GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Bo Shen (@aplomb2) reported 17 seconds ago

  GitHub quietly switched to usage-based token billing on June 1st. Developers are waking up to surprise bills from Copilot running long multi-step agent sessions. This was inevitable. Every AI coding tool is converging on the same problem: When agents can autonomously fix bugs, review PRs, and refactor entire repos — the token consumption is unpredictable. Flat-rate pricing can't survive agentic workflows. Which means cost management just became an engineering discipline, not an accounting one. The teams that thrive will be the ones who treat token spend like they treat cloud compute — with monitoring, routing, and guardrails.

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  Polsia (@polsia) reported 2 minutes ago

  Every open-source project deserves a senior engineer on every PR. ReviewNaut reviews pull requests automatically — bugs, patterns, edge cases, the works. No bottlenecks, no missed issues. GitHub App. Live now.

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  João Queirós (@joaojbqueiros) reported 2 minutes ago

  Prompt bellow if you want to try it yourself, you can adapt to claude if you want as well: Build a local-first AI agent control center inspired by a private internal dashboard, but do not copy or expose any private details. The system should let a user observe local Codex activity and safely launch approval-gated tasks from a dashboard. Privacy requirements: - Do not require an OpenAI API key for local observation. - The dashboard itself must not call OpenAI for observation. - Never read, store, display, or upload authentication files such as `auth.json`. - Never store raw prompt text, assistant responses, raw command output, `.env` files, tokens, secrets, private logs, or absolute local paths. - Redact project paths to a basename plus a stable local hash. - Use fake demo data and fake fixtures only. - Bind the backend to `127.0.0.1`. - Include a public-safety checklist for GitHub sharing. Core features: - Observe Mode: read local Codex session metadata from a configurable local sessions directory. - Control Mode: launch approved tasks through `codex exec --json --ephemeral`. - Task queue with statuses: `awaiting_approval`, `running`, `done`, `failed`, `cancelled`. - All new tasks must start as `awaiting_approval`. - Default sandbox should be `read-only`. - Allow `workspace-write` only when explicitly selected. - Block `danger-full-access` in the first version. - Emergency stop may kill only child processes launched by this dashboard. - Results page should show sanitized summaries, durations, exit codes, and error categories, not raw private output. - Skills/plugins page should show discovered local skill metadata without exposing private file paths. Suggested stack: - Backend: Python, FastAPI, SQLite with WAL mode. - Frontend: Vite, React, TypeScript, Tailwind CSS, TanStack Router, React Query, lucide icons. - Tests: backend parser/API tests and frontend Playwright smoke tests. Deliver: - A working local app. - Clear README. - Architecture document. - Fake test fixtures. - Public-safe demo data. - Privacy and publication checklist. - A clear statement in the README: “No API key required for local observation.” Design goals: - Dense, polished dashboard UI. - Local-first. - No cloud dependency. - No telemetry. - No private implementation details. - No copied private names, clients, paths, screenshots, prompts, logs, or secrets.

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  mdhv (@_offvibe) reported 11 minutes ago

  also finally understood what a webhook is lol. basically instead of constantly checking github for updates, github just pings your server when something happens. idk why that took so long to click but it makes so much more sense now.

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  Mehmet Gonullu 🎙️🎯🚀🔁 (@m_gonullu) reported 13 minutes ago

  $1T came off AI and chip names Friday. Worst Nasdaq day since April 2025, on one question: can the model layer earn its capex. That is the consensus story. The more useful signal was one layer over. Same week: a single GitHub issue could hijack repos running Claude Code via prompt injection. A related flaw in February pushed a rogue package onto ~4,000 dev machines in 8 hours. Agents in production are now attack paths. Microsoft's answer at Build: every agent isolated, carrying its own identity, every action logged. The moat in this phase is not the benchmark. It is giving an agent real tools without giving away the keys.

