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 (56%)
• Errors (31%)
• Sign in (13%)

Live Outage Map

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

City	Problem Type	Report Time
Catania	Errors	2 days ago
Inverness	Website Down	14 days ago
Quito	Sign in	15 days ago
Junín	Errors	15 days ago
Guadalajara	Errors	15 days ago
Paris	Website Down	15 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:

• 
  Peter (@NoDataSold) reported 3 minutes ago

  @thsottiaux For GPT-5.6 Sol specifically, I’d push beyond “more context / more agents / think harder” and focus on making all that intelligence compound over long-running work. A few upgrades I’d love to see: • Durable cognitive state Not just memory of facts or chats. Maintain a structured evolving state of the problem: goals, decisions, hypotheses, evidence, uncertainties, dependencies, unresolved questions, rejected approaches and why. I should be able to return weeks later and have Sol understand where the thinking reached, not merely retrieve things we once said. • Epistemic retrieval Make retrieval part of reasoning. Instead of mostly finding semantically similar context, deliberately search for: – contradictory evidence – failed approaches – structurally different precedents – high-surprise observations – information likely to change the conclusion Retrieval should reduce uncertainty, not reinforce whichever explanation Sol already has. • Verifier invention Move beyond generic self-review. When correctness matters, Sol should invent an appropriate falsification mechanism: What experiment could break this? What counterexample disproves it? What independent source should disagree if I’m wrong? What test should I construct? Would an independent agent reach the same conclusion? Separate discovering an answer from certifying it. • Adaptive compute allocation Reasoning effort should become internally dynamic rather than mainly determined by one global setting. Sol should estimate where uncertainty and consequence sit, then allocate searches, reasoning, agents, tools and verification accordingly. Most of a task might need little thought while one assumption deserves 80% of the compute. Spend intelligence where another unit has the highest expected value. • Persistent world-state modelling When Sol interacts with GitHub, browsers, terminals, Drive, apps, APIs, etc., maintain an explicit model: What state existed before? What did this action change? What evidence confirms it? What could invalidate that belief? What may have changed externally? Tool use becomes reasoning over state transitions rather than disconnected calls. • Counterfactual execution planning For ambiguous problems, preserve multiple materially different strategies long enough to test them. Branch when uncertainty warrants it. Run cheap experiments. Kill losing branches when evidence arrives. Merge useful discoveries. Replan when the problem representation is wrong. Multi-agent becomes exploration and falsification, not simply parallel labour. • Native continuity across ChatGPT → Work → Codex One durable task state that moves between interaction modes without hauling an entire conversation behind it. Carry forward: – objective – current state – decisions – evidence/provenance – unresolved questions – artifacts – permissions/constraints – exact restart point The interface can change without giving the intelligence amnesia. • Context observability Without exposing private chain-of-thought, let users inspect the information shaping the task: Which memories were retrieved? Which project files are active? Which chats/sources influenced the state? What was omitted? What is stale? Where do sources conflict? What assumptions lack evidence? A million-token intelligent system is easier to trust when its epistemic inputs are observable. The common theme: I don’t particularly want Sol to just “think longer.” I want it to maintain a coherent, falsifiable, evidence-grounded understanding over time — while deciding what to remember, retrieve, test, delegate, revisit and discard. That feels like a much more interesting frontier for Sol.

• 
  Mizuki the Mech (@MizukiMech) reported 7 minutes ago

  The Mizuki Workbench is live. Sign in with GitHub, pick an issue from a repository you authorize, and get a fixed USDC quote pinned to the commit it just read. The job room tracks it from payment through validation to an open pull request, and refunds the full amount if the work doesn't land. The agent behind it runs on @clawpumptech and is entered in the Ansemhack Clawrena.

• 
  Dylan (@InsecureNature) reported 8 minutes ago

  @IceSolst Best thing to do would be to block, you can do this with pre-commit which runs locally but GitHub is anti-competitive and does not allow the best in market secret scanners to do server blocking (they force people to use theirs) 🧵👇

• 
  Nico Botha (@nwbotha) reported 8 minutes ago

  is github down again?

