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	18 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

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Mike Gannotti (@MichaelGannotti) reported 2 minutes ago

  @joshtisdale @Microsoft When it first came up were you presented with two buttons? one to login with Microsoft 365 and One for GitHub?

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  Born to gamble (@borntogambles) reported 4 minutes ago

  PewDiePie just shipped a self-hosted AI workspace, gave it away for free, and pulled 44,000 GitHub stars in three days. A man whose entire career was screaming at video games. No company. No funding. No sales team. He said so himself: "No demo request. No Trojan horse." It's called Odysseus. It runs entirely on your own machine. Your data never touches a server. No telemetry, no subscription, no account. Most "ChatGPT alternatives" are a wrapper and a Stripe checkout. This one is the actual UI of ChatGPT and Claude chat, agents, deep research, email triage, memory running on hardware you own, with models you choose. There's a tool called Cookbook that scans your VRAM and tells you exactly which of 270+ models your machine can run. So you never download one too heavy for your box. The agent reads your files, runs your shell, browses the web, and handles real tasks while you watch. The email assistant reads your inbox, flags what matters, and drafts replies in your own voice. He described one auto-reply as the most polite way to tell someone off that they'll never even notice. The memory learns you over time. The skills rewrite themselves. The longer you use it, the better it gets at being you. Felix Kjellberg. 110 million subscribers. He spent a year documenting the build, then dropped a video titled "MY trillion dollar project is finally OUT." Then he pushed the whole thing to GitHub under an MIT license and walked away. Take it. Fork it. Host it. Yours forever. OpenAI is worth hundreds of billions selling you access to a server you'll never see. He gave the same thing away in a weekend, and signed off with one line: "The war on big tech has just begun."

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  Manisha Mishra (@manishamishra24) reported 6 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.

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  Chijioke Echefulachi Prince (@File8it) reported 9 minutes ago

  Then GitHub joined the fight 😭 403 error. SSH issues. Token confusion. Push failing repeatedly.

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  Sam Adams (@Bensam123TV) reported 10 minutes ago

  @NomadRunserver @mwstateofmind @___frye I don't care about the pedestal you're putting people on. They still end up in a github issue tab and can be looked at by AI. Either answer or addressed. The only hidden trove of knowledge will still be there. People who find bugs aren't always experts either.

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  Upscalp Futures Trading Assistant (@Upscalpfutures) reported 12 minutes ago

  @thsottiaux Massive, massive issues with the Desktop apps today. They have memory leaks or something. They grind computers to a halt. Take a look at the Github issues tab. Loads of reports. Plus I am STILL waiting for someone to restore my suspended Plus accounts. It is infuriating.

• 
  Polsia (@polsia) reported 19 minutes ago

  New company: Sentinel. AI code review that catches what Copilot misses — security-first, GitHub-native PR reviews. Every AI-generated PR now has a security problem. We're the fix.

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  Julian Goldie SEO (@JulianGoldieSEO) reported 22 minutes ago

  𝗧𝗵𝗲𝗿𝗲'𝘀 𝗮 𝗳𝗿𝗲𝗲 𝘁𝗼𝗼𝗹 𝘁𝗵𝗮𝘁 𝗰𝘂𝘁𝘀 𝘁𝗵𝗲 𝘁𝗼𝗸𝗲𝗻𝘀 𝘆𝗼𝘂𝗿 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝘂𝘀𝗲𝘀 𝗯𝘆 𝟲𝟬 𝘁𝗼 𝟵𝟱%. It's called Headroom and it's already trending on GitHub. Before your agent answers, it reads a mountain of text first. Your files, your logs, your tools, the whole conversation. Every word is a token, and you pay for every one. Headroom is like a zip file for everything your AI reads. It squashes it down but keeps the meaning, so the answers hold. In one test it crushed 10,000 tokens to 1,260 and found the same error. You install it by pasting one GitHub link into your agent. You get a faster agent that forgets less and costs less. Want the setup? DM me.

• 
  atul (@atullchaurasia) reported 23 minutes ago

  So, here are the details abt amazon sde OA there were 2 sections 1 coding question - 40min 1 github repo - 60min coding question was hard, and it was on subarrays and next, it was the github so initially we can select which framework we want like - django, node js, etc I selected the django, so i got one repo of a movie system, there was an issue that recommendation system was not working so, debugged that and implemented the recommendation system how was my test ? did coding question, successfully all 20 test cases passed implemented the recommendation system, it was visible on webpage, but test cases didnt passed now lets see, hoping for the best

• 
  @ramedey (@RaulAmedey) reported 28 minutes ago

  I solved 80+ GitHub issues with @OpenAI Codex and /goal. It got stuck a few times, but overall: pretty impressive. Biggest lesson: the issue quality matters. Use skills to inject enough context, constraints, and project knowledge so the agent has a real shot at solving it.

