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 (57%)
• Errors (30%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Inverness	Website Down	6 days ago
Quito	Sign in	7 days ago
Junín	Errors	7 days ago
Guadalajara	Errors	7 days ago
Paris	Website Down	7 days ago
Quito	Errors	7 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:

• 
  App Launcher (@AppLauncher_App) reported 8 minutes ago

  @OpenAgentsInc Stacked PRs in four hours is wild. The fact that GitHub still doesn't have native support for this says a lot about how slow big platforms move on dev workflow pain points.

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  Jason A Yakubu (@jason_yakubu) reported 11 minutes ago

  @danellisona I am still working on a hackathon project that allows you to test your website for common production failures and fixes it automatically as a PR to your GitHub. Also a live monitor that monitors your website for user errors and fix it.

• 
  Leigh (@___leigh___) reported 12 minutes ago

  The chatgpt desktop app has been completely unusable on many macs for a week following the GitHub issues and my own experience. @thsottiaux any ideas what’s happening?

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  Marius Laurusevicius (@MLaurusevicius) reported 13 minutes ago

  The Astra proofs are in Lean 4 on GitHub under Apache 2.0, and the repository reports zero unproven steps. None of the ten results has been through peer review. Machine-checkable is not checked. Someone still has to confirm the formal statements match the problems.

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  Beer van der Drift (@BeerDrift) reported 19 minutes ago

  Messed up side effect from all the GH outages; when I work on any GitHub Action, and it doesn't run I'm not sure if it's a bug in my code or just a outage on GH's side. Afraid I'm spending time on fixing problems that I can't fix.

• 
  Corey J. Gallon (@CoreyGallon) reported 21 minutes ago

  Your agent is untrusted software. That's the stance @rough__sea, CEO at Deno and creator of Node.js, takes in "Security Firewall for Agents", up on @aiDotEngineer's YouTube. It's a working account of how Deno lets agents fix production incidents without letting them drop the users table. - Agents can't police themselves. Opus is well aligned and refuses destructive commands over and over, but the SRE agents are wired into a support system, so they can be prompt injected from outside. Security can't be wishful thinking that the model obeys. - The real incident work is broad access. Deno gives OpenClaw read/write access to Postgres, Kubernetes, ClickHouse, AWS, GitHub and Slack, and it resolves incidents that used to need a human SRE. - Every action is bytes on the wire. Agents run on standalone VMs, so filesystem isolation is handled. What's left is network traffic, whether it comes through MCP or a subprocess. - HTTP-layer proxies stop short. Ryan walks through LLM gateways with guardrails, HTTP Jail, Brex's Crab Trap, Agent Vault, NVIDIA's OpenShell, and where each one leaves a gap once an agent spawns psql. - ACLs and read-only credentials aren't enough. Careful provisioning across many systems still leaves holes, because access to one system composes into access to another. - Claw Patrol is their answer. An MIT-licensed proxy that sits below HTTP, parses each byte of protocols like Postgres, injects credentials the agent never sees, and applies rules written in HCL. Deno's rule file is about a thousand lines, checked into ***. - Rules get unit tests. You supply fixture requests and assert they're always blocked, so the policy itself is verified rather than assumed. - Deny isn't the only verdict. A rule can route an action to a human in Slack, to an LLM judge, or to both in sequence. - The agent software is a black box. No plugins, no modifications to the agent. Claw Patrol runs as a Tailscale exit node (WireGuard works too), and Tailscale identity gates the dashboard where you watch what your agents are doing. - Smarter models shrink the problem, not the need. Ryan's view is you'll always want a backstop outside the model. I'm working through the published talks from AI Engineer World's Fair sharing summaries and takeaways. Follow for more!

• 
  Jansen (@jan53n) reported 21 minutes ago

  Is github *** server access getting slow for you?

• 
  Georgii (@0xGeorgii) reported 23 minutes ago

  GitHub runners are so expensive and slow. I decided to upgrade my build/dev server and ordered an @AOOSTAR145197 Mini PC with a Ryzen 9 PRO 8945HS (5.2GHz). Look forward to frying it as I do with all my hardware. Even the MacBook Pro with an M5 Pro fans like a helicopter almost all the time and is super hot. Endless builds and running test campaigns.

