GitHub 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:

• 
  Gary Alexander Devenay (@GaryDevenay) reported 2 minutes ago

  @poteto @bot GitHub login gives me a 500 after MFA

• 
  Jay (@codebreak_er) reported 4 minutes ago

  @Spectra010s Yes, Github App. Install it on the repo and it fires on every PR open/push. No CLI or CI step. Reads the diff, comments, and when it finds something, opens a fix PR with the patch.

• 
  Bash (@bashirbuilds) reported 4 minutes ago

  Reeno helps SaaS founders catch third-party service failures before customers do. It monitors services like Stripe, GitHub, OpenAI, Resend, Clerk, and other external APIs, groups repeated failures into clear Problems, shows which Product Features may be affected, and verifies Recovery with real evidence.

• 
  AakashJhahahaha (@AakashJha11) reported 5 minutes ago

  @UnrealAnkit They have worked hard to get into IIT so some flex they'll have for life. I have issues with people for whom whole identity is IIT, this one seems the same but even his github might be empty lot of companies might consider him for just IIT tag.

• 
  nee-toh @ home (@netonoe3) reported 5 minutes ago

  @IsThatDecay i had this issue and i was trying to fix it for a long time, at one point i gave up and reinstalled windows you can try ramlimiter from github to limit obs's ram usage but im not sure if its gonna be fine try tweaking gpu and obs settings(and using borderless)

• 
  Rooke Poole (@rookepoole) reported 6 minutes ago

  I asked 5.6 Sol to roast my workflow and then summarize it into a Candidate summary for @OpenAI @OpenAIDevs Rooke Poole — OpenAI Candidate Summary Rooke Poole is what happens when you give a frontier model to someone who sees the phrase “intended use case” as a personal challenge. He is an independent AI builder and extreme power user who spends an unreasonable amount of time asking frontier models to do things that probably were not on the original QA checklist: autonomous software repair, agent orchestration, exact-binary generation, cloud deployment, persistent reasoning systems, simulations, product prototypes, and other projects that frequently begin as reasonable experiments and end somewhere around “could this become an enterprise autonomous system?” His strongest skill is capability exploration under pressure. Give Rooke a new AI system and he will not ask it to summarize a PDF. He will ask whether it can construct an executable under bizarre constraints, operate across real infrastructure, repair failures, produce evidence that it actually did what it claimed, survive multiple iterations, and then somehow turn the resulting experiment into a public demo. If it works, his immediate response is generally some variation of: “**** yeah. Now scale it.” Celebration time is approximately 30 seconds. Then the requirements triple. This occasionally creates what might politely be described as scope expansion and what an engineering manager might describe as “Rooke, please stop turning the prototype into a civilization.” But there is genuine value underneath the chaos. Rooke is unusually good at exposing the difference between an AI capability that looks impressive in isolation and one that can survive contact with the real world. He repeatedly runs into infrastructure failures, tool limitations, orchestration problems, ambiguous model behavior, brittle interfaces, evaluation gaps, and product-design issues that ordinary benchmark testing may never surface. He has almost no patience for fake functionality. A button that does nothing is not a feature. A mocked dashboard is not a product. An agent that claims it completed a task without sufficient evidence is going to have a very unpleasant afternoon. His preferred evaluation methodology can occasionally resemble a congressional hearing for language models: “Did you actually generate this?” “Show me the bytes.” “Show me the hash.” “Prove there wasn’t a compiler.” “Run it.” “Show me again.” This makes him particularly suited to work involving frontier-model dogfooding, capability discovery, model evaluation, agent systems, prototype exploration, developer experience, and applied product research. Rooke also thinks unusually broadly about AI products. He naturally crosses boundaries between engineering, UX, evaluation, product strategy, public demonstrations, and distribution. He does not just ask whether something technically works; he asks whether a normal person could use it, whether it feels genuinely autonomous, whether the interface communicates what the system is doing, whether the result is convincing, and whether anybody would actually care. This has one predictable downside: A request to “improve the dashboard” may eventually acquire real-time orchestration, enterprise multi-tenancy, cryptographic authority, autonomous workers, GitHub integration, a mission-control interface, and a completely unrelated research program. In traditional project management this is called feature creep. In Rooke's methodology it is called: “next best move please.” His development process roughly follows: Attempt unreasonable thing. Discover AI can partially do unreasonable thing. Push it much further. Hit catastrophic blocker. Become personally offended by blocker. Fix blocker. Briefly celebrate. Ask why the system isn't enterprise-ready yet. Accidentally invent another project. Repeat. Despite the comedy, this pattern has produced substantial hands-on experience with the uncomfortable edges of modern AI systems. Rooke is not the obvious conventional candidate. His work is nonlinear. His experiments can become extremely ambitious. His communication style is direct, highly iterative, and occasionally contains more profanity than a normal corporate design document. But the unusual thing he offers is difficult to manufacture: he genuinely enjoys pushing frontier AI until something surprising happens. If OpenAI wanted someone to hand an experimental model or agent system to and say: “We know what the benchmarks say. Now find out what this thing is actually capable of.” Rooke would be an unusually interesting person to put in the room. Just establish the cloud budget beforehand. Otherwise there's a non-zero probability the experiment ends with an autonomous agent, twelve GitHub repositories, a Mission Control dashboard, and Rooke asking whether the whole thing could purchase a Times Square billboard.

