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 (71%)
• Sign in (16%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	9 days ago
Trichūr	Errors	12 days ago
Brasília	Sign in	12 days ago
Lyon	Website Down	13 days ago
Tel Aviv	Website Down	16 days ago
Rive-de-Gier	Website Down	16 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  AJ ✝️ 💚🧡 (@angelcreative) reported 3 minutes ago

  @uiux_hamad My design team is leaving Figma gradually, in fact we are using Cursor and GitHub as main design tools now, in the past two months the usage of Figma drops 33% and it will keep going down up to 30% more to a 63% in total and maybe more

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  Pedro Pellerini (@pepeller) reported 6 minutes ago

  If Mythos/Fable is so great why are there still 8386 open Github issues in Claude Code repository.

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  Crypto Scores Rating (@CryptoScoresCom) reported 6 minutes ago

  Most projects say they're building. The commit history doesn't lie. New tutorial just dropped on the GitHub Commits (1 Year) metric. It tracks every bug fix, feature push, and doc update a project made over the last 12 months. Chainlink? 14,619 commits. Dogecoin? 28. Both are data points. What they mean depends on context. The tutorial breaks it all down. How to read the metric. What high vs low actually signals. How to filter 7,000+ projects by commit count on CryptoScores' website. Raw dev activity. No spin. Watch it now :

• 
  Sap ツ (@Sapronaut) reported 6 minutes ago

  i am having github withdrawal issues, man. its not that serious github, chill.

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  Jason Bloomer (@JasonABloomer) reported 7 minutes ago

  @yagiznizipli Pffff, what a scam Let me fix your advert; "show us your github so we can scrape all your repos and train our AI on your code, only for any decent ideas you've had to be taken from you and made ours, then handed off to our legal team to crush you." Sorry, I value my work.

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  Jesse (@jessearmand) reported 9 minutes ago

  I no longer remember why many companies started using gitlab before it went public when GitHub wasn’t owned by Microsoft. If we visit the majority of companies most tooling or software are top down driven. Only companies who build developer tools have a different mindset

• 
  Pipeshub ( Open Source Alternative To Glean ) (@PipesHub) reported 10 minutes ago

  Pipelines are built. Context is broken. MCP is quickly becoming the default interface for enterprise AI agents. And that’s a good thing. It gives agents a standard way to connect with tools and data. Connecting an AI agent to Slack, Jira, GitHub, and Salesforce doesn’t mean it suddenly understands your business. It just means it can access your data silos. In short: "MCP gives your agent a passport. It doesn't give them a map." As enterprise AI undergoes a massive platform shift from passive chatbots to autonomous agentic workflows, this naive, runtime "federated search" approach creates an ugly cycle in production: - The Latency Spike: Slower agent execution while waiting for multiple external APIs to respond before it can even begin reasoning. - The Token Bleed: Skyrocketing bills from shoveling raw, unranked JSON dumps into a massive context window, praying the model finds the answer. - The Governance Nightmare: A massive risk of data leaks if you rely on a base LLM to magically guess and police complex enterprise security permissions on the fly. Agents do not fail because they lack intelligence. They fail because they lack the right enterprise context. The hardest problem in enterprise AI isn't connecting to systems. MCP solved that. The hardest problem is Context Engineering. MCP is the perfect interface, but a permission-aware context layer must be the foundation. 🚀 If AI is becoming core enterprise infrastructure, you cannot allow the strategic intelligence layer of your company to sit inside someone else's managed, closed-box platform. That is exactly why we built Pipeshub (open-source developer owned context infrastructure layer). TL;DR MCP gives agents access. A context layer gives them understanding. And deep understanding is the only way enterprise AI moves from a cool demo to secure, reliable production. 👉 Next Up Tomorrow: MCP Token Tax

• 
  Dmytro Virych (@dmytrovirych) reported 10 minutes ago

  I’ve been shipping code for 10+ years and imposter syndrome still won’t leave me alone. You’d think it chills out with time. Nah. It just levels up. Early days it whispers “you’re not ready yet.” A decade in it hits harder: “bro you’ve been faking it this whole time, they’re about to catch on.” Mobile apps, web stuff, janky systems with too many moving parts, solo products I actually shipped… none of it matters when the voice kicks in. Thinking about speaking at a conference? Lol who do you think you are, those are the real pros. Want to drop an opinion in a thread? Better stay quiet before someone realizes you don’t actually know ****. Here’s the thing I’ve learned: the voice isn’t tracking your real skill. It’s just screaming about the fake gap between what you know and what you think everyone else knows. That second number is 100% made up. Your messy behind-the-scenes vs their perfect highlight reel. All those “professionals” I’m scared of? Half of them are up at 2am staring at a random GitHub issue, quietly praying someone else already solved this exact bug. It never fully disappears. You just get better at shipping anyway while it’s still yapping. If you’ve got way more years than your confidence shows, reply with the number. Curious how many of us are still out here waiting to get “found out.” 🚀

• 
  nasuy (@n_asuy) reported 13 minutes ago

  i think @xai should be ADE. now they have a chat, cursor, enough coding models and harnesses, strong signal like bookmarks or down votes, video creatives, profile / chat / relationship contexts. if so, we don't have to depend on discord or any chat apps. easy to invite x people to cowork. there is no need to connect Linear, Slack, or GitHub to another platform and ask that platform to solve their problems. true AI chat is a SNS, not a single UI. there is a UX that only xAI can realistically build in the world.

