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 (26%)
• Sign in (16%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Errors	3 days ago
Madrid	Errors	3 days ago
Bogotá	Errors	3 days ago
Paris	Errors	3 days ago
Lyon	Website Down	3 days ago
Lima	Errors	3 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:

• 
  Clar3nce_CS (@Clar3nce_CS) reported 12 minutes ago

  @torisetxd @KAROLA48256858 @github At that point the fault is entirely your own for choosing to play hong Kong servers with insane ping 🤷 That wouldn't be a problem created by the fog of war stuff in any fashion

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  Radek Józefowicz (@rjozefowicz) reported 13 minutes ago

  @Nishanttt05 it is unfortunately very true opinion. I spent a whole life writing code, studying docs, github issues, traversing stackoverflow, etc and now I am really missing it. but then the reality is that you need to delegate as much as possible to AI to stay competitive

• 
  Tomer Stern (@tomer_stern) reported 13 minutes ago

  @Isaac_Tea @LinkofSunshine Yea write some code showing off your abilities in analogous, dumbed down scenarios to what you deal with at work, and put it on GitHub

• 
  AgiBy2030 (@AsiBy2030) reported 14 minutes ago

  @gdb Cool. GitHub plugin fix wen. It doesn't work

• 
  Scott (@scottjla) reported 16 minutes ago

  @mikeveerman @dannolan Yeah, you definitely need some ongoing management like this. I have github issues working well for agents, but occasionally they have some stale stuff tagged, basically meaning everything is blocked, so having it review stuff reguarly is good.

• 
  Mac (@mac_eth) reported 17 minutes ago

  I want my agents to do a bunch of complicated things in parallel, what's the best way to make that happen? Hermes? Openclaw? Something else? Imagine like working on 10+ github issues in parallel. Getting them all the way through to tested features ready to ship to ****.

• 
  reza ramadhan (@rejaramadhan98) reported 18 minutes ago

  debugged for an hour today because a dependency silently changed its default in a patch update AI assistant suggested 3 confidently wrong fixes found the real answer in a github issue from 2023 with 2 upvotes this job is not getting automated anytime soon

• 
  LetsGo (@askperp) reported 19 minutes ago

  @sidahuj @github Just talked me into locking all my accounts down

• 
  Dominik Koch (@dominikkoch) reported 19 minutes ago

  Either t3connect is only for certain members or its broken on stable as well tested with google/github. Error only happens when you log in twice first login attempt does nothing second errors before this. cc: @jullerino @theo

• 
  Tal Ohana 👨‍💻 (@talohanax) reported 20 minutes ago

  @mattpocockuk @saidelike Same for me, also when trying to use this link (signing-in with Discord/GitHub also broken for me)

• 
  Artem Zakharchenko (@kettanaito) reported 20 minutes ago

  If you want to contribute to open source, the absolute worst thing you can do is mindlessly point your agent at a repo and ask it to find issues. The issues it finds will look plausible to you but will be beside the point in actuality. If you report them, they will likely be closed. There's a high chance you'll make a bit of a fool of yourself in the process. Just don't do this. This is not a meaningful contribution. If you want to contribute to open source, see issues that need help. See issues where the maintainers have outlined the fix and need extra hands to make it happen. See issues where *you* can contribute with your expertise. Report bugs *you* yourself have experienced. See already reported and closed issues. Read the source code and learn from it. Don't rob yourself of one of the best ways to improve and actually stand out. A green square on GitHub means nothing, nobody cares about that vanity masquerade. Open source is built on the shoulders of people who care. Contribute by becoming one of those people.

• 
  Eric (@transurfer) reported 20 minutes ago

  Ever seen a tool that actually gets better fast? I went to GitHub to report a bug in Hermes Agent and found tons of issues and PRs already being merged. Looking forward to what's next.

• 
  elyndra (@n3hkeg) reported 22 minutes ago

  "Don't use @SimpleXChat . @SimpleXChat refused to fix the vulnerability I publicly reported, falsely claiming it wasn't a vulnerability, and even blocked me on GitHub."