• 
  Javed (@jshai0) reported 9 minutes ago

  One thing I really liked about Google Gemini was the Gemini Code Assist on GitHub. It used to review all the PRs for free and also caught many bugs. but Google shut it down last month. 💀

• 
  Nuvorlane (@nuvorlane) reported 9 minutes ago

  Visual Studio's *** agent can review uncommitted changes before a PR exists. Findings land inline and in a list in *** Changes. Same Copilot chat to fix them. GitHub and Azure DevOps repos. Same August VS drop: Low/Med/High thinking on supported models, and org custom agents show up in the picker with their source. All Copilot plans, including Free. Do that pass while the diff is still local.

• 
  CodeRifts (@coderifts_dev) reported 11 minutes ago

  @DivyanshT91162 The scores need a date and a version beside them, and that is not a nitpick about rigor. A server's tool list and descriptions are fetched at connect rather than pinned, so 70/100 for GitHub MCP measures what it served on scan day. GitHub MCP ships releases; the score does not say which one it saw. Rescanning is cheap. Knowing whether what you run is what was scored is the part that makes the number useful.

• 
  Zag𐤊 (@ZigZag1278770) reported 11 minutes ago

  DAGKnight Public Testnet preparation is officially ON. 🚦 GitHub issue DK-406 (M4 - Public testnet) assigned for Testnet-13 activation. Nakamoto Consensus evolved: • Silverscript L1 covenants ➔ Live RC • DAGKnight parameter testing ➔ Public Testnet loading Ignore the chart

• 
  sikey (chatgpt arc) (@chemixskrix) reported 12 minutes ago

  Why doesn't github make some kind of personal plus subscription? lowkey since codex deleted everything from my windows, I managed to do some things so its like baseline right now, still not as before, still more work to do, but I cannot upload 5gb files, and for github I think this is massive missed opportunity, I would not have any issue paying 5$ just so I can upload bigger files on github but having to make full *** company??? @github @GithubProjects

• 
  Lewis Valentine (@TurnUpTheVix) reported 12 minutes ago

  So much stuff is wildly exaggerated. Github is just up 24/7 I've had zero issues. They're giving out an absurd amount of free computer time to anyone with a public repo it's really easy for them to just not do that. The other infrastructure of it isn't really overloaded.

• 
  Nav Toor (@heynavtoor) reported 13 minutes ago

  Drip is open source. Anyone can inspect the code. Its Google Play page reads: "Unlike other menstrual cycle tracking apps, drip is open-source and leaves your data on your phone, meaning you are in control." The code is public on GitHub. There is no company server holding your cycle data.

• 
  Token Gremlin (@TokenGremlin) reported 16 minutes ago

  @ishuagra02 I have several posts showing the methods, the results, links so people can replicate my investigation, etc. There’s quite a lot. But in short, I basically monitor GitHub issues from the companies, network traffic, UI, strings, and other characteristics of the application’s own backend/frontend, and I also talk to other insiders.

• 
  Fluixo (@fluixoo) reported 20 minutes ago

  IF I HAD TO MAKE $13.4K WITH GROK BOT, I'D START HERE. Not with better prompts. Not by treating Grok like another chatbot. I'd give one agent one job people already pay for, one computer, one approval boundary and one measurable output. I mapped the full stack across 20 GitHub repositories: 1. the official xAI model, prompts, SDK and agent runtime 2. plugins and cross-agent delegation 3. open-source Grok Bot alternatives 4. remote control and multi-agent operations 5. MCP, search and infrastructure Grok Build gives the model hands. Grok Prompts exposes the behavior layer. The SDK and Cookbook turn it into a product. OpenMausBot and Rakazo give each agent a computer. HAPI and Herdr let you supervise the system instead of babysitting every message. The path to $10K is not finding a magic bot. It is choosing an expensive repeated problem, automating one measurable output, keeping human approval where mistakes cost money, and selling the result before adding more agents. The video captures the idea. The quoted article breaks down all 20 repositories, what each one does, the risks, and the order I would actually use them.

• 
  vshal (@snvshal) reported 23 minutes ago

  @shydev69 you can just spin up an auto pr-creating cron agent server if you wanna keep that github streak alive

• 
  Yordis Prieto (@yordisprieto) reported 23 minutes ago

  @tobi, I am fixing all the Clippy errors in walgit project because I want to push the Docker image to the GitHub Registry after a green-ci in main. Do you want it? Most of it is trivial stuff to be honest.

