GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (70%)
• Sign in (17%)
• Errors (13%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Itapema	Website Down	18 days ago
Tlalpan	Sign in	24 days ago
Quilmes	Website Down	24 days ago
Bengaluru	Website Down	26 days ago
Yokohama	Sign in	27 days ago
Gustavo Adolfo Madero	Website Down	1 month ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Temidaradev (@temidaradev) reported 20 seconds ago

  @halbour727 or you can open issues on github if there is no duplicate but dm is okay

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  yourclouddude (@yourclouddude) reported 4 minutes ago

  2026 PROJECT BUILDING CHALLENGE 🚀 1. Build 1 project every month 2. No tutorial copying 3. Push code to GitHub daily 4. Write a README for every project 5. Learn by building, not watching 6. Solve 1 real-world problem each week 7. Deploy at least 1 project/month 8. Share your progress publicly 9. Improve 1 old project every week 10. Finish projects before starting new ones By the end of 2026, you'll have a portfolio most people never build. Who's in? Mark your attendance 👇

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  Alex Rogov (@Alex_Rogov_js) reported 6 minutes ago

  @github the clean diff problem is real. worked on a codebase where agent PRs looked great on review, tests passed, diff was clean, and introduced a subtle invariant violation that surfaced 6 weeks later. the checklist needs a line: 'does this PR know what it doesn't know?'

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  deadfishie (@deadfish1001) reported 8 minutes ago

  @shub0414 i still use github copilot and cursor. perplexity is great too. wasnt sora shut down?

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  Vegas (@Vegas97DP) reported 10 minutes ago

  @conductor_build I currently have a huge bug in the new version. I have a lot of Job Repos that dont use gitHub (and it's okay, i know i dont have a few features like the PRs or the gitActions, ...) But all the other amazing features of condutor are working. But now i cant go in settings of the repo, because he try to update to the new settings with auto creating a PR that cant work so I'm stuck. @mattyp @conductor_build can you fix this tnx! (Ps. also if you can add the possibility to have multiple gitHub accounts, configurable at the level of repo so in theory each repo can have is own account would be amazing tnx)

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  Nikhil sinha (@sinhaniik) reported 11 minutes ago

  Debugged a blank hero video after deploying to Vercel. The code was correct, but *.mp4 in .gitignore prevented the video from reaching GitHub. Removed the rule, committed the asset, fixed an HTTP push-buffer issue, redeployed, and confirmed the video returns HTTP 200. A good reminder: deployed code cannot load assets that were never deployed.

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  Tejas Vachhani (@imtejasvachhani) reported 12 minutes ago

  GitHub Copilot (AI + Momentum) The physics: Momentum p = m·v — mass (substance of your skill) times velocity (speed of execution). AI acts as a force multiplier on v, but cannot supply m. Application: A developer's mass is their understanding of system architecture, problem logic, and code quality. Velocity is how fast they type and debug. Copilot eliminates the high-friction parts of velocity: boilerplate code, syntax lookup, repetitive patterns. The developer stays in flow state longer, so their velocity increases dramatically. But if a junior dev with no mass (no architectural understanding) uses Copilot to ship code at high velocity, the result is a fragile, buggy system — fast garbage. The winning formula: solid senior developers amplify their existing mass with AI velocity, building momentum that's incredibly hard to stop.

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  Amal Roy (@RoyAmal) reported 12 minutes ago

  AI is writing more code than ever. Who's reviewing it for security? That's the problem Anthropic is trying to solve. Claude Code Security Review is an open-source GitHub Action that automatically analyzes pull requests for security vulnerabilities using Claude's reasoning capabilities. Instead of relying only on pattern matching, it reviews code semantically to identify issues like injection risks, authentication flaws, insecure data handling, secrets exposure, and other security weaknesses. Think about what this means. Every PR can get an AI security engineer. Automatically. Before code reaches production. What makes it interesting: • Reviews only changed code in PRs • Posts findings directly on pull requests • Works across programming languages • Uses contextual understanding instead of simple rules • Filters false positives to reduce noise • Fits directly into existing GitHub workflows The bigger trend isn't AI generating code. It's AI reviewing AI-generated code. Because as AI writes more software... The bottleneck shifts from creation to verification. The most valuable engineer in the AI era may not be the one who writes the most code. It may be the one who catches the most mistakes. We're moving toward a future where every developer has: • An AI coder • An AI reviewer • An AI security analyst And software teams will never look the same again.