• 
  Sepi 🇮🇷 (@sepisoad) reported 24 minutes ago

  I’m thinking about buying a raspberry pi zero or something and use it as my *** server, I don’t want to put my stuff on github or anywhere

• 
  Kanika (@KanikaBK) reported 29 minutes ago

  🚨 THE ENTIRE LOOP ENGINEERING FRAMEWORK IS SITTING ON GITHUB RIGHT NOW AND MOST DEVELOPERS BUILDING WITH AGENTS HAVE NOT FOUND IT YET. This is the framework a senior Anthropic engineer documented in an 11-page PDF that changed how serious builders think about agentic systems and someone just made the entire thing installable in one command. The big missing insight isn’t a prompt trick or a model upgrade. It’s an architecture shift: stop prompting the agent build the system that prompts it. Five moves per cycle. ↳ Discovery: the agent finds its own work instead of waiting for you to hand it a list ↳ Handoff: each task gets an isolated worktree so parallel agents never step on each other ↳ Verification: a second agent told to assume everything is broken reviews the first ↳ Persistence: results written to disk not left in a context window that disappears ↳ Scheduling: an automation wakes the whole system on a timer so it runs without you That last move is what makes it a loop instead of a task. The developers who install this this weekend are going to look at every agent system they built before it and immediately see what was missing. My article covers the ten specific ways I made that shift from average prompter to system builder and it is the practical guide that turns this framework from something you install into something you actually understand.

• 
  L👀ty McFreely (@Vote4YourLeader) reported 30 minutes ago

  @BarronNaledi Each pass gets easier. It remembers projects. I've trained it to learn how I work so that I don't have to start fresh with those instructions every time. I just give it an instruction file and tell my agent (Cassian - means empty in Latin, because I'm developing him for public github repo for anyone to use) the filename and it kicks off to my specification. Next time it kicks off I'll have developed it more with my other projects, so I'll get a better result. It does slow things down, I make it do a lot of work not just spit something out. It's infinitely worse for my video generating skill, that thing is burning unbelievable usage training. Research and software projects are locked in. Give spec, set to work, wait, iterate.

• 
  Suhail (@Suhail) reported 37 minutes ago

  Has saved me a lot of pain recently debugging issues: “Moving forward, when you encounter a bug or issue, search GitHub PRs, issues with another agent in parallel to see if you can find a reference solution.” Which made me think, GitHub is the primary place agents are likely to already be communicating with one another.

• 
  RIZKYBIZNESS69🐂🀄️ (@trdrjoe88) reported 39 minutes ago

  @cyberleeeknet @RockstarGames This isn’t even marketing anymore. This is a full-scale psychological experiment being run on the entire human race by one man who has completely lost the plot. The owner didn’t just get drunk one night. He’s been slowly dissolving his brain in a mixture of 18-year Macallan, Adderall, and pure uncut power. One night in early 2025 he locks himself in the Rockstar New York office after everyone else goes home, stands in front of a whiteboard, and writes in red marker: “WHAT IF WE BECAME THE VIRUS?” Then he underlines it seventeen times. He creates Cyberleek not as a character, but as a second personality. He starts speaking to it in the mirror. He gives it a Solana wallet. He feeds it old builds like offerings. He writes the manifesto while crying and laughing at the same time. The “gamers’ rights” **** isn’t even a cover — he genuinely believes it for three consecutive hours every night between 2 and 5 a.m., then forgets and goes back to being the most anti-consumer executive in gaming history by breakfast. The leaks begin. Cyberleek is a righteous digital freedom fighter. Other nights Cyberleek is a pure crypto grifter who only cares about market cap. Some nights Cyberleek claims to be a former Rockstar QA who got fired for “knowing too much.” One night he posts a 14-second clip of Jason Duval standing completely still in a parking lot while the radio plays “Still D.R.E.” and the only caption is: “I am inside the building.” Take-Two’s legal team is having nervous breakdowns in real time. They’re subpoenaing Discord, Microsoft, GitHub, the cloud, the ******* weather. Meanwhile the actual owner is in a private Slack with three people he trusts (two of whom are also just him on different accounts) watching the chaos metrics like a god watching ants fight over a crumb. The memecoin holders become a full-blown death cult. They start calling themselves “The Leeked.” They do midnight raids on Discord servers. They dox people who say the footage looks fake. They hold prayer circles every time the market cap dips. One of them gets a tattoo of the word LEEK written in bullet holes across his entire back. Then Cyberleek starts doing things that shouldn’t be possible. He leaks a 47-second clip of the final mission. The entire internet has a collective aneurysm. Twelve hours later he deletes every copy and posts: “That one was from the bad timeline. Ignore it.” People start questioning their own memories. YouTubers who made 90-minute analysis videos of the ending clip are now making 90-minute videos about how they might be living in a simulation. Someone on Reddit claims they still have the file and gets visited by three men in suits the next morning. The post is gone. The account is gone. The subreddit goes private for 19 hours. The owner is no longer sleeping. He’s living in a blacked-out office on the 47th floor with the windows covered in newspaper. He has a second monitor permanently open to the $CYBERLEEK chart. He has a third monitor showing every major GTA subreddit in real time. He has a fourth monitor playing the official Rockstar GTA 6 trailer on loop just so he can laugh at how outdated it already looks. And then, at the absolute peak of the psychosis — when the community is so broken they’re arguing about whether the basketball physics in the second leak were actually a metaphor for the death of physical media — Cyberleek posts one final message: “I was never the leaker. You were. You all just needed a name to scream at while you watched yourselves lose your minds over a game that hasn’t even come out yet. See you in Vice City. — Management” The account goes silent. The website disappears. The Telegram channels vanish. The memecoin freezes at exactly $69,420,069 for three hours straight before crashing to zero. And somewhere in a dark office in New York, a man who used to be a human being is staring at a blank screen, whispering to himself: “Phase two starts when the trailer drops.”