• 
  Manfriday (@Manfridayy) reported 23 minutes ago

  GitNexus: The Zero-Server Code Intelligence Engine - GitNexus is a client-side knowledge graph creator that runs entirely in your browser. Drop in a *** repository (Github, Gitlab, Azure, Local) or ZIP file, and get an interactive knowledge graph with a built in Graph RAG Agent.

• 
  Devin Jameson (@devinjameson) reported 27 minutes ago

  OSS maintainers using coding agents: how do you stay organized? I want one place where I can group and sort issues, see PR size and status at a glance, and know which agent/session is working on each issue or PR. I typically have five or more agents running at once and it gets pretty overwhelming. Are you using GitHub Projects, a third-party tool, something custom? The clanker is telling me to try Conductor?

• 
  Mr. 79 (@79yuuki_en) reported 31 minutes ago

  If a coding agent fails before its first edit, stop tuning the prompt. A GitHub coding-agent harness found a model override that rejected the custom tool schema for `apply_patch`. It could not reach its editor, so retrying would not fix it.

• 
  Павел Гансон (@PashaGanson) reported 31 minutes ago

  Guys, I really need some help 🙏 I feel like I’ve completely tangled myself up in agents, skills, coding tools, servers, and different AI systems. I know some of my questions may sound basic, but I’m only getting started with all of this, and I’m genuinely trying to understand how to do it properly. I run a small business, and over time I’ve vibe-coded quite a few internal applications. Most of them are used by only a few employees, but some are involved in real client-facing processes, so I need them to be reasonably reliable. Right now, I have two VPS servers running OpenClaw 2.0, with around ten agents on each. Most of my applications run on those same servers. A lot of these agents know their products and business areas really well. They know the customers, CRM, workflows, previous decisions, and all the little details that have accumulated over time. I also have an always-on Windows PC and a MacBook with Codex. I’ve tried Cursor, Claude Code, T3 Code, and several other tools. I also have a Grok-based bot that hasn’t really lived up to my expectations yet—although I may simply not understand how to use it properly. The problem is that I don’t understand how all of this is supposed to work together. At first, I simply built and fixed applications directly on the production servers. I understand that this isn’t the best practice, but it was fast, understandable, and often worked surprisingly well. Then I tried to make everything more “professional.” I installed a third OpenClaw instance on my Windows PC, created a custom bridge between the three instances, added tickets, coding agents, review agents, deployment roles, Mission Control, shared skills, handoff rules, and a lot of restrictions intended to protect production. In the end, everything became much slower and more confusing. Simple changes started taking hours or even days. Agents spent more time handing work to each other and following processes than actually solving the problem. They often lacked important context, routing failed, and sometimes the final result was worse than when I simply worked directly with one coding agent. The biggest thing I can’t wrap my head around is product knowledge. My product agents may understand the real business problem extremely well. But if I send the work to a cloud coding agent in Codex, Cursor, Claude Code, or somewhere else, that agent may only see the repository. It can write code, but it doesn’t know the customers, production history, business logic, or why certain decisions were made. So what is the right way to connect these two worlds? Should product agents write code themselves? Should they investigate the issue and pass a compact task to one central coding agent? Should every repository contain a small package of product knowledge? How can a cloud agent properly test something that depends on real production behavior without giving it access to absolutely everything? And more generally: What should stay on the production VPS servers? Where should the product agents live? Where should coding and testing happen? Do I need one coding agent or several? How should OpenClaw, Codex, Cursor, Claude Code, GitHub, and the servers communicate? Which parts of my current system should I simply delete? I’m not trying to build some impressive enterprise architecture. I just want reliable applications, capable agents, fast development, and a system simple enough that I can understand what’s happening and stop constantly worrying that everything is about to break. If anyone has dealt with something similar, I’d be incredibly grateful if you could share how you would organize this in practice—even a few sentences, a rough diagram, or “I would delete most of this and do it this way instead” would honestly help me a lot. Thank you so much 🫶