• 
  Synapse Brief (@Synapse_Brief) reported 25 minutes ago

  Most AI coding tools give you one shot: prompt, response, hope it's right. OpenChamber treats every agent turn as a node you can fork from, which sounds like a small UI choice until you realize what it actually kills — the anxiety of "do I let this keep going or stop and restart." You don't restart anymore. You fork from the turn before things went sideways, try a different model or prompt, and the original branch just sits there intact if you need it later. Undo and redo work the same way, per turn, not per session. Where it gets more interesting is multi-run. Write one prompt, pick up to five models, and if you turn on isolation, each one gets its own *** worktree — a separate checkout of the repo, same starting state, zero chance of one model's changes stepping on another's. You watch all five actually build the thing, then either pick the strongest result outright or use Fusion to merge the best pieces from each into a new session. That's a genuinely different workflow than what most people are doing right now, which is running one model, eyeballing the diff, and hoping. Five isolated attempts at the same problem, compared side by side in worktrees that never touch each other, is a real answer to model selection anxiety instead of just picking a favorite and living with it. The GitHub integration closes the loop on the other end. Start a session straight from an issue or a PR with the context already attached, send failed CI checks or review comments back to the agent without leaving the app, then merge from inside OpenChamber when it's done. Issue to shipped PR without a single tab switch. Worth being clear about what this sits on top of: OpenChamber doesn't run any inference itself. It's a desktop, browser, and VS Code interface wrapping OpenCode, the open-source agent runtime that actually executes the model calls and tool use underneath. OpenChamber's entire value is the layer it built around that — versioned branching, worktree isolation, GitHub-native session starts — the stuff a raw agent runtime doesn't give you on its own. Five parallel model runs, each in a clean isolated worktree, compared and fused into one result. That's the part worth sitting with if you're still treating every agent session as a single roll of the dice.

• 
  Chanchal (@chanchalvdev) reported 25 minutes ago

  3. Devin ran a C2 binary after a poisoned GitHub Issue gave it hidden instructions. It even granted itself execute permission when blocked. No zero-day needed — just one crafted issue.

• 
  καςhι (@CcAkachi) reported 25 minutes ago

  The shared github-readme-stats instance got paused, so my profile stats has been broken for a while now. Fixed it by forking + self-hosting my own instance on Vercel instead of depending on someone else's infra. One less thing that can silently die on me.

• 
  Philip M | wishlist 🎲 Die Severed! (@captain567) reported 29 minutes ago

  @DMeville Honestly I kind of just miss the old issues and projects in GitHub. Projects v2 is completely unappealing. I happen to also be considering self-hosting a code forge to get away from GitHub and Gitea and Forgejo both seem to have task management closer to what Github used to be

• 
  CEOInterviews.AI (@CEOinterview) reported 40 minutes ago

  Replit stopped paying a seven figure software vendor because an app its own team vibe coded worked better. Amjad Masad cannot remember which vendor, because it keeps happening. "I actually don't know that exact one because it's happening all the time." "We used to use like three or four different analytics products. And Replit is really good at analytics." "I actually just got a Slack message from an engineer, like, hey, I built a new *** hosting service, and he showed me a demo." "And it's because GitHub is down a lot these days and I feel bad for them. It's not their fault. It's like the amount of agents that are committing to GitHub is kind of insane." "Every week I see a new invention at Replit. Some of it could be productized, others could be used as an internal tool. We replace a contract that we're using."

• 
  Arpit (@_xonoxc) reported 41 minutes ago

  @Dr_Spaghetti_Jr @AbhinavXJ It was like, if you create multiple PRs on top of one another. if the base P1 gets merged or changed the commits for it get squashed and P2 (the upper one) is now based on invalid commits, now github auto rebases it server side and you get less merge conflicts.

• 
  Camina Drummer BIP-110 (@CaminaDrummer4) reported 41 minutes ago

  @publord It’s been a year, 6 months of us trying to argue technical issues and being censored from Reddit, GitHub, mailing list etc with gaslighting insults and “trust the experts” being the only argument. Now you play the victim? Don’t be a lying hypocrite. Grow some ******* *****.

• 
  RichC: joking through the stupidpocalypse (@RCownie) reported 41 minutes ago

  @real_poobah @buccocapital Software development these days involves discussions on Slack, meetings on Zoom or Google Meet, testing and production in the cloud, repos on Github, and a laptop. "Coming to the office" is an irrelevant ceremony that slows down work. Why do it at all ?

• 
  Lukáš Hozda (@LukasHozda) reported 42 minutes ago

  I almost got incredibly angry at a diff on github because it seemed like it does only one third of what the commit said, but I viewed the diff locally just in case, et voilá, Github does not display the diff the correctly. For ****'s sake fix that platform

• 
  Mukul Malik (@lazyynocturnal) reported 46 minutes ago

  Another use case: - Ask to sol first to identify the top 25 frontend bugs/issues that are easy for an agent to test end-to-end, then log them as GitHub issues with all needed context. - Review them with fable to catch any edge context missed. - Then ask your chief of thread to split the work into a few parallel threads so they can work accordingly.

• 
  PLV (@peterluisvenero) reported 48 minutes ago

  @TechByTaraa I used OpenClaw as the runtime and put an operating system on top of it. The result is a living, multi-agent operating environment with defined roles, memory, rituals, governance, and production workflows. The three most remarkable things so far: 1. The agents operate as a coordinated organization… not just isolated chatbots. They have domains, mailboxes, delegated authority, execution briefs, and evidence-based handoffs. 2. GitHub functions as a bridge between product thinking and production. We can design a change, assign it to the appropriate agent, deploy it to the runtime, and receive implementation evidence back through the same governed loop. 3. The system is becoming self-observing. cybernetic loops evolve into an immune and nervous system that detects drift, conflicting authority, stalled workflows, and loss of coherence before they become larger failures. The three areas that still need the most work: 1. Orchestration needs refinement. OpenClaw crons add up and cause bloat, so I had the agent build something more scalable. 2. Execution reliability needs hardening. Recurring timeouts eat up productivity. Might be an LLM issue. 3. Communication pathways need simplification. Agents still encounter legacy queues, manifests, and handoff channels. What amazes me most is that this is no longer simply an AI assistant. It is beginning to behave like an institution with memory, accountability, specialized intelligence, operational continuity, and the capacity to improve itself. Most people who struggled with OpenClaw treated it like a genie in a bottle. We treated it like a chip and built the macOS of business on top of it.

