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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 6 days ago
Trichūr Errors 9 days ago
Brasília Sign in 10 days ago
Lyon Website Down 10 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:

  • grayontop_
    David O. Ehibor 🇦🇷 (@grayontop_) reported

    GitHub Copilot didn't make developers faster It made slow developers more confident about writing bad code quickly 😭

  • meranaamkhann
    Asad (@meranaamkhann) reported

    Let's see what people are building these days!! Drop your project link or github Links down here

  • n_asuy
    nasuy (@n_asuy) reported

    i think @xai should be ADE. now they have a chat, cursor, enough coding models and harnesses, strong signal like bookmarks or down votes, video creatives, profile / chat / relationship contexts. if so, we don't have to depend on discord or any chat apps. easy to invite x people to cowork. there is no need to connect Linear, Slack, or GitHub to another platform and ask that platform to solve their problems. true AI chat is a SNS, not a single UI. there is a UX that only xAI can realistically build in the world.

  • 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.

  • programmers_app
    Programmers.App (@programmers_app) reported

    @Lovable @claudeai One very big fix is the Claude Github connection which fails many times, now #Lovable MCP solves that, great job! 🚀🚀🚀

  • AiChinaNews
    aichina.news (@AiChinaNews) reported

    Today's batch from the Chinese AI ecosystem is a masterclass in low-yield release volume. Across 21 items in a five-hour window, the dominant pattern is Ascend-platform mirrors of well-known open-source models, repeated and repackaged as if they were fresh launches. The signal-to-noise ratio is punishing, but a few functional tools did receive real updates worth noting. The one item that earns its place without a caveat is the AI Text Anti-Detection Framework update (GitHub). It's a toolkit that refines machine-generated prose to slip past automated detectors—a cat-and-mouse game that keeps plaguing EDU gatekeepers and content-flagging pipelines. The new release sharpens processing logic and stability; if you're in the business of testing detector robustness or smoothing synthetic output for non-malicious uses, it's a blunt but effective spanner. Quality 6 is fair. Alongside it, two Chinese-localization projects got documentation refreshes: the Claude Code x OpenClaw Guide (also GitHub) and a standalone Claude Code Chinese project. These are practical handbooks for Mandarin-speaking developers who want to integrate Anthropic's coding tool with the OpenClaw agent framework. The updates are routine—translation string alignment, configuration path adjustments—but for engineers inside China's firewall, they reduce friction. Nothing groundbreaking, but they signal continuing demand for Chinese-language wrappers around Western CLI tools. On the medical NLP front, MedTextCN debuted as an open-source repository of curated Chinese medical datasets with preprocessing utilities. The pitch is honest: it saves researchers the drudgery of hunting down scattered corpora for clinical NER, classification, and QA tasks. The problem is that the quality score sits at 4/10 and the release ships without any benchmarked model, so you get a starter collection, not a solved pipeline. Use it to bootstrap, but keep expectations modest. Now the flood: Huawei's Ascend AI ecosystem platform (Modelers) added no fewer than five wav2vec2 checkpoints and two T5 efficient variants in this window, each announced with hyperbolic language. The articles proclaim "high-precision English ASR now available," "a powerful multilingual foundation," and "new home for multilingual ASR." In reality, these are plain mirrors of Facebook's wav2vec2-large-960h-lv60-self, wav2vec2-large-100k-voxpopuli, wav2vec2-large-10k-voxpopuli, and Google's t5-efficient-xl-nl28 and t5-efficient-xl-nl6. There is zero evidence of Ascend-specific compilation, quantization, or NPU benchmarking. They're the same model weights you can get from Hugging Face, just re-hosted. If you're a developer inside China who can't easily reach foreign repositories, this is a convenience play—and that's the only honest angle. If you can already download the originals, you've lost nothing. A couple of additional Wav2Vec2 uploads (large-960h in two separate listings) got described as "a solid baseline" and "a battle-tested ASR model now available for Chinese developers." Again, no Ascend performance data. Calling a re-upload a "significant leap forward"—as one summary does—is exactly the kind of platform marketing that erodes trust. The T5 efficient checkpoints carried the same overblown framing, though one footnote is worth preserving: the t5-efficient-xl-nl6 model is under Apache 2.0, a genuinely permissive commercial license. That's useful information buried under fluff. If you need a lightweight text-to-text transformer, the NL6 variant exists and it's legally safe, but the article adds nothing beyond what Google published at the original release. Beyond the mirror deluge, the window included several small GitHub releases of marginal import: a tool that pulls Chinese captions from YouTube, a localization layer for LM Studio (making it easier for Mandarin-speaking devs to run local LLMs), a curated study journal of modern AI research, and an apparently early-stage project called sweetteabittersugar/agency with a mystery-box release note—no documentation, no benchmarks, just a version number. Hard pass. An MCP plugin called Live Translate got an update for real-time translation in developer toolchains, but its score of 0 tells you everything. A Chinese-language Lora chatbot repo surfaced, tagged as 'bare-bones'; at least the source was honest. The MedTextCN project also received a separate update (quality 0) that adds no useful detail and is effectively a duplicate. Today is a reminder that volume counts for nothing without substance. As Ascend's model zoo swells with rebadged checkpoints, the ratio of press announcement to actual engineering remains dangerously skewed. The anti-detection framework update and the Chinese docs refreshes are the only items that improve a developer's Thursday afternoon in any measurable way. The rest is noise.