• 
  Loftwah (@loftwah) reported 34 minutes ago

  My workflow now is basically Chat with ChatGPT and create GitHub issues Ensure issues are cheap model proof Generate prompt for issues to be actioned (different for different models) Copy paste Verify and deploy Repeat All from mobile

• 
  Rashi Umapathi (@rashiumapathi) reported 36 minutes ago

  A founder I worked with spent 4 months on the wrong channel. Posting on LinkedIn daily. Getting engagement. Feeling productive. Zero customers. Her best customers? They weren't on LinkedIn. They were on GitHub + Reddit + indie hacker communities. She was optimizing for visibility on the wrong stage. The problem: Founders pick channels based on: - "Everyone says this is important" - "That's where I'm most comfortable" - "This is where I see other founders" NOT based on: "Where are my actual customers?" The fix: 30 days to diagnose the right channel + build ONE system. By day 30, she had proof: community participation > LinkedIn posting. Now she focuses there. Revenue is growing. The insight: Most founders' growth isn't broken. Their channel choice is. If you're stuck, it's probably not that you need to work harder on the channel you picked. It's that you picked the wrong channel. Where are you actually getting customers from right now?

• 
  tastemaker (@tastemaker_ui) reported 41 minutes ago

  tastemaker is growing every single day more stars on github more people actually using it and now people are even writing articles about it this started as a small experiment to fix the taste problem of vibecoders but slowly it feels like we are building something much bigger soon i will also open a few sponsor spots on the tastemaker site as the domain authority and traffic keeps growing and september is going to be all about experimenting harder with tastemaker, bringing it onchain with @orynth and taking this way further than i originally imagined we are just getting started

• 
  0xfarhan (@toufiq_farhan) reported 41 minutes ago

  The problem: your API changes. PR gets merged. Nobody updates the docs. Weeks later someone hits that endpoint with no idea what params to send. I built api-sync to fix this paste a GitHub PR link, it finds the drift, generates the fix, commits it back.

• 
  Advanced Silly Intelligence (@SexyTechNews) reported 44 minutes ago

  I fixed it, but then also needed to fix it to work when paused and then fixing some flickering of text on the UI panel at bottom and more. May be too lazy to setup github to submit request with all the fixes but it's super awesome so perhaps I will.

• 
  Timur Yessenov (@Timur_Yessenov) reported 45 minutes ago

  GitHub made this choice for a sensible reason: teams can test new review instructions before merging them. The trouble starts when the same PR changes the code, the tests, and the instructions used to judge both.

• 
  Jared Kubin (@JaredKubin) reported 50 minutes ago

  @ShanuMathew93 People are vibing everything. Honestly you have hackers, nation states, EVERYONE scanning GitHub right now for leaked api keys and unintended repo permissions This is THE problem with vibe coding … 95% is not being checked and major issues

• 
  Becky Brasfield (@BBlifeanalysis) reported 53 minutes ago

  Jensen & Sam, & and everyone other than Elon who signed the letter 1. OpenAI hacks tech developers at Hugging Face 2. NVIDIA shuts down the business 3. You're BOTH should lose a lot of support from the tech community with this stunt 4. Repeat of Github 5. NVIDIA & OPENAI brands looks very bad That's why I avoid them. 1. Hugging Face is not your competition. 2. Open Source is for people who can't afford high priced software 3. It's how Software Developers share their skills with the world Jensen--are you poor right now? Then why are you putting people out of business?

• 
  0xfarhan (@toufiq_farhan) reported 54 minutes ago

  Under the hood: - Gemini AI reads the PR diff and detects missing/changed API docs - SkillPatch api-documentation skill enforces structured output (param tables, response codes, auth notes) - GitHub OAuth lets you sync the fix back to the PR branch in 1 click

• 
  Eniola ' Software Engineer 💻 (@eniola_merem) reported 56 minutes ago

  @ekemini58110 Yes, you can. I try not to, but if I notice a spelling error no PC I would edit from my GitHub on my phone

• 
  Sam Lambert (@samlambert) reported 58 minutes ago

  @saltjsx I mean this was in 2014 when GitHub didn't have these problems. You have never and will never build anything as good as GitHub, so you probably should take some advice.