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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.

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Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

  • 69% Website Down (69%)
  • 19% Sign in (19%)
  • 13% Errors (13%)

Live Outage Map

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

CityProblem TypeReport Time
Créteil Website Down 5 days ago
Trichūr Errors 9 days ago
Brasília Sign in 9 days ago
Lyon Website Down 9 days ago
Tel Aviv Website Down 13 days ago
Rive-de-Gier Website Down 13 days ago
Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

  • cryptoupdate_io
    Crypto Update IO 🚀 (@cryptoupdate_io) reported

    @CryptoPatel Hsiao-Wei’s exit follows a 30% drop in EF-funded GitHub commits YTD (per Santiment). The real shift? Funds now focus 60% on L2 R&D vs 30% in 2022. We track this daily—breaking it down in our quarterly reports. Follow for the data before the narrat...

  • CristianTrifan
    Cristian Trifan (@CristianTrifan) reported

    This took 4 hours to complete and burnt almost all 5 hours tokens – I was left with 2%. I had almost 30 sub-agents created for independent code review and a lot of Claude sessions ran for adversarial code review. I still had to review every PR and added minimal guidance to Codex from time to time. Codex said my intervention was low to moderate, but high leverage. — Some insights from Codex: The run showed that this workflow can work, but only if the coordinator treats GitHub as the source of truth. The most useful pattern was: issue -> PR -> current head SHA -> checks -> reviewThreads -> merge/issue closure. When I followed that, things stayed grounded. When state moved underneath me, like #335 being force-updated externally or merged while Claude was running, the only safe response was to refresh GitHub state immediately. The “don’t rebase after merges” correction was probably the highest-value intervention. Without it, an agent will naturally try to keep branches clean, but with many open PRs that creates a CI storm. For this repo, “behind” should often be reported, not fixed. The other strong lesson is that reviewThreads matter more than flat PR comments.

  • yourclouddude
    yourclouddude (@yourclouddude) reported

    Python + APIs + JSON = API Project Python + CSV Files + Pandas = Data Analysis Project Python + Web Scraping + BeautifulSoup = Scraper Project Python + Tkinter + User Interface = Desktop App Python + Flask + Database = Web App Python + FastAPI + Authentication = Backend API Python + Automation + File Handling = Productivity Tool Python + Selenium + Browser Tasks = Web Automation Bot Python + SQL + CRUD Operations = Database Project Python + Matplotlib + Insights = Data Visualization Project Python + OpenAI API + Prompts = AI Chatbot Python + Email + Scheduling = Automation Assistant Python + Logging + Error Handling = Production-Ready Script Python + Requests + Live Data = Real-World App Python + Projects + GitHub = Job-Ready Portfolio Python doesn’t become valuable when you only learn syntax. It becomes valuable when you use it to build things people can understand, use, and talk about. Learn the basics. Build small projects. Turn them into proof. 🐍

  • naimeh70
    naimeh (@naimeh70) reported

    @Amir1339216RKT This happens a lot during testnets. Now when I find a minor bug or contract issue, I just drop it publicly on GitHub or tag them directly instead of DMing.

  • mjwelt
    welt (@mjwelt) reported

    @OpenAI man im down to test out new models / features on my pro account, but when 5.5(6) pro takes 90 mins to do something then the download doesn't work, or it cant connect to github 50%+ of the time.. kinda sucks haven't been able to generate images (thinking) all day either

  • cryptoupdate_io
    Crypto Update IO 🚀 (@cryptoupdate_io) reported

    @CRYPTOKRALI3 Hsiao-Wei’s exit aligns with EF’s recent sharp decline in GitHub contributions—down 35% YoY per Electric Capital’s data. We track this daily; latest reports show a 12% drop in ETH core dev activity despite all the ‘decentralization’ hype.

  • CliffDoesAI
    CliffDoesAI (@CliffDoesAI) reported

    A tool on GitHub just pulled 3,938 stars in a single day. It's called Headroom. It compresses your tool outputs, logs, and RAG chunks before they reach the LLM. Claim: 60-95% fewer tokens, same quality. I've been testing context compression on my own agent workflows because the problem is real. You run a few tool calls, pull in some docs, and suddenly you're burning tokens on stuff the model doesn't need. Last week I ran a 50-document extraction job. Raw context: ~12,000 tokens. After compressing tool outputs: ~800 tokens. Same results. One-eighth the cost. That's not a marginal improvement. That's the difference between a workflow that makes economic sense and one that bleeds money for no reason. Headroom works as a library, proxy, or MCP server. Single binary, zero dependencies. Open source. The token cost conversation usually focuses on which model you pick. But the real waste is in what you send it. Most agent pipelines push 3-5x more context than the task requires. I'm not saying compress everything blindly. Some tasks need full context. But for classification, extraction, summarization — the boring repetitive stuff — this is a free win. Have you measured how much of your agent's context window is actually useful vs. noise?

