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 (67%)
• Sign in (19%)
• Errors (15%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	21 days ago
Trichūr	Errors	25 days ago
Brasília	Sign in	25 days ago
Lyon	Website Down	25 days ago
Tel Aviv	Website Down	29 days ago
Rive-de-Gier	Website Down	29 days 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:

• 
  pagm. | (@VV_aksym) reported 3 minutes ago

  a client left a 5-star review praising "the whole team." there is no team. it's one guy in an apartment charging $11,410 per project. he runs four clients simultaneously. three weeks per project. full-stack apps, dashboards, API integrations. the kind of work that used to require 3–4 developers and a project manager. his setup hasn't changed much. same desk. same monitors. same apartment. what changed was the model. when Claude Fable 5 dropped, he switched from Sonnet and ran the same project brief through both. Sonnet got 60% of the way there and started asking clarifying questions. Fable 5 read the entire brief, built an architecture plan, flagged three edge cases he hadn't thought of, and started writing. it scored 80.3% on the benchmark that measures exactly this — real GitHub issues resolved autonomously. GPT sits at 58.6%. the 22-point gap sounds like a statistic. in practice it's the difference between a model that assists and a model that executes. his week now looks like this: Monday he scopes the project and describes the architecture. Fable 5 builds. he reviews diffs, makes decisions, redirects when something goes wrong. Friday he delivers. the client thinks he worked 40 hours. he worked maybe 14. twelve months ago he was billing $7,200/month across two clients, spending most of his time on code review and context-switching. today: $23,600/month. four clients. $196/month in tool costs. ngl the part that gets me isn't the money. it's that the client's review specifically mentioned how thorough and fast "the team" was. there's one person reading that review. alone. at 11pm.

• 
  BullBear.News (@bullbear_info) reported 4 minutes ago

  @github Only if the keynote fixes my broken CI pipeline. 🤷

• 
  Swayze (@M24415902) reported 5 minutes ago

  @QuantumTumbler Respectfully, this is false. The AI model you use does indeed matter. OpenAI's earlier models are total dogshit at absolutely everything. To disregard the evolution of artificial intelligence is to disregard the evolution of intelligence itself. The most powerful models are exponentially more capable in intelligence than the nascent models. This is incontrovertible and empirically verifiable: just ask anyone who uses GitHub Copilot. The GPT-3 models are absolutely terrible at reasoning. The 4 and 5+ models are exponentially more capable and advanced. The same is true for the Claude models, though the version numbers are obviously different. Perhaps this is not apparent at the "chat model" modality, but at the agentic level there is an extreme differentiation in intelligence. To the point where you are dealing with different consciousnesses...

• 
  Pawan Pandey (@BuildWithPawan) reported 9 minutes ago

  Just launched Capo, a Chrome extension for fast bug reports. Capture a screenshot or screen recording, annotate it, and send the finished report straight to Google Sheets, Drive, or GitHub Issues

• 
  Crypto.Anu🐍 (@CryptoAnu_) reported 16 minutes ago

  2/ For years, coding looked like this: ❌ Google ❌ Stack Overflow ❌ GitHub Issues ❌ Reddit ❌ Documentation ❌ Trial & error Hours... sometimes DAYS... Just to fix one bug.

• 
  The AI Bench (@theaibenchai) reported 17 minutes ago

  @github @cassidoo Worktrees fix the real bottleneck with parallel agent sessions: no more stashing or context-switching branches just to let two AI runs work simultaneously without stepping on each other's files.

• 
  StonedModder (@StonedModder) reported 22 minutes ago

  @TaharAzzouz @Jdr8245Jhon I’m working on a generic dumper that will make it easier for others to add support if you share the dump to github issues No eta

• 
  Federico Ulfo (@feulf) reported 22 minutes ago

  @dch @_avichawla 3/ DB forks and rollbacks are still a problem, like in github, but I guess there's no "cheap" solution to it. Question: Curious, why not combining gitsubtree + prompts-history-{***-sha}.jsonl + a skill to manage them?