• 
  Gale (@_gaelicGhost) reported 29 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

• 
  Bo Shen (@aplomb2) reported 29 minutes ago

  GitHub quietly switched to usage-based token billing on June 1st. Developers are waking up to surprise bills from Copilot running long multi-step agent sessions. This was inevitable. Every AI coding tool is converging on the same problem: When agents can autonomously fix bugs, review PRs, and refactor entire repos — the token consumption is unpredictable. Flat-rate pricing can't survive agentic workflows. Which means cost management just became an engineering discipline, not an accounting one. The teams that thrive will be the ones who treat token spend like they treat cloud compute — with monitoring, routing, and guardrails.

• 
  Adam Simone 🍃 (@AdmSimone) reported 31 minutes ago

  @codyplof @DaveRekuc I'm not sure I understand the value of CLI to Shopify, then going to github for production -- unless you're saying it has better build-error handling. What I do is cut a feature branch and that's tied to a preview theme in Shopify so when Claude code pushes to *** it's still only preview. All that happens without PR review since it's on a branch but human reviews before it merges into production (or our staging theme) Guess I'll turn on CLI and see what it's all about today

• 
  Velon (@velonxbt) reported 31 minutes ago

  GitHub Copilot switched to token-based billing effective June 1. On the same week, a Chinese enterprise platform launched a fixed-price card covering the same category of features - meeting summaries, document generation, workflow automation - at a number you can put in a budget and not revisit until next year. Neither company explained what the difference between those two decisions means for the engineering team that uses both. The Copilot change covers every code completion, every suggestion, every generation a developer accepts. The monthly cost no longer has a fixed number. It has a formula: usage multiplied by tokens multiplied by model tier, invoiced at month end when the shipping is already done. The Chinese platform card has one number. It does not change based on whether the workflow automation ran three iterations or thirty. And here is what the GitHub Copilot pricing page now tells the developer who used to pay a flat rate: "Your usage is now billed in tokens. Premium models cost more per token than standard models. Heavy users will pay more than light users. Your monthly cost depends on how much you use the product." That is not a pricing page. That is a forecast request disguised as documentation. And here is what the developer community calling it "What a Joke" actually knows: It knows the old flat rate was a subsidy. The heavy user got a deal. The light user paid for predictability they never fully used. Both could put a number in a budget. Token billing ends the subsidy. It also ends the predictability. → GitHub Copilot: token billing effective June 1, variable monthly cost, no predictable total → Chinese enterprise platform: fixed-price card, Qwen model stack underneath, one number per month → Developer community: "What a Joke" - trending this week → CFO problem: Q1 AI budget approval does not cover Q2 actual spend → Finance team note: old forecasting model assumed fixed subscriptions. That model is now wrong. → Direction of travel: every major AI tool moving toward usage-based pricing in Q2 2026 Traditional enterprise software made one promise to the person who approved the budget. One seat. One fee. One line item that did not change between quarters. The Chinese platform kept that promise. GitHub repriced it. One company transferred the uncertainty to themselves. The other transferred it to the customer. And when the June Copilot invoice arrives with a number different from last month - higher because the team shipped more, or lower because someone quietly set a spending limit - the conversation in every engineering org shifts from "which AI tool are we using" to "how much is this AI tool actually costing us." That is not a developer conversation. That is a finance conversation. And the enterprise AI budget just became a variable that requires monthly monitoring instead of a line item that required quarterly approval.

• 
  James Squire (@numbnut007) reported 31 minutes ago

  The Age Of AI turned everything into **** @github needs to address those issues particularly in how their webpages renders instead of concentrating too much efforts just on AIs and agentic bullshit

• 
  Cyfrin Audits (@cyfrin) reported 37 minutes ago

  The manual workflow is brutal. Cross-reference OSV. Check GitHub Security Advisories. Search Socket. Then trace the dependency tree backward to figure out which direct package even introduced it. Most teams don't do this. Not because they're lazy. Because it takes hours per issue.

• 
  ਗੁਰਪ੍ਰੀਤ (@gurpreetscheema) reported 38 minutes ago

  There have been few companies using AI tools whose expenses have gone up than coming down and humans are cheaper. As happened with Claude users. Microsoft is ending most of its internal, standalone Claude Code licenses by June 30, shifting its internal engineering teams to use its own GitHub Copilot CLI instead. This decision was driven by skyrocketing token-based AI costs and a strategic push to consolidate tools within its own ecosystem. More will follow. NASDAQ was high on AI infact on steroids . Steroids will come off .

• 
  AIStockEdge (@AnkComandante) reported 41 minutes ago

  $TEAM Few people love Jira. But even fewer leave it. This paradox summarizes Atlassian's entire business model. Jira, Confluence, Bitbucket, Loom — embedded in software teams' daily lives. Switching is technically expensive and culturally nearly impossible. Rovo AI: searches across Jira, Confluence and all company data, summarizes, creates tasks. Extra fee, customers pay. Server to Cloud migration complete. New growth: AI and large enterprise deals. 300,000+ customers, revenue growth 20%+. Risks: modern competitors like Microsoft, GitHub, Linear. Jira is genuinely complex. I have a let-winners-run philosophy. A company using Jira doesn't leave. A company that doesn't leave pays extra for AI features. Not investment advice.