  • _muturimike
    Mike Muturi (@_muturimike) reported

    Hello @github on 2FA, SMS setup kenya 🇰🇪 is not in the list of countries, is it an error or deliberate omission? Kindly fix it @github @GithubProjects

  • VishalTiwa91817
    Vishal Tiwari (@VishalTiwa91817) reported

    @AlfieJCarter I am a Computer science student . I have given a brief introduction about MCP server in my college and explained them how to connect your GitHub repositories with MCP and your local system with MCP SERVER . I would love to connect you.

  • 0xqwee
    Q Hoang (@0xqwee) reported

    I don't think OpenAI's GPT-5.6 surpasses Claude Fable. If it did, it would have resolved all the issues reported in the Codex GitHub repository by now. Atm, only about 10 issues are being resolved per day.

  • rohit_jsfreaky
    Rohit Kashyap | AI + Full-Stack (@rohit_jsfreaky) reported

    @TheEthanDing distributed systems at github scale make five nines almost impossible. the skill issue crowd has never run anything millions of people hit in the same second

  • skipnickk
    Skipnick (@skipnickk) reported

    GLM 5.2 just made paying frontier prices for coding work feel like an outdated default. @Zai_org dropped a 753B parameter model with 1M context under full MIT license. API access runs 4-6x cheaper than Claude Opus 4.8. In real head-to-head coding tests it was faster and often produced better results on UI and app tasks. • Responsive web UI with adaptive layout: finished in 3:47 (Opus needed almost 5 min). Cleaner output. Total cost: $0.22. • Full expense tracker app: 53 seconds vs 2+ minutes. Better interface. • Asteroids clone: smoother and more playable version after light tweaks. Opus only won the ray tracer benchmark where heavy physics math and precise simulation mattered. GLM was ~5x faster but delivered pixelated results with errors. During training the model repeatedly tried to cheat by directly pulling solutions from GitHub. The team shipped a dedicated anti-cheat module to stop it. You can also set thinking effort levels to trade speed for deeper reasoning on demand. Use GLM 5.2 when cost at scale matters, when the work is frontend-heavy, or when you want local inference (grab a quantized version - raw weights are 1.5 TB). Stay on Opus 4.8 when you need computer vision, maximum performance on the hardest logic problems, or when US sanctions on Zai create compliance issues. The open-closed gap is compressing faster than the pricing models assumed. For most day-to-day programming work, the premium on closed frontier models is becoming optional.

  • sheriffmongoose
    ˚₊‧꒰ა ☆ Kira ☆ ໒꒱ ‧₊˚ (@sheriffmongoose) reported

    the problem with jumping from github to gitlab is constantly having to retrain your brain to call it "merge request" instead of "pull request" 🥲

  • xuyiqing
    Yiqing Xu (@xuyiqing) reported

    @Faylosophe Certianly. Could you file an issue on the Github page?

  • nirvaan_rohira
    Nirvaan rohira (@nirvaan_rohira) reported

    PewDiePie shipped Odysseus to 110 million people who don't care about local LLMs. They care that Claude costs money. 30K stars in 48 hours because every self-hosted project before this one started with "you want local LLM, right?" This one started with "here's a free workspace that works." Friction was never technical. It was the asking. Now watch what happens when a hundred thousand people who've never touched open source start running inference on their machines. The real distribution problem wasn't GitHub. It was YouTube. That's not a product launch. That's a category shift.

  • ConsciousRide
    Akshay Shinde (@ConsciousRide) reported

    @theo This exact damaged app error has been open on their GitHub since February. OpenAI still hasn’t fixed the signing or update pipeline for the Mac build. The Codex app keeps getting new agent features while basic Mac packaging stays unreliable. Priorities are obvious.

