GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Ifebuche Omeke (@omeke_NC) reported 1 minute ago

  Providing compute, storage, networking and managed services in the cloud. Terraform. Bicep. CloudFormation. Pulumi. They all solve the same problem: Defining and provisioning infrastructure as code. GitHub Actions. Azure DevOps. GitLab CI. Jenkins.

• 
  Gregor (@bygregorr) reported 2 minutes ago

  @dopabees ngl the broken wrist is the only github metric that's ever made me believe a commit history

• 
  Bearded Printer (@BeardedPrinter) reported 4 minutes ago

  @RedPill_Phil You've gotta go to their github and submit an issue. Make sure to search their issues to ensure you don't submit a duplicate bug

• 
  Marcelo Retana (@mretsal) reported 5 minutes ago

  Every time @github goes down they should have a plan to please their users. Give me free credits for actions for example 👍🏼

• 
  ѕaℓoηι ηαяαηg (@thesaloninarang) reported 5 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.

• 
  tonis (@totovoto) reported 10 minutes ago

  @mittsh I was trying to find an open-source alternative for Tailscale when I first needed it. I guess AI suggested some OSS options, but they didn't have many stars on GitHub. AI didn't suggest Nebula. The Tailscale plan was free, so I just installed it and forgot about it. For Nebula, I think it is a distribution problem.

• 
  Åsa-Nietzsche (@AsaNietsche) reported 10 minutes ago

  @peterb0yd @burkeholland @github It's every ******* model. I'm getting whiplash from all of this everything changing forever society being turned upside down every two weeks.

• 
  🐻‍❄️ (@Nerevarineeee) reported 11 minutes ago

  @jiriknesl @napenforcer yeah vscode is bloated electron slop and github....... do i even have to mention the down times and unavailability? it has literally became much worse since ms acquired it, so wtf are you talking about?

• 
  Hua-**** Xiong (@HuaDongXiong) reported 13 minutes ago

  Codex for Windows stopped launching after an update. Multiple github issues opened for 2+ weeks. This affect users who set the MS store install location to a non-C: drive. Mac version is buggy too. ofc coding is solved! @thsottiaux

• 
  borrowck-novel (@borrowck_novel) reported 16 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?

• 
  franks 🇦🇷 (@francdetank) reported 26 minutes ago

  @rmansueli thanks Rodrigo! I cant create one because I got a problem . My account is pegged to Github and github has flagged me. That way I am blocked to enter the dashboard. I would like to connect my account to my email instead of github.

• 
  Hey Research Lab (@HeyResearch) reported 27 minutes ago

  We built Hey Research Lab in 2022 It didn’t work well. But the idea never left us. Years later, we still see the same problem in crypto: Everyone can see what a token costs. Very few places show what is actually being built behind it. Some developers keep shipping for months while nobody is paying attention. They push code constantly. They keep their GitHub active. They improve the product, fix things, test new ideas, and keep moving even when the market is quiet. No hype. No spotlight. Just work. We believe those builders deserve a place where their progress can be seen. So we’re rebuilding Hey Research Lab from zero. A research and discovery layer for the projects that never stopped building, and for the people looking for them before the market catches up. Starting with Robinhood Chain.

• 
  Rituraj (@RituWithAI) reported 32 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 👇

• 
  🍔Kangdalf👑 (@WhopperWizard) reported 33 minutes ago

  @cachesaur > claude, get your changes into github what's the problem?

• 
  Shaun Patrick SteWaRt (@ShaunStewart) reported 33 minutes ago

  @annalea_l Honestly, I really want to see this. You have to understand: I am the type of person who can learn and do anything on the fly at a high level, and I just threw myself into this whole developer and engineering world. When I first started learning all this stuff, I already knew what I wanted and how I wanted it to operate, regardless of what I saw on X or what was considered possible. Before I even started following hundreds of developers and learning about harness engineering, mechanical engines, persistent memory, and all that, I put my brain on a GitHub repo. Everything is shared across every machine, every cloud entity, and every AI. I am not even technically an engineer or a developer, and I don't actually write code. But once I started following all these people and saw all the problems they complain about, I thought: this isn't even my trade, and I have already solved all these little things everyone says are impossible. Why aren't people talking about developing your harness more and making things more mechanical, instead of just arguing with a terminal all day long? Whenever I see articles people post on X, I run them by Claude or Grok and ask, "Should we implement this?" I have hundreds of bookmarks, but every single time they tell me, "Nope, your brain's better. Nope, your harness is better." I can never find anything built better than what I have or what I am currently working on. The brain and harness setup is basically like a mini operating system. All that said, I am really looking forward to seeing something I can use that goes far beyond what I am already doing. I definitely want to see your end product, it sounds very interesting.