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GitHub

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
Veigné, Centre 1
Paris, Île-de-France 1
Saint-Paul, Réunion 2
Mexico City, CDMX 1
León de los Aldama, GUA 1
Créteil, Île-de-France 1
Trichūr, KL 1
Brasília, DF 1
Lyon, Auvergne-Rhône-Alpes 1
Tel Aviv, Tel Aviv 1
Rive-de-Gier, Auvergne-Rhône-Alpes 1
Itapema, SC 1
Cleveland, TN 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:

  • francip
    Franci Penov (@francip) reported

    Doing the same work twice now, because neither the iOS ChatGPT app, nor Codex Web is able to push my changes to github, despite the connector installed and configured with read/write permissions for my org. As much as I love Sol, the coding tools around it are in dire need of someone at @OpenAI actually using Sol to fix them and make them usable.

  • ephraim_17
    Ephraim Nwachukwu (@ephraim_17) reported

    Typing every line of code was never what made someone an engineer. Before the internet, developers relied on books and libraries. Then Google, Stack Overflow, GitHub and modern frameworks changed how software was built. Now it is Codex, Claude Code, Cursor and AI agents. The tools changed. The thinking did not. The real measure is still whether you can understand the problem, make sound decisions, recognise bad output and build something that actually works. Every generation mocks the tools of the next one. Then eventually, everyone uses them.

  • R11manish
    Manish rawat (@R11manish) reported

    @github action service is down again 🥲

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

    @Harry_The_Nerd sorting the articles sequentially in a github repo is the fix for x random ordering, smart

  • dev_Treks
    Treks.dev (@dev_Treks) reported

    **Post MVP:** GitHub integration that matches pull requests to tasks and automatically generates review reports, so leads don't have to search for the problem. If turning a big goal into a real plan is something you’ve struggled with, this is exactly what I’m creating.

  • santoretech
    🇺🇸 Santore (@santoretech) reported

    Your company doesn't need another AI tool. It needs an operating system and you already have one.. it's @github. Tasks? Issues and Projects. Related to code? What isn't, in 2026. Strategy, playbooks, decisions. If it isn't versioned, your agents work from stale context. Skills and prompts? Same place. Writing voice, review checklists, compliance guardrails. Stored, updated, shared. Improve a prompt once, everyone gets it. Approvals? Built in. Define who reviews what before anything ships. Sharing? Invite someone to the repo. One source of truth, not twelve tools with twelve versions. Humans and agents, same playbook. The company brain isn't a metaphor. It's our operating model and @blockskunk is the lab. One repo at a time.

  • Degen_calls_sol
    DegenCalls (@Degen_calls_sol) reported

    GITHUB REPOS YOU SHOULD KNOW ABOUT Most scrapers break for boring reasons. A button moves, a class name changes, Cloudflare gets in the way, or the crawler dies halfway through a long run. Scrapling turns scraping into a more resilient system. Scrapy-style spiders, concurrent crawlers, pause and resume, anti-bot handling, and adaptive element finding in one framework. The detail most people miss: the adaptive selectors are the real unlock. Instead of hard-coding brittle CSS paths and praying the site never changes, the scraper can relocate elements after redesigns. That matters when you are scraping production targets, not toy pages. This is the shift from scripts to infrastructure. A script extracts data once. A scraping framework keeps extracting when the website changes, slows down, blocks, or moves the target. Most people still build scrapers like one-off hacks. The better setup is a crawler that expects failure and keeps going anyway.

  • LGLLGL1997
    0xMadman (@LGLLGL1997) reported

    @skalskip92 People have major questions about authenticity right now. If we put the CA up on GitHub or a website, that’ll fix the whole problem.

  • thedatadavis
    Chris Davis (@thedatadavis) reported

    I thought people were being a little dramatic about the github performance issues but using their api is far too hit or miss for a serious company.

  • eugenioclrc
    another anon (@eugenioclrc) reported

    @Kritt_AI @_blockian @ControlZ_1337 GitHub not working 👉👈🙏🙏

  • JulianGoldieSEO
    Julian Goldie SEO (@JulianGoldieSEO) reported

    The Agent OS origin story: every problem became an agent. Here's the simplest system-building rule I've seen: Every problem you have becomes an agent. → Hated spending hours on videos? Built a video agent. → Hated the SEO grind? Built an SEO agent. → Agents kept forgetting everything? Built the memory system. One by one, every time-drain became a worker. And here's the upgrade loop: see something trending on GitHub? Plug it in. Open Montage was blowing up, so it went straight into the system. Now it makes cinematic films in one click. The system gets better every single day because the internet keeps building parts for it. The mindset shift: you have to be brave enough to ask Claude for something big and risk hearing "I can't do that." The honest truth? It hasn't said that in 6 months. Any idea in your head is now buildable. Most people just never ask. Save this. You'll want it later. Want the SOP? DM me.

  • PNeelamraju
    Padma Neelamraju (@PNeelamraju) reported

    Open-source supply chain security continued: These attacks stem from specific platform design choices. GitHub introduced a feature called pull_request_target that exposes secrets to untrusted code submitted in pull requests. Exploits based on misconfigured pull request actions are common enough to have a name: pwn requests. GitHub could fix this. They could escape substitutions correctly for shell commands, disable the feature for certain operations, or prevent secrets from being exposed in those contexts. They publish documentation warning users to be careful but have not addressed the underlying vulnerability. npm made a choice that npm install always downloads the latest version of every dependency to deliver bug fixes immediately. In practice, this means malware gets distributed immediately when published. Go chose different rules: downloads retrieve the versions the package author tested against, not whatever is latest today.

  • unclebigbay143
    U N C L E BIGBAY ✨ (@unclebigbay143) reported

    Most of us build products with React, Next.js, PostgreSQL, Redis, TensorFlow, or countless npm packages without knowing every line of their source code. When React has an internal bug, many React downstream frameworks and developers blocked. They read the docs, inspect the source, search GitHub issues, or wait for a fix. That doesn't mean they didn't build their product. AI-generated code is similar. You don't have to understand every implementation detail from day one, but if it becomes part of your product, you should understand it well enough to debug, maintain, and improve it. Software engineering has never been about writing every line yourself. It's about taking ownership of the systems you ship.

  • OlsenUAE
    Alviss Ambassador to NAF0 (@OlsenUAE) reported

    @elashera_ @a_green_being @XBToshi If you do a deep scan of around half of the AI GitHub repos out there, you will find that, intentionally or not, they contain code snippets that either enable remote scanning or allow the agent you pulled down to inject code at runtime. I.e **** you if it wants to #sovereignAI

  • vorty279
    vorty (@vorty279) reported

    how they make these ai influencers without nano banana and higgsfield. that is how the video opens. and the answer is right in your lane, because the whole stack is open source that others charge a subscription for the paid logic they sell you. subscribe to higgsfield, pay for nano banana, burn credits on every face. as if face consistency is a secret button inside one service what is actually under the hood. comfyui plus flux for the face, plus a lora trained on your character so the face does not drift frame to frame, plus motion control to transfer movement from a reference. all open, sitting on github, forkable that is the whole trick. face consistency is not a feature of one paid app. it is a lora plus pose control. build the pipeline once and generate endless variations locally, no credits, no one else's server but honestly, two things the video does not say. tiktok and fanvue require labeling realistic ai content, and that is a rule, not an option. and second, the point is not generating a face. the point is a recognizable character and a funnel. the face is the easiest part and the main thing for your brand. the course they charge for sells you higgsfield as a secret. under it sit open blocks. comfyui, flux, lora. the pickaxe is handed out for free

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