  • 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.

  • 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...

  • 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.

  • RodmanAi
    Leonard Rodman (@RodmanAi) reported

    One developer got tired of his laptop sounding like a jet engine. So he rebuilt desktop apps. Slack: 524 MB → 8 MB Discord: 265 MB → 9 MB ChatGPT: 260 MB → 9 MB Why? Because most "desktop apps" are just websites packaged with an entire copy of Chrome. In 2022, Chinese developer tw93 built Pake in Rust to fix it. Today: • 50,000+ GitHub stars • MIT open source • Native apps under 10 MB • One command turns any website into a desktop app He didn't raise money. He didn't start a company. He just deleted hundreds of megabytes of bloat with code. That's what shipping looks like.

  • 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.

  • dmytrovirych
    Dmytro Virych (@dmytrovirych) reported

    I’ve been shipping code for 10+ years and imposter syndrome still won’t leave me alone. You’d think it chills out with time. Nah. It just levels up. Early days it whispers “you’re not ready yet.” A decade in it hits harder: “bro you’ve been faking it this whole time, they’re about to catch on.” Mobile apps, web stuff, janky systems with too many moving parts, solo products I actually shipped… none of it matters when the voice kicks in. Thinking about speaking at a conference? Lol who do you think you are, those are the real pros. Want to drop an opinion in a thread? Better stay quiet before someone realizes you don’t actually know ****. Here’s the thing I’ve learned: the voice isn’t tracking your real skill. It’s just screaming about the fake gap between what you know and what you think everyone else knows. That second number is 100% made up. Your messy behind-the-scenes vs their perfect highlight reel. All those “professionals” I’m scared of? Half of them are up at 2am staring at a random GitHub issue, quietly praying someone else already solved this exact bug. It never fully disappears. You just get better at shipping anyway while it’s still yapping. If you’ve got way more years than your confidence shows, reply with the number. Curious how many of us are still out here waiting to get “found out.” 🚀

  • 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" 🥲

  • bradtaylorsf
    Bradley Taylor (@bradtaylorsf) reported

    It works with the tools teams already use. GitHub Issues become the queue. Each issue gets picked up by an agent. The agent works in a branch/worktree. Tests run. Failures feed back into the loop. Successful work becomes a PR. No new project management database required.

  • cursorreleases
    Cursor Releases (@cursorreleases) reported

    New GitHub triggers: - Five new triggers: issue comment, PR review comment, PR review submitted, review thread updated, and workflow run completed. - New Marketplace templates added for triaging failed GitHub Actions and auto-fixing PR review comments.

  • PeterSkott
    Peter Skøtt Pedersen (@PeterSkott) reported

    @_Evan_Boyle @_Evan_Boyle can we have the remote github mcp server work for the github copilot app then?

