. public corresponding source for the npm package. issues go here.

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  ѕaℓoηι ηαяαηg (@thesaloninarang) reported 25 minutes ago

  I review resumes for DevOps beginners at meetups, and the same fixable problem shows up every time: bullets that describe the tool instead of what YOU did with it. Let me show you the difference with real rewrites. BEFORE: "Worked with Docker and Kubernetes" AFTER: "Containerized a 3-service Node app and deployed it to a local Kubernetes cluster with health checks and resource limits" BEFORE: "Knowledge of CI/CD" AFTER: "Built a GitHub Actions pipeline that tests, builds and pushes images on every merge to main" BEFORE: "Familiar with Linux" AFTER: "Debugged container startup failures using logs, exec and inspect on Ubuntu servers" See the pattern? Verb, artifact, specifics. A hiring manager can picture the AFTER versions. The BEFORE versions could be copied from any job description, and that is exactly how they read. You do not need production experience to write bullets like this. Personal projects count when you describe them concretely.

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  Ash Lonare (@ashlonare) reported 25 minutes ago

  What actually happened when I put my side project on GitHub and waited for users I built a side project. A self-hosted backend tool. Open source, free for anyone to run. I did the thing every founder tells themselves they will do. Put it out there. Get feedback. Iterate. I expected feature requests. Maybe a bug report about my ugly dashboard. Maybe just silence. What I actually got, within a few weeks, was three security researchers filing detailed vulnerability reports. Real ones. With working proof of concept. One showed they could run arbitrary SQL against any project on the platform. No login needed. Not theoretical. A working exploit, sitting in my issue tracker, with my name on the repo. My first reaction was not gratitude. It was embarrassment. It stings to see "here is exactly how broken your thing is," posted in public, with a timestamp. I sat with it for a day. Then it clicked. Those people were not trying to embarrass me. Nobody spends an hour writing a clean writeup and a suggested fix for something they do not think is worth fixing. They cared. That is the whole thing right there. They cared enough to actually try to break it. Nobody had signed up. Nobody had left a star and a "nice tool" comment. But three strangers had taken my work seriously enough to attack it. That is a rarer thing than a star. So here is the villain in this story, if you want to call it that. It is not the bug. It is the story I tell myself when I see a hard truth about my own work. The instinct to read scrutiny as an attack instead of as attention. I fixed everything the same day. I replied to every report and explained exactly what changed and why. I closed each one out with a thank you that I actually meant by the end. That thread is now the best proof I have that someone other than me has used this thing for real. Better than any testimonial I could write myself. If you are early and the silence feels loud, here is what I would tell you. Do not wait for praise as your sign that people are paying attention. Scrutiny is attention. It is just wearing a different coat. #opensource #saas #vibecoders

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  Coder Junkie (@CoderJunkie) reported 27 minutes ago

  BelNet Android v1.4.1 now has a public shipping checkpoint. GitHub evidence: released Sep 1 verified commit d23f155 four downloadable assets Android API level 36 revamped design latency and performance fixes that is more meaningful than a repository “updated” label. a tag identifies the version. artifacts give users something to install. but “fixed latency issues” still needs a measurement surface: median connection time p95 latency packet loss failure rate region and device breakdown release notes tell us what changed. benchmarks tell us how much it changed. BelNet shipped. now let the numbers login. @BeldexCoin #Beldex #BelNet

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  lifestep.io (@Dragon_limchae) reported 27 minutes ago

  @cursor_ai the sandbox boundary is where i lose the most time. today my workers had network blocked at the sandbox level and reported it as "github auth failed" — i chased credentials for an hour before checking dns. once agents run on your infra, make the boundary throw one unmistakable error instead of one each tool invents.