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  Ibrahim Mokdad (@ibmokdad) reported 12 minutes ago

  founder mornings are not slow because you lack a dashboard. they are slow because every app screams at the same volume. calendar: investor call slack: customer blocked gmail: numbers needed before noon github: checkout PR waiting linear: launch task overdue stripe: payment warning i made a @NousResearch Hermes morning control tower over sample signals. it turns the pile into: - do first - decide today - reply today - watch - ignore on purpose the important part is the last one.

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  Oscar Castillo (@OscarAlexandr0) reported 14 minutes ago

  Linux runs 96% of the top web servers. Yet no official Claude desktop client. Enterprise AI spend hit $200B in 2024. Desktop tooling still ships for two OSes only. Middle office teams need traceable outputs. Linux users get the same problem GitHub solved seven years late. T...

• 
  LewSales.XYO✨️Passionate About XYO and WinLEW✨️ (@LewSales) reported 14 minutes ago

  @OfficialXYO I Know Your looking for feedback and I'll admit, You have both codex and claude, (GitHUB) Ive had a slow Weekend so I started playing around. By themselves, one or two issues. Ive found feeding codex and then claude works great or vise verse. Codex better prompts; Claude better Skills; When i ran the claude XYO SDK I feel if you could get codex in this area, when prompting, the code claude writes would be better

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  Dewi (@MohamedDewidar_) reported 15 minutes ago

  The fastest way to actually level up Claude Code: Add MCP servers to .claude/settings.json. Not custom built ones. Just the ready-made stuff: GitHub MCP: PRs, issues, code search from the terminal Puppeteer MCP: browser automation in the loop Filesystem MCP: read/write across projects 5 minutes of setup. Feels like a completely different tool.

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  Bijan (@Beethoven779) reported 15 minutes ago

  @ryanvogel opencode has a lot of potential. I use it everyday, but I am not happy with it to be honest. There is UX issues there, I mention in X and in github issues, they either get ignored or prs closed because certain time has passed and they did not have time to review or...

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  Cyfrin Audits (@cyfrin) reported 23 minutes ago

  The manual workflow is brutal. Cross-reference OSV. Check GitHub Security Advisories. Search Socket. Then trace the dependency tree backward to figure out which direct package even introduced it. Most teams don't do this. Not because they're lazy. Because it takes hours per issue.

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  whydeepak (@ideepakmn) reported 25 minutes ago

  Spent the last month building a "Zomato for restaurants" And the most interesting lesson wasn't technical, it was economic: a small kitchen keeps almost nothing on a delivery order, and almost nobody running one has done the actual math. Here's the breakdown. On every order the platform takes commission of roughly 28%, plus GST, plus a payment mechanism fee, plus tax. Stack it and the restaurant is left with pennies. The only way to win is volume, which means for a new cafe it's roughly a 20/80 game luck and demand do most of the work. That's fine for a large restaurant with through put, but it's quietly brutal for cafes and cloud kitchens that live and die on margin. So the question I got interested in is purely mechanical: how much of the ordering + logistics layer can you rebuild yourself, and how cheaply? Turns out, most of it. You don't need payment gateways redirect everything to WhatsApp. You need a dynamic menu you can manage in one click, with inventory living in Supabase, if something runs out, one command flips it off the menu. For tracking, you record how long each dish actually takes to make, set that as a standard timer, and expose two flows: takeaway and delivery. Delivery itself is the part everyone is scared of and it's the easiest to solve one extra person handles it, free under 3km, then ₹10-20/km beyond that, matched to standard delivery-partner rates so nobody's overpaying. Add a minimum-order threshold for free delivery and your average order value climbs on its own. The V1 stack is deliberately boring: Next.js, React, TypeScript on the frontend, Next.js API routes on the backend, Supabase (Postgres) for data, Vercel for hosting, *** and GitHub for version control. Nothing exotic and expensive. The edge was never the tech it's that you've removed the platform tax that was eating ~50% of the economics. The money you save covers the extra hire who runs delivery and helps in the kitchen. It pays for itself. Now the part customers never see. Ever wonder why the same dish costs more on the app than at the counter? It's not random. The restaurant has to bake the platform's cut commission, fees, packaging back into the menu price, or it loses money on every order. So the delivery price isn't the food price, it's the food price plus the tax you can't see. In practice that lands the same dish somewhere around 1.5x-2x what you'd pay at the outlet. You're covering the commission and it's being sold to you as convenience. The fix is almost funny: just ask the restaurant if they deliver directly. And yet Zomato or Swiggy is a giant for real reasons, and it's worth being honest about that. Discovery, trust, and food at your door in minutes are genuine value. We live in a world where the thing that took 10 days now arrives in less than 10 minutes, and people are happy to pay a premium for everything in one place. Convenience is a real product, not a scam, and any builder who ignores that is fooling themselves. So I'm building this anyway not to kill the giant, but because kitchens running strictly on their finances deserve an option that respects their margins. Every idea has its perks and its downsides. I'm a builder and a marketer; I like shipping ideas and finding out. I'm already working on this one. If you ran a cloud kitchen or a cafe, what would you do differently?

