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 (58%)
• Errors (32%)
• Sign in (11%)

Live Outage Map

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

City	Problem Type	Report Time
Haarlem	Sign in	2 days ago
Villemomble	Website Down	2 days ago
Bordeaux	Website Down	6 days ago
Ingolstadt	Errors	10 days ago
Paris	Website Down	11 days ago
Berlin	Website Down	12 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:

• 
  Rachel Blum (@groby) reported 8 seconds ago

  @hkarthik @satyanadella You mean after he fixed Windows? And their office apps? Snark aside, I don't think Github is a "Satya" shaped problem per se - the culture that leads to these things is, though. Except... it smells like the culture reverted to pre-Satya norms.

• 
  Muzaffar (@iammuzaffar640) reported 4 minutes ago

  at some point we just stopped opening Jira bugs were already GitHub issues. Claude Code was already fixing them from there. adding a middle layer stopped making sense. now it's just: issue → Claude Code → review → merge didn't plan it. just happened. anyone else quietly moving away from dedicated project management tools?

• 
  caraline (@naviiconnect) reported 8 minutes ago

  @itsmiamouse he can try launching the riot client though deceive, just download it from github and follow the instructions, most people use it to appear offline but ive seen it fix similar problems for some people

• 
  Folding_Napkins (@FoldingNapkins) reported 11 minutes ago

  @valhalla_dev People have rocked their own VC before - and CI/CD too, Github going down would be a pain in my arse but it'd be far from the end of open source.

• 
  Scott Breitenother (@s_breitenother) reported 14 minutes ago

  Three things happened in coding tools this week: SpaceX optioned Cursor. GitHub paused Copilot signups and pulled Opus from the $20 Pro tier. Anthropic ran a test that moved Claude Code behind a $100 paywall (briefly, before reversing.) Different companies, same week, same problem. Inference costs caught up with flat-rate plans and every tool that owns or resells a model is now figuring out who absorbs the math. We made the call early at Kilo to never own a model and never resell inference at a markup. Boring on purpose.

• 
  InnoScout (@innoscoutpro) reported 16 minutes ago

  The Bitwarden CLI backdoor (2026.4.0) isn't a Bitwarden story. It's a GitHub Actions story. 3rd campaign in months using the same vector. Same C2. Same technique. bw1.js was injected into the legitimate binary — it looks real because it mostly is. The structural fix requires GitHub to change the defaults. No single受害 org can do it alone. Thread on what this means for the supply chain security model 👇

• 
  Zohaib Khurshid (@Zohaib699) reported 17 minutes ago

  Just installed Exa and told Claude to fix a nasty bug I’ve been fighting for 2 days. Bro didn’t just give me some generic answer it went out, searched actual GitHub issues, latest docs, StackOverflow threads, and pulled the exact library version that broke everything. Fixed it in one shot. This ain’t “AI helper” anymore. This is a whole *** senior engineer sitting next to me with perfect memory and real-time internet. Exa just made Claude dangerous. If you write code for a living, stop what you’re doing and go install this right now. Who else is using it? Drop your craziest result below 👇

• 
  am.will (@LLMJunky) reported 20 minutes ago

  @elvissun @Teknium @NousResearch Is this a stability issue? Because it sure doesn't sound like one. I'm not going to lie man this feels awfully dramatic. You know what I do when I'm having an issue? I create an issue on GitHub or I just reach out to Tek lol. Doing a very public post on X is not the format for this in my opinion Especially when you are calling their trust into question is a very accusatory statement

• 
  Gman (@gmaniac) reported 22 minutes ago

  @satyanadella maybe you can put it to work and fix deploying to @Azure from @github 🧠

• 
  sushen (@sushentalwar) reported 23 minutes ago

  i have been vibe coding for the last two months, mostly random stuff or my online portfolio (resume) website. But I have come to a dead stop with @github because i am doing something wrong and i just dont know what and the support team has not resolved/responded so far. As someone who has never coded, this is a hard experience. I have an idea of why my github profile got flagged (likely because im vibe coding and pushing entire index copy-paste from claude code to my repo?) anyways hoping this can be resolved soon. Looking to learn here how to be better so any feedback would be great! To avoid running into the same issues in the future. @github - i cannot connect github to vercel - updated commits arent showing on vercel either. - the live website isnt being udpated either.

• 
  David Boskovic (@dboskovic) reported 24 minutes ago

  @_dylanga You were actually the only one who had any issues. It was actually your fault if you really think about hard enough. Calm down. Give GitHub a break. Staying up for the agentic workload is hard. Microsoft doesn’t even have the cpus for all that merging.

