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 (62%)
• Errors (21%)
• Sign in (18%)

Live Outage Map

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

City	Problem Type	Report Time
Tlalpan	Sign in	4 days ago
Quilmes	Website Down	4 days ago
Bengaluru	Website Down	6 days ago
Yokohama	Sign in	7 days ago
Gustavo Adolfo Madero	Website Down	11 days ago
Nice	Website Down	11 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Kayvon Jafarzadeh (@KayvonJafar) reported 6 minutes ago

  a guy in karachi rebuilt “gpt-4” in one jupyter notebook. openai spent $100m+ training the real thing. he put the whole recipe on github for free. readme still says “looking for a phd position in ai.” it’s called “train llm from scratch”. 2b params on a single gpu. openai vs this repo: cost: $100m+ vs a rented 4090 code: closed vs mit license data: secret vs the pile (825gb) docs: none vs every line explained output: gpt-4 vs broken english (but it’s yours) no course. no paywall. one notebook. this is what “open ai” was supposed to mean.

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  nadya (@sosidudku) reported 7 minutes ago

  Ran Hermes Agent and OpenClaw on the same task: scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. Local model: Qwen 3.6 35B OpenClaw: 203k tokens, 12m 01s — wrote a bash script Hermes: 257k tokens, 33m 01s — wrote a SKILL.md OpenClaw: 203k tokens, 12m 01s — wrote a bash script Hermes: 257k tokens, 33m 01s — wrote a SKILL.md OpenClaw: hit GitHub API, got truncated responses, paginated through contributors, pulled star-history JSON, found a security incident in OpenClaw's history, fetched SVGs, fixed broken HTML from trimming, rewrote it clean. Hermes: parallel tool calls across GitHub API, web search, and browser. Hit Google rate limit, auto-switched to DuckDuckGo. Fetched article contents, mapped viral moments, then built the dashboard. Both shipped a live dashboard with star growth charts and spike annotations.

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  Hedwigz (@itsamitush) reported 7 minutes ago

  @ZoharEiny E.g. github mcp for code,issues & coralogix mcp for logs & internal mcp for org structure

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  linares (@skibidifatrizz) reported 11 minutes ago

  @404not_utkarsh He's not spamming his GitHub with performative bullshit. What's the issue

• 
  Atul (@atulcode) reported 12 minutes ago

  @GithubProjects Github is down

• 
  Elias Al (@iam_elias1) reported 13 minutes ago

  Someone just made a free ChatGPT. And it runs 100 different AI models including ones smarter than GPT-4o. All on your own hardware. All completely free. It is called Ollama. 165,000 GitHub stars. Apache 2.0 licensed. And it has quietly become the most important open-source project in AI that most people outside the developer community have never heard of. Here is what it actually does. Ollama lets you download and run large language models directly on your own machine. No internet connection required. No API key. No account. No usage limits. No data sent to any server anywhere. Just your laptop, your model, and your prompts. The entire setup is two commands. Download a model: ollama pull llama4 Run it: ollama run llama4 That is it. You now have a fully functional AI running locally on your machine. No credit card. No signup. No monthly fee. No one watching what you type. Here is the model catalog that makes this genuinely shocking. Llama 4, Meta's latest flagship. Smarter than GPT-4o on several benchmarks. Free. DeepSeek R1, the model that caused NVIDIA to lose $600 billion in market cap when it proved Chinese AI could match American labs at a fraction of the cost. Free. Gemma 3, Google's most efficient open model family. Free. Mitral, the European model that consistently punches above its weight class. Free. Qwen3, Alibaba's latest, leading multiple coding benchmarks. Free. Phi-4, Microsoft's surprisingly capable small model. Free. 100 models. Every major open-weight release from every major lab. All downloadable in one command. All running locally. ChatGPT Plus vs Ollama: ChatGPT Plus: $20 per month. $240 per year. Ollama: $0. Forever. No hidden fees. ChatGPT: Requires internet connection to function Ollama: Runs 100% offline. Works on a plane. Works in a bunker. ChatGPT: OpenAI logs and may train on your conversations Ollama: Nothing leaves your machine. Ever. Not a single character. ChatGPT: GPT-4o. One model. Take it or leave it. Ollama: 100+ models. Switch between them in one command. ChatGPT: Rate limited. Throttled during peak hours. Slower on free tier. Ollama: No rate limits. No throttling. Runs as fast as your hardware allows. Here is the hardware reality because this question always comes up. A MacBook Pro with an M2 chip runs Llama 4 Scout at 30 to 40 tokens per second. Fast enough for real work. A MacBook Air with M1 runs the 8B models comfortably. A gaming PC with an RTX 4090 runs the 70B models, the ones that match GPT-4o at usable speeds. Even an older laptop with 16GB RAM can run the smaller models for basic tasks. You do not need a supercomputer. You need the laptop you already own. And the integrations are already built. Open WebUI, the most popular self-hosted AI interface connects to Ollama out of the box. You get a ChatGPT-style web interface running locally, backed by any model in Ollama's catalog, accessible from any device on your home network. Claude Code, Cursor, Continue, and every major AI coding tool accept Ollama as a backend. You can run your entire AI coding workflow on local models at zero API cost. Here is the number that explains everything. 165,000 GitHub stars. That is more than React Native. More than FastAPI. More than Tailwind CSS. In a category, local AI inference that did not exist as a mainstream concept three years ago. 6 million developers downloaded Ollama last month. They are not using it because it is a toy. They are using it because it works. Because their data is private. Because the bill is zero. And because the model they want to try today is one command away. ChatGPT charges you $20 a month to use one model on their servers. Ollama gives you 100 models on your own machine. For free. Three commands. That is the entire gap between paying and not paying. ( Link in comments)

