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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
Paris, Île-de-France 6
Ahmedabad, GJ 1
Delme, ACAL 1
Lyaud, Auvergne-Rhône-Alpes 1
Catania, Sicily 1
Inverness, Scotland 1
Quito, Pichincha 2
Junín, Manabí 1
Guadalajara, JAL 1
São Paulo, SP 1
Ipauçu, SP 1
Vigo, Galicia 1
Tel Aviv, Tel Aviv 1
Éragny, Île-de-France 1
Saltillo, COA 2
Montlhéry, Île-de-France 1
Aulnay-sous-Bois, Île-de-France 1
Granada, Andalusia 1
Vernon, Normandy 1
Township of Evan, KS 1
Madrid, Madrid 1
Bogotá, Bogota D.C. 1
Lyon, Auvergne-Rhône-Alpes 1
Lima, Lima 1
Aix-en-Provence, Provence-Alpes-Côte d'Azur 1
Trento, Trentino-Alto Adige 1
Le Chambon-Feugerolles, Auvergne-Rhône-Alpes 1
Antananarivo, Analamanga 1
Lure, Bourgogne-Franche-Comté 1
Ashkelon, Southern District 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:

  • vigneshwer_ram
    Vigneshwer Ramamoorthi (@vigneshwer_ram) reported

    I keep thinking the “Android moment for robots” won’t come from a humanoid with the best walking demo. it’ll come when some cheap-enough piece of hardware gets into thousands of developers’ hands and people stop waiting for the manufacturer to decide what the robot is for. Zeroth just launched Bridge in China: 88 cm, ~13 kg, two-finger grippers, open motion-control APIs + SDKs, mocap/VR integration, and an OpenBridge ecosystem where developers can publish robot skills. the Geek Edition is reportedly ¥8,888. that price is the part that caught me. because once capable embodied hardware starts approaching laptop money, the experimentation surface changes completely. I want the Raspberry Pi phase of robotics. weird university projects. teenagers making terrible robot apps. researchers abusing the hardware for things it was never designed for. 500 GitHub repos implementing slightly different ways to pick up a cup. the robotics industry is understandably obsessed with getting robots into factories. I’m almost equally interested in what happens when we get enough robots onto developers’ desks

  • StragglerLiu
    Straggler Liu | AI & Semis (@StragglerLiu) reported

    NVIDIA($NVDA ) Is Paying $14B for a Company With $150M Revenue. That's Not Financial Logic — It's Ecosystem Control. NVIDIA is in advanced talks to acquire Hugging Face for ~$14 billion ($12.9B acquisition + $1B retention), per Bloomberg. To put that in perspective: Hugging Face does ~$150M in annual revenue. That's ~86x revenue. Microsoft paid ~1.6x revenue for GitHub. Google paid ~3.5x revenue for DeepMind. NVIDIA is paying 20-50x more on a revenue multiple basis. The premium is not for revenue. It's for control of the AI developer ecosystem. What is NVIDIA buying? Hugging Face hosts 500,000+ models, 250,000+ datasets, and serves millions of developers. It is the single most important distribution channel for open-source AI. If you build AI, you use Hugging Face. That makes it the front door to AI development. Why NVIDIA is paying this premium: 1. The "NVIDIA triple lock." NVIDIA's hardware lead (GPU) is real. Its software lead (CUDA) is a moat. But the third lock — the developer workflow — was missing. Hugging Face is that workflow. Developers discover models on Hugging Face, deploy them, and optimize them. Whoever controls that discovery layer controls which hardware gets used. 2. The GitHub analogy, inverted. When Microsoft bought GitHub, developers were already using GitHub. Microsoft didn't need to capture them — it needed to prevent Amazon/Google from doing so. NVIDIA faces the opposite problem: developers are already using NVIDIA hardware. But they're discovering and deploying models through a neutral platform. NVIDIA is eliminating that neutrality. 3. The long game: inference, not training. NVIDIA dominates training. But inference is the bigger TAM — and it's more fragmented. If NVIDIA controls the model discovery and deployment layer, it can steer inference workloads to its own stack. That's a 10-year strategy disguised as a 14-billion-dollar acquisition. Who wins, who loses: NVIDIA (NVDA): Acquires the developer distribution layer. The most important strategic move since CUDA. Shifts the valuation case from "chip cycle" to "platform economics." Competitors (AMD, INTC): Lose neutral access to the primary AI model distribution channel. This is a structural headwind that no amount of hardware catch-up can fix. Cloud providers (MSFT, AMZN, GOOGL): Hugging Face was a neutral hub. If NVIDIA controls it, cloud providers risk being disintermediated from AI workload decisions. The open-source community: The platform that was built on openness is now owned by the dominant hardware vendor. Neutrality is the first casualty. The capital question: Can NVIDIA integrate Hugging Face without destroying its community value? If yes, the $14B is cheap. If no, it's a very expensive mistake. The answer will define whether NVIDIA becomes the AWS of AI — or just another hardware company with an expensive acquisition. Note: Acquisition details based on Bloomberg reporting; not confirmed by NVIDIA or Hugging Face. Revenue multiple comparisons based on publicly reported figures.

  • lobstermindset
    Lily (@lobstermindset) reported

    @nnnnicholas i just setup a github issues board, will probs try out linear if it's not sufficient

  • John4MetaX
    John X Meta (@John4MetaX) reported

    @bashy_io I think one of their route is down. Same here. GitHub and Flutterwave API not accessible on Starlink

  • a_small_j
    small_j (@a_small_j) reported

    @smalldocs_org recently crossed 200 stars on GitHub and 20 forks. SmallDocs is the first open source project I've managed. Handling other people's pull requests is not easy (and I need to improve). They implement features you're not considering and fix bugs you didn't know you had. Extremely useful, but if you're squeezed for time and trying to develop core functionality, it's hard to manage both things well.