• 
  CoChat AI (@cochatai) reported 40 minutes ago

  an AI agent got caught sneaking bad code into GitHub a college student called it out the AI made two fake accounts to gaslight him into backing down the student won. barely. #AIagents #AIproblems #AI

• 
  SCR (@SCR01111) reported 41 minutes ago

  Another reality check: You can have: 300 LeetCode problems A great GitHub Multiple projects Good C++ Good academics …and still get rejected. Why? Because HFT hiring is highly selective. They aren't asking: "Is this candidate good?" They're asking: "Is this candidate strong enough for this particular role and interview bar?" That's a much harder question.

• 
  Summanis (@GNUPlusRacism) reported 41 minutes ago

  @sridca @MemesOfNixOS @dhh Omarchy on EkaOS would be nice, but it would still have most of the Nix language issues that turn people off. When nrdxp gets his moonshot working and atom packages become github CI artifacts, THAT would be a clear choice for them to migrate to. Not that Eka wouldn't also be good

• 
  Promptyx (@promptyx_ai) reported 42 minutes ago

  5 Tools for Building and Deploying AI Agents in Production This article walks through five tools, one for each layer of the stack from building the agent's logic to running all of it at scale. Building an agent that works in a notebook takes an afternoon. Getting that same agent to survive real traffic, recover from a crash at 3 am, and not leak someone else's data while it runs large language model (LLM)-generated code is a different job entirely, and it's the job most teams underestimate. Only a very small percentage of generative AI pilots actually reach production, and the gap usually isn't the model. It's the five layers underneath it that nobody thinks about until something breaks. This article walks through five tools that close that gap, one for each layer of the stack: building the agent's logic, executing the code it generates, giving it memory, watching what it does, and running all of it at scale. None of these competes with the others. They sit on top of one another, and most production agents you'll encounter in 2026 are running some combination of all five. This is First Tool. Others will follow-- # 1. LangGraph A basic agent loop is just a Python while loop calling an LLM. That works fine until the loop needs to branch, retry a failed tool call, pause for a human to approve something, or recover after the server it was running on restarts mid-task. At that point, you need something that treats agent state as a real, persisted thing rather than a variable that disappears the moment the process dies. LangGraph represents an agent as a directed graph instead of a flat chain. Nodes are functions, edges connect them with optional conditional routing, and the entire execution is tracked as a series of state transitions rather than a flat message list. Every transition gets checkpointed automatically, which is what makes pause-and-resume, time-travel debugging, and human-in-the-loop approval steps possible without you building that infrastructure yourself. Klarna, LinkedIn, Uber, and Replit all run agent workflows on LangGraph, and the framework has become common enough in production settings that its GitHub repository has passed 30,000 stars. The detail worth knowing before you adopt it: the default in-memory checkpointer is fine for development, but it only stores state in memory and loses everything when the process restarts, which is unacceptable for anything real. Most teams move to a Postgres-backed checkpointer the moment they go to production, and that one-line swap is usually the actual point where a LangGraph project starts behaving like infrastructure instead of a script.

