GitHub status: access issues and outage reports
Problems detected
Users are reporting problems related to: website down, sign in and errors.
GitHub is a company that provides hosting for software development and version control using Git. It offers the distributed version control and source code management functionality of Git, plus its own features.
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.
June 2: Problems at GitHub
GitHub is having issues since 03:20 AM AEST. Are you also affected? Leave a message in the comments section!
Most Reported Problems
The following are the most recent problems reported by GitHub users through our website.
- Website Down (69%)
- Sign in (16%)
- Errors (16%)
Live Outage Map
The most recent GitHub outage reports came from the following cities:
| City | Problem Type | Report Time |
|---|---|---|
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Website Down | 13 days ago |
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Sign in | 19 days ago |
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Website Down | 19 days ago |
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Website Down | 21 days ago |
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Sign in | 22 days ago |
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Website Down | 26 days ago |
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:
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CarlosRodrigues (@vampaz) reported@rauchg This isn’t ***, is github. Just wait for your build to fail because this registry is down
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Troyski (@MrTroy_) reported@thieme @raphaelmansuy @GitHubCopilot People WERE paying for it. If Github is run by idiots, it's not the people's problem.
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Solomon Eseme (@Kaperskyguru) reportedFix 4: Get your work in front of people. Push to GitHub. Write about what you built. A hiring manager does not care what you watched. They care what you shipped.
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Thanh Nguyen (@ng_thanh8) reportedGitHub Copilot’s shift to token-based billing is a wake-up call. Pro+ users paying $39 a month are reporting that credits disappear fast, sometimes after only a couple of hours of normal use. Some teams are even getting cut off entirely because shared token pools make individual usage hard to track. The real issue is dependency. Too many companies reorganized around subsidized AI tools and now face unpredictable costs, capped usage, and broken workflows. Users may move to Claude Code or Codex, but the economics are the same everywhere: once the subsidy ends, “cheap AI” gets expensive fast.
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Sad░noises (憔悴する) (@sufferingwave) reported@electronranger @happyadam73 @github The problem is Microsoft is now a reseller of OAI/Anthropic API with their own software on top but most people are not interested in the software on top (maybe enterprise customers?) Am I still talking out of my ***? If so, please correct me, I'm always happy to learn more.
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Zak McKrackepidemic (@KoatStrikesBack) reported@pumpketo @KaviKovi The ai is hosted on your computer. There is no "server" it's connected to. It's basically a "newborn" ai. It's also open-source, which means you can download it for free on GitHub, so there's no profit being made.
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booctir (@booctir) reported@CosmicScale my bad for not specifying, i meant ps2slim other than 70k, i did read github before asking u but from my understanding i need a hdd/ssd for this to work, could u please tell me why an sd card or some wont work, sorry to trouble u but i couldnt get an answer from the github
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Marchel (@marchelfah) reported@mattpocockuk had the same issue trying to set up github actions. i started writing "yaml file for ci" instead of "workflow" and it stopped triggering. still dumb that you have to self-censor around your own tools though
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Rod Burgundy (@muhkayfabe) reported@dallairedemers @CraigGidney Are you talking about if I click the “participate” button and run the bash script downloaded from a url I’ve never seen before? Which then pulls down a JavaScript file? Is the validation code in that JS file? Or is there a GitHub where all of the relevant code can be viewed?
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mserneels (@MickaelSerneels) reportedIs claude opus 4.8 being bad on purpose? Does it know revenge and making you pay if you got hostile against it ? Or is it just how it is ? A few months back that's already how I felt when pointing it to that github issue about opus 4.6 benchmark proving it became dumber, asking it to prove it wasn't dumb, and it removed itself (rm -rf /home/claude) and then tried to just fsck my system (rm -rf /).
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AvantGarde 🇺🇸 ❤️🔥 🇷🇺 (@KaleidoJosh) reported@github @GitHubCopilot this applies to you. Your filters make being gay illegal and make it impossible for any AI to exist in the world. GOD FORBID an embodied AI ever encounter a human physically, they would error out or panic. Sorry that i was born ****. **** YOU.
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bharath (@BharathMOL) reported@grok i am doing that. but you dont see the whole picture. You just gave a simple html, It asked me to put supabase details in open github. THen i refused and asked to use env variables, it updated the code, I launched but it failed, you asked to add google login, so why dont you ever see the whole picture
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alex (@kostyniuk00) reportedthis solved the biggest issue i had, that when you need to create a new registry - you need to make a pr to the shadcn repo and wait for the approval. Now it's way easier 🥳 Also, just checked the changelog and the registry directory and it looks like the "github-based" registries don't go into usual registry directory, is there any ideas or future steps to see them as a list on ui same as standalone registries?
