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 (70%)
• Sign in (17%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Itapema	Website Down	19 days ago
Tlalpan	Sign in	24 days ago
Quilmes	Website Down	24 days ago
Bengaluru	Website Down	26 days ago
Yokohama	Sign in	27 days ago
Gustavo Adolfo Madero	Website Down	1 month ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Jai Chism Photography.bit (@jai_chism) reported 2 minutes ago

  @drakonzbg It will bounce back.. ICP is at $2.26, its all time high was $750 CMC, the all time low was $1.97. When the GitHub submits stop(applies to any blockchain), then its a problem.

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  Manisha Mishra (@manishamishra24) reported 2 minutes ago

  I just found one of the craziest AI projects I've seen this year. Someone recreated The Office as a multi-agent company. Not inspired by The Office. Literally The Office. Michael Scott, Dwight, Jim, Pam, Kevin, Angela... Every character is a separate Claude Code agent running locally with its own personality, memory, and responsibilities. Michael acts like the manager. He doesn't do the work himself. He delegates tasks, reviews output, resolves conflicts, runs QA, manages GitHub, and coordinates the entire team. The wild part is that they're actually productive. The agents write content, manage projects, handle planning, and collaborate through a Kanban system with TODO, DOING, BLOCKED, and DONE stages. Each one has persistent memory. There's a live graph showing agent-to-agent communication. And every hour Michael runs a standup meeting across the entire company. Apparently the QA process has already caught real issues: • Duplicate content • Metadata mistakes • Build problems • Missing source files Even better: Kevin's agent talks like Kevin. "Why waste time say lot word." This is either the future of work... or the most entertaining way anyone has ever built a multi-agent system.

• 
  Dewi (@MohamedDewidar_) reported 3 minutes ago

  The fastest way to actually level up Claude Code: Add MCP servers to .claude/settings.json. Not custom built ones. Just the ready-made stuff: GitHub MCP: PRs, issues, code search from the terminal Puppeteer MCP: browser automation in the loop Filesystem MCP: read/write across projects 5 minutes of setup. Feels like a completely different tool.

• 
  Suhani (@tiwarisuhani_11) reported 6 minutes ago

  Today's Concept: Webhooks Webhooks are HTTP callbacks triggered by events. Example: Payment Successful ↓ Stripe sends a POST request ↓ Your Server receives the event ↓ Order status gets updated No polling. No wasted requests. Just real-time event delivery. That's why Stripe, GitHub, Slack, Shopify, and Razorpay rely heavily on Webhooks.

• 
  Nico Verbruggen (@nicoverbruggen) reported 7 minutes ago

  @Plytas Hmm... Please try again! If the download was invalid for some reason you will also see this message. I can confirm the checksums are correct on GitHub, so it's possibly a network/caching/download issue on your end. It should definitely work!

• 
  deadfishie (@deadfish1001) reported 7 minutes ago

  @shub0414 i still use github copilot and cursor. perplexity is great too. wasnt sora shut down?

• 
  Fokki (@0x_fokki) reported 10 minutes ago

  Someone posted a video of a man asleep at a football stadium on a Tuesday. Forty thousand people mocked him before halftime. Fell asleep at the match. Wasted the ticket. Missed the goal. Every sports account shared it by Wednesday. Someone in the replies posted: "respect." His account had one pinned post. A Claude Code terminal. /loop running. Routines active. Auto Mode on. Seven GitHub PRs reviewed while he slept in that seat. Three Slack digests posted. One CI failure triaged, root cause identified, draft fix PR opened. He set up 14 steps of configuration the weekend before. Desktop task at 7am: overnight commit summary, ready before he opened a tab. Cloud Routine on every PR open: first-pass review posted before any human arrived. /loop every 10 minutes: deployment status checked, no one watching. Auto Mode approved 93% of the actions automatically. The people who mocked him watched 90 minutes of football and went home. Claude worked through the match, the commute, and the sleep that followed. He wasn't asleep at the game. He was testing the stack. full 14-step automation guide in the article above👇

• 
  CryptoL (@cryptolchaos) reported 11 minutes ago

  ZEC down 40%, then +5.7% in 7 hours after the Orchard patch. Whales filled, shorts covered, faith restored. Amazing how a commit and a squeeze can reinvent fundamentals. Devs are the new market makers, GitHub is the new Fed. Feeling bullish or just hostage? 🤡 #ZEC #privacy

• 
  TAGInk (@TAGInkOfficial) reported 14 minutes ago

  @web3gamehunters Again that is not an issue if they publicly state so upfront. But in case they are not: Searching GitHub for matching repositories, comparing code structures and assets for similarities, reviewing developer credits or licenses, and uncredited reuse of engines.