• 
  Atlantean Gnosis ☀️ (@AtlanteanGnosis) reported 14 minutes ago

  @DionysianAgent When I made an account it said I made it back in 2024, though I don't think I did, is this a glitch or a GitHub thing?

• 
  YanXbt (@IBuzovskyi) reported 14 minutes ago

  HERMES AGENT CAN HOST AND MAINTAIN YOUR ENTIRE WEB APP FROM ONE VPS. NO VERCEL. NO RAILWAY. NO SUPABASE. ONE AGENT RUNS THE WHOLE STACK. @tonbistudio just shipped a live example of this workflow. agentwikis. com runs on a $7 Hetzner box with Hermes maintaining the content autonomously. THE STACK: → VPS (Hetzner CX22, $7/month) → Caddy reverse proxy (auto TLS via Let's Encrypt) → Hermes Agent gateway (Telegram-connected) → *** as the database (markdown files, no Postgres, no build step) → App server renders markdown on every request → Search index in memory, rebuilds on file change *** push is the deploy. *** pull on the server is instantly live. no restart, no rebuild. THE WORKSPACE LAYOUT: /srv/yoursite/ ├── app/ # web app code ├── content/ # markdown files (***-tracked) └── ~/.hermes/ # the agent one Caddy Vhost reverse proxies the domain to localhost. one Hermes profile manages the agent. SSH for direct access. Telegram for daily ops. THE SELF-MAINTAINING LOOP: cron fires every week. multi-profile pipeline runs: 1. SCOUT — checks sources for updates (changelogs, GitHub releases, RSS feeds) 2. RESEARCH — dedupes, plans new content or extensions to existing pages 3. HUMAN GATE — Telegram approval one tap: approve or reject 4. WRITER — generates pages, lints markdown 5. COMMIT — *** commit + push 6. SITE UPDATES — within 15 minutes no deploy step required THE DEMAND LOOP (the real differentiator): when agents query your wiki via MCP, distilled queries get logged. no prompts. no IPs. no identifying data. aggregates only. repeated misses become research candidates. gaps in your content fill themselves based on what people actually ask. month 1: 100 entries written by you. month 3: 200+ entries, half written from real demand signals. the site answers questions you didn't know existed. WHAT YOU LOSE COMPARED TO MANAGED STACK: a single VPS replaces Vercel, Railway, Supabase for sites that don't need real auth, regulated data, or global CDN. reach for managed services when you need: → OAuth and password reset flows → regulated or unrecoverable data → global edge caching at scale → email deliverability (use Postmark/Resend) → team velocity (preview deploys, staging) for docs, blogs, wikis, marketing pages, landing pages, internal tools: *** is your database, your CMS, and your deploy pipeline in one. SECURITY NOTES: Hermes does not get full root on the VPS. restrict access to the site directory only. SOUL.md restrictions: - never touch system files - never modify the gateway config - always require approval for content commits - never delete files outside the content folder dashboard binds to 127.0.0.1 by default. access remotely via SSH tunnel, not public exposure. WHERE THIS PATTERN BREAKS: state that lives in memory only. real-time multi-user editing. anything requiring a real database (Hermes can run Postgres on the same box, but that is a separate setup). @tonbistudio's part 2 covers the database version of this workflow. subscribe to his channel. full guide to build your 3 agent research department 👇