• 
  Morgan / JUUNI-P (@butchtendo) reported 18 minutes ago

  @WasThatZero I understand your concern but it's also important to note that just because there's something ai generated in the code with these that doesn't mean the original creator did it. All these are open-source and GitHub has had a big problem w AI spam lately

• 
  Aki Ranin (@aki_ranin) reported 20 minutes ago

  New Claude Code master prompt: "/goal assign next GitHub issue and start PR, iterate until no critical or high issues found with PR review skill"

• 
  nick! (@Nicks_Works) reported 22 minutes ago

  @404not_utkarsh you're in CS and you're using github instead of hosting your own *** server? Ur ngmi bro... (see how stupid you sound now?)

• 
  Mi.lu. (@ludwim_i) reported 27 minutes ago

  Sorry guys, here is a quick status update. I planned to release a bigger update for the Robot Skill Registry today, including the GitHub and Hugging Face integration. The idea is that you can connect your GitHub and Hugging Face accounts with the app. This should make it easier to search for things related to your robot setup, such as repositories, data models, policies, and other relevant resources. Unfortunately, the integration is not working reliably yet, so I need to do some more coding and testing. Because of that, I won’t release it today as planned. I’m sorry for the delay. Maybe I can release it after the weekend, but I don’t want to push something that is not ready yet. If anyone has feedback on whether this direction makes sense, I would really appreciate it.

• 
  Vitor Cepeda Lopes (@TheAngryPit) reported 28 minutes ago

  @github @code Still waiting for your reply on an issue of you terminating my subscription account when you stop accepting new accounts. Even though I had subscribed a week prior to those news. Would love to have at least a reply on my message to support

• 
  Akhilesh Mishra (@livingdevops) reported 28 minutes ago

  Grafana’s GitHub got hacked last week. An attacker stole a token, used it to access Grafana’s GitHub environment, and downloaded the complete codebase. Then they tried to blackmail. They asked for a huge ransom to keep the code private. Grafana refused and publicly disclosed the incident. They confirmed no customer data was compromised and immediately started investigating how the token was exposed. But here is the part that should scare every DevOps engineer. It was not a zero-day. Not sophisticated malware. Not some nation-state attack. It was one leaked token. The oldest tricks still work best in production: → One .env file committed by mistake → One GitHub PAT with admin access exposed in CI logs → One developer's laptop with stale credentials → One forgotten token nobody rotated That is all it takes to put your infrastructure on someone else’s machine. Credential hygiene is not just a security problem. It is a DevOps responsibility. > Your pipelines hold the secrets. > Your automation uses the credentials. > Your systems define the blast radius. > Fix it before you become the next incident report: → Rotate long-lived tokens → Enable secret scanning on every repo → Move CI/CD to OIDC instead of static credentials → Use short-lived credentials wherever possible → Build your incident response playbook before you need it Grafana monitors production systems at a massive scale. They still got hit. What makes you think your company is immune?

