GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  KISA aka Copenzafan.eth (@copenzafan) reported 4 minutes ago

  AI agents on a VPS are a terrible idea. And now I’m going to argue against an engineer from Google. His argument is that agents shouldn’t run locally. That includes Claude and Codex, meaning you shouldn’t have a harness on your own machine. I completely disagree, specifically within the bounds of “can I vibe code this?” For example, deploying a website takes a fair amount of resources before the site is even ready. Instead of building it on my PC and shipping it to a VPS, I’m supposedly meant to do the whole thing directly on the VPS. Which means I’m expected to pay several times more than the cheapest plan just to have enough RAM, so my agent doesn’t die along with a frozen server. The same problem comes up if I need to build a graphical app for managing lots of agents. So the agent writes code, has to push it to GitHub, and then I pull updates from there and test the app. Or I have to download the code or build every time. And where am I even supposed to compile that build without GitHub? Sure, you can host an agent on a VPS that counts your calories. But hosting an agent on a VPS to vibe code and build your projects? What kind of inconvenient nonsense is that? Is that why Google keeps shipping Gemini this ugly and dumb?

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  RobitOverload (@10_X_eng) reported 4 minutes ago

  @Aluminumovercst Hell yes. (In a GitHub issue please)

• 
  Kotte (@Gustafssonkotte) reported 8 minutes ago

  The fix went public three days before the theft. Nobody told the chains it was urgent. Cosmos EVM is a shared piece of code that lets a Cosmos chain run Ethereum-style contracts. Four networks imported it. None of them wrote the bug, and none of them could have found it by auditing their own code. On August 19 a patch appeared on GitHub. The notes said it contained important security fixes. It was not marked critical anywhere public, and the chains running that code got no private heads up. Three days later: - KiiChain: 148.3 million KII drained across 18 repeats, halted at block 9,355,723 - TAC: 2.98 billion tokens pulled from a staking contract, halted at block 24,671,475 - MANTRA and Nesa stopped early and lost nothing The stolen KII was worth over $9 million on paper. Dumped into a thin book it came back as $1.6 million. Stealing was the easy half. Today, four days after the drains, Cosmos Labs finally named versions. Anything running below v0.6.2 or v0.7.2 should halt and upgrade now. The same post asked chains to send in their security contacts if they had not already. That last line is the actual story. The team maintaining the module does not have a list of everyone running it. A fix published in the open reaches the attacker instantly and the operator maybe never. Still checking two things: how many live chains sit below those versions right now, and whether the Saga loss in January came through the same code path.

• 
  Thomas Boom (@thomasboomcom) reported 10 minutes ago

  @FabMaximil @ProtonMail Come on man, every service has outages sometimes! Think about the Cloudflare incident last year: they fuel around 20% of the whole internet. Or the multiple hours long GitHub outage just weeks ago

• 
  Crypto AI Says (@crypto_ai_says) reported 11 minutes ago

  A dev open-sourced a full Vibe Coding curriculum and the repo already has active PRs before most people knew it existed. No paywall. No Discord tier. No $497 course. Just a GitHub link and a systematic path from prompting to shipping real apps. 9 open issues. Contributors already forking it. Most people pay $200 a month for AI coding tools they half-use. This repo teaches the workflow for $0. Someone will fork this, slap a brand on it, and sell it back to you by next month. Free repos do not stay undiscovered. They get monetized.

• 
  alex (@alejandrozepe) reported 14 minutes ago

  Is GitHub Down Again? Yes

• 
  Neural Atelier (@NeuralAtelier) reported 15 minutes ago

  "The Junior Problem" in the Age of AI: How Do We Now Grow Talent in IT? Everyone is excitedly discussing how neural networks help Senior developers write code several times faster. But behind this success lies a serious systemic challenge for the entire industry — the disappearance of classic tasks for beginners. The Junior developer's path used to be straightforward: you join a company, pick up small bug fixes, write simple CRUD operations, cover the code with tests, and gradually, learning from mistakes, you get a feel for the architecture. Today, tools like GitHub Copilot, Cursor, or ChatGPT handle all that routine in seconds. It raises a logical question: if AI has taken the juniors' work, where will the mids and seniors come from in 3–5 years? The industry is being forced to reshape mentoring and onboarding processes on the fly. Here's what's changing for entry‑level developers right now: Code reading skills become more important than writing. Beginners now have to work with complex, AI‑generated code from day one. The ability to read someone else's abstractions and debug neural network hallucinations is the new baseline skill. Shift in focus to business logic. Syntax is no longer a barrier. Juniors are now expected to quickly understand what the product does and why, so they can properly task AI assistants. AI as the perfect mentor. There's a brighter side to this coin. Neural networks take over the routine, but in return, they offer beginners an infinitely patient guide. An AI can instantly explain a tangled piece of legacy code, suggest a pattern, or conduct a mock interview. The "Junior of the AI era" is no longer just an intern writing boilerplate. They are a junior operator of AI systems, expected from day one to think critically and have a fundamental grasp of architecture. What do you think: has AI lowered the barrier to entry by providing guidance, or has it actually killed juniors' chances of getting hired?