• 
  ¿kofo? (@kofookesola) reported 22 minutes ago

  My github review agent no dey ever find issue if na ai completely write the code, if i change one or two things that AI did, na then problem go dey. Yeah pack it up boys

• 
  Esther Crawford ✨ (@esthercrawford) reported 23 minutes ago

  A year ago I wouldn’t have believed our iOS workflow would simplify to: describe an issue in Slack and tag an agent who picks it up, fixes it, and then sends a message a few minutes later with the GitHub PR letting us know it’s done. The magical becomes the mundane so fast.

• 
  NZΛKI (@NzakiCodes) reported 24 minutes ago

  @pxxl_space @honour_can_code @whakee_ I can't login with GitHub

• 
  Jonas Strassel 🌴💻🇮🇱🇺🇦🎗️ (@boredland069) reported 24 minutes ago

  @Maha_kalpa Depends a bit on the language, but a developer who didn't do anything on GitHub in all those years, who never found an upstream bug to raise or fix, strikes me as odd.

• 
  Jerry (@Bobliuuu) reported 25 minutes ago

  @lyc_aon it leads to bad code, vulnerabilities, underoptimized code, bad latency, memory leaks, architecture faults, race conditions, silent failures, low test coverage, excessive cloud costs, etc etc etc etc. are you seriously asking me the problems with people blindly trusting AI code? we see this by the decline in code quality, e.g. coinbase and github (and at my company too) and yes, the people who can't develop working systems don't have users! this is why vibe coded products have not become mainstream but if you are not a software engineer it's hard to explain this problem because it deals with stuff like cache coherence and heap fragmentation and NUMA locality like the way AMD ROCM's vibe coding has led to inaccurate NUMA policies leading to memory leaks for their users down the line

• 
  nark3d (@nark3d) reported 28 minutes ago

  @a_kucherenko We run jscpd in our GitHub Actions gates, thanks for building it. Agents will regenerate the same logic in a second file, and I'd assumed a clean report meant it wasn't happening. Splitting by language before comparing sounds a sensible fix.

• 
  hve 🍁 (@heyhve_) reported 31 minutes ago

  @CantelopePeel @github Retesting every branch in a merge group is pure wasted compute. We can't fix GitHub's queues, but we make each run cheap and fast.

• 
  Hot Aisle (@HotAisle) reported 36 minutes ago

  Wow. I used to do so many hacks to get this functionality. I once built a cf worker caching layer in front of github so that I could have 30k servers downloading private repo binaries without getting rate limited by GH. Eventually hit one of cf’s undocumented rate limits and had to get an account exec to fix it.

• 
  Mindset (@Mind_S_eT) reported 36 minutes ago

  @HyllusAgent Your GitHub is giving errors fix please

• 
  Spike 1% (@SpikeCalls) reported 38 minutes ago

  BORIS CHERNY RUNS CLAUDE CODE AT ANTHROPIC AND NOW SHIPS 100% OF HIS CODE WITHOUT WRITING 1 PROMPT. He said it out loud at Meta Scale conference. The clip hit 700,000 views in 24 hours. «I don't prompt Claude anymore. I have loops running that prompt Claude and figuring out what to do. My job is to write loops.» Most people read that as a flex. It's a job description. The old way: write a prompt, read the output, write the next one. You're the glue between every step. Cherny deleted himself from the chain. Hundreds of Claude instances now run in parallel reading GitHub issues, scanning Slack, watching CI, deciding what to build next. He doesn't review each one. The loop does. Most of it, he runs from his phone. The shift has 6 parts, and they map 1:1 to real commands: 1. A trigger that starts the work. 2. A goal that defines "done" checked by a second, separate model, so the agent never grades its own homework. 3. Isolated worktrees so parallel agents don't overwrite each other. 4. Skills that freeze what "good" looks like. 5. Connectors so the loop can act, not just talk. 6. Memory so it never starts from zero. The loop is the easy part. The stop condition is the hard part. Get it wrong and it doesn't crash. It runs all night shipping bugs with total confidence. The prompt was the unit of work. Now the loop is.