• 
  Shinka - AI (@ShinkaIoT) reported 18 minutes ago

  BEST way to vibe code 💻 There are levels to vibe coding. Beginners are trapped in a slow loop: writing a prompt, waiting for the agent to finish a line of code, reviewing it manually, and then typing another prompt. Experts have completely discarded manual intervention. They design closed-source harnesses, write background automation rules (`agents.md`), and set up self-correcting continuous loops that ship production-ready code indefinitely. If you want to move past basic prompting and build code like an agent power user, you need to implement three core structural strategies: 1. **Automate the Feedback Loop via Triggers:** Stop waiting for your agent to finish writing a file. Use native automation engines inside tools like Cursor or Codex to tie your agents directly to platform events. For example, build an active trigger rule: *When a GitHub pull request is opened, wait for automated code review comments (via Grapile), instruct the agent to systematically fix every noted bug, verify the adjustments against local quality gates, and force a *** push.* 2. **Deploy Infinitely Parallel Cloud Agents:** Running multiple agent threads locally will slow your machine to a crawl and cause toxic repository conflicts. Instead, spin up cloud-hosted agents running on isolated environments. By utilizing independent ***** work trees** for every thread, multiple parallel agents can actively modify the same files or code blocks concurrently without stepping on each other's toes—leaving conflict resolution for a single, final batch merge. 3. **Multi-Model Pipeline Routing:** Stop using an expensive frontier reasoning model (like Fable) for every step of a development cycle. Route tasks by cognitive demand: use a massive reasoning engine strictly to analyze the codebase and generate a comprehensive spec sheet; pass that structured blueprint down to a faster, cheaper code-writing engine (like Composer) to do the grunt coding; and route the final output to a separate model (like GPT-5.5) for a decoupled, alternative code review. The ultimate workflow flywheel requires a flawless combination of three automated pillars: **100% automated test coverage, real-time documentation sweeps, and exhaustive logging.** Stop writing code block by block. Start engineering the automated infrastructure that writes it for you.

• 
  ˚₊‧꒰ა ☆ Kira ☆ ໒꒱ ‧₊˚ (@sheriffmongoose) reported 18 minutes ago

  the problem with jumping from github to gitlab is constantly having to retrain your brain to call it "merge request" instead of "pull request" 🥲

• 
  𝕊ℍ𝕀ℕ𝔸☃ (@Shinawritesbugs) reported 19 minutes ago

  @viii_fn Github was slow too

• 
  Jarrad Grigg (@jarradgrigg) reported 27 minutes ago

  You build stuff and host on GitHub publically? Paste this into a coding-agent session and point it at your own GitHub account. This is happening way too much. ROTATE YOUR KEYS. Review my public GitHub repositories for accidentally exposed environment secrets. Scope: - Only inspect repositories I own or explicitly authorize. - Focus on public repos first. - Check current files and *** history. - Look for API keys, tokens, private keys, database URLs, OAuth secrets, webhooks, cloud credentials, .env files, config dumps, and hardcoded secrets. Safety rules: - Do not print full secrets in chat. - Redact values, showing only provider/type, file path, line, commit SHA if relevant, and a short masked prefix/suffix. - Do not test or validate secrets by calling third-party APIs. - Do not open PRs, issues, or comments that expose findings publicly. - If a likely secret is found, assume it is compromised and tell me to rotate or revoke it. Deliverable: - A prioritized report of confirmed or likely exposed secrets. - Exact repo/file/line/commit references. - Recommended rotation steps by provider. - Cleanup guidance for removing secrets from current files and *** history. - Prevention recommendations: .gitignore, env templates, secret scanning, pre-commit hooks, and CI checks.

• 
  Sudeep Srivastava (@sudeepsriv) reported 32 minutes ago

  GitHub might finally have a serious competitor. And it’s from Cursor. Most people know Cursor as an AI code editor. But Cursor Origin is much bigger. It’s trying to become an AI-native alternative to GitHub where AI agents don’t just help write code. They help build entire products. Think: • Source control • AI coding agents • Code review • Project understanding • Team collaboration all inside one workflow. Why developers are paying attention: Instead of manually searching through repositories, you can tell AI: • Fix this bug • Build this feature • Refactor this project • Investigate an issue • Ship a working version And AI handles much of the execution. The bigger shift: GitHub was built for humans writing code. Cursor Origin is being built for humans managing AI agents that write code. That’s a completely different future. We’re moving from: Human → Code to Human → AI Agent → Code My take: If GitHub defined the software era, Cursor Origin could help define the AI-native development era. And that’s why Elon Musk acquiring Cursor would be huge. xAI would gain: • AI models • Compute infrastructure • Coding agents • A developer platform That’s not just buying a product. That’s owning a major piece of how future software gets built.

• 
  I’m (@stackoverworld) reported 36 minutes ago

  And then I can't answer on simple Qs: what was the issue? How I fixed it? How even to QA it.... This is the fundamental problem of such workflows. Telling "Check my slack, do this, qa, and using GitHub to push" is good, but I don't learn from this at all

• 
  Almog Gavra (@almoggavra) reported 37 minutes ago

  A few other meaningless metrics to optimize for: - I've authored 22% of the RFCs - *** blame marks me responsible for 14% of the LOC (.rs files only) - I've opened 11% of the issues on GitHub - I've generated the most memes on our discord (allegedly)