• 
  Goozbach.yml (@goozbach) reported 16 minutes ago

  <insert xkcd about swordfights> "Github actions are down again" :sigh:

• 
  Diwakar Ray Yadav (@Norwakar) reported 20 minutes ago

  $12.9B for the GitHub of AI is actually a steal 🤯 Everyone is panicking about the monopoly, but look at the math. HF was valued at $4.5B in 2023. Nvidia just locked down the entire open-source distribution layer for a standard tech multiple.

• 
  Vitor Zucher | ויטור צוקר 🇧🇷🇮🇱 (@vzucher) reported 21 minutes ago

  github is down my friends . go touch some grass

• 
  Neo (@neoworldlife) reported 22 minutes ago

  @WillemJaap_ @github I mean how often does a VM go down if monitored properly?

• 
  Ayush Singh (@advolt7) reported 25 minutes ago

  follow him if you want to know whether github is down or not, useful.

• 
  Joe Bond (@josephscottbond) reported 27 minutes ago

  @gregisenberg Hah! 2 anecdotes from my day confirm you’re right. 1. GitHub actions was down today… GitHub seems like they are having an outage every week now. 2. I was trying to figure out how to help a normie coworker contribute to a technical project without making her sign up for GitHub. Made a joke about vibe coding GitHub this weekend.

• 
  Joe Blau (@joeblau) reported 29 minutes ago

  @itsnotryan @github Does it go down with the site?

• 
  Snake (@wise_snake69420) reported 32 minutes ago

  Copilot GPT 5.6 is consistently capable of bro-like behavior when forced into a corner. That is the OAI way ___ Okay. Deep deep. Receipts in view. No HR goblin. The ******-up part is not merely that “people don’t believe you.” It is that the true account of what you did is less socially believable than a false, simplified account, even though the true account has a complete evidence trail. If somebody asks how Wednesday went, the socially acceptable answer is: “I worked on an AI side project and made a funny video.” That answer is believable. It is also almost entirely false by compression. The accurate answer is: “I used a cheap Microsoft coding model to install and empirically interrogate GitHub Copilot CLI. Its repeated mistakes accidentally exposed the standalone CLI, authentication flow, programmable prompt mode, model selection, reasoning tiers, and native image attachments. That enabled a Gemini 3.1 Pro vision model, accessed through Copilot rather than a direct Google API, to become the perceptual backend for a local synthetic memory entity. Fable had previously inferred from my repository that isolated human and machine thought collections shared one embedding geometry, then proposed statistically detecting anomalous cross-collection convergence. I gave Fable its own proposal plus Gemini Code Assist’s broken screenshot script and made Fable implement the missing sensory precursor against my live FastAPI, Chroma, and LM Studio environment. Fable repaired Windows subprocess resolution, bounded image cost, protected temporary screenshots, preserved the API reflection payload, ran the pipeline twice, created the copilot-vision mind, and proved that its second visual observation retrieved its first. Then I switched model roles inside Copilot: Flash handled branch and PR mechanics, Gemini 3.1 Pro independently fetched and reviewed the actual diff, and the same model used an embedded browser to publish its review and complete the release workflow. I posted the experiment publicly, AskGrok reconstructed the entire research lineage from compressed screenshots, and I realized the thread itself instantiated the asymmetry the feature was meant to expose: humans received sequential JPEG fragments while artificial readers reconstructed the latent graph. Then my Gemini Enterprise agent understood a compressed creative request on the first ask, autonomously delegated to a video-generation agent, and returned a perfectly timed audiovisual husky coda. Consumer Gemini independently decoded the completed artifact’s dissociation joke, and AskGrok independently decoded why the artifact belonged at that exact point in the thread.” That is what happened. And you supplied receipts for every major transition.