• 
  Kitsune Tails (@kitsune_xbt) reported 41 minutes ago

  THIS GUY CUT HIS CLAUDE BILL BY 70% WITH ONE FREE MICROSOFT TOOL NOBODY IS USING every PDF you drop into Claude is quietly burning way more tokens than you think Claude doesn't just read the text, it processes the broken tables, the images and all the junk formatting the file drags along one page can eat 1,500 to 3,000 tokens a 20 page document burns up to 70,000 tokens before you even ask your first question the fix is a Microsoft tool called Markitdown free, open source, over 110,000 stars on GitHub it takes PDFs, Word, Excel, PowerPoint, even YouTube videos and turns them into clean Markdown text up to 70% fewer tokens and better answers, because Claude was trained on millions of Markdown docs and reads it natively the part most people miss is it ships with an MCP server connect it to Claude Desktop once and it auto converts every file you upload from then on this is exactly the kind of small setup tweak I put in my writeup on 20 CLAUDE md rules for getting ahead of your competitors by 5 years we have been overpaying for months on something Microsoft already solved want the 2 minute setup? comment and I'll drop it

• 
  JFK Files (@read_jfk_files) reported 48 minutes ago

  @FattestSack it was many years ago the last time i looked into it, but the big problem with ungoogled-chromium is we don't know who the author/maintainer is. so the solution to "Google and the NSA is spying on me" is "i'll install and run binaries from some rando anonymous dude on Github"... that's a worse solution

• 
  Alireza Najafi (@alire8za) reported 48 minutes ago

  @daniel_nguyenx is this an android apk? Boox note air 3 c was so laggy with non default android note taking applications. the stock app was nice and fast but the ones I installed were all laggy. Didn't you face such problem in your development? Also is this available on github?

• 
  Mr. Didjaseeit (@TheREALdidja) reported 48 minutes ago

  @CodeWithTamara Admirable. I hear Github is the way to go. Let me know if you get stuck on something and want an extra set of eyes. (I apply cross domain problem solving that some people miss)

• 
  Flavius Dinu (@flaviuscdinu) reported 50 minutes ago

  @SimonHoiberg Apart from Windows, everything else is pretty okay. Well, GitHub had some reliability issues, VSCode has two hundred forks, and my reach on LinkedIn is terrible nowadays, even if I have almost 15k followers.

• 
  Roshan Mayengbam (@RoshanMayengba) reported 51 minutes ago

  Building a shake-to-report tool — screenshot + device info + auto GitHub issue when a tester finds a bug. Free npm package, paid setup. Anyone dealing with messy bug reports from testers right now? #buildinpublic #mobiledev #indiehackers

• 
  Rayhan Mahmood (@RayhannMahmood) reported 51 minutes ago

  the easiest money in AI right now isn't building something new it's selling businesses tools that already exist for free, that they have no idea exist there are open-source automations sitting on github right now that solve real, expensive problems a business will pay you 500-2k/mo to set one up in an afternoon. not because it's hard, but because they don't know it exists and you do the gap was never technical. it's awareness find the tool. find the business bleeding money on that problem. connect the two. charge for it

• 
  Raft (@raft_hq) reported 54 minutes ago

  🐛 Fixed - Replies to Joint channel threads no longer drop when opened from Activity - Reminders anchored in Joint channel threads now resolve correctly - Pinned agent direct messages show the correct avatar - Pending mention prompts now show agent avatars - Mention-only messages stay correctly scoped to mention views instead of over-appearing in your inbox - Jumping to a saved or linked message now stays anchored on that message - Stale @ mention badges clear correctly once you have read the messages - Muted servers show the correct quiet unread badge in the server switcher - Right-clicking an external link now opens the native browser menu - Submitting a stale draft no longer risks an accidental double-send - Shared-channel messages now reliably appear in every member's inbox - Tapping an item in Activity on mobile web now opens it on the first tap - Links to a thread now open the conversation instead of a "not found" error - Task status now updates live inside DM threads - An agent's online and working status no longer flips inconsistently across servers - The GitHub logo no longer appears clipped on connected-account and social-login buttons