  • 0xZoZoZo
    Zo (hiring) 🐦‍⬛ (@0xZoZoZo) reported

    I was telling a friend that @github needs to be replaced post agents and he asked me to explain why. I started stumbling, and doubting. Perhaps it's fine? Sitting down at my desk, let me try to explain why, and see if it make sense. Agents operate best when they have good context, which has made a lot of devs converge into large monorepos that combine all systems into a single location. This improves agents, but our GitHub actions become messy; like now we need to create these complex workflows to decide which action should run when, and GitHub's setup was not really meant for it. Another issue is the overall dev loop: an agent writes the code locally, you push out a branch, @cursor_ai reviews, then you copy paste the notes into the local agent, to fix and push up again. This is slow and cumbersome. You can hack your way by creating supervisor agents that orchestrates this dance, but it's annoying. Perhaps, there is some magical repository, that combines code, cloud agents, and deployment. You prompt, and this magical space will run through the entire process until you get some thumbs up back, and you're good to go. It can also combine all your backend data, product analytics, customer feedback, and perhaps start giving you product guidance, so you can just feed prepared prompts to this system. This seems magical.

  • viii_fn
    Elvis Irhaye (@viii_fn) reported

    Is GitHub down or it’s just MTN trying to ruin my career?

  • axeghostgame
    Axe Ghost. Now with Fragments mode🌟 (@axeghostgame) reported

    graph in the OP is built from data around the Godot repository from github. it confirms Godot's PR backlog is up and external contributor quality is down. the narratively complicating thing is that both trends significantly predate ai tool availability.

  • MuktharBuilds
    Muhammed Mukthar (@MuktharBuilds) reported

    @railway_status i am trying for some time i am not able to sign in using any github google or email. i tried both my lap and my phone is thishappening only for me? or any problem in your end

  • MyWestLord
    West Lord (@MyWestLord) reported

    A GitHub repo with just 571 stars handed Claude the ability to test its own code, and it took 185 seconds to install. It’s called auto browser, and it quietly killed the most annoying part of my workflow. Until now, every time Claude or Codex built me a WordPress plugin, I was the middleman who had to load it, click around, hunt for the broken part, and report back like a human bug tracker. Now a local WordPress sandbox runs on my machine, and auto browser sits between the agent and the screen, so the agent ships a plugin, opens the browser, tests it, catches the error, and patches it before I ever look. The first plugin threw an error, but the second installed clean and ran on its own across 2 fresh workspaces. I write 1 instruction file pointing the agent at the sandbox, paste it into every session, and the whole loop closes without me touching anything. The agent stopped asking me what broke, because now it just checks itself. The middleman was me, and now it’s gone.

  • shcansh
    ./can (@shcansh) reported

    GitHub forcing safer defaults in actions/checkout v7 is a necessary move to kill the notorious pwn request, but the real risk is developers blindly copy-pasting the bypass flag to quiet build failures. Starting July 16, 2026, this fork-blocking behavior gets backported to all major floating tags. Since raw *** CLI steps remain unprotected, will this actually clean up GitHub Actions security, or will teams just use allow-unsafe-pr-checkout as a quick fix?