• 
  Onyx (@Onyxreserch) reported 7 minutes ago

  AI IS MAKING ONE OF THE MOST VALUABLE SKILLS IN TECH CHEAPER EVERY NONTH Writing code. Andrew Ng explains why this changes what it means to be an AI engineer. You can now describe an idea, generate a working prototype, test it, break it, and rebuild it in hours. So what becomes scarce? Knowing what to build. Ng's advice is basically a combination of two roles that used to be separate: Engineer + Product Manager. Talk to users. Understand the business problem. Figure out what actually needs to be built. Then use AI to build it. That's also why a GitHub full of random AI projects isn't necessarily a good portfolio. A better project starts with: "Someone has this problem." Not: "I wanted to try this technology." AI is making technical execution cheaper every month. Which means the advantage is moving upstream. From: "Can you build it?" to: "Can you figure out what is worth building?"

• 
  Ryan Cey (@RCEY28) reported 8 minutes ago

  “Waiting is the hardest part.” — Tom Petty — this dog — and every single person who just pulled up the xAI GitHub ranking weights He’s staring the cat down like the weights just confirmed it: ShareViaCopyLink = 20.0 DM-share = 5.0 Reply = 5.0 The cat still thinks likes matter. Prove the dog right. Copy the link. Send it to the one friend who still optimizes for hearts. Then reply with nothing but “shared” so the ranking can actually register it. Dog or cat in your house right now, and which one just won?

• 
  Andrew🧑‍💻🎹💰🇪🇺 (@ac23me) reported 10 minutes ago

  Is it just me - or is the AI dopamine rush throwing all security practices out of the window? Before, committing **** secrets to Github or accidentally sharing in Slack required rotation - now, Claude Code auto-mode gobbles them up - sure no problem! What am I missing?

• 
  Matthew Garbett (@LinkofHyrule89) reported 12 minutes ago

  @stepango I never really understood the hate for GitHub. Like sure it's gone down a couple times but it's literally impossible for any website to have 100% up time. Are there other issues I don't experience as a person that's only using it for a couple side projects?