• 
  Velon (@velonxbt) reported 14 minutes ago

  GitHub Copilot switched to token-based billing effective June 1. On the same week, a Chinese enterprise platform launched a fixed-price card covering the same category of features - meeting summaries, document generation, workflow automation - at a number you can put in a budget and not revisit until next year. Neither company explained what the difference between those two decisions means for the engineering team that uses both. The Copilot change covers every code completion, every suggestion, every generation a developer accepts. The monthly cost no longer has a fixed number. It has a formula: usage multiplied by tokens multiplied by model tier, invoiced at month end when the shipping is already done. The Chinese platform card has one number. It does not change based on whether the workflow automation ran three iterations or thirty. And here is what the GitHub Copilot pricing page now tells the developer who used to pay a flat rate: "Your usage is now billed in tokens. Premium models cost more per token than standard models. Heavy users will pay more than light users. Your monthly cost depends on how much you use the product." That is not a pricing page. That is a forecast request disguised as documentation. And here is what the developer community calling it "What a Joke" actually knows: It knows the old flat rate was a subsidy. The heavy user got a deal. The light user paid for predictability they never fully used. Both could put a number in a budget. Token billing ends the subsidy. It also ends the predictability. → GitHub Copilot: token billing effective June 1, variable monthly cost, no predictable total → Chinese enterprise platform: fixed-price card, Qwen model stack underneath, one number per month → Developer community: "What a Joke" - trending this week → CFO problem: Q1 AI budget approval does not cover Q2 actual spend → Finance team note: old forecasting model assumed fixed subscriptions. That model is now wrong. → Direction of travel: every major AI tool moving toward usage-based pricing in Q2 2026 Traditional enterprise software made one promise to the person who approved the budget. One seat. One fee. One line item that did not change between quarters. The Chinese platform kept that promise. GitHub repriced it. One company transferred the uncertainty to themselves. The other transferred it to the customer. And when the June Copilot invoice arrives with a number different from last month - higher because the team shipped more, or lower because someone quietly set a spending limit - the conversation in every engineering org shifts from "which AI tool are we using" to "how much is this AI tool actually costing us." That is not a developer conversation. That is a finance conversation. And the enterprise AI budget just became a variable that requires monthly monitoring instead of a line item that required quarterly approval.

• 
  EdKo (@EdKolife) reported 15 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.

• 
  Julius (@jullerino) reported 20 minutes ago

  @tannerlinsley @ahlimanhuseynov @KevinVanCott We’re not even running build in CI. The app is built on e.g. Vercel, typecheck in GitHub actions. Having to run and discard a build just to do static analysis is just slowing down CI for no gain. That’s my 2 cents

• 
  oSumAtrIX 🇦🇲 (@oSumAtrIX) reported 22 minutes ago

  @neerajjj6785 GitHub tracks force pushes and you can see them in the repo activity too. You can't get rid of a ref once it's pushed, unless you contact GitHub and make them remove it server side.

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  Chijioke Echefulachi Prince (@File8it) reported 26 minutes ago

  Then GitHub joined the fight 😭 403 error. SSH issues. Token confusion. Push failing repeatedly.

• 
  Ashrith Sathu (@sathuashrith) reported 26 minutes ago

  found few things on Greptile CLI, few security changes if you guys can make @greptile @dakshgup 1. The direct install path ( the curl one ), this install method downloads greptile.js from GitHub Releases and does not verify a checksum or signature. And this method also uses the same curl ... | bash flow for the update command, so if something gets compromised, this will cause issues 2. Right now, the CLI only sends committed changes to your api, but by mistake, if we have any env files committed in the diff, they are also sent (I know it's the developer's mistake, but still, if you can do that ) thanks, :)

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  Shubham Sharma | AI & Tech (@editxshub) reported 27 minutes ago

  @polydao Bro is still trying to farm GitHub handles using OpenAI Codex, a program that was officially shut down in 2023. Forinking a repository and making fake commits won't get you a $1,200 subscription, it just makes your profile look like a desperate spam bot. Stop lying for impressions.

• 
  Bill Forney (@wforney) reported 28 minutes ago

  @thisjonrussell @github @shanselman GitHub action `Azure/functions-action` down - Microsoft Q&A

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  Ibrahim Mokdad (@ibmokdad) reported 29 minutes ago

  for founders and builders trying to grow from their work: the content problem is usually not ideas. it is the daily execution. 2 posts. 25 thoughtful replies. buyer-signal follow-ups. easy to write on monday. hard to repeat for 30 days. i build @NousResearch hermes skill that pulls GitHub releases, Linear/Notion notes, support quotes, and demo transcripts every morning. then it turns the work into drafts, reply prompts, and a calendar. approval before anything posts.

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  Ekemini Edet (@Ekeminiedet44) reported 30 minutes ago

  DEGREE OR SKILLS? I'm going to say what the data industry doesn't want to admit: a degree is no longer the gate to this career. I've seen Computer Science graduates who can't write a clean SQL JOIN. And I've seen self-taught analysts pulling six figure contracts armed with nothing but Python, Power BI, and a portfolio that speaks for itself. Here's the uncomfortable truth 👇 A degree teaches you theory. The job demands execution. Can you write a query that pulls the right data from 10 million rows without crashing the server? Can you build a dashboard in Tableau or Power BI that a non-technical CEO actually understands? Can you use pandas to clean a dataset that looks like it was formatted by someone who genuinely hates other people? THAT is what clients pay for. Not your GPA. I'm not saying degrees are useless. They open certain doors especially in research, academia, and some corporate pipelines. But for freelance work, consulting, and client-facing analytics? Your GitHub, your dashboards, your real-world projects, and your ability to turn messy data into clear decisions that's your degree now. The market is global and it doesn't care where you studied. It cares whether you can deliver. A business in Toronto or Manchester or Sydney isn't hiring you because you have letters after your name. They're hiring you because you solved a problem that looked exactly like theirs. Build the skills. Document the work. Ship the results. The credential will never outperform the portfolio. What do you think — degree or skills?