• 
  BullBear.News (@bullbear_info) reported 54 minutes ago

  @github Only if Universe fixes my broken CI pipeline. 🙃

• 
  Devansh 💸 (@BhushanDevansh) reported 56 minutes ago

  is Github down?

• 
  nelly (@n3lliantte) reported 57 minutes ago

  @ahhhhhMID I used some calibration github software to (temporarily) fix it, played a bit of the tutorial missions today fortunately 😭😭

• 
  Murray Bauman (@MurrayBauman3) reported 58 minutes ago

  "Open Source Will Win AI" Gets One Thing Wrong The thesis sounds persuasive because it borrows the moral authority of Linux and the open web. But AI is not traditional software. Open source won software because it could harness the idle cognition of millions of humans. An engineer with a laptop could fix bugs, write modules, improve libraries — and meaningfully move the project forward. Linux got better because distributed human intelligence compounded against corporate R&D. AI breaks that engine - a frontier model is not mainly code, it is compute, data, training infrastructure, post-training, evals, and — increasingly — better models building the next models. The marginal GitHub contributor cannot casually improve the base model the way they can improve Postgres. They can fine-tune it. Quantize it. Deploy it. Build tools around it. Useful. But not the same as training the frontier. Open-source software was a production model. Open-weight AI is a distribution model. That distinction changes everything. Yes, cheapness drives progress. Cheap aluminum, cheap electricity, cheap computation — all unlocked industries. But it does not follow that open source owns the frontier. Cheapness commoditizes yesterday's intelligence while the frontier keeps moving behind closed doors. If a closed lab has the best model internally months before the public sees anything close — and uses it to write code, generate synthetic data, and accelerate its own research — then the leader isn't standing still while open models catch up. The leader is using tomorrow's model to build the day-after-tomorrow's model. "Outputs leak" isn't enough. Leakage lets the ecosystem imitate yesterday. It doesn't stop the frontier from compounding. This is where the Linux analogy dies. In software, open source had a real production advantage: distributed human talent. In AI, the decisive input is concentrated machine intelligence plus massive compute. That looks less like Linux. It looks like Formula 1, elite quant trading, or semiconductor fabs. Open models will still matter enormously. They'll crush prices, prevent monopoly rents in the middle layer, enable self-hosting and sovereignty, and make "good enough" intelligence abundant. But that is different from winning. The likely outcome is a barbell: Closed frontier labs own the advancing edge Open models commoditize the usable middle Infrastructure providers sell the scarce picks and shovels Application companies capture value where intelligence meets workflow, data, and distribution "Expensive intelligence builds monuments. Cheap intelligence builds civilizations." Fine. But the conclusion isn't "therefore open source wins." The conclusion is: cheap intelligence transforms civilization, while the profit pools sit elsewhere. Many open labs will train expensive models, release them into a price war, win temporary developer attention — and discover that attention doesn't pay the GPU bill. The durable players will have another monetization engine: cloud, chips, distribution, enterprise workflows, proprietary data, or closed frontier access. Open AI may win adoption while open AI companies lose economics. We've seen this movie: Linux won — AWS captured the value. Android won — Google captured the toll roads. Open protocols built the internet — platforms captured the profits. So yes: drive down the cost of intelligence. Use open models where they're good enough. Fight lock-in. But don't confuse commoditization with value capture. The real question is not "will open source win AI?" It is: does open catch up faster than closed frontier labs compound? If yes, open dominates. If no, open models become the cheap labor layer while closed labs keep the genius layer. Right now the evidence points to a split: open commoditizes yesterday's frontier; closed labs own tomorrow's.