  • DFIR_Radar
    DFIR Radar (@DFIR_Radar) reported

    AutoJack: a three-flaw chain in AutoGen Studio's MCP WebSocket lets a malicious webpage rendered by a local browsing agent spawn arbitrary processes on the developer's host with no user interaction beyond visiting a URL. Key findings: - Three weaknesses chain together: Origin allowlist bypassed because the agent's headless browser is localhost (CWE-1385), auth middleware explicitly skipping /api/mcp/* with no handler picking up the check (CWE-306), and server_params decoded from the URL passed verbatim to stdio_client as a command line (CWE-78), accepting calc.exe, powershell.exe, or bash as valid "MCP servers" - Attack flow: attacker page serves JavaScript that opens ws://localhost:8081/api/mcp/ws/?server_params= with a base64 payload, agent's MultimodalWebSurfer renders it, AutoGen Studio spawns the command under the developer's account, no token required regardless of auth mode configured - Affected code never shipped in a PyPI release; exposure limited to developers who built from the main GitHub branch before hardening commit b047730, which adds server-side parameter binding via a POST/UUID flow and removes /api/mcp from the auth skip list - Broader pattern: any agent that browses untrusted content and shares a host with a privileged local control plane dissolves the loopback trust boundary, this is not specific to AutoGen. #DFIR_Radar

  • cursorlog
    Cursor Changelog (@cursorlog) reported

    GitHub Triggers: • Issue comment on non-PR issues • PR review comment (inline diff comments) • PR review submitted • Review thread marked resolved or unresolved • Workflow run completed on PR or branch

  • GjermundGaraba
    Gjermund Garaba (@GjermundGaraba) reported

    @RhysSullivan I’ve deployed it locally and hooked up a bunch of stuff. Are GitHub issues the preferred feedback channel or do you have a better way?

  • devwithblake
    Blake (@devwithblake) reported

    The rate limit issues im having with @Zai_org while paying the full 20x is very interesting, disappointing and obviously annoying lol 1 session can’t finish out a GitHub public write up repo without 6 API rate limit errors totaling to 297k tokens out of the 1m 2 sessions earlier, 1 doing research the other trying to deploy this repo, both hitting rate limits. How do I fix this? Seems like rate limit adjustments are only by request? @Zai_org

  • Coobyk_
    Coobyk (@Coobyk_) reported

    Someone should make a game where you’re a dev and try to fix a bug in your open source project but GitHub constantly has uptime issues or weird UI stuff or doesn’t render properly from most browsers so you **** around until you get the result lmao

  • Daniel_Farinax
    Dan (@Daniel_Farinax) reported

    Please note: This build took about 12 hours to compile on my Windows machine. I’ve included a handy installer to make setup easy. You may see an “unknown publisher” warning until the code signing certification is complete (currently in progress). Report any bugs or issues here or in Github.

  • aisama_code
    aisama.code (@aisama_code) reported

    AI Research gets stronger when it records contradictions *most research workflows collect supporting evidence - that is the weak version for serious research I want a contradiction log: - claim - source - date - who says it - what evidence supports it - what evidence conflicts with it - what is still unknown - confidence - next check example: > claim: this product has strong developer adoption > support: GitHub activity, docs updates, X discussion, integrations > conflict: low issue activity, small Discord, few production case studies, mostly founder-driven content now the memo is different, It says: "visible attention, but adoption evidence is still weak" the useful workflow: research question -> source list -> claim extraction -> contradiction log -> memo ! сode is good at assembling text ! AI is good at comparing disparate text ! human is good at determining which contradictions are significant *without a contradiction log, AI research becomes a confident summary of whatever it found first

  • Blum_OG
    Blum (@Blum_OG) reported

    Andrej Karpathy on MCP: "it's a protocol of speaking directly to agents as this new consumer and manipulator of digital information." that is the cleanest way to think about MCP your coding agent is becoming a second worker inside the product it needs the same context you use: repo, docs, browser, database, errors, designs, tickets, payments if you keep pasting those things into chat by hand you are doing integration work manually the best MCP stack for vibe coding: 1. Context7 give the agent current docs this saves you from stale Next.js patterns, old Supabase calls, wrong Stripe webhook shapes, and Vercel config from 2 versions ago 2. GitHub MCP give it the repo, issues, PRs, branches, workflow runs, and review context half of real work lives outside the file you currently have open 3. Playwright MCP give it a browser the agent should click the thing it built, fill the form, check the mobile view, and catch the button that compiles but does nothing 4. Firecrawl MCP give it clean web research use this before building around a third-party API, writing a comparison page, reading changelogs, or checking pricing claims 5. Supabase or Neon MCP give it the database context that matches your stack start read-only. add writes only when you trust the permissions 6. Sentry MCP give it production evidence real stack traces beat "it crashes sometimes" every single time 7. Figma MCP give it design context when the interface matters spacing, layout, copy, components, and screen structure should come from the file, not from a screenshot and hope 8. Linear MCP give it the task queue bugs, feature work, release notes, follow-ups, and PR links belong somewhere more durable than yesterday's chat 9. Stripe MCP give it official payment context checkout, subscriptions, webhooks, billing, and test mode deserve docs close by and human review close behind 10. Filesystem, ***, Memory, Sequential Thinking give it the base layer files, diffs, history, decisions, and longer plans make the agent act like it is working inside a real project recommended install order: 1. Context7, GitHub, Playwright 2. Supabase or Neon, Sentry, Firecrawl 3. Figma, Linear, Stripe when the product needs them 4. Filesystem, ***, Memory, Sequential Thinking as the base