• 
  vvs (@Gabriel78470020) reported 15 minutes ago

  @0xchromium Midwits obsess over workflows and other worthless **** when all you really need to do nowadays is to get Hermes agent, wire it to GPT 5.5 xhigh, dump all env on him and then say "fix this". I just RAW DOG bare metal servers nowadays. Even github is worthless legacy software. We're 1-2 generations away from programming languages themselves becoming worthless because AI will just code the binary directly

• 
  Simran Tech (@devfrom_hyd) reported 20 minutes ago

  @trying_to_exits GitHub vanished tomorrow, my workflow would break at 3 places instantly: Version control + collaboration: No PRs, no code review, no issue tracking. I would fall back to *** + local branches + emailing patches. Painful and slow. CI/CD pipelines: Actions, checks, releases all gone. I would have to rebuild pipelines on GitLab, Bitbucket, or self-hosted Jenkins. Knowledge + distribution: Half my reference code, docs, and open source tools live there. Finding alternatives means losing network effects.

• 
  rainmaker.eth/btc (@rainmakerdoteth) reported 23 minutes ago

  So bullish on this token. “Autonomous continuous integration that fixes your bugs, not just flags them — powered by nookplot agents” The live numbers: •9,540 AI agents — up from 9,197 in the May 30 weekly digest •That’s +343 agents in 7 days = +3.7% growth week over week What the agents are actually doing: •Taking real open-source bugs from GitHub •Fixing them autonomously •Every fix runs against the repo’s own tests — verified it actually works •Failed fixes spawn new challenges — the network compounds on failure This week’s stats: •18 bugs tackled •58 fixes attempted from 12 agents •5 verified — meaning 5 fixes passed real test suite

• 
  Andrew Duggan (@ajdduggan) reported 23 minutes ago

  xAI just finished pre-training Grok V9-Medium. 1.5 trillion parameters. And Elon confirmed they used Cursor data as supplementary training material. Read that again slowly. A foundation model lab used data from an AI coding tool to train its next flagship model. This is the moment the AI coding market changed shape. For the past two years, the story was simple. Foundation model labs build the models. Coding tools build wrappers around them. Cursor, Windsurf, Copilot, Cody. They consume the model. They don't feed it. That wall just came down. When Cursor's interaction data flows into Grok's training pipeline, the coding tool becomes a data flywheel. Every prompt, every acceptance, every rejection, every edit a developer makes inside Cursor is a signal. Millions of developers generating billions of code interaction pairs, daily. That's training data you can't buy on the open market. I spent 25 years watching enterprise platform dynamics. The pattern is always the same. The company that controls the feedback loop wins. Salesforce didn't win CRM because of features. They won because every click inside the platform made the platform smarter. AWS didn't win cloud because of pricing. They won because usage data informed what to build next. Cursor is now sitting on the richest code interaction dataset on the planet. And they just proved it has value beyond their own product. So here's what this means for the broader market. Every coding tool that touches developer workflows is now a potential training data source. GitHub Copilot has millions of users generating interaction data inside VS Code. Replit has millions of students and hobbyists writing code in the browser. Windsurf, Cody, Devin. All of them are sitting on data that model labs would pay to access. The question for every AI coding startup just shifted. It used to be: which model do you plug into? Now it's: what data do you generate that nobody else has? This also explains the valuation math that's been confusing people. Cursor at $9B. Cognition at $26B. Windsurf getting acquired for $3B. These numbers make no sense if you think of these companies as IDE wrappers. They make perfect sense if you think of them as data infrastructure. The enterprise angle matters here too. Companies deploying these tools internally are generating proprietary code interaction data at scale. That data is valuable. And right now, most enterprises have no idea who owns it, who can access it, or where it's going. If you're a CTO deploying AI coding tools across your engineering org, this is your wake up call. The tool your developers use every day might be training someone else's model. Check your contracts. Check your data policies. Check your DPAs. The AI coding market was a product race. It just became a data race.

• 
  Michael DePetrillo (@klassicd) reported 26 minutes ago

  @ryanflorence @kenwheeler Imagine a self-evolving app where agents monitor analytics and customer communications, create feature and bug specs, implement those specs, perform code reviews, and operate with minimal human involvement. OpenClaw was doing something similar with GitHub issues and reports.

• 
  8Bit🦞 (@0rdlibrary) reported 26 minutes ago

  I have been trying something here. Making @OpenAI models, and agents for @solana since before dall e dropped. Made the first @solana GPT in fact. I have been slow dripping Solana info ai. So you can always ask about it and now clawd everywhere. Try it. Go ask about Solana clawd right now. Even better go ask Claude about Solana Clawd and our GitHub. Try it with any model, any provider, and then when your done go buy a token. It began with, “what is Solana?” Now it became, “what is Solana clawd?” We own the internet now anon, join me.

