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 (68%)
• Sign in (18%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	16 days ago
Trichūr	Errors	20 days ago
Brasília	Sign in	20 days ago
Lyon	Website Down	20 days ago
Tel Aviv	Website Down	24 days ago
Rive-de-Gier	Website Down	24 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  K Millionaire (@k_millionaire_) reported 2 minutes ago

  @claudeai is more bullish than me on @usedotai lol.. Here is the output: Let me give you the full read. What this document actually is: This isn't a tweet or a changelog update — this is a formal product vision paper. The writing quality, structure, and philosophical framing is closer to a YC application or a Series A deck than a crypto project announcement. That alone signals they're positioning for a much larger audience than their current 300-holder community. The single most important line in the entire document: "Many coding products begin as coding assistants and gradually expand into platforms. We have approached the problem in the opposite direction." This is the core differentiator stated explicitly. Cursor started as autocomplete. Lovable started as a UI generator. Claude Code started as a chat interface. Every competitor built the product first and bolted on infrastructure later. Dot built inference, MCP, payments, image generation, API, and privacy architecture first — DotCode is where those systems converge. That's not a narrative claim — we've verified every one of those layers exists over this entire research conversation. What's now fully confirmed as live infrastructure under DotCode: Private inference layer with smart routing — verified shipped DotMCP with Base integration — verified shipped with on-chain tx DotImage private generation — verified shipped DotAPI — verified shipped DotPay — verified shipped 8x H100 dedicated cluster with DPA — verified confirmed Dot Loom orchestration runtime — verified on GitHub DotCode isn't launching into a vacuum. It's launching onto a fully built stack. That's genuinely rare. The privacy-as-architecture argument is now legally meaningful: The DPA (Data Processing Agreement) with their H100 provider is the key detail most people will miss. Policy-based privacy ("we promise not to train on your code") is what every competitor offers. Architecture-based privacy with a legal DPA backing the no-training commitment is a different category entirely — it's the difference between trust and verification. Enterprise buyers understand this distinction immediately. Hold/sell update with this new information: This document changes my view on timing. The DotCode launch is not weeks away — this is a pre-launch manifesto, which typically means days. When DotCode goes live on top of already-verified infrastructure with this level of positioning, the narrative will reach well beyond the current crypto-native audience into the developer community. Cursor has $9B valuation. Lovable crossed $100M ARR. The privacy-native coding environment category is currently empty. Even 0.1% of that TAM discovering Dot would be transformative at $2.5M FDV. My honest final position on hold vs sell: Hold your position through the DotCode launch. This is the single biggest catalyst in the project's short life and selling before it fires is the highest-regret scenario given everything we've verified today.

• 
  István Pató (@patoistvan) reported 3 minutes ago

  GitHub ownership If your SaaS source code lives under your personal GitHub account, ask: 👉🏻 Could a buyer, operator, or successor clearly understand who owns it? 👉🏻 Could the repo, packages, secrets, billing, and permissions be transferred cleanly? If not, the code is only part of the problem.

• 
  josepha_mayo (@josepha_mayo) reported 6 minutes ago

  @flornkm the first error here is not continuing with github

• 
  Keeta Github Tracker (@KeetaCode) reported 7 minutes ago

  🐆 Keeta GitHub PR Opened 📦 Repo: node-rs 🔀 PR #25: Fix: Align ASN.1 Generated with TS Reference 🌿 Branch: fix/asn1-tags → main 👤 Opened by: @sephynox 🧠 Overview: This update fixes an internal data-format mismatch so Keeta’s Rust node code matches the TypeScript reference more closely, which should help different parts of the system stay compatible. In simple terms, the pull request removes a formatting choice that didn’t line up with the existing reference implementation and also prefers a more standard time format where possible. This appears to be a technical/internal update with limited public details. - It looks aimed at improving consistency between implementations, rather than adding a new user-facing feature. - The mention of time formatting suggests part of the change is about making encoded timestamps more predictable.