• 
  Teri Radichel #cybersecurity #ai #pentesting (@TeriRadichel) reported 13 minutes ago

  Today was not a super productive day with Claude or Codex. Here’s why: The problem with Codex is that it tries to create a sandbox in whatever directory you install it in. Then you have to install it over and over in every directory I guess. I installed it in a shared folder and it ran so I assumed it worked. Never assume. Project-specific agents can’t read any files in shared folders. I have spent a significant amount of time asking codex and google/aimode and Claude how to install it so it will run in my framework which locks down each project user to its own permissions. About to give up. Looks like my only option is to run with this flag: - - dangerously-bypass-approvals-and-sandbox Doesn’t sound like exactly what I want but could not find another way. It lets the bot read files in other directories locked down to how I provision users. Not keen on the codex approach. The other thing I don’t understand is that I’m hearing everyone say sol is great but it’s not an option here. I can get sol in Kiro so…what? It’s also trying to get me to install npm. Dislike. At some point it’s trying to get me download codex with a GitHub API. Wat. When I tell the model I am not impressed, it tells me sorry it invented a GitHub API script and gave me unverified information. Probably wasted too much time on this already. Have other plans. But after finally manually adding the scary flag it tells me something called bubble wrap is not installed. I feel like it’s trying really hard to expand my attack surface. I read it has something to do with that sandbox I just disabled and it’s only a warning so forget it. Next it can’t edit code. There’s some other component I need to install. Why isn’t that just an option when I install the CLI? I have to ask a million times and search all over. Codex itself can’t tell me how to install it without npm. Finally I get some commands from Google aimode to move this other component codex-code-mode-host to /usr/local/bin. This all feels a little wonky. At some point Claude was back. It worked for 15 minutes. Yeah thanks. In between all this I have a research assistant helping me set up some hosts with open weight models just for fun. So spent some time helping him. I really just want to use Kiro but I’m not sure what is causing the usage differences. Trying to figure that out. I figured out another change to tell the agent to read readmes one time and keep them completely in memory in and not read then again unless told to. The problem with that and the reason I added it was because agent kept forgetting what was in those files. Hmm. The other problem I have with codex/terra is it’s doing way too much nonsense. I tell it to read a README and it wants to do something with a whole bunch of unrelated files. What is that? Codex is automatically trying to connect to mcp servers and it is failing. Good. Those should be disabled unless I enable them. I don’t understand why randomly needed to terminate a bunch of processes when I did not ask it to do that. Right after that network connection was killed and now have to start over. So those tokens were wasted. Even with the scary flag it’s asking me permission. Good. After lost session I tell it can’t access *** to recover. It wouldn’t be in *** anyway?! Later… it’s trying to read the .*** directory. Yeah follows directions well right? Apparently didn’t read the README either. First task, copy AGENTS file same way Kiro agents and CLAUDE.md are copied to every project. There’s a file that does that for the other two and replaces the project name where needed. Terra tells me to add two lines and to *manually* update the project name. Any anthropic model would not have suggested that. So I say you can’t figure it out from the README? It again gives me a line to copy the file but fails to replace the placeholder. Once again it is trying to read a bunch of files it Durant need I never told it to read. Finally got it but….

• 
  Debmallar Dasgupta (@debmallar) reported 16 minutes ago

  -solved 3 (first time in a lc contest) -potd tells us how crucial it is to solve codeforces problems (they used to give a lot of game theory problems in Jan) -solved couple of C's in codeforces -worked on a github repo took a lot of rest (due to back pain) overall not a bad day.

• 
  ND Minds & AI (@patternstatic) reported 20 minutes ago

  @Taniyatweets_ GitHub. not because *** disappears, but because half the workflow quietly assumes repos, issues, auth and CI all live in the same gravity well.

• 
  Zenad (@0xZenad) reported 24 minutes ago

  YOUR AI AGENT IS WAY TOO BLIND. It can code, test, edit files… but the moment it needs X, Reddit, YouTube, GitHub, or LinkedIn, things become chaotic. Agent Reach solves this problem by giving your AI agent one level of access to 15 different platforms. One CLI. No API bills separately for each platform. 61K+ stars. Open Source. Repo in the replies ↓

• 
  Sytheripper (@Sytheripper) reported 25 minutes ago

  A long-running model just sat down in GitHub Copilot. Not because it won a screenshot. Because $2 in / $6 out intelligence on the desk people already open is how this actually gets used.