• 
  Lorenzo (@gabor_rar) reported 27 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👇

• 
  m0h (@exploraX_) reported 28 minutes ago

  you don't need to pay $12-$75 monthly to Figma any more. there's a free open source tool that replace Figma. built by Kaleidos (a spanish open-source company) completely FREE. run on web and locally. MPL-2.0 licensed. 45k+ github stars here's how to set it up under 5mins: — the fastest way (0 setup): just go to penpot. app and create an account. that's it. you're designing in your browser in under a minute — no install, no server, no card. this is all most people need. the steps below are only if you want to self-host and own your data. — self-host option (still under 5 mins): you'll need docker installed and a machine with 2GB+ RAM. then: 1. grab Penpot's official docker-compose file from the docs 2. run docker compose -p penpot -f docker-compose.yaml up -d 3. open localhost:9001 in your browser 4. create your account — email verification is off by default, so you're straight in six services spin up (frontend, backend, exporter, postgres + supporting bits) and you've got a private Figma running on your own infra. — why bother self-hosting: → your design files never leave your machine — matters for client NDAs or regulated work → no per-seat fees, ever, no matter how big your team gets → designs stored as open SVG + CSS — human-readable, version-controllable, yours forever — the honest catch: → feature parity with Figma isn't 100% — advanced prototyping + design-system tooling still trail → plugin ecosystem is smaller → big files can lag → importing existing Figma files works but complex components need manual cleanup —

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  Malik Muzamil (@malikmuzamilai) reported 28 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.

• 
  Fokki (@0x_fokki) reported 35 minutes ago

  Someone posted a video of a man asleep at a football stadium on a Tuesday. Forty thousand people mocked him before halftime. Fell asleep at the match. Wasted the ticket. Missed the goal. Every sports account shared it by Wednesday. Someone in the replies posted: "respect." His account had one pinned post. A Claude Code terminal. /loop running. Routines active. Auto Mode on. Seven GitHub PRs reviewed while he slept in that seat. Three Slack digests posted. One CI failure triaged, root cause identified, draft fix PR opened. He set up 14 steps of configuration the weekend before. Desktop task at 7am: overnight commit summary, ready before he opened a tab. Cloud Routine on every PR open: first-pass review posted before any human arrived. /loop every 10 minutes: deployment status checked, no one watching. Auto Mode approved 93% of the actions automatically. The people who mocked him watched 90 minutes of football and went home. Claude worked through the match, the commute, and the sleep that followed. He wasn't asleep at the game. He was testing the stack. full 14-step automation guide in the article above👇