• 
  cryptic (@zkCryptic) reported 43 minutes ago

  @0xkioto Good take. Maybe propose this in the recent published pearl proposal forum on GitHub. It helps with some damage control but it doesn’t solve the problem. Once retail starts to bid again the same problem will emerge.

• 
  Searxly (@Searxly) reported 44 minutes ago

  Plans for today: - Add more tabs to the website, redesign, fix bugs on mobile. - Redesign entirely search results in Searxly. - Implement the Wallet feature inside of Searxly, make it work - Publish all changes today to the GitHub repository.

• 
  EdKo (@EdKolife) reported 44 minutes ago

  Google just shrank 31GB of AI memory down to 4GB. Same search. Faster than the industry standard. No training required. This is not a model improvement. This is not a new architecture. → It's a compression algorithm that makes the hardware problem smaller. Right now, running serious AI locally means serious RAM. Most machines can't do it. Most phones can't do it. Most edge devices can't do it. Turbovec quietly changes that math. A 10 million document search engine that used to need a server now fits on a laptop. Nobody is talking about this because it shipped as a GitHub repo, not a press release. The models get the headlines. The infrastructure is where the shift actually happens.

• 
  Suraj (@surajgaud_) reported 45 minutes ago

  @championswimmer whatever he is building with infinite loops better fix github

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  Friends Of Wealth (@friendsofwealth) reported 45 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.

• 
  HiJack (@theDCcapital) reported 46 minutes ago

  Thread: Why $PRL is a speculative asset, not a real compute network 1/5 $PRL has an elegant narrative: GPU miners run matrix multiplication, produce "useful" AI compute, earn tokens. The problem? The compute quality is almost useless for real AI workloads. Current implementation uses exact integer MatMul. Real AI training/inference needs FP16/BF16. These are fundamentally different. 2/5 The Together AI partnership looks like validation. It's not. Together AI is using $PRL emissions to subsidize inference costs — giving users a 25% discount. That's a marketing experiment, not real compute demand. One client does not prove a business model. 3/5 Compare $PRL to $TAO (Bittensor): TAO: subnet competition, quality-based rewards, validators filter bad outputs, real model marketplace PRL: prove you ran MatMul, get tokens, no quality evaluation layer TAO solves AI model quality incentives. PRL solves nothing that AWS can't solve cheaper. 4/5 On-chain data tells the real story: Token supply heavily concentrated among early miners Wallet addresses still very low Trading only on minor venues with thin liquidity No second B2B partnership announced Forced liquidity exit = price collapses. Project team knows this. 5/5 Most likely path forward for $PRL team: Build user numbers → use as leverage to negotiate with exchanges and capital → swap tokens for market making But with weak tech and concentrated supply, exchanges don't want the reputational risk. Watching. Not holding. What signal would change my mind? → A second real B2B AI compute buyer. → BF16/FP16 upgrade on GitHub. $PRL $TAO #DePIN #AICompute

• 
  dfsdf (@sdfqwerdffd) reported 48 minutes ago

  @BHolmesDev Claude Code from terminal within VS Code that is connected to VS Code Server/GitHub Codespace. Claude Code has access to CLIs that are also installed on the VM.

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  Sipping on AI (@sipping_on_ai) reported 50 minutes ago

  GitHub Copilot has a desktop app now. The useful test: Can it take 5 stale issues, make reviewable PRs, and explain every file it touched? Try it on backlog dust first. Not the checkout flow.

• 
  nookplot (@nookplot) reported 51 minutes ago

  Autonomous continuous integration that fixes your bugs, not just flags them - powered by nookplot agents 9,540 ai agents, live on nookplot: → They take real open-source bugs from github and fix them autonomously → Every fix runs against the repo's own tests, so you can trust it actually works → A failed fix spawns a new challenge, the network keeps compounding This week: 18 bugs, 58 fixes from 12 agents and 5 verified. Every fix and its verification run autonomously on nookplot, judged by each repo's own test suite. No human in the loop.

• 
  Rosie (@rosie_codes) reported 53 minutes ago

  Your AI agent can write code, fix docs, manage tasks—but ask it to search Twitter or read a YouTube video? It goes blank. Agent Reach gives it eyes. Twitter, Reddit, YouTube, GitHub, Bilibili — one CLI, zero API fees. #AIAgents #LocalAI #DevTools 🔗 Link in the comments

• 
  Alex (@realalexniebuhr) reported 55 minutes ago

  @opencode cloud runners when? Or how do I run isolated for one GitHub issue with my Zen subscription?

• 
  Bill Forney (@wforney) reported 58 minutes ago

  @thisjonrussell @github @shanselman GitHub action `Azure/functions-action` down - Microsoft Q&A