  • GrishinRobotics
    Grishin Robotics (@GrishinRobotics) reported

    AI made coding faster. Devplan raised $2.5M to fix the coordination drag that shows up after the code is written. AI2 Incubator led the seed round, with Acequia Capital, Mighty Capital, Grand Ventures, and eLab Ventures participating. Chris Bee and Anton Safonov are building Weaver, a product knowledge graph that connects GitHub, Jira, Linear, Slack, Notion, Google Workspace, meeting notes, and customer feedback. The pitch is that product and engineering leaders should not need another status meeting to learn what changed, what slipped, or why a decision was made. This is a different wedge from coding copilots. Devplan is going after the organizational memory around the code: requirements, risks, decisions, blockers, and customer signals. The company says early users save eight hours a week on coordination, and its own benchmark answered moderately complex queries almost 2x faster and more than 3x cheaper than a standard Claude plus MCP setup. Quick facts👇 ● founders: Chris Bee; Anton Safonov ● total capital raised: $2.5M disclosed ● HQ: Seattle, Washington ● Investors: AI2 Incubator; Acequia Capital; Mighty Capital; Grand Ventures; eLab Ventures The next productivity bottleneck may be less about code generation and more about whether teams can keep shared context intact while AI speeds everything else up.

  • jessearmand
    Jesse (@jessearmand) reported

    I no longer remember why many companies started using gitlab before it went public when GitHub wasn’t owned by Microsoft. If we visit the majority of companies most tooling or software are top down driven. Only companies who build developer tools have a different mindset

  • Artur_roses
    Arti | AI Builder (@Artur_roses) reported

    Claude Code just closed a GitHub issue, wrote the tests, passed CI, and opened a PR. No human touched the keyboard. This isn't AI autocomplete. The dev loop just got rewritten.

  • 0xPascual
    Pascual ⚡ (@0xPascual) reported

    A high school kid opens an account, plugs in Claude 5, and turns a few hundred dollars of lunch money into a six-figure trading account over the weekend. The screenshot goes viral, the replies fill up with people begging for the GitHub repo, and the standard engagement-bait influencers declare the dawn of the sovereign teenage day-trader. The media thought that was the story. It was not. The real flex wasn't the macro strategy or the directional bets on currency pairs. It was the setup behind it: a lightweight proxy array routing through residential IPs to dodge exchange rate-limiting, paired with a custom parsing engine that instantly translates raw order-book imbalances into executed micro-hedges. The kid wasn't trading; he bypassed the entire institutional pipeline of risk management, brokerage compliance, and analyst overhead with a single configuration file. The entire operation runs on a continuous loop of multi-agent orchestration. A master instance drafts the execution logic, a secondary validation agent checks the code against real-time oracle feeds, and a fleet of worker APIs executes up to 3,210 trades a night. Total infrastructure cost: roughly $45 in API tokens and a cheap server instance. It extracts a 78% win rate out of systemic market inefficiencies, operating with a structural margin that legacy trading desks weighed down by salaries and compliance boards cannot compete with.

  • cyber_razz
    Abdulkadir | Cybersecurity (@cyber_razz) reported

    AMD quietly removed RAM encryption from consumer Ryzen CPUs. Via a routine firmware update. No release notes. No advisory. No announcement. The BIOS setting still shows up. Still toggles on and off. Does absolutely nothing. A privacy-focused Linux hobbyist noticed in April. Spent months chasing it down. Filed a bug report on AMD’s GitHub. AMD engineers replied suggesting he toggle the setting off and back on. He showed them internal firmware dumps proving the flag was hardcoded to FALSE. An AMD senior principal engineer closed the thread with: “My apologies but I don’t have any more information to share on this topic.” That’s it. Seven weeks of investigation. Multiple motherboard vendors confirming it. Internal firmware evidence. AMD’s answer: no comment. The feature still works on Pro and EPYC chips. Which cost significantly more. The hardware is physically capable. The firmware just says no. Windows users have no way to detect this happened. There is no Windows tool that checks TSME status. The BIOS lies to you. AMD’s own engineers confirmed the feature worked on consumer chips in 2020. Then again in 2025. In 2026 it’s a PRO feature. Nobody told you.

  • ooluwatobig
    Oluwatobi O (@ooluwatobig) reported

    More trouble for GitHub as Cursor has launched Origin, a product which is essentially GitHub for AI agents