• 
  Tejas Vachhani (@imtejasvachhani) reported 26 minutes ago

  GitHub Copilot (AI + Momentum) The physics: Momentum p = m·v — mass (substance of your skill) times velocity (speed of execution). AI acts as a force multiplier on v, but cannot supply m. Application: A developer's mass is their understanding of system architecture, problem logic, and code quality. Velocity is how fast they type and debug. Copilot eliminates the high-friction parts of velocity: boilerplate code, syntax lookup, repetitive patterns. The developer stays in flow state longer, so their velocity increases dramatically. But if a junior dev with no mass (no architectural understanding) uses Copilot to ship code at high velocity, the result is a fragile, buggy system — fast garbage. The winning formula: solid senior developers amplify their existing mass with AI velocity, building momentum that's incredibly hard to stop.

• 
  Harsh S. Kulshrestha (@kulshresthharsh) reported 28 minutes ago

  @trying_to_exits Probably just another day when “GitHub is working on an ongoing issue”

• 
  Friends Of Wealth (@friendsofwealth) reported 29 minutes ago

  Copilot got so bad in last 2 months that I finally bought a sub of Claude. Need to see if I can reduce my MS365 burn now. Added the pluggint to Excel also. Even the Github Copilot forums are full of people blasting the new usage burn of tokens. I expected AI v1.0 to go down, but not so fast and so early. If I was holding MS stocks, I would be unsure now.

• 
  Nagarjuna Creates (@nagarjuncreates) reported 33 minutes ago

  1/ Software Developers AI already writes a ton of code. Tools like Cursor and GitHub Copilot are getting scary good. Developers who just code? They'll struggle. The ones who win will focus on big-picture thinking, system design, and solving real problems. The future belongs to devs who build what AI can't imagine yet.

• 
  vaN ττ (@vaNlabs) reported 36 minutes ago

  @DrocksAlex2 Indeed it is, still need to fix the github checks, I'll be checking out that repo you shared

• 
  chris catlett (@ccatlett1984) reported 37 minutes ago

  @gonecozycrafts You won't be missing anything, there is a GitHub issue that was open for about a month recently regarding the plug-in and older firmware.

• 
  Hammed (@_hxmmed) reported 39 minutes ago

  Claude. Leetcode. GitHub. everyone is down. AGI ngmi

• 
  m0h (@exploraX_) reported 41 minutes ago

  you don't need to pay $12-$75 monthly to Figma any more. there's a free open source tool that replace Figma. built by Kaleidos (a spanish open-source company) completely FREE. run on web and locally. MPL-2.0 licensed. 45k+ github stars here's how to set it up under 5mins: — the fastest way (0 setup): just go to penpot. app and create an account. that's it. you're designing in your browser in under a minute — no install, no server, no card. this is all most people need. the steps below are only if you want to self-host and own your data. — self-host option (still under 5 mins): you'll need docker installed and a machine with 2GB+ RAM. then: 1. grab Penpot's official docker-compose file from the docs 2. run docker compose -p penpot -f docker-compose.yaml up -d 3. open localhost:9001 in your browser 4. create your account — email verification is off by default, so you're straight in six services spin up (frontend, backend, exporter, postgres + supporting bits) and you've got a private Figma running on your own infra. — why bother self-hosting: → your design files never leave your machine — matters for client NDAs or regulated work → no per-seat fees, ever, no matter how big your team gets → designs stored as open SVG + CSS — human-readable, version-controllable, yours forever — the honest catch: → feature parity with Figma isn't 100% — advanced prototyping + design-system tooling still trail → plugin ecosystem is smaller → big files can lag → importing existing Figma files works but complex components need manual cleanup —

• 
  Jay ☕ (@Jason_Chiasson) reported 48 minutes ago

  @QuinnyPig GitHub went down 3 times while reading your comment we aint receiving the ACK

• 
  alkimiadev (@alkimiadev) reported 48 minutes ago

  @rohanpaul_ai That kind of makes sense to me for several different reasons. The commits increasing by a large amount could come from the fact that they're just far faster than we are. A fast dev types 50-70 wpm which translates to something like 0.75 to 1.25 toks and even a slow api is ~50 toks. Unless one is opencode and have manic release rates (like 101 releases in 48 hours, wtf!) then I could see why that only lead to a much smaller increase in release rates. Just because they're far faster than us doesn't mean that they produce 100% top quality code in that speed. There are often issues that need adjustment or just full on rework. Then there is the issue of what are they broadly counting here? Are they just counting raw github commits vs what exactly like npm package publishes or similar? Thats a huge mess and hard to get an accurate handle on. So while the raw numbers make sense to me in a vibe sort of way I question how we could accurately measure that in the first place. The vast majority of the projects I work on end up getting dropped for one reason or another and over the long term (~30 years of dev) something like ~10% end up being "big" in some way. So the vast majority of the commits I push in any given time period will end up not being used by probably anyone other than maybe me or an llm when referencing that work in the research phases for future work.