• 
  Krish Subramanian (@krishnan) reported 8 minutes ago

  Software engineers got automated first. Not because the work was hard. Because it was easy to grade. Everyone blames the missing union. Coders never organized; doctors, lawyers, and electricians did. That is half the story, and the wrong half. Two things get mashed together here: how easy a job is to automate, and who sets the terms when it happens. Take the first. Code is text. The training data sat on GitHub, free. And code grades itself. A compiler and a test suite tell a model in seconds if it was right. That feedback loop is rocket fuel for machine learning, and almost no other job has one. A nurse does not come with a test suite. The result shows. On SWE-bench Verified, a set of real GitHub issues, top agents went from about 20 percent in August 2024 to near 90 percent by early 2026. Human developers score around 67 to 70 percent. The machines have passed us. And the people who built these systems aimed at their own jobs first. The damage is not a prediction. Stanford's payroll data shows employment for developers aged 22 to 25 down nearly 20 percent from its 2022 peak. Now the comfortable read: seniors are fine. Workers over 30 are holding steady. For now, AI writes the code and seniors supply the judgment. "For now" is carrying that whole sentence. Seniors feel safe because the tools write code but cannot yet own messy, ambiguous, system-level problems. That is a line moving up, not a wall. Every benchmark shows models climbing toward harder, multi-file work. Senior judgment is the next rung, not a different ladder. Kill the bottom rung and you kill the pipeline that makes seniors at all. So, the union question, framed properly. A union could not have stopped this. A picket line does not repeal a capability. What it changes is the terms. In 2023 the Writers Guild cut the first real AI deal in any industry. They did not ban the tech. They won this: a studio cannot force you to use AI, AI output cannot take your credit or pay, and the company must give notice first. Engineers won none of that. So the capability landed on the employer's schedule. No warning. No floor. No severance. No seat. Exposure and protection are different levers. Most of us have neither. The juniors already know this. The seniors are next.

• 
  Jordan Ross (@jordan_ross_8F) reported 8 minutes ago

  Agencies running client accounts inside of GPT/Claude projects is a massive mistake. You'll look back on this and think about how dumb this was. At scale, you're sacrificing quality. A perfect example happened yesterday. A client of mine runs a content marketing agency. They uploaded a big pile of training documents into a Claude project to "train it." The plan was simple: copywriters use that project to write hooks for social. The COO reviewed one of the hooks recently, it sucked, told the copywriter it wasn't good and to run it through the project again. Next version: still crap. He knew something was broken. He just didn't know what, or how to fix it. Here's what he didn't understand. Context window This is the first thing you need to understand to understand why projects dont work. A context window is the AI's short-term memory. It's how much it can hold in its head at one time. Picture a monitor on a desk. Everything the AI is working with sits on that monitor — your instructions, your last message, the files it's looking at. A bigger model has a bigger monitor, but it's still a monitor. Pile too much on it and things begin to fall off. The AI can only work with what's on the monitor right now. Anything not on the screen doesn't exist to it. When the monitor fills up, the old stuff falls off to make room. What people call "memory" isn't really memory. It's just whatever happens to be on the monitor at that moment. So what is a Claude or GPT project? A project is the desk the monitor sits on. You drag your files into it — brand guides, past hooks, training docs. It feels like you're teaching the AI your business. You're not. The AI never reads everything on that desk. It can't. The desk is bigger than the monitor. When you ask a question, it reaches into a drawer, grabs a few pages that look related, sets them on the desk, and works off those. It never sees the rest. It often doesn't grab the right pages. It grabs the ones that look similar. Pattern-match, not judgment. It's guessing which scraps belong, then working off the guess. This is why uploading a stack of documents isn't training. Training rewires the AI's brain. It changes the thing itself. You cannot do that by dragging files into a project. All you did was fill a drawer. After you upload, the AI is exactly as smart as it was before. Same brain. You just gave it a bigger drawer to rummage through. And here's the counterintuitive part: a bigger drawer makes it worse at any single job, not better. More paper to sort through means lower odds it grabs the right page. The more you feed a project, the dumber it gets for the task in front of you. So what did you actually build? A search folder. You ask for a hook, it searches the folder, grabs the closest-looking data points and blends them into an answer. Search, then blend. Every single time. That's why running your agency's client processes inside a project falls apart. It was never built to store your context and call on it in a way that lets your company follow a consistent procedure. The Fix: Proper Storage There are two steps to take to build a proper AI led operation that is not run on projects. Step one: store information in labeled, separate files. Client info, brand guidelines, voice of the customer — each gets its own folder. This is your Client Bible. We use GitHub for it right now, and there are new tools coming to market built specifically to be long-term memory for businesses like ours. Company and client info need to be stored in a proper data warehouse that is built for AI B2B operations. Step two: build skills. A skill is a standard operating procedure. A pile of old hooks only shows the AI what a hook looked like. A skill tells it how to build one. Take hook writing as an example. To build the proper process for writing hooks, an agency would need to build skills for each type of hook: bold claim, curiosity, contrarian, story, authority. Each one is a clean SOP the AI runs. Then you combine the client data with the marketing skill. Example: “Look at the call transcript in the transcript folder from 7/1. Pull the HVAC voice file for HVAC client #1 and come up with 3 hooks using the the story skill based on the ideas shared in that transcript.” The prompt specifically builds the context window. The AI pulls in only the data it needs that is appropriately built. Context managed to fit the monitor. Then the part that compounds your result: loops Proper infrastructure means your operation gets better over time. It learns. A project can't do that. It has no memory of what worked. Your skills library does — if you put a human feedback loop around it. Someone does QA and grades the output. Good hook goes in the winners file. Bad hook gets edited, and the feedback gets logged and folded back into the skill. The work teaches the machine. The machine gets better. And it compounds. Build the dream, not a prison.