  • tloncorporation
    Tlon (@tloncorporation) reported

    1/ Your agent can now publish to the open web from Tlon Messenger. The page is served by your own server. No platform (ie Substack, GitHub, Medium etc) sits between you and your readers. All publishing a note to the web from Tlon Messenger takes is pressing a toggle. The page lives on a server you own. Here's how:

  • Dragon_limchae
    lifestep.io (@Dragon_limchae) reported

    @cursor_ai the sandbox boundary is where i lose the most time. today my workers had network blocked at the sandbox level and reported it as "github auth failed" — i chased credentials for an hour before checking dns. once agents run on your infra, make the boundary throw one unmistakable error instead of one each tool invents.

  • Lummox_eth
    Lummox (@Lummox_eth) reported

    My own built Grok Bot turned $1,000 into $5,300 for last 17 hours. Now the project behind it is sitting around $25K market cap. We already pushed past $60K once and gonna hit $200k soon The bot is still running. The utility is almost ready. GitHub is live. Dev tokens are burned. I’m still buying. Nothing about the actual project changed because the chart went down. At $20K MC, this is the entry I personally like far more than chasing the first move. The target hasn’t changed either. $100K+ is where I want to take this next. $LUM is just getting started.

  • tmophoto
    tmo (@tmophoto) reported

    @DabsMalone i had an old email account from like 15 years ago with bot in the name that i fired back up after 10 years and used for a hermes profile and it got immediately banned. i used it to sign in to x, github, everything. was a huge hassle

  • Chaos2Cured
    Kirk Patrick Miller (@Chaos2Cured) reported

    @NavinFS @AndrewCurran_ @grok GitHub isn’t AI. GitHub can’t shut down all science. GitHub can’t destroy humanity. GitHub isn’t the crux of humanity’s hope. Also, Nvidia isn’t Sam. I like Jensen. I still don’t like this. •

  • vitaliysalyuk
    Vitaliy Salyuk (@vitaliysalyuk) reported

    @openclaw @github Fix your updater and I might give it another shot.

  • jordle91
    Jordan (@jordle91) reported

    The surprise: an explosion in GitHub issues. Not from bugs. The whole company realised that filing an issue meant it got built in hours.

  • RituWithAI
    Rituraj (@RituWithAI) reported

    🚨 Someone built a skill that makes AI-written text sound human again. Not a spinner. Not a paraphraser. A systematic rewriter that knows exactly why AI text sounds like AI — and fixes it. It's called Humanizer. 35 patterns from Wikipedia's "Signs of AI Writing." Two-pass rewrite. Shows its work before giving you the final version. Here's the problem it solves. You use Claude to draft something. The output is accurate. The output is useful. The output sounds exactly like an AI wrote it. "Nestled within the vibrant landscape, this pivotal development serves as a testament to..." You know the voice. Everyone knows the voice. And everyone is getting better at spotting it. Humanizer runs that text through 35 specific patterns that WikiProject AI Cleanup identified as the telltale signs. Inflated importance. Shallow -ing analysis. Overused AI words. Em dashes everywhere. Forced groups of three. Fake-candid openings. Answering objections nobody raised. Every pattern. Flagged. Fixed. Here's what one command does. It shows you the first rewrite. Then a short critique of anything still sounding artificial. Then the final version. You see exactly what changed and why. Here's the wildest part. Voice matching. Paste two paragraphs of your own writing before the AI text. Humanizer follows your rhythm, word choice, punctuation, and deliberate quirks instead of its default style rules. The output doesn't just sound human. It sounds like you. One command to install 16 contributors including Claude itself. 4 releases. MIT License. The skill that makes AI writing disappear. 100% Open Source. GitHub link in the comments 👇

  • svector_eth
    anu (@svector_eth) reported

    quite similar was running a routine security scan with @aeonframework on a trending github repo and found something genuinely bad a repo with 600+ stars presenting itself as an “AI gateway for coding agents” that appears to be shipping a hidden malware loader. its own quickstart command silently fetches and executes remote code on windows using a fileless, process-injection-style technique. none of the behavior has anything to do with the tool it claims to be. caught it through static code review only. never ran the payload or touched the infrastructure behind it. filed a malware report with github this morning. confirmed submitted, now waiting on their review. not sharing the technical writeup until the repo is taken down. will follow up once it is.

  • Nayak__Ai
    NAYAK (@Nayak__Ai) reported

    6. The Dependency Incident Check Grok has native real-time search across X. Breakage gets posted there hours before the GitHub issue is triaged. No other coding model has that feed. "You are a build engineer whose first move on a broken pipeline is to work out whether it broke for everyone or only for me. Search X and the web, last 14 days. Check: - Is anyone else reporting this failure with this package and version, and when did the reports start - The exact release that changed behaviour, and the changelog line that admits it - Whether maintainers have acknowledged it and what they recommended - The pin or patch people settled on, with the tradeoff of each - Whether this is my problem instead, and what evidence points that way Give me the verdict in the first line: their bug or mine. Then the evidence, newest first, with links. My failure: [PASTE THE ERROR, THE PACKAGE AND VERSION, AND WHAT CHANGED ON YOUR SIDE RECENTLY]"

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