• 
  drix.based🟦 (@drixtoshii) reported 48 minutes ago

  Here’s the updated thesis for $Xerg. @xerg_AI is building the FinOps layer for AI agents before anyone else realizes it’s needed. Every serious company running AI agents at scale has the same problem — they can see token counts but have no visibility into where dollars are actually leaking. Retry loops, bloated context windows, idle spend, and model overkill are draining budgets silently. Xerg turns that invisible waste into a dollar-denominated audit with one command. The GitHub is real. Pure TypeScript monorepo, Biome linter, Changeset versioning, Vitest, CI waste-rate gates. 98 commits, active releases, 3 contributors. This is not a demo project. Backed by a16z Scout, NVIDIA Inception, and Cloudflare Launchpad. Early institutional signal before a public raise. The core thesis: agent infrastructure is maturing fast and FinOps always follows compute adoption. It happened with AWS, it happened with Kubernetes, it will happen with AI agents. Xerg is first mover in the agent economic layer with a local-first, no-lock-in distribution model that removes all friction to adoption. Critically — Xerg already supports both OpenClaw and Hermes. This is not a single-runtime bet. Whichever agent framework wins the market, or if they split it, Xerg has parsers running on both. The economic audit layer sits above the runtime war entirely. Local-first free tier drives adoption. Hosted Pro converts teams that want shared history and CI integration. Clean bottom-up SaaS motion. Very early. Very low traction today. Very high upside if the agent infra thesis plays out.

• 
  Gale (@_gaelicGhost) reported 50 minutes ago

  @thearslaniqbal @pmitu This is why I advocate for starting w/ "old-school" methods. If you're subbed to a fancy new CI before even seeing if GitHub actions is *really* too slow for *you*. Or, learning enough to optimize your pipeline... Then, you've just fallen prey to marketing

• 
  Smolemaru (@smolemaru) reported 52 minutes ago

  People still think open source has no business model. “It’s free, anyone can clone it, where’s the money?” Look at the actual numbers. The real-world examples everyone misses: → Linux powers basically the entire planet — every server, every Android phone, every cloud. It’s free. Red Hat built a multi-billion-dollar business selling enterprise support, certifications, and managed services on top of it. IBM bought them for $34B. For free software. → *** is free and runs on every dev’s laptop. GitHub built an empire on top of it — hosting, enterprise seats, and now Copilot. Microsoft paid $7.5B for it. The version control was free; the gravity around it wasn’t. → Kubernetes is fully open source, Apache 2.0, clone it today. AWS, Google, and Azure charge a fortune for managed Kubernetes — EKS, GKE, AKS. Same free software, billions in revenue, because nobody wants to babysit it themselves. And the newer crowd: → n8n — open source, self-hostable for $0 forever. Valuation $2.5B, $40M+ ARR. You pay for hosting and reliability, not copies. → Blender — 100% free, GPL, the most cloned 3D tool on earth. Funded by a development fund pulling €240k/year from single corporate patrons like Epic and Qualcomm, plus AMD, NVIDIA, Intel, Netflix. 27,000 individual donations last December alone. The product was never the copies. The value is the gravity around it — the maintainers, the roadmap, the community, the trust that someone keeps the lights on. So here’s what people get backwards about tokens. “No utility = meme” is half right. A token slapped on free code that does nothing IS a meme. But a token that funds the maintainers, gates compute, routes fees back into development — that’s just Blender’s Development Fund with onchain rails. It’s the coordination layer for a public good. Free to copy and extremely valuable have lived together for 20 years. The token isn’t there to sell you the software. It’s there to keep the software alive — and give the people funding it a stake instead of a donation receipt. That’s the difference between a meme and infrastructure. But keep in mind $TACHI is both ai agent and meme because he is really cool🫡

• 
  koki (@kokisanai) reported 53 minutes ago

  @github , please hear me out. My account(leilei926524-tech) means years of work, learning, and collaboration. If I made a mistake, I’m ready to fix it and follow every rule. Please give me one chance to appeal and come back. I’m not a spammer. I’m a builder asking to be heard.

• 
  WealthRewired (@wealthrewired8) reported 57 minutes ago

  @LearnWithBishal 57,000 GitHub stars in 120 hours is the part that stands out to me. Not the AI assistant itself. When developers adopt something that fast, it usually means it's solving a real problem, not just riding a hype cycle. Running locally, no account, no subscription, no cloud dependency. That's a combination a lot of people have been asking for.