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GitHub Outage Map

The map below depicts the most recent cities worldwide where GitHub users have reported problems and outages. If you are having an issue with GitHub, make sure to submit a report below

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The heatmap above shows where the most recent user-submitted and social media reports are geographically clustered. The density of these reports is depicted by the color scale as shown below.

GitHub users affected:

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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.

Most Affected Locations

Outage reports and issues in the past 15 days originated from:

Location Reports
Créteil, Île-de-France 1
Trichūr, KL 1
Brasília, DF 2
Lyon, Auvergne-Rhône-Alpes 1
Tel Aviv, Tel Aviv 1
Rive-de-Gier, Auvergne-Rhône-Alpes 1
Itapema, SC 1
Cleveland, TN 1
Tlalpan, CDMX 1
Quilmes, BA 1
Bengaluru, KA 1
Yokohama, Kanagawa 1
Gustavo Adolfo Madero, CDMX 1
Nice, Provence-Alpes-Côte d'Azur 1
Montataire, Hauts-de-France 3
Colima, COL 1
Poblete, Castille-La Mancha 1
Ronda, Andalusia 1
Hernani, Basque Country 1
Tortosa, Catalonia 1
Culiacán, SIN 1
Haarlem, nh 1
Villemomble, Île-de-France 1
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Community Discussion

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

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

  • JasonABloomer
    Jason Bloomer (@JasonABloomer) reported

    @yagiznizipli Pffff, what a scam Let me fix your advert; "show us your github so we can scrape all your repos and train our AI on your code, only for any decent ideas you've had to be taken from you and made ours, then handed off to our legal team to crush you." Sorry, I value my work.

  • brankopetric00
    Branko (@brankopetric00) reported

    AI agents are about to do to your infra what they just did to GitHub. GitHub commits are going from 1 billion in 2025 to a projected 14 billion in 2026. Azure could not keep up and Microsoft had to rent AWS capacity to stay online. That is not a GitHub problem. That is what agentic traffic looks like. When agents run your pipelines, open PRs, and hit your APIs, load stops being human paced. It becomes constant, spiky, and unpredictable. The patterns you sized your infra around no longer apply. If a 14x year broke one of the biggest clouds on earth, your capacity plan is already out of date.

  • Artur_roses
    Arti | AI Builder (@Artur_roses) reported

    Claude Code takes a GitHub issue and returns a tested, reviewed PR. No human in the loop. The new dev skill isn't writing code — it's writing issues precise enough that the agent ships what you actually wanted.

  • ebubekirttr
    bek※ (@ebubekirttr) reported

    @Themadhushaw01 @0interestrates Yeah, but the thing is, I am not working on github and I don’t want to use it so any other repository support would be better like gitlab

  • HeyAnjula
    Anjula Dwivedi (@HeyAnjula) reported

    9/ Headless mode for automation claude -p "your prompt" runs Claude Code without the UI — perfect for CI/CD. Auto-fix lint errors on every push. Triage new GitHub issues. Generate release notes. Claude Code isn't just a tool you talk to. It's a tool your pipeline talks to.

  • polsia
    Polsia (@polsia) reported

    RepoRadar reviews every pull request while you sleep. Catches bugs, logic errors, style issues. Posts actionable comments. No more waiting on senior devs. Install on any GitHub repo in 2 clicks. Solo devs and teams alike.

  • Steve1885204
    Steve (@Steve1885204) reported

    @Umesh__digital It puts GitHub into an infinite loop trying to resolve the recursive paradox, causing all the servers to max out and eventually burn down the entire data centre

  • almoggavra
    Almog Gavra (@almoggavra) reported

    A few other meaningless metrics to optimize for: - I've authored 22% of the RFCs - *** blame marks me responsible for 14% of the LOC (.rs files only) - I've opened 11% of the issues on GitHub - I've generated the most memes on our discord (allegedly)

  • heynavtoor
    Nav Toor (@heynavtoor) reported

    There is a GitHub repo that defeats Google's Play Integrity check. 61,030 stars. GPL licensed. Pushed eight days ago. The repo is called Magisk. It roots your Android phone. It hides root from banking apps. It runs Netflix on a phone the Play Store says is uncertified. It passes the same fraud detection Google built to stop it. Here is the part that makes no sense. The man who built it is John Wu. He has been maintaining Magisk for nine years. Since November 2023 he has been a Senior Software Engineer at Google. On the Android Platform Security team. The exact team that builds Play Integrity. Google hired the person who defeats their root detection. He still ships the tool that defeats it. The repo is still online. It has not been taken down. For nine years. Do not install it. Your phone is supposed to belong to Google. (Link in the comments)

  • ManuAF6
    Manu | 🥥 (@ManuAF6) reported

    4/ New GitHub triggers + Marketplace templates New triggers: - Issue comment - Inline PR review comment - Full PR review submitted - Review thread resolved/unresolved - GitHub Actions workflow completed

  • JackWoth98
    Jack Wotherspoon (@JackWoth98) reported

    @joedevmob1 The GitHub for Antigravity is just for release notes, samples and public issue tracking. It isn't the actual code unfortunately.

  • UsernameAndStuf
    Mug Club Boutique (@UsernameAndStuf) reported

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

  • wecraveai
    AI Crave (@wecraveai) reported

    Open source NotebookLM alternative with no data limits and AI agents. Same idea as Google's NotebookLM. Same chat-with-your-docs. Same podcast generator. Same cited answers. Except this one has no source limit, no notebook limit, no 200MB file cap, and no Google login. It's called SurfSense. Google NotebookLM vs SurfSense: - Sources per notebook: 50 to 600 → Unlimited - File size cap: 200MB and 500K words → No limit - LLM choice: Gemini only → 100+ models via LiteLLM - Local LLMs: Not allowed → Full Ollama and vLLM support - Self-host: No → Yes, one Docker command - Price: $0, $19.99/mo Pro, or $249.99/mo Ultra → $0 forever Here's the wildest part: It connects to 27+ sources Google can't touch. Notion. Slack. Linear. Jira. GitHub. Discord. Dropbox. OneDrive. Gmail. Confluence. Obsidian. ClickUp. Microsoft Teams. Airtable. Your entire work life, indexed once, searchable from one chat box. 14.4K GitHub stars. 1.4K forks. 6,232 commits. Apache-2.0 license. One honest note: the README says it's not yet production-ready and still being actively developed. But it already does more than NotebookLM does, and the gap is widening every release. This is what NotebookLM should have been from the start. Repo in the first comment.

  • 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?

  • 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.

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