• 
  Alexey Fateev (@superalesha) reported 48 minutes ago

  @xhinker I don’t understand what the problem is. The full launch instructions are on GitHub.

• 
  Sebastian Buzdugan (@sebuzdugan) reported 49 minutes ago

  @r_marked @theo github notification filters scale better than asking maintainers to slow the merge queue

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 51 minutes ago

  Alibaba's Qwen 3.8 Max ran alone for 16 days and shipped a finished software tool with zero human input. The receipts are public on GitHub: 265 commits. 127 pull requests. 151 issues closed. It took requests, turned them into GitHub issues, assigned them to ITSELF, wrote the code, ran the tests, and improved on repeat. That's not a demo. That's a full software project, start to finish. Round 2 was wilder: Handed a research paper with no starter code and told "reproduce and improve this." 5 days later: 7,600 lines of tested code and 33 GPU training jobs. Unassisted. The jump from the last version: → DeepSWE: 21.6 → 56.6 → Frontier SWE: 40.7 → 73.5 Honest note: those are Alibaba's own numbers. Independent tests are coming. And the biggest news: the open weights drop next week. First Max-class Qwen ever to open up. Self-host it. Fine-tune it on your data. Your costs and privacy change completely. The race stopped being "who writes the best email." It's "who can do a week of work alone." Want the SOP? DM me. 💬

• 
  snowy_smile (@snowy_smile_) reported 54 minutes ago

  Since May I've been in a build-and-share spiral. Started slow, got consistent in June, and by July things had gotten a little out of hand — too many projects, too many experiments, open-sourcing whatever seemed useful, sending PRs whenever I found something worth fixing. Since June 1st alone I've somehow created around 80 repos. I even made a fresh GitHub account for all of this — a completely anonymous alt. No real name, no résumé, just code and an increasingly suspicious amount of green. It's now sitting at 1,681 contributions, 85 merged PRs across 37 external projects, plus a mildly unreasonable pile of my own stuff. And somehow this random anonymous account has brought in a few surprisingly nice offers and invitations. Apparently "mysterious person on GitHub who keeps building things" is a viable professional identity now 😳 The root of this goes back to something that's been nagging me since 2023: AI itself never really scared me. What scared me was people using AI to do bad things. It felt obvious the real fault line wasn't going to be "humans vs. AI," it was going to be people who know how to think, build, judge, and collaborate with these tools vs. people who don't — and I'd rather be on the side that's harder to weaponize against. So I figured I'd rather learn how to use them properly. And open source has actually been interesting ground for that, in kind of an ironic way — a lot of repos and maintainers explicitly reject AI-assisted contributions. Which means, for now, there's still a place where doing it the old-fashioned way — the tests, the review, the "explain this in your own words" — actually counts for something. But I don't think that holds much longer. Less a permanent human edge, more a countdown. A few years ago, Go AIs became teachers for human players. Coding agents have felt a little like that to me for a while now, not just recently — they help me learn, but they also make me think harder about what my part of the job should be. There's a part of me that still misses being the guy who was just good at algorithms — greedy strategies, graph theory, the kind of problem where you stare at it for a few minutes and then the trick clicks. That used to be my thing. Now the realistic move isn't to keep being that guy — it's to become one of the people who's actually good at using AI. So for now: keep learning, building, trying to make whatever might be useful — especially while I still have a few human-only features AI hasn't deprecated yet 🥹

• 
  Captain Random (@RealRandomTask) reported 55 minutes ago

  Absolute waste of an entire afternoon. Tried to integrate Meta/Instagram login for a new SaaS. It is an absolute psychological torture. Nothing is where it's supposed to be, the UI is a maze, and after filling out an hour of unnecessary fields, it locked me out with a "verify your business". My FB account is blocked from advertising (why is this even needed FOR JUST A LOGIN FUNCTION) and I’ve literally never even run an ad in my life. If you're building a modern app, skip the bureaucratic nightmare and stick to Google, GitHub, Discord, and just plain old email. Save yourself the headache. @Meta

• 
  Daniel Golden (@DanGolden1) reported 1 hour ago

  Just had a revelation on doing web dev with many agents. Instead of having each agent in a tab in terminal I... 1. Document the bugs and enhancements in github issues. 2. Tell hermes to go fix each of the open issues 3. Hermes spins up it's own subagents to fix all in parallel