GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Rohit (@rohit4verse) reported 27 seconds ago

  In 2026, harness engineering is the difference between an agent that ships and one that burns tokens. If you want to learn it, someone just dropped the one-stop resource on GitHub, free. 12 lectures, 6 projects, 14 languages, 8k+ stars. Inside: - 12 lectures, each on one hard question: why strong models still fail, why agents call "done" too early. - 6 projects where you build a real Electron app, your harness getting sharper with each one. - Copy-ready templates (AGENTS.md, feature_list.json, init[.]sh) you drop into your own repo today. - A harness-creator skill that scaffolds a production harness in minutes. It even opens with Anthropic's experiment: the same model going from a broken build to one that ships, on harness changes alone. Codez wrote the 14-step map. This repo is the course underneath it.

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  Hugo Ruiz (@HugoRz_) reported 1 minute ago

  GitHub was built for humans. Origin is being built for agents. Different problem, different tool. Makes sense.

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  Newslit News (@newslit) reported 2 minutes ago

  Microsoft is turning to Amazon Web Services to handle GitHub's AI-driven capacity crisis. GitHub faced dozens of major outages in 2026 as AI-generated code pushed commit volumes from roughly 1 billion in 2025 to a projected 14 billion this year. Microsoft originally planned to migrate GitHub fully to Azure by 2027. That plan is now on hold. This is a remarkable admission. Microsoft owns GitHub. Microsoft owns Azure. And it still had to call its biggest cloud competitor because its own infrastructure couldn't keep up with demand that AI generated on its own platform. AI didn't just create a product problem for Microsoft — it created an infrastructure emergency that Azure couldn't solve alone.

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  Mathias Onea (@mathiasonea) reported 5 minutes ago

  package docs are distribution. a good docs page can rank for the exact problem, explain the tradeoff, show the install path, answer the security question, and give AI search a source to cite. GitHub alone is not enough. Packagist alone is not enough. the boring docs page does a lot of work.

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  Jason Nguyen (@jasonngsx) reported 5 minutes ago

  someone built a note app where every vault is a *** repository, every note is a plain Markdown file on your machine, and the whole thing is free. it's called Tolaria. the architecture is the point. there's no cloud sync to pay for. *** handles history, branching, conflict resolution, and syncing across machines. the same infrastructure you already use for code, now managing your notes. here's what that unlocks: → every vault is a *** repo. *** push syncs it. *** log shows every edit. no proprietary cloud watching your notes. → plain Markdown + YAML frontmatter. the format is yours. not theirs. → AGENTS.md support built in. Claude Code, Gemini CLI, and Codex can read your entire vault context natively, without a plugin. → built-in MCP server. connects to Claude, local LLMs, or any MCP-compatible tool directly. → command palette, keyboard-first. Tauri binary for macOS, Windows, and Linux. → zero accounts. zero vendor dependency. zero subscription. the creator runs 10,000+ notes in his personal vault with it. 13K GitHub stars. 918 forks. open source. free. brew install --cask tolaria most note apps don't say this out loud, but their business model is the sync layer. Obsidian cloud sync is $4/month. Roam is $15/month. Notion keeps your notes in a proprietary database. Tolaria removes the sync layer and replaces it with ***. in 2026, when your AI coding agent needs to read your notes for context, you want those files on your machine in a format every tool understands, not sitting in someone else's cloud.

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  Jay.TL (@JayTL00) reported 8 minutes ago