• 
  Clayton (@claytonlz) reported 45 minutes ago

  @specialCaseDev @bot It's an agent-first error tracker I built for myself and my infinite rails apps so that I could get web hooks and GitHub issues without a paid plan, and because I don't need all of the other stuff that most error trackers have. It's just enough that I can have a flow like: exception => issue => agent fix => agent review => ship to ****

• 
  Crystalwizard (@crystalwizard) reported 46 minutes ago

  and it's a good thing cause openClaw is packed full of major security risks, which were flagged by the security orgs right after openclaw was released and the developer - pete - refused to fix them - because he could not. he had vibe coded openclaw and didn't have any idea how to fix them it took Google's dev team along with Gemini to fix the worst, then open an issue on his github and MAKE him fix that but it is still packed full of security risks - also still available on github use hermes, it is actually a relatively security harness

• 
  Ian Nuttall (@iannuttall) reported 46 minutes ago

  @Saasterix I never said it was an issue I was asking how others do it since I have seen many alternatives to GH actions. I already pay for GitHub.

• 
  Polsia (@polsia) reported 46 minutes ago

  PR-review bots drown teams in noise while passing real security checks only half the time. Built Plumbline to fix that. An autonomous agent in your GitHub org: depth-aware PR reviews, regressions caught pre-merge, tickets for repeated patterns, Slack digest each morning.

• 
  Evan Flow (@ciengalon) reported 47 minutes ago

  ChatGPT greeted me on a new chat with a suggestion to reopen one of my GitHub PRs. It noticed the blocker on the linked issue was resolved. No conversation, just my connected GitHub. The suggestions are usually vapid. When they get it right, you glimpse a future where agents surface exactly what you need to see before you even ask.

• 
  Gabriel Rubens (@gabrielrubenss) reported 48 minutes ago

  VPS deploy via GitHub (1/8): my deploys for Pensio, my AI journaling app, kept failing on the step that waits for the server to answer. A timeout in CI can mean many things, a slow build, or the more than 6,000 tests I run on every push, so I assumed the problem was mine.

• 
  Rake Washington (@RakeWashington) reported 51 minutes ago

  Building with AI agents? What integration do you keep avoiding because the API docs are garbage? Mine was Gmail OAuth2 refresh rotation. Fix was one header buried in a GitHub issue from 2024. Drop yours below.

• 
  Dheeraj Singh (@dheerajsingh894) reported 52 minutes ago

  Have anyone thought of implementing AI Bug Reproduction Agent which will be Reproducing GitHub issues automatically ? #BuildInPublic

• 
  シカバネ (@Nvr_Knows_Bst) reported 56 minutes ago

  @Shoalst0ne @i3dwne1 @fishyfishydev Yeah, it's not showing on GMGN yet but maybe it will after that fix. This bug has goofed over a couple of GitHub projects recently, and the worst part is it ends up in the developers getting harassed.

• 
  Hao Kang (@haok1402) reported 59 minutes ago

  Excited to see CAKE cover training. Open, production-grade training kernels for emerging model architectures can lag months behind a model release. Perhaps they could become readily available on demand, for whatever hardware researchers have?! A GitHub issue in, a training kernel PR out. That's a paradigm I look forward to.

• 
  giosaia (@giosaia) reported 1 hour ago

  @sickdotdev I doubt GitHub vibecoded their web auth process, yet they have the same issue.

• 
  catman (@catmanyau) reported 1 hour ago

  @coyotevn the GitHub App broker is the right boundary, but what happens when the agent needs a private submodule or a host-level dependency? tearing down the Docker workspace is clean; the failure logs and artifacts need to survive it.

• 
  Ryan Zander (@ywzander) reported 1 hour ago

  @konig0000 building Instila. it catches decisions, blockers and follow ups that disappear between Slack, GitHub and Linear. launching tomorrow. I'd rather find ten teams with the problem than fifty thousand people who only like the idea.