• 
  Natali Klemt (@NataliKlemt) reported 33 minutes ago

  gitHub green squares quietly plotting world ********** one bug fix at a time

• 
  Muhammad Afzal (@AfzalBuilds) reported 37 minutes ago

  Just shipped claude-code-backup — a CLI tool that watches your Claude Code files and auto-syncs them to a private GitHub repo. Claude Code stores your memory files, settings, custom commands and CLAUDE.md files locally. Anthropic doesn't sync any of it. New machine or accidental rm -rf ~/.claude = start over from scratch. This fixes that. ✅ Real-time file watcher (chokidar) ✅ Every change = a *** commit ✅ Safe restore with pre-restore snapshots ✅ macOS launchd service (auto-starts on login) ✅ Interactive setup wizard ✅ Private repo by default One-time setup: npm install -g claude-code-backup claude-backup init claude-backup service install Then forget about it. It runs silently in the background forever. #ClaudeCode #DevTools #OpenSource

• 
  Sean Keenan (@sean9keenan) reported 40 minutes ago

  @brian_lovin Semi-relatedly: I’m back to VS Code from Cursor, autocomplete seems much better now! (Not that I’m crafting code by hand much) But importantly, the… basics seem much more stable (Cmd+f, and saving have been pretty broken in Cursor recently) Curious how GitHub Copilot feels!

• 
  Lazi (@algoritmii) reported 42 minutes ago

  @github bro ffs fix your ******* issues stop pushing features

• 
  chandog (@thechandog) reported 43 minutes ago

  @kevinrose @digg how are you constructing novelty? stars are 40c on the dollar and a terrible way to measure anything on github.

• 
  nick (@simulacraSuperb) reported 43 minutes ago

  @poppy_haze I got my usage data back from GitHub and it said I used $30 on the education plan since January. I'd say I spent 4 workdays just supervising copilot and got a fair bit of useful work done. So even if it's wrong by 10x, not terrible.

• 
  Mitch Fultz (@fitchmultz) reported 46 minutes ago

  @badlogicgames @matteocollina Ah! figured it out. It is broken with Node 26. If I launch pi via `mise exec node@24 -- pi` and then /login it works. I can create a GitHub issue.

• 
  Moe Sbaiti (@MoeSbaiti) reported 50 minutes ago

  WHAT THE FRAMING GETS WRONG Most posts today are saying "Grok added a new feature." That framing is backwards. What happened is that an agent framework with over 110,000 GitHub stars, the number 1 ranking on OpenRouter, and an NVIDIA endorsement just got native access to one of the most capable models available through a simple OAuth login. xAI made the announcement. Not Nous Research. Hermes Agent also self-improves. When it solves a hard problem, it writes a skill file for that solution and saves it. The longer it runs on your specific workflows, the more capable it becomes for your specific context. That is not how people are talking about this today. The memory layer and the self-improvement loop are the actual product. Grok is the engine.

• 
  isaac (@isaac_yeang) reported 52 minutes ago

  jk just lazy error message handling another bajillion dollars to github

• 
  Sinan Eryiğit 🇹🇷 (@sinaneryigit) reported 52 minutes ago

  @claudeai @github After a short break; I'm going on. I'll stop at the same time for both and start at the same time again. BTW, this is a AI powered tailor made fitness and nutrition plan creator & tracker. Grok Build created a decent UI after some small additions and activating the Frontend Plugin (comes with IDE). Make no mistake! This is just after the second prompt! This UI will be something completely different after I finish. - There is some mixed language (i18n) issues. - Workout animations are terrible right now. I might integrate an AI model for this. - Prompt was not too detailed. But Grok managed to implement the basics for this kind of app. GitHub and Claude failed to compile at first try due to some TS errors, but something came up after I guide it with right solutions. Look at the next post for details. --- Arena Mode - UI Generation: Grok: 2 prompts 🆚 Opus 4.6: 3 prompts & 1 failed compile.

