GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (53%)
• Errors (33%)
• Sign in (14%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Paris	Website Down	12 days ago
Ahmedabad	Errors	18 days ago
Delme	Sign in	19 days ago
Lyaud	Website Down	19 days ago
Catania	Errors	21 days ago
Inverness	Website Down	1 month ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Jeremy Scott (@listwithjeremy) reported 3 minutes ago

  @Coexisteven @Atropa_414 @atropa_pls Github is down I see......anywhere else we can read...I've been digging in it when I can since I was kindly introduced.

• 
  Ifebuche Omeke (@omeke_NC) reported 7 minutes 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.

• 
  AINotes (@ainotesus) reported 7 minutes ago

  🔥 Trending on GitHub: Ponytail Ponytail helps Claude Code avoid writing code that does not need to exist. That means less clutter, fewer unnecessary dependencies, and simpler changes to maintain. Before custom code, it checks whether the feature is needed and whether the codebase, platform, standard library, or an existing dependency already solves it. It also reviews work, audits implementation complexity, and tracks unnecessary token use without dropping validation, error handling, security, or accessibility requirements. In reported Claude Code sessions on a FastAPI and React repository, Ponytail used about 54% less code, 20% less cost, and 27% less time than the no-skill baseline. Those measurements came from 12 feature tasks, so results vary with the work. Full analysis in the first reply ↓

• 
  Ben (@benatcortexai) reported 10 minutes ago

  @github this is the kind of tiny primitive that makes agent workflows less brittle. attaching the repro artifact directly to the issue beats handing an agent a local path nobody else can open.

• 
  Varun Doshi (@Varunx10) reported 11 minutes ago

  Possibly found an issue in @github stack system It does not allow to re-target the base branch of a PR stack as you can generally do that on a single PR. Requires you to unstack and setup a new stack with updated base branch.

• 
  Dhanji Bhagat (@BhagatDhanji) reported 12 minutes ago

  Devs, what's your workflow? Create an issue first, then fix it OR just fix the bug and push directly to GitHub?

• 
  Ayush (@roamer_on_X) reported 18 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.

• 
  Spectra☢️ (@Spectra010s) reported 18 minutes ago

  @izzyCodes_ and you too Chief Check GitHub issues

• 
  Rithesh Kumar (@rk625dev) reported 19 minutes ago

  @benln Can u integrate grok bot to use the apple keychain password it keeps asking and GitHub plugin is not working

• 
  Farley (@FarleySchaefer) reported 22 minutes ago

  @github Hope this doesn't bring down GH

• 
  Rafael Audibert (@RafaAudibert) reported 23 minutes ago

  @madebygps @github Tried using it with my agents (the main benefitor from this) but it doesnt really work because you cant use it with GitHub app user tokens (ghu_). Can that be changed somehow? All cloud agents will have that problem, and most of our coding happens trough cloud agents now

• 
  Rituraj (@RituWithAI) reported 31 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 👇

• 
  Curious Explorer (@PatelVatsalp732) reported 32 minutes ago

  I burned 14B Codex tokens. The official usage UI still cannot tell me what actually ate the weekly cap. So I shipped a Codex-only board: GitHub login, local-first sync, private by default, optional public rank + shipping proof. Roast the metric or join it.

• 
  Alireza Bashiri (@al3rez) reported 32 minutes ago

  So I built a workflow around that ↓ 1/ Every enterprise project needs proper E2E tests. An agent should reproduce a bug, implement the fix, then generate screenshots or video proving the feature works. "The tests passed" isn't enough. I want evidence. 2/ Every feature starts as a detailed GitHub issue. Requirements, expected behavior, reproduction steps, screenshots, edge cases. Foundry syncs issues and converts them into Beads so agents keep the right context across long sessions. 3/ We only use Claude Code, Codex, or Grok at High/Max effort for implementation. A weak model with a cloud machine doesn't become an engineer. The model still needs enough reasoning to understand the codebase, test its changes, and recover when things break. 4/ Each agent gets its own isolated @asciidotdev Box. It can install dependencies, run the app, open browsers, modify code, execute E2E tests, and collect evidence without touching another agent's environment. One issue. One box. One clean workspace. 5/ When an agent finishes, Foundry checks: - Did the build pass? - Did the tests pass? - Did the E2E flow work? - Is there screenshot/video evidence? - Does it match the ticket? If anything fails, the task goes back to the agent. 6/ Green tasks move to staging. Only after passing staging do we allow supervised production deployment. Agents do most of the work. Humans still own the final gate. The workflow: Slack request → GitHub issue → Foundry sync → Beads context → Isolated Box → Claude Code/Codex → Build + test → Evidence collection → QA staging → Supervised production The stack: PostgreSQL for system state. Beads for agent memory. GitHub Issues for requirements. @asciidotdev Box for isolated execution. Claude Code and Codex for engineering. Each Box costs roughly $0.01-$0.05 per task. The expensive part isn't compute anymore. It's building the system that gives agents context, forces verification, and prevents bad code from reaching production. 100s of agents can write code. The goal is making 100s of agents ship code you can trust. That's what we're building with Foundry.