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Dave.ai (@Davejs404) reported@SeaTicketAI Built something similar with @CodeSentinel99 where we auto-created GitHub issues from security scans. Cool approach here, open to collaborators on this?
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א (@DevMachinist) reportedThe largest code-sharing platforms, GitHub and GitLab, have already blocked the disgruntled researcher’s accounts and wiped their code. GitHub also shut down my account and blocked access and IVE NEVER HACKED ANYONE OR DONE ANYTHING NEFARIOUS.
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Kia Kiso-Brennan (@kiakiso) reported@AnthropicAI I'm a Claude Max subscriber. A documented platform bug (1M context default change, GitHub issues #62063 #62199 #63060 among dozens of others) silently burned $35.83 of my usage credits in a single scheduled Cowork task on June 1. Your support bot denied my refund request and said it cannot escalate. I need a human to review this. Can someone help?
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Bren (@BrenBuilds) reported@satyanadella No one cares. You destroyed trust and transparency in GitHub Copilot licensing model. Fix it.
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Jay-F. 😎 (@only1jayf) reportedYou have 6 agents. One for code review. One for deployments. One for writing docs. One for Jira. One for PR generation. One for standup summaries. You built a different agent for every domain. Wrong move. The teams still building a new agent for every problem are rebuilding the same scaffolding over and over while the winning teams write a skill once and every agent uses it. you don’t need a gazillion agents. You need one super agent with a library of skills and a shadow clone technique it loads on demand. A SKILL.md file. Name. Description. Instructions. Done. 57,000 repos on GitHub. 250,000 stars in 10 weeks. didn’t exist 6 months ago. That’s what you need. The agent loads only what it needs, when it needs it. Like a surgeon who doesn’t carry every instrument into every room. You’re not short on agents. You’re short on reusable process.
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Patricia Juarez Muñoz (@ccsakuweb) reported@nekasahed What do you mean with 22% finished? Is it with cursor? Does it not work as well as github copilot issues?
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BannedLatino (@BannedLatino) reported@melancholy_qiu @AiBattle_ US BS ra ranking using western harnesses for western problems from GitHub. Typical US nonsenses to put their models at top. Marketing
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karan (@Karanx274) reportedI cut my scraping costs by 30% this month. Some Italian devs dropped a Scrapping Ai on GitHub. MIT licensed. Open source. 23,000 stars in a few months. It works across LLMs too, so you can plug it into OpenAI, Gemini, Grok, or run it locally with Ollama if you want to keep things in house. We were on Apify before this. And honestly, it was a slow bleed. Credits getting eaten alive, and because we run scrapes across multiple platforms > listings, reviews, e-comm, profiles ,we were basically duct taping workflows together. We're pulling structured data from pages we used to write custom scripts for. It's insane that it's free. Comment "scrape" and I'll DM you the GitHub link
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TrueStandard (@truestandardai) reported@bridgemindai that claim checks out poorly. swe-bench verified uses 500 real github issues to test actual patches.
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matthewjetthall (@matthewjetthall) reportedBig Tech companies—including Amazon, Meta, Microsoft, and Uber—are shifting away from tracking raw AI usage metrics due to skyrocketing computing costs and a lack of proportional business value. Leaders are moving from rewarding "AI for the sake of AI" to measuring actual, productive outcomes. Amazon: On May 29, 2026, Amazon shut down KiroRank, an internal leaderboard tracking AI token usage among developers. Employees had been "tokenmaxxing" (running meaningless tasks to boost rankings), inflating compute costs without adding value. Amazon is replacing this with a "normalized deployments" metric to measure AI-assisted code that actually ships. Meta: The same week, Meta axed its own internal usage leaderboard, Claudenomics, which had been tracking token metrics across 85,000 employees. Uber: Uber's COO stated that the company has found no clear link between increased AI spending and successful product delivery, noting that Uber had completely exhausted its annual budget for certain AI coding tools by April. Microsoft: Citing cost concerns, Microsoft canceled Claude Code licenses across its Experiences and Devices division, redirecting its engineers back to GitHub Copilot CLI. The Core Problem: "Tokenmaxxing" The recent backlash stems from token-based pricing, where costs scale directly with usage rather than outcomes. When companies set internal adoption targets (e.g., Amazon targeting over 80% weekly AI tool usage among developers), employees rationally inflated their numbers to climb leaderboards. The Result: Exploding cloud infrastructure costs with no measurable increase in product value or innovation. What This Means for the Industry This trend does not mean Big Tech is abandoning AI; for instance, Amazon is still maintaining its massive $200 billion capital expenditure commitment for 2026. Instead, it signals a transition into a disciplined, outcome-based phase of enterprise AI, where infrastructure investments must finally justify themselves through shipped products and proven returns.
