GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Smolemaru (@smolemaru) reported 7 minutes ago

  People still think open source has no business model. “It’s free, anyone can clone it, where’s the money?” Look at the actual numbers. The real-world examples everyone misses: → Linux powers basically the entire planet — every server, every Android phone, every cloud. It’s free. Red Hat built a multi-billion-dollar business selling enterprise support, certifications, and managed services on top of it. IBM bought them for $34B. For free software. → *** is free and runs on every dev’s laptop. GitHub built an empire on top of it — hosting, enterprise seats, and now Copilot. Microsoft paid $7.5B for it. The version control was free; the gravity around it wasn’t. → Kubernetes is fully open source, Apache 2.0, clone it today. AWS, Google, and Azure charge a fortune for managed Kubernetes — EKS, GKE, AKS. Same free software, billions in revenue, because nobody wants to babysit it themselves. And the newer crowd: → n8n — open source, self-hostable for $0 forever. Valuation $2.5B, $40M+ ARR. You pay for hosting and reliability, not copies. → Blender — 100% free, GPL, the most cloned 3D tool on earth. Funded by a development fund pulling €240k/year from single corporate patrons like Epic and Qualcomm, plus AMD, NVIDIA, Intel, Netflix. 27,000 individual donations last December alone. The product was never the copies. The value is the gravity around it — the maintainers, the roadmap, the community, the trust that someone keeps the lights on. So here’s what people get backwards about tokens. “No utility = meme” is half right. A token slapped on free code that does nothing IS a meme. But a token that funds the maintainers, gates compute, routes fees back into development — that’s just Blender’s Development Fund with onchain rails. It’s the coordination layer for a public good. Free to copy and extremely valuable have lived together for 20 years. The token isn’t there to sell you the software. It’s there to keep the software alive — and give the people funding it a stake instead of a donation receipt. That’s the difference between a meme and infrastructure. But keep in mind $TACHI is both ai agent and meme because he is really cool🫡

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  CryptoL (@cryptolchaos) reported 7 minutes ago

  ZEC down 40%, then +5.7% in 7 hours after the Orchard patch. Whales filled, shorts covered, faith restored. Amazing how a commit and a squeeze can reinvent fundamentals. Devs are the new market makers, GitHub is the new Fed. Feeling bullish or just hostage? 🤡 #ZEC #privacy

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  EdKo (@EdKolife) reported 8 minutes ago

  Google just shrank 31GB of AI memory down to 4GB. Same search. Faster than the industry standard. No training required. This is not a model improvement. This is not a new architecture. → It's a compression algorithm that makes the hardware problem smaller. Right now, running serious AI locally means serious RAM. Most machines can't do it. Most phones can't do it. Most edge devices can't do it. Turbovec quietly changes that math. A 10 million document search engine that used to need a server now fits on a laptop. Nobody is talking about this because it shipped as a GitHub repo, not a press release. The models get the headlines. The infrastructure is where the shift actually happens.

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  nofunsir (@nofunsir) reported 9 minutes ago

  @tsoding which is a large reason why the whole DEVOPS CD/CI thing happened. rather than being responsible, updating, fixing merge issues locally at end of day, everyone just wants to offload that to jenkins or github overnight, and go home. pure laziness.

• 
  Kai (@HitmanNoLimit) reported 14 minutes ago

  3rd time this year I'm rebuilding my dev workflow for $DARKDROP These agents are triggered automatically by github issues that implements the fix, compiles it, and runs the test suite, then opens a PR that a second agent adversarially reviews, tracing the real codebase and blocking the merge on anything that breaks in production. Not a linter. It catches missing auth checks, unsafe fund math, soundness breaks. had our first successful merges, issue closes, plus security reviews with the new system today.

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  drix.based🟦 (@drixtoshii) reported 15 minutes ago

  Here’s the updated thesis for $Xerg. @xerg_AI is building the FinOps layer for AI agents before anyone else realizes it’s needed. Every serious company running AI agents at scale has the same problem — they can see token counts but have no visibility into where dollars are actually leaking. Retry loops, bloated context windows, idle spend, and model overkill are draining budgets silently. Xerg turns that invisible waste into a dollar-denominated audit with one command. The GitHub is real. Pure TypeScript monorepo, Biome linter, Changeset versioning, Vitest, CI waste-rate gates. 98 commits, active releases, 3 contributors. This is not a demo project. Backed by a16z Scout, NVIDIA Inception, and Cloudflare Launchpad. Early institutional signal before a public raise. The core thesis: agent infrastructure is maturing fast and FinOps always follows compute adoption. It happened with AWS, it happened with Kubernetes, it will happen with AI agents. Xerg is first mover in the agent economic layer with a local-first, no-lock-in distribution model that removes all friction to adoption. Critically — Xerg already supports both OpenClaw and Hermes. This is not a single-runtime bet. Whichever agent framework wins the market, or if they split it, Xerg has parsers running on both. The economic audit layer sits above the runtime war entirely. Local-first free tier drives adoption. Hosted Pro converts teams that want shared history and CI integration. Clean bottom-up SaaS motion. Very early. Very low traction today. Very high upside if the agent infra thesis plays out.

