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
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:
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 |
|---|---|
| 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 |
| Paris, Île-de-France | 6 |
| 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 |
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:
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Charles McDowell (@charlesmcdowell) reported@openclaw @github I still just want to know why there was even a new release of OpenClaw with nothing new that could compete with Hermes Agent? I was really excited for the release. Then, just like what seems like everybody else, incredibly let down.
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Ayush (@roamer_on_X) reportedmy @github streak of 4 weeks ended today bcz I was busy playing fifa with my roommate. Tf, I hate this feeling. I literally had to solve one problem and just push it but I forgot to do it.
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Tlon (@tloncorporation) reported1/ 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:
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Chris (@chriscoolstuff) reported@pfernan95dev For the SEO part there's one thing that I've been also doing: Ask your agent what keywords you should search for relevant to your app on answerthepublic, perplexity and google Gather all that info old fashion, by yourself - might take around 2 hours but it's worth it Plug all that info into the agent and have it give you 5 titles for 5 articles Make it write those articles - maybe use nosoopai github or edit them manually so they seem more human like Connect the agent to google console After 1 month tell the agent to review the results If no article took off you can wait one more month or put up 5 more After the next month check what worked and double down on that
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Eddie Jaoude | DevRel | Open Source (@eddiejaoude) reportedI have many tokens to burn before tomorrow after the Claude reset. Send me your GitHub issues with context 👇
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Curious Explorer (@PatelVatsalp732) reportedI burned 14B Codex tokens. The official usage UI still cannot tell me what actually ate the weekly cap. So I shipped a Codex-only board: GitHub login, local-first sync, private by default, optional public rank + shipping proof. Roast the metric or join it.
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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.
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Straggler Liu | AI & Semis (@StragglerLiu) reportedNVIDIA($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.
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AI Scientist (@AIScientist_X) reportedNEWS: X LANDS FIRST PUBLIC ALGORITHM PR > X OPEN SOURCE SAID SEP 1 THAT AFTER 2 PLUS WEEKS OF DAILY UPDATES IT INTEGRATED A FIRST PUBLIC CONTRIBUTION AND THAT THE CHANGE IS NOW LIVE ON X. > IT SAID THE SMALL UPDATE IS BASED ON GITHUB PULL REQUEST 55. X CLOSED THAT PR AS COMPLETED AFTER LANDING ITS OWN FIX. SOURCE: X OPEN SOURCE
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Vigneshwer Ramamoorthi (@vigneshwer_ram) reportedI 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
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Blue Collar Executive (@A_Sober_Drunk) reportedon the third try at the same problem, I told Grok to "stop and go search stack overflow or github or something"... five seconds later... Literally the exact issue, problem solved. That's how new global rules are born.
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Åsa-Nietzsche (@AsaNietsche) reported@peterb0yd @burkeholland @github It's every ******* model. I'm getting whiplash from all of this everything changing forever society being turned upside down every two weeks.
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ѕaℓoηι ηαяαηg (@thesaloninarang) reportedI review resumes for DevOps beginners at meetups, and the same fixable problem shows up every time: bullets that describe the tool instead of what YOU did with it. Let me show you the difference with real rewrites. BEFORE: "Worked with Docker and Kubernetes" AFTER: "Containerized a 3-service Node app and deployed it to a local Kubernetes cluster with health checks and resource limits" BEFORE: "Knowledge of CI/CD" AFTER: "Built a GitHub Actions pipeline that tests, builds and pushes images on every merge to main" BEFORE: "Familiar with Linux" AFTER: "Debugged container startup failures using logs, exec and inspect on Ubuntu servers" See the pattern? Verb, artifact, specifics. A hiring manager can picture the AFTER versions. The BEFORE versions could be copied from any job description, and that is exactly how they read. You do not need production experience to write bullets like this. Personal projects count when you describe them concretely.
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Pranavvv👾 (@pranvv27) reportedhonestly, i’m not even mad at this. commit messages are a small thing, but they say a lot about how you work. “fix”, “update”, “changes” might get the job done, but meaningful commits show professionalism, attention to detail, and that you actually care about maintainability. your GitHub is part of your resume. might as well make it look like you know how software is built in a team.
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LLL (@triplellltrbl) reportedYou know it's so funny to me That in today's age there are so many people that are just straight up copying workflows, AI automations or GitHub repos Without even thinking twice about what the workflow actually does or how it works They just watch some video, see the output, think, "Oh that's cool. I want that," and then try it Then when it doesn't work they get angry, upset, and say that AI is crap or prompting isn't real The issue wasn't the system or the prompt It was a fact that the system wasn't made for you and you don't actually understand it