  Microsoft just admitted the economics of unlimited AI don't work. Their fix? A Chinese open-source model. Axios reports Microsoft is exploring an Azure-hosted DeepSeek V4 as a cheaper backend for Copilot Cowork. The company has already fine-tuned the model. Final decision is pending, but the direction is clear. The reason, from Microsoft's Charles Lamanna, is brutally honest: "We have users who do hundreds of tasks a week... the consequence is the costs can go very high." Read that twice. The problem isn't adoption. Adoption is the problem. Here's what's actually happening across Microsoft's AI stack: 1. GitHub Copilot flipped to token-based billing on June 1. Flat subscriptions are dead. Power users now pay per-token at API rates. Developers called it "a joke." 2. Microsoft internally cancelled Claude Code licenses for thousands of its own engineers — too popular, too expensive. The company with a $13B OpenAI stake watched its devs pick a competitor. 3. Now Copilot Cowork moves to usage-based pricing. The premium product that justified "AI tax on Microsoft 365" can't survive flat-fee economics. The pattern is clear: every Microsoft AI surface is converging on metered billing because the old promise — "pay once, use unlimited" — was always a land grab, never a business model. The Jevons paradox is doing what it does. Better agents → more tasks → more tokens → higher costs. Usage is up. Margins are down. The more successful your AI product, the faster it bleeds. Gary Marcus read this correctly weeks ago: hyperscalers couldn't wait until after IPO to switch to pay-per-use because staying on flat pricing "would bankrupt them." Microsoft just proved him right. Which brings us to DeepSeek. DeepSeek closed its first-ever funding round the same day — $7.4B at a $50B+ valuation. Founder Liang Wenfeng personally committed $3B. No board seats for investors. Tencent, CATL, NetEase, China's national AI fund on the cap table. So the deal is: Microsoft, the company whose former CEO called Linux "a cancer," is now reaching for Chinese open-source weights to keep its AI business solvent. That's not a punchline. That's a pricing signal. The national security angle is real. Senator Josh Hawley is already demanding a ban on AI transfer to China, specifically citing Microsoft-DeepSeek cooperation. Microsoft will host DeepSeek on Azure, fine-tune it with safeguards, and insist it's all contained within US infrastructure. Maybe. But once a Chinese-trained model sits inside Microsoft's enterprise stack — the same stack serving US government, military, and Fortune 500 clients — the blast radius of a supply-chain compromise is generational. But here's what most coverage missed: The real story isn't Microsoft choosing DeepSeek over OpenAI. It's that Microsoft now needs a cost-arbitrage play at all. This is the company that invested $13B in OpenAI specifically to lock in GPT as the enterprise default. That bet assumed model costs would stay manageable at scale. They didn't. Now Microsoft is shopping for the cheapest competent model it can find — and the cheapest competent model happens to be Chinese. The implication for the rest of the industry is uncomfortable. If Microsoft — with Azure scale, OpenAI preferential pricing, and $13B skin in the game — can't make unlimited AI economics work, who can? Anthropic's Claude Max lawsuit (filed this month) is the same problem from the other end: users suing because "unlimited" wasn't unlimited. The subscription model that fueled AI's consumer growth is structurally incompatible with the cost curve that AI is actually on. Usage-based pricing isn't a feature. It's a confession. The companies that survive the next 18 months won't be the ones with the best models. They'll be the ones who figured out how to charge per-unit AI without making customers feel like they're being punished for using the product. That is a harder problem than building the model. And nobody has solved it yet.

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  said köylü (@SaidKoylu56337) reported 11 minutes ago

  The Apache IoTDB database community maintains active channels: GitHub Issues, mailing lists, Slack, and WeChat groups. Whether you have a bug report, feature request, or just a question — the community is here. #Community

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  The Glowtail/RatEmperor/Poweringsales (@Glowtail31) reported 14 minutes ago

  @LuuvsLuna @BrisketCaek I gotta love linux when it comes to downloading **** God that flatpak github bullshit is brilliant So brilliant and not stress inducing God I loved hot setting up and Manager for a game because of some bullshit and you spend a month trying to fix it to work again.

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  AbideenTheDev (@codestorm1875) reported 15 minutes ago

  @honour_can_code @pxxl_space Github oauth currently returns 500 when trying to login.

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  Christian Findlay (@CFDevelop) reported 16 minutes ago

  @EddCoates In just host all my sites on GitHub pages. Never had any issues

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  whiteboy (@worldofwhiteboy) reported 20 minutes ago

  @HSVSphere @popovicu94 @esotericgooner in production you obviously do all the modern, correct things that you're supposed to do. on my personal box ? where i dont even run a web browser ? yeah my surface is minimal and i own my system, again. you're the problem. go re-invent the wheel another 1000 times, when you die we'll look over your github contributions and wonder how someone could waste so much time running in circles like a actual bon-a-fide retard. we'll wonder about all these software nerds that sat clicking buttons all day when the software was already written properly the first time. we'll marvel at how some fat idiot could sit around all day lil bro-ing people about "SELinux" and "self contained execution enviornments" instead of doing anything that actually matters to anyone or posterity. you're like a horse with blinders on, i bet you dont even know what GNU is.

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  l-lacker (@llacker_ru) reported 22 minutes ago

  @telegram 11/12 So yes, this is what Telegram is turning into: → support black hole → rushed updates → inconsistent official clients → memory leaks → broken AI bot features → delayed GitHub source drops → Fragment money stuck with no answer

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  Abhay Ganti (@silvermango9927) reported 23 minutes ago

  I’m testing a CLI that optimizes the generated server. GitHub-ish issue response: Before: ~7.8KB After: ~1.3KB Slack user response: Before: ~2.5KB After: ~417B The goal is not compression for its own sake. It’s making the agent see only the fields it needs.

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  Xiaoyan Tang (@xytangme) reported 26 minutes ago

  One trick works for me lately is to use github issue as the context layer. then I realized I just reinvented the colab part of software engineering?

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  Aakash (@zenmode_code) reported 27 minutes ago

  I spent 6 hours trying to optimize a slow database query that was killing our app's load time I tried every index and caching trick I could think of, but nothing seemed to work Then I stumbled on a GitHub issue that mentioned a specific config setting