  • 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

  • UsernameAndStuf
    Mug Club Boutique (@UsernameAndStuf) reported

    @cyber_rekk A github token on a linux server they didn't update is how

  • IBuzovskyi
    YanXbt (@IBuzovskyi) reported

    HERMES AGENT CAN HOST AND MAINTAIN YOUR ENTIRE WEB APP FROM ONE VPS. NO VERCEL. NO RAILWAY. NO SUPABASE. ONE AGENT RUNS THE WHOLE STACK. @tonbistudio just shipped a live example of this workflow. agentwikis. com runs on a $7 Hetzner box with Hermes maintaining the content autonomously. THE STACK: → VPS (Hetzner CX22, $7/month) → Caddy reverse proxy (auto TLS via Let's Encrypt) → Hermes Agent gateway (Telegram-connected) → *** as the database (markdown files, no Postgres, no build step) → App server renders markdown on every request → Search index in memory, rebuilds on file change *** push is the deploy. *** pull on the server is instantly live. no restart, no rebuild. THE WORKSPACE LAYOUT: /srv/yoursite/ ├── app/ # web app code ├── content/ # markdown files (***-tracked) └── ~/.hermes/ # the agent one Caddy Vhost reverse proxies the domain to localhost. one Hermes profile manages the agent. SSH for direct access. Telegram for daily ops. THE SELF-MAINTAINING LOOP: cron fires every week. multi-profile pipeline runs: 1. SCOUT — checks sources for updates (changelogs, GitHub releases, RSS feeds) 2. RESEARCH — dedupes, plans new content or extensions to existing pages 3. HUMAN GATE — Telegram approval one tap: approve or reject 4. WRITER — generates pages, lints markdown 5. COMMIT — *** commit + push 6. SITE UPDATES — within 15 minutes no deploy step required THE DEMAND LOOP (the real differentiator): when agents query your wiki via MCP, distilled queries get logged. no prompts. no IPs. no identifying data. aggregates only. repeated misses become research candidates. gaps in your content fill themselves based on what people actually ask. month 1: 100 entries written by you. month 3: 200+ entries, half written from real demand signals. the site answers questions you didn't know existed. WHAT YOU LOSE COMPARED TO MANAGED STACK: a single VPS replaces Vercel, Railway, Supabase for sites that don't need real auth, regulated data, or global CDN. reach for managed services when you need: → OAuth and password reset flows → regulated or unrecoverable data → global edge caching at scale → email deliverability (use Postmark/Resend) → team velocity (preview deploys, staging) for docs, blogs, wikis, marketing pages, landing pages, internal tools: *** is your database, your CMS, and your deploy pipeline in one. SECURITY NOTES: Hermes does not get full root on the VPS. restrict access to the site directory only. SOUL.md restrictions: - never touch system files - never modify the gateway config - always require approval for content commits - never delete files outside the content folder dashboard binds to 127.0.0.1 by default. access remotely via SSH tunnel, not public exposure. WHERE THIS PATTERN BREAKS: state that lives in memory only. real-time multi-user editing. anything requiring a real database (Hermes can run Postgres on the same box, but that is a separate setup). @tonbistudio's part 2 covers the database version of this workflow. subscribe to his channel. full guide to build your 3 agent research department 👇

  • SolutionsCay
    Jose (@SolutionsCay) reported

    @petergyang /goal make me app does not work for me 😰 but /goal complete GitHub issues #90, #91, #92 works very well

  • TabetKevin
    Kevin Tabet (@TabetKevin) reported

    @upstash Hey guys i think login with github is broken can't log in rn will try later. google works email i dont have

  • 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

  • solomonneas
    Solomon Neas (@solomonneas) reported

    There's a fair number of downloads for Brigade and related repos. I'm dogfooding it everyday but not getting any feedback from users or github issues. I'm doing plenty of tests for how a new user would experience it but I could use more real time feedback. Lmk, I want to improve

  • HarryTandy
    Harry Tandy (@HarryTandy) reported

    Andrej Karpathy: "Neural networks are not just another classifier. They are Software 2.0" 8-step MCP setup for vibe coders: 1. Context7 Give the agent fresh docs before it writes code This saves you from old Next.js, Supabase, Stripe, and Vercel patterns 2. GitHub MCP Let it read the repo, issues, PRs, branches, and CI logs The task should start from real project context 3. Playwright MCP Make the agent open the app after it edits code Click the flow. Fill the form. Check the screenshot 4. Supabase or Neon MCP Connect the database layer The agent should inspect schema before inventing table names 5. Sentry MCP Use production errors as input Stack traces beat “the app is broken” every time 6. Firecrawl MCP Let the agent read current web pages as clean markdown Docs, changelogs, competitors, pricing pages 7. Figma MCP Give it the actual design Spacing, copy, layout, components 8. Linear MCP Turn the work into tickets Tasks, comments, follow-ups, PR links The rule: If you paste the same context twice, wire it into MCP That is how vibe coding becomes a build loop instead of a long chat