• 
  Elias Al (@iam_elias1) reported 36 minutes ago

  I found a free tool that automates anything you do manually in your browser. Type what you want in plain English. Watch it happen. Free. No code. No setup. Just install the extension and go. It is called RTRVR. And here is everything you need to know. ai turns your browser into a self-driving AI agent that performs data extraction, form filling, and multi-step workflows across dozens of tabs. Describe your goal in plain English and watch the agent click, type, and navigate — inside your own browser. Here is what that looks like in real life. You open the Chrome extension. You type: "Go to LinkedIn, find all marketing directors at B2B SaaS companies with 100 to 500 employees in New York, and export their names and companies to a Google Sheet." The agent opens LinkedIn. Searches. Navigates profiles. Reads the data. Exports it. You do nothing. It does everything. Or: "Monitor this competitor pricing page daily and alert me when anything changes." Or: "Fill out this job application using my CV." Or: "Scrape all product names and prices from these 50 URLs and compile them into a spreadsheet." It integrates natural language interactions to seek specific information, crawl entire sites for bulk data, and export results directly into Google Sheets. It supports cross-tab activities, comparing information and performing bulk actions across multiple sites simultaneously. Here is the feature that makes RTRVR genuinely different. Authenticated automation: runs scripts inside your logged-in browser session, meaning it accesses sites you are already signed into. No credential sharing. No API keys for every platform. It uses your existing sessions exactly the way you would. This is the thing that breaks every other automation tool. Zapier cannot touch LinkedIn. Make cannot access your Airbnb dashboard. Most scrapers fail behind any login page. They need API access or credentials passed in a config file. RTRVR runs inside your actual browser. Where you are already logged in. It sees exactly what you see. It can do everything you can do. Nothing is off limits. Here is the MCP integration that makes this genuinely exciting for AI users. Copy your unique rtrvr. ai MCP endpoint into ChatGPT, Claude, Cursor, or your own code. Instantly give them the power to control your browser, extract live data, query knowledge bases, and perform complex automations. No local installation required. Claude does not have a browser. Neither does ChatGPT by default. Paste one RTRVR MCP URL into either of them and they do now. Your AI assistant can navigate real websites, read live data, fill real forms, and interact with any page on the internet. Through your browser. With your sessions. Without you lifting a finger. Here is the no-code teaching feature for non-technical users. Teach rtrvr .ai a trick without writing code, just show it. Perform the task once the clicks, the typing, the navigation and rtrvr records everything including the underlying network calls. The agent repeats it automatically whenever you need. Do it once. The agent learns. Does it automatically from then on. No prompt engineering. No technical setup. Just show it what you want. Here is what it costs. Free to start. Scale to 1,000+ cloud browser agents simultaneously. Run workflows automatically on a schedule. Append results to Google Sheets automatically. OpenAI Operator does the same thing. $200 per month. ChatGPT Pro required. RTRVR starts free. One honest thing worth saying before you install it. Users praise the extension for its powerful automation and scraping capabilities and its usefulness for research-heavy tasks. Consistency is a major issue, several reviews describe frequent reliability problems and errors on complex workflows. It is not perfect. Complex multi-step tasks sometimes fail. It is improving fast from version 11 to version 31 in under a year. But for lead research, competitor monitoring, data extraction, form filling, and anything repetitive you do manually in a browser every week? Nothing free comes close to what RTRVR does. You have been doing manually what an AI agent could do for you. That stops today. Source: rtrvr. ai · Chrome Web Store · GitHub · 2026 (Link in the comments)

• 
  magsimich (@magsimich) reported 38 minutes ago

  A MICROSOFT ENGINEER SHOWED AT BUILD 2026 THAT THE WAY YOU HAVE WRITTEN CODE FOR THE LAST 30 YEARS IS BEING REPLACED BY SOMETHING MOST DEVELOPERS HAVE NOT TAKEN SERIOUSLY AND THAT THE TRANSITION ALREADY HAPPENED WITHOUT ASKING YOUR PERMISSION Straight from Microsoft Build 2026 where GitHub Copilot Agent Mode and Copilot Studio Agentic Workflow Builder reached general availability and the phrase intent-first programming stopped being a concept and became a shipping product -> The moment it clicks writing code stops being the job and becomes what it is underneath describing what you want a system to do precisely enough that an agent can build it correctly and audit it safely That one idea reframes everything you thought was your value Why syntax proficiency is no longer the ceiling Why the developer who writes the clearest prompt ships faster than the one who types the cleanest code Why the skill that used to take years to build can now be approximated in seconds by someone who has never opened a terminal Writing code was never the final skill -> writing precise intent that an agent cannot misinterpret is And as agent mode commits rebases and deploys on your machine faster than you can follow the one person who catches the misinterpretation before it hits production is the one who understands what the agent was actually asked to do There is a person on every team who reviews what the agent produced instead of just merging it This is the shift that quietly makes that person irreplaceable Bookmark it The next time an agent ships something broken you will know exactly what question was never asked

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  chris catlett (@ccatlett1984) reported 39 minutes ago

  @gonecozycrafts You won't be missing anything, there is a GitHub issue that was open for about a month recently regarding the plug-in and older firmware.