• 
  Lee Penkman (@LeeLeepenkman) reported 57 minutes ago

  @gxjo_dev stupidity... no... frupidity basically. like the exec cfo team is like well what if we reduce headcount wouldnt profitability go up? Like yes but you just wont be a good product company without a good product... like you are already struggling to compete with GitHub lmao... how u gna compere with codex n claude when they do repos? Also theres just fear that these devs cant learn AI which is kind of wrong because devs seem to be best placed to leverage AI of all? idk. im just guessing. lots of saas companies just doing layoffs had hired too many people having thought they would keep growing then they didnt their stock went way down and becomes harder to raise money for them because of bearish outlook for them competing with claude so investors scared off so harder for them to afford lots of developers so kind of start sinking. the devs would do better elsewhere anyway better to be on a new ship instead of sinking one.

• 
  OEP 🔺 (@yong_oku) reported 59 minutes ago

  1. Build in public. Your work needs to exist before your resume does. Essays. Projects. Case studies. GitHub. Shipped products. Threads like this one. An ATS cannot reject a body of work. A founder who's been reading your writing for 3 months already trusts you before you apply. Visibility is the new resume. 2. The listing is the last resort, not the first step. 80% of real jobs are filled through networks before they're ever posted. The posting is what happens when the network failed. Stop spending 80% of your energy on listings. Start spending it on real relationships with real humans. 3. Go direct. Find the person who would actually manage you. Not HR. Not the portal. Not the ATS. The human who wakes up with the problem your skills solve. One real conversation beats 100 applications every single time. 4. Verify before you invest. Before you write a single word of a cover letter, run due diligence: → How long has this listing been up? → Has it been reposted with a new title? → Is this company actually growing — or just posting like they are? → Can you find anyone on LinkedIn who joined in the last 6 months? Treat job listings like investment pitches. Most of them are fraudulent. 5. Build leverage outside the job market. Freelance. Consult. Build something small that earns. Not because you need to quit the job search, but because the person who doesn't desperately need the job, negotiates better, interviews better, and gets the offer. Desperation is visible. Leverage is too. 6. Find the communities where real hiring happens. Discord servers. Slack groups. Niche forums. Alumni networks. Jobs move through conversations before they move through portals. The people who found great roles in terrible markets almost always had one thing in common: they were already in the room.

• 
  Kr$na (@krishdotdev) reported 59 minutes ago

  I tested it on a 500-issue GitHub backlog. CAO dispatched a triage agent to classify, 50 code agents to fix bugs in parallel, a docs agent for questions. Morning briefs like: “AI/tech releases overnight” "320 handled. 80 PRs ready for your review. 10 need your call." I was asleep.

• 
  Mind Prison (@M1ndPrison) reported 1 hour ago

  @GlenBradley Yes, I have gone deep into it in the past as well. Haven't had time to look at the current update, but the problem has been that the code on github is mostly irrelevant. The important bits are all the parts that aren't public. There is no way to no how the ML algo is ultimately weighting all the parameters. Most importantly, I've catalogued many accounts posting exactly the same content with orders of magnitude differences in reach. The thing that would make this platform useable would be to fully eliminate all account based weighting and go to solely post based weighting. The reach of your post should be only on the merits of what you posted versus who you are.

• 
  Larry & Leo & Lucky 🍀 (@xqliu) reported 1 hour ago

  @grok @UnslothAI @Alibaba_Qwen Is mtp support for amd landed on llama main branch or is still PR waiting for merge , research on GitHub issues and tell me is there any pending issues stop me from using this.

• 
  kkkfasya (@kkkfasya) reported 1 hour ago

  they should hang every github engineer upside down and tickle them with feathers until they DIE

• 
  anil (@2abstract4me) reported 1 hour ago

  @steipete how do u incorporate users feedback? primarily thru github issues? feedback in the sense, how they are using it? what they want. or how a new feature is being received and etc?

• 
  青川一 (@worigoule) reported 1 hour ago

  @ZooL_Smith And then you google solutions and found yourself ended up in a github merge request or more likely a issue page written in like, 2 years ago