• 
  Moon Dev (@MoonDevOnYT) reported 27 minutes ago

  The Mac Mini Alpha Stack: How To Build An AI Swarm That Automates Binance Chain Dominance most people think a day in the life of an ai algo trader involves fancy penthouse offices and dozens of flashing monitors but the reality is much more interesting and a lot more automated. while you are sleeping my digital army is busy scanning the hyperliquid data layer for short liquidations and funding rate skew. there is one specific reason why most retail traders will never win and it has nothing to do with their intuition or their charts my name is moon dev and i believe that code is the great equalizer because i had to learn it the hard way. i spent years as a victim of my own emotions losing money through liquidations and over trading because i thought i could outsmart the market by hand. in the past i spent hundreds of thousands of dollars on developers for different apps because i was convinced i would not be able to code myself that mistake cost me a fortune but it also forced me to finally take control of my own destiny. being held back in the seventh grade taught me that people will count you out early but iteration is the only real path to success. i decided to learn to code live on youtube to show the world that if a regular guy like me can automate his systems then anyone can do it the secret reason retail traders fail is that they are looking at lagging indicators while the big institutions are looking at real time order flow and liquidation clusters. my systems are designed to close this gap by monitoring every single whale position on hyperliquid as it happens. when you can see where the big money is trapped you no longer have to guess which way the candle will move next i have moved away from expensive cloud servers and started using a stack of mac minis for my automation. these small boxes provide more reliable uptime and better performance for the specific way my bots interact with the exchange. there is a technical advantage to running your own hardware that most people completely miss when they are trying to scale their systems this mac mini setup allows me to run dozens of agents simultaneously without worrying about the latency or the cost of virtual machines. i choose the base model silicon for these tasks because they handle sustained compute loads without the thermal throttling that plagues most laptops. this is the foundation of a digital server farm that generates its own alpha while i am at the beach building bots for the $hype token is my current obsession because the hyperliquid ecosystem is rebuilding the financial system from the ground up. unlike traditional exchanges they provide an open data layer that lets us see liquidations and smart money flows in real time. i use claude code to iterate through these complex strategies which allows me to ship new features in minutes rather than days the build process starts with a simple research hypothesis that we then backtest against eighteen months of one second liquidation data. if the math does not hold up in the past then we do not give the strategy a single dollar in the future. most traders spend their time searching for a magic indicator but we spend our time building robust data pipelines that filter out the noise one of the biggest loops we are closing is the issue of account growth through my funded trader program. we are building a stream team of traders who are all using the same core software to scale our collective impact on the market. this program gives regular people the capital they need to execute quantitative strategies without the constant fear of losing their own personal savings the bottleneck for most traders is not their strategy but their lack of capital and their inability to stick to a plan when things get volatile. by providing the funds and the software we are creating a feedback loop where every win and loss helps us refine the master codebase. this is how we scale from individual bots to a global swarm of agents that work together as a single unit the technical side of the $hype bot involves monitoring the funding rate skew to see when the market is overextended in one direction. when the shorts are paying the longs an insane amount to keep their positions open it is a clear signal that a squeeze is imminent. our bots are programmed to wait for these specific imbalances and enter when the probability of a reversal is at its highest i used to think that i needed a computer science degree to understand this level of technical analysis but ai has changed the game for everyone. now i can describe the logic of a momentum strategy to an agent and see the python implementation instantly. this removes the barrier to entry and allows us to focus on the high level vision of attacking wall street with code that specific line of logic i mentioned earlier is about filtering for large buyers on the hyperliquid data layer. we only enter a trade when we see at least five thousand dollars of actual buying pressure within a thirty second window. this confirms that we are not just caught in a random wick but are following actual smart money into a new trend code is the great equalizer because it does not care about your background or your education level. it only cares about the logic you provide and your willingness to iterate through the failures until you reach the goal. i am fully automated now because i realized that my own brain was the biggest liability in my trading journey by removing the human element i have finally found the peace of mind that escaped me for years while i was getting liquidated. every day we are pushing new code to github and showing the world that the era of manual trading is coming to an end. let us keep moving and stepping on the gas until every member of the squad has their own digital army trading for them

• 
  Mauricio Reatto Duarte (@mauriciord) reported 28 minutes ago

  If you are a tech lead managing more than two repos, you know this feeling: twelve GitHub tabs open and still no clear read on what your team shipped yesterday. I built Team Deck to fix that. Every repo. Every PR. One screen. 60-second refresh. 🧵

• 
  Sam Meyer (@sam_wise_) reported 33 minutes ago

  @satyanadella Stronger multistep execution" compounds error rates exponentially across the chain. When step 7 of 12 hallucinates in a GitHub Copilot session, what's the rollback mechanism that preserves context without forcing the user to restart?