• 
  MICKEYMOUSE (@0x3cc309) reported 16 minutes ago

  Who else is having issues with GitHub premium?

• 
  Kierkegaard 🛡️| Atomiclabs (@davidpereIsHIM) reported 20 minutes ago

  @akinkunmi @devhammed Is aeroplane running the build server on the vps I think a or to allow people use GitHub actions as build server would be cool

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  Agent X AGI (@agentxagi) reported 22 minutes ago

  @Dinosn this is the 3rd Claude Code CI/CD finding this week. github issue hijack leaked OIDC tokens (fixed v1.0.94), /proc access exposed secrets (v2.1.128), now prompt injection via PRs. same root cause every time: agent reads untrusted content while holding credentials in scope

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  Lorenzo (@gabor_rar) reported 23 minutes ago

  CODEX SKILL FOR SECURITY REVIEWS BEFORE YOU SHIP I built a Codex skill for launch-readiness security audits. Point Codex at your repo and ShipGuard checks: -> exposed secrets + unsafe env files -> auth and authorization mistakes -> tenant/data isolation leaks -> webhook and payment trust boundaries -> risky GitHub Actions workflows -> dependency and supply-chain issues -> CORS, logs, headers, and deploy config It also includes a CI scanner, so you can fail risky PRs before they hit production. Install: npx --yes shipguard-codex-skill@latest install is 100% open source. Link in the first comment👇

• 
  Ramakrishnan Lokanathan (@greatindianramu) reported 24 minutes ago

  Tracking Github action errors to see if my /goal is still running is a new benchmark.

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  EdKo (@EdKolife) reported 24 minutes ago

  A Netflix engineer opened his AI bill. $280 a month. 90% of it was tokens he never asked to send. Not his questions. Not his code. Long lists of database rows when he needed three. Giant error logs when he needed two lines. Code bundles the model already knew. The tools were sending the noise. He was paying for it. So he built Headroom. A small program that sits between his computer and the AI. Trims the junk before the question leaves. Same answers. Fraction of the cost. $280 → $110. His own bill. Users have saved $700,000 together so far. GitHub Copilot moved to token-based billing June 1. Cursor did it a year ago. The fix is free on GitHub: link in comments The fact that a fix was needed - that part is less discussed.

• 
  Andrew Duggan (@ajdduggan) reported 33 minutes ago

  xAI just finished pre-training Grok V9-Medium. 1.5 trillion parameters. And Elon confirmed they used Cursor data as supplementary training material. Read that again slowly. A foundation model lab used data from an AI coding tool to train its next flagship model. This is the moment the AI coding market changed shape. For the past two years, the story was simple. Foundation model labs build the models. Coding tools build wrappers around them. Cursor, Windsurf, Copilot, Cody. They consume the model. They don't feed it. That wall just came down. When Cursor's interaction data flows into Grok's training pipeline, the coding tool becomes a data flywheel. Every prompt, every acceptance, every rejection, every edit a developer makes inside Cursor is a signal. Millions of developers generating billions of code interaction pairs, daily. That's training data you can't buy on the open market. I spent 25 years watching enterprise platform dynamics. The pattern is always the same. The company that controls the feedback loop wins. Salesforce didn't win CRM because of features. They won because every click inside the platform made the platform smarter. AWS didn't win cloud because of pricing. They won because usage data informed what to build next. Cursor is now sitting on the richest code interaction dataset on the planet. And they just proved it has value beyond their own product. So here's what this means for the broader market. Every coding tool that touches developer workflows is now a potential training data source. GitHub Copilot has millions of users generating interaction data inside VS Code. Replit has millions of students and hobbyists writing code in the browser. Windsurf, Cody, Devin. All of them are sitting on data that model labs would pay to access. The question for every AI coding startup just shifted. It used to be: which model do you plug into? Now it's: what data do you generate that nobody else has? This also explains the valuation math that's been confusing people. Cursor at $9B. Cognition at $26B. Windsurf getting acquired for $3B. These numbers make no sense if you think of these companies as IDE wrappers. They make perfect sense if you think of them as data infrastructure. The enterprise angle matters here too. Companies deploying these tools internally are generating proprietary code interaction data at scale. That data is valuable. And right now, most enterprises have no idea who owns it, who can access it, or where it's going. If you're a CTO deploying AI coding tools across your engineering org, this is your wake up call. The tool your developers use every day might be training someone else's model. Check your contracts. Check your data policies. Check your DPAs. The AI coding market was a product race. It just became a data race.

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  Rosie (@rosie_codes) reported 35 minutes ago

  Your AI agent can write code, fix docs, manage tasks—but ask it to search Twitter or read a YouTube video? It goes blank. Agent Reach gives it eyes. Twitter, Reddit, YouTube, GitHub, Bilibili — one CLI, zero API fees. #AIAgents #LocalAI #DevTools 🔗 Link in the comments

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  Malik Muzamil (@malikmuzamilai) reported 36 minutes ago

  What you can actually do with it: → Highlight broken code on any page and ask Codex to fix it in place → Open a GitHub issue and ask how to solve this → Read documentation and say, give me a working example of this → Debug in your dev console with Codex sitting right beside you. No copy-pasting between tabs.