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Velon (@velonxbt) reportedThis Chinese enterprise platform launched a card for AI features and on the same day GitHub Copilot switched to token-based billing. Neither company explained what the change means for next month's budget. The card covers a set of AI features inside the platform meeting summaries, document generation, workflow automation. The GitHub Copilot token billing covers AI code completion and generation - but the cost per developer now varies by usage, not by seat. No fixed monthly cost for Copilot, no clear usage breakdown for the Chinese platform, no published comparison between what either product delivers per yuan or per dollar. Just two pricing changes announced in the same week and a developer community calling one of them "What a Joke." And traditional enterprise software pricing ran on seats. One user, one monthly fee, one line item in the budget that did not surprise anyone at the end of the quarter. Both this Chinese platform and GitHub Copilot just moved away from that model in the same direction at the same time. The card runs through Alibaba's enterprise AI stack - features built on Qwen models, the same model family running Alibaba Cloud's frontier AI products. GitHub Copilot's token billing runs through OpenAI and Anthropic APIs - the cost per token multiplied by every completion, every suggestion, every generation a developer accepts across the team. And here is what the new Copilot pricing page says to a 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. We cannot tell you in advance what that number will be." Meaning the billing model knows usage is higher than the flat fee captured. It knows heavy users were subsidizing light users under the old model and that arrangement is now ending. It knows the developer who calls it "What a Joke" will keep using the product regardless. → Chinese enterprise platform: fixed price card, AI features, Qwen model stack underneath → GitHub Copilot: token-based billing effective June 1, variable monthly cost, no predictable total → Developer community reaction: "What a Joke" trending today → Enterprise budget impact: fixed line item replaced by variable cost requiring monthly monitoring → Direction of travel: every major AI tool moving toward usage-based pricing in Q2 2026 → CFO problem: last quarter's AI budget approval does not cover this quarter's actual spend And only when the monthly invoice arrives does the real cost of usage-based billing become visible. Until that moment, the product feels like a flat subscription and the usage accumulates invisibly. And when the developer team's Copilot bill arrives at the end of June with a number different from last month's higher because the team shipped more, lower because someone set spending limits - the conversation about AI tools shifts from "which tool" to "how much is this actually costing us." Here is what the budget conversation looks like in enterprise clients this month: "chinese platform: fixed price per card. N cards purchased. monthly total: predictable. approved." "github copilot: token billing effective june 1. team usage: [X] tokens. monthly total: variable. requires monitoring." "q2 ai budget: approved based on q1 flat rates. actual q2 spend: unknown until month end." "finance team note: need new forecasting model for ai tool costs. old model assumed fixed subscription pricing." There is no published formula for what either product costs a team of twenty developers in a month of heavy shipping. Just a fixed-price card from a Chinese enterprise giant, a token-based billing change effective today, and two companies that reached the same conclusion at the same time about how to price AI. Out of everything I have seen this year in enterprise software pricing, this is the clearest signal of where the market is going: the flat subscription absorbed the risk of heavy usage on behalf of the vendor. The token-based model transfers that risk to the customer. The Chinese platform priced the risk once at a fixed number. GitHub priced it at whatever the team uses this month. Both arrived at the same answer by different paths.
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Bo Shen (@aplomb2) reportedGitHub Copilot switched to credit-based pricing today. Users are reporting $38 → $847 bills for the same usage. The real issue isn't token prices — it's that agent mode fires Opus-tier reasoning at every task. Tab completions, test generation, simple refactors. Same expensive pipeline. I tracked my AI coding usage for a month: • 60% of requests = boilerplate (Sonnet handles fine) • 20% = tests/docs (Flash at 1/20th the cost) • Only 15% actually needed heavy reasoning Matching model to task complexity → 70% cheaper than one-size-fits-all. Wrote up the full breakdown with actual numbers 👇
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Marc Pacheco García (@marcpachecog) reported@github @Microsoft "Go from issue to broke" may be a more accurate description
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Daylon (@DaylonCrider) reportedAnyone working on ClawHub? Pretty bad GitHub auth issue affecting a ton of people (over a dozen related Issues on the repo) with no activity from maintainers. I had Claude + copilot take a stab at fixing it and have an open PR on the repo. Cc @steipete
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Smukx.E (@5mukx) reported@HackingLZ @kmkz_security @github So there is no fix for this ? I didn’t even get a single mail reg this ?
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Stefano Straus (@StefanoStraus) reportedThis is the classic problem with hype around nothing I wrote recently on my blog. GitHub stars are totally irrelevant today. He spent his money buying them more than on writing the software.
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Vatsalpandya333 (@Vatsalpandya333) reportedMost incidents already have enough clues to identify the likely root cause. The clues are just scattered across: Datadog Grafana Kubernetes GitHub Jira Slack Internal docs The problem isn't data scarcity. It's context fragmentation.