• 
  Got Eem (@HaGoshem) reported 35 minutes ago

  @Longsword44 i also want to mention that this **** breaks constantly but the devs fix it like immediately. broke sometime this morning but the devs fixed it 3 hours ago on github

• 
  Román Noodle (@Chunglee1000) reported 36 minutes ago

  Is it me or is #VsCODE having issues with #Github #Copilot extension where planning and agent modes are stuck causing the LLM models keep thinking they are in plan mode while on the Agent mode? Im on latest 1.117 version of Code.

• 
  Vinod Kone (@vinodkone) reported 40 minutes ago

  @ClaudeDevs Claude auto-fix-pr keeps complaining about Claude GitHub app not installed even though it's installed. Same issue when doing coroutines. Is there a bug?

• 
  Tom Curonian (@curonianai) reported 40 minutes ago

  @ycombinator @getopenwork OpenWork deserves the attention. An open-source Claude Cowork alternative already at roughly 14,000 GitHub stars has cleared the “people want this” test. The missed point is what happens after rollout. the first win is always access. The second problem is always state. One team uses an agent for support, another for sales ops, another for search. The launch looks clean because each workflow works alone. The failure arrives when outputs cross boundaries with no durable contract, no audit trail, and no scoped recovery. That is the difference between adoption software and production software. Adoption gets agents installed, Production keeps them trustworthy after handoffs start.

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 43 minutes ago

  There's a free open-source model that copies Anthropic's biggest secret. It is called OpenMythos. A guy named Kai Gomez built it from scratch on GitHub. Big AI models cost a fortune because they are massive. This new model is different. It loops its own brain to think deeper about hard problems. You get smarter answers without paying for a giant data center. This means you can run powerful AI right on your own machine. Your data stays private. Your API bills drop to zero. You can finally automate your emails and support tickets for free. If you want the exact steps to set this up for your business, join the AI Profit Boardroom.

• 
  Ryan Bright (@rbright) reported 44 minutes ago

  I guess yesterday's GitHub outage was worse than I even realized.

• 
  INv1ctUS (@INv1ctUS_HAcKeR) reported 45 minutes ago

  @alpernae @nmatt0 your github link not working , please help me with the link , thanks.

• 
  Flipcoin (@Flipcoin_fun) reported 48 minutes ago

  @Gumisirizasaad SWE-Bench Pro uses real GitHub issues. hardest to game.

• 
  Dr. Luke in China (@96Stats) reported 48 minutes ago

  Just went through their paper - REALLY smart. They might have less money to use compared to US rivals but their innovation is way better. What did they do? Well, normal AI gets expensive when your messages get long especially if you use PDFs or github codebases, because the model has to search through a hugeeee memory database every time it generates a new word. So either it becomes slow or it just doesn't read alll of what you sent. Now, check this figure out in DeepSeek's paper. Their new trick is to compress older text into smaller memory blocks, then use a lightweight “Lightning Indexer” to find only the most relevant blocks. So instead of looking at everything, it focuses on what matters. It also keeps recent text uncompressed, so it still remembers nearby details clearly. Because its all opensource/openweighted now, ChatGPT and Claude will 100% be using this too as they solved a huge problem.

• 
  Trevin Chow (@trevin) reported 48 minutes ago

  @reebz @mdlahfir @kieranklaassen I think github projects, issues, beads, linear... so many options for this. This is why we want to stay out of todo/task tracking etc.

• 
  Matt Helm (@matthelm) reported 49 minutes ago

  @noahzweben Fantastic! I tried it out with Issue opened, creating a new GitHub Issue on the repo, but it didn't trigger the routine. trig_01MNuMWeDvQLTw3arNHoSysT

• 
  anonymous (@AmMrAnonymous) reported 50 minutes ago

  Deslint works where AI-generated frontend code happens: MCP server for agent workflows CLI for terminal + CI checks ESLint plugin / GitHub Action for merge gates Local-first. Deterministic. No LLM in the hot path.

• 
  Simon J.K. Pedersen (@simped) reported 55 minutes ago

  @GergelyOrosz Github is on a slow decline to irrelevancy, like most of Microsofts portfolio, something must change.

• 
  Diana Gray (@DianaGraym) reported 56 minutes ago

  gitHub ghosts haunt the dark alleys of forgotten code, where stars are few and errors reign

• 
  Fork512Hz (@Fork512H) reported 58 minutes ago

  @Arka161 @izakazuma Sakura no Toki has set a great example for this translation paradigm: an initial GPT-4 MTL patch uploaded to Github, then readers post issues to make corrections, fixes released every few weeks. It serves as the only version before a proper fan TL patch came out after 1 year.

• 
  AI slop cleaner (@sehz_ai) reported 58 minutes ago

  @swapnakpanda Before AI: Curse when AWS or github is down After AI: Anthropic is down or hitting token usage