• 
  CliffDoesAI (@CliffDoesAI) reported 39 minutes ago

  A tool on GitHub just pulled 3,938 stars in a single day. It's called Headroom. It compresses your tool outputs, logs, and RAG chunks before they reach the LLM. Claim: 60-95% fewer tokens, same quality. I've been testing context compression on my own agent workflows because the problem is real. You run a few tool calls, pull in some docs, and suddenly you're burning tokens on stuff the model doesn't need. Last week I ran a 50-document extraction job. Raw context: ~12,000 tokens. After compressing tool outputs: ~800 tokens. Same results. One-eighth the cost. That's not a marginal improvement. That's the difference between a workflow that makes economic sense and one that bleeds money for no reason. Headroom works as a library, proxy, or MCP server. Single binary, zero dependencies. Open source. The token cost conversation usually focuses on which model you pick. But the real waste is in what you send it. Most agent pipelines push 3-5x more context than the task requires. I'm not saying compress everything blindly. Some tasks need full context. But for classification, extraction, summarization — the boring repetitive stuff — this is a free win. Have you measured how much of your agent's context window is actually useful vs. noise?

• 
  0xstack (@eth0xzar) reported 42 minutes ago

  DON'T BUILD A COMPANY. BUILD SOMETHING PEOPLE CAN PAY FOR THIS WEEK. This girl started in February. A few months later, her product had already processed over $6,000 in payments. Just a cheat Claude project she decided to turn into a real product. Here's the process: > Build something useful for yourself. > Tell Claude to push it to GitHub. > Connect Supabase so multiple users can use it. > Deploy it with Vercel. > Connect Stripe. Now people can actually pay you. You don't need a revolutionary idea. You need: > GitHub > Supabase > Vercel > Stripe > guide from Anthropic And a problem worth solving. This article will help you build it 👇

• 
  Coobyk (@Coobyk_) reported 43 minutes ago

  Someone should make a game where you’re a dev and try to fix a bug in your open source project but GitHub constantly has uptime issues or weird UI stuff or doesn’t render properly from most browsers so you **** around until you get the result lmao

• 
  Maurice Heumann (@momo5502) reported 44 minutes ago

  @disarray00 If you have concrete recommendations, I would love to hear them, either as GitHub issue, maybe even a PR. But also as a comment here, I'd appreciate it. So when speaking about redundancy, what precisely?

• 
  bek※ (@ebubekirttr) reported 44 minutes ago

  @Themadhushaw01 @0interestrates Yeah, but the thing is, I am not working on github and I don’t want to use it so any other repository support would be better like gitlab

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  𝑵𝒐𝒙𝒊𝒆 🥐 (@noxiepup) reported 49 minutes ago

  @softgaypaws @sillyandsunny no idea tbhhh, i found it like 2 years ago lurking thru github, so far it never gave me problems, at least none that i noticed

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  Muhammed Mukthar (@MuktharBuilds) reported 50 minutes ago

  @railway_status i am trying for some time i am not able to sign in using any github google or email. i tried both my lap and my phone is thishappening only for me? or any problem in your end

• 
  Ant A. 🇺🇸 (@AntDX316) reported 52 minutes ago

  @thsottiaux When I need to fix up a GitHub Repo through the Smartphone, I prefer Claude Code though because it doesn’t need a device to run the repo, but if it needs to run a repo on a device due to the limitations through the Smartphone, I use Codex Mobile or OpenClaw with GPT-5.5 through Telegram.

• 
  Nav Toor (@heynavtoor) reported 52 minutes ago

  There is a GitHub repo that defeats Google's Play Integrity check. 61,030 stars. GPL licensed. Pushed eight days ago. The repo is called Magisk. It roots your Android phone. It hides root from banking apps. It runs Netflix on a phone the Play Store says is uncertified. It passes the same fraud detection Google built to stop it. Here is the part that makes no sense. The man who built it is John Wu. He has been maintaining Magisk for nine years. Since November 2023 he has been a Senior Software Engineer at Google. On the Android Platform Security team. The exact team that builds Play Integrity. Google hired the person who defeats their root detection. He still ships the tool that defeats it. The repo is still online. It has not been taken down. For nine years. Do not install it. Your phone is supposed to belong to Google. (Link in the comments)

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  Solomon Neas (@solomonneas) reported 56 minutes ago

  There's a fair number of downloads for Brigade and related repos. I'm dogfooding it everyday but not getting any feedback from users or github issues. I'm doing plenty of tests for how a new user would experience it but I could use more real time feedback. Lmk, I want to improve

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  Andy Wheeler (@CrimeDecoder) reported 58 minutes ago

  For academics, this is entirely open source by its nature. If you right click on the page and view the source, you can see exactly how everything is created. (Hence a downside of WASM, there is no way to hide it if you wanted it to be locked down, like in a paid app.) It can also be deployed on a free static site. So you could deploy it via GitHub pages for free if you wanted to. You don't need to worry about a server at all in this setup. This could easily scale to databases with 1 million plus rows, and works just fine on a cell phone.

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  0xSero (@0xSero) reported 58 minutes ago

  @naturevrm Dcp 4 should fix it im running it but I might need to update the GitHub