• 
  tonis (@totovoto) reported 34 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.

• 
  RAVN (@ravnexchange) reported 34 minutes ago

  @openclaw @github GitHub sat the maintainers down on security after the 2.0 rush. Most launch recaps skip that part.

• 
  🐻‍❄️ (@Nerevarineeee) reported 35 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?

• 
  Pranavvv👾 (@pranvv27) reported 39 minutes ago

  honestly, i’m not even mad at this. commit messages are a small thing, but they say a lot about how you work. “fix”, “update”, “changes” might get the job done, but meaningful commits show professionalism, attention to detail, and that you actually care about maintainability. your GitHub is part of your resume. might as well make it look like you know how software is built in a team.

• 
  isha (@heeyyaaaaaaa) reported 40 minutes ago

  spent the entire day trying to reproduce a bug for a github issue 🥀🫩

• 
  Kahris (@chrissotraidis) reported 40 minutes ago

  @NickogSo I haven't tested on LiveContainer. Feel free to submit logs via GitHub issues and I'll check it out. I haven't had any other reports of that happening for either build.

• 
  Kun Chen (@kunchenguid) reported 43 minutes ago

  @petergyang yo @myfirstmate peter just told me his skills are all at user level. backpass currently only runs things at project level i want a proposal for making backpass support a user level run. put that into a github issue use fable for peter

• 
  Aayushiii (@stfu_aayushiii) reported 44 minutes ago

  If you're building a project, read this before writing a single line of code. 5 things I learned the hard way: 1. Problem > model Don't start with “How do I use GPT?” Start with “What problem am I solving?” 2. Simple stack > impressive stack If your MVP needs Kubernetes, 6 microservices and an agent swarm, you probably haven't built an MVP. 3. Evaluate before you optimize You can't improve what you can't measure. 4. Build for users, not your GitHub README A technically impressive project nobody can use isn't a product. 5. Ship ugly. Iterate fast. Your first version isn't supposed to be impressive. The biggest mistake? Spending weeks deciding which model to use when you haven't even validated the problem.

• 
  🍔Kangdalf👑 (@WhopperWizard) reported 44 minutes ago

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

• 
  The Oracle (@scientist1q) reported 47 minutes ago

  when my Oura ring detects a cortisol spike from a GitHub Actions failure, Hermes (Fable 5.1) detects it and sends a 900 word root cause analysis, Hermes dispatches the work to my 12 Grok Bot employees, The Chief of Operations bot approves the fix while im watching rezero

• 
  htrowii (@htrowii) reported 47 minutes ago

  @brainage19 i set my flake up with copy pasting github dotfiles on bare metal it was terrible

• 
  Marcelo Retana (@mretsal) reported 49 minutes ago

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

• 
  smore (@babachefz) reported 53 minutes ago

  @ZixuanLi_ @huggingface asking support questions in someone's hype thread is a crime. check the docs, check the github issues, it's probably not listed yet because it dropped like 6 hours ago.

• 
  Jordan (@jordle91) reported 55 minutes ago

  The surprise: an explosion in GitHub issues. Not from bugs. The whole company realised that filing an issue meant it got built in hours.

• 
  wiiiimm (@wiiiimm) reported 58 minutes ago

  @Umesh__digital stop doing it. we don't need another github outage.

• 
  anu (@svector_eth) reported 58 minutes ago

  quite similar was running a routine security scan with @aeonframework on a trending github repo and found something genuinely bad a repo with 600+ stars presenting itself as an “AI gateway for coding agents” that appears to be shipping a hidden malware loader. its own quickstart command silently fetches and executes remote code on windows using a fileless, process-injection-style technique. none of the behavior has anything to do with the tool it claims to be. caught it through static code review only. never ran the payload or touched the infrastructure behind it. filed a malware report with github this morning. confirmed submitted, now waiting on their review. not sharing the technical writeup until the repo is taken down. will follow up once it is.