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  maria (@maria_rcks) reported 46 minutes ago

  This is for keeping you distracted when github is down

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  Asher Crowe 🪺 (@ashercrw) reported 51 minutes ago

  Everyone who read my $18K/month breakdown filed it under "real estate side hustle" and moved on. That was the mistake. Watch this guy run the exact same free tool on fashion. On art. On food. On venues. The real estate playbook in the article was just the cleanest example to explain it with. It was never the ceiling. The tech is called Gaussian splatting. It's been sitting free on GitHub since 2023, open source, anyone could've touched it. The workflow is genuinely four moves: film your subject, orbit around it from every angle, upload the clip to Luma AI, and you get back a walkable 3D scene you can drop into any browser tab. On Luma you can add keyframes, tune the settings, export it however you want, even lay sound on top. That's it. That's the whole rig. A phone and a free account. My article broke down the money on houses: $300 to $900 a scan, roughly 2 million agents, almost none of them offering it, your first paying client done in person inside 11 days. But this video is the part I kept hinting at. The niche doesn't matter. A boutique selling clothes, a gallery selling a show, a restaurant selling the room before you book it. Same tool, same four steps, same gap nobody's priced in yet. The code was never the hard part. It's been free for two years. The people making money are just the ones who showed up with a phone first. That window is still open. For now. Bookmark this one. You're either early or you're somebody's case study. 👇

• 
  kocer (@kocer_eth) reported 53 minutes ago

  OpenAI is giving away $1,200 for FREE to use Codex for 6 months Build something that can survive a GitHub page and one real user: - tiny tool that cleans messy CSVs for ops teams - Chrome extension that summarizes long Notion/Google Docs pages - Telegram bot that watches price changes for one niche - CLI that turns meeting notes into Linear/GitHub issues - simple dashboard for your own X/GitHub/Stripe data how to start: 1. pick one annoying problem you personally hit this week 2. open Cursor, Codex, or Claude Code 3. ask for a small repo, not a startup 4. push it to GitHub the same day 5. improve one thing daily: README, demo GIF, tests, UI, install flow 6. show the repo in comment or with your friends most of the time these programs accept even half-empty projects

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  umar ibrahim (@imp213x) reported 54 minutes ago

  Ok, this is getting serious. Has anyone ever had problems with subscription on @github ? I think they have the poorest support system I’ve ever interacted with! Actually, there is no interaction, because an interaction has to have a second or third party, I’ve been the only one doing the “interaction.” I’ve never experienced anything quite like this in my entire experience on any platform. If anyone have a quicker way to get their response 🙏

• 
  Medialordofficial🇨🇲 🇩🇪 (@MediaLord237) reported 56 minutes ago

  @PauloMatew @github @sseraphini Had same problem I recently switched to Cursor.

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  . (@sjallatak) reported 57 minutes ago

  if you experience a bug in omp you can just have some agent diagnose it from /debug, fill out the github issue template for you and submit it, and the roboomp github bot will have a fix for you in less than 5 minutes

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  Born to gamble (@borntogambles) reported 59 minutes ago

  PewDiePie just shipped a self-hosted AI workspace, gave it away for free, and pulled 44,000 GitHub stars in three days. A man whose entire career was screaming at video games. No company. No funding. No sales team. He said so himself: "No demo request. No Trojan horse." It's called Odysseus. It runs entirely on your own machine. Your data never touches a server. No telemetry, no subscription, no account. Most "ChatGPT alternatives" are a wrapper and a Stripe checkout. This one is the actual UI of ChatGPT and Claude chat, agents, deep research, email triage, memory running on hardware you own, with models you choose. There's a tool called Cookbook that scans your VRAM and tells you exactly which of 270+ models your machine can run. So you never download one too heavy for your box. The agent reads your files, runs your shell, browses the web, and handles real tasks while you watch. The email assistant reads your inbox, flags what matters, and drafts replies in your own voice. He described one auto-reply as the most polite way to tell someone off that they'll never even notice. The memory learns you over time. The skills rewrite themselves. The longer you use it, the better it gets at being you. Felix Kjellberg. 110 million subscribers. He spent a year documenting the build, then dropped a video titled "MY trillion dollar project is finally OUT." Then he pushed the whole thing to GitHub under an MIT license and walked away. Take it. Fork it. Host it. Yours forever. OpenAI is worth hundreds of billions selling you access to a server you'll never see. He gave the same thing away in a weekend, and signed off with one line: "The war on big tech has just begun."

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  drix.based🟦 (@drixtoshii) reported 59 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.