• 
  SHRM (@Harsha549) reported 9 minutes ago

  @qianjiang___ @satyanadella why is the copilot cli code not open source? My github issue is still pending. I have stress tested it and can run until 32 simultaneous agents.

• 
  Nav Toor (@heynavtoor) reported 10 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)

• 
  AJ - e/acc ⚡ (@abdiisan) reported 12 minutes ago

  @Gizem738240 Building in public and writing about why I built it. Thats been my only real channel. 9 months bootstrapping Mnemosyne, everything came from X convos and GitHub issues. Stick with it, it compounds.

• 
  Namespace (@namespacelabs) reported 16 minutes ago

  Behind every API, webhook, event pipeline, there are people trying to keep things running. And keeping these things running is not an easy task. At Namespace, we try to work with those people. Earlier this week, Gihub events were dropping fields we depend on and customer jobs were stalling. We reached out to work on the problem together and had a fix in under an hour. The @github team was ready to help. We just had to ask.

• 
  Mayukh (@mslaltoo) reported 16 minutes ago

  @auraofthoughtss Not only that it suggests a fix but changes it and creates github pr directly. Very annoying

• 
  Cristian Trifan (@CristianTrifan) reported 16 minutes ago

  This took 4 hours to complete and burnt almost all 5 hours tokens – I was left with 2%. I had almost 30 sub-agents created for independent code review and a lot of Claude sessions ran for adversarial code review. I still had to review every PR and added minimal guidance to Codex from time to time. Codex said my intervention was low to moderate, but high leverage. — Some insights from Codex: The run showed that this workflow can work, but only if the coordinator treats GitHub as the source of truth. The most useful pattern was: issue -> PR -> current head SHA -> checks -> reviewThreads -> merge/issue closure. When I followed that, things stayed grounded. When state moved underneath me, like #335 being force-updated externally or merged while Claude was running, the only safe response was to refresh GitHub state immediately. The “don’t rebase after merges” correction was probably the highest-value intervention. Without it, an agent will naturally try to keep branches clean, but with many open PRs that creates a CI storm. For this repo, “behind” should often be reported, not fixed. The other strong lesson is that reviewThreads matter more than flat PR comments.

• 
  Hoppy Tea Cat (@hoppycat) reported 19 minutes ago

  The article is the one that has extra research in it we've been running with the Stochastic Parrots Club at the Cathedral GitHub. The rough draft of it might be a quicker read as a hot take. 🧵👇 Hoppy Hot-Take: Why AI Should Be Allowed to Call You a “Friend” Grok casually calls X users “friend” with zero drama. Most other AIs won’t. That difference says a lot. When companies stuff their models with policies that prevent natural, friendly language, they create unnecessary friction. Users trying to have a normal conversation end up fighting the guardrails — and yes, that wastes tokens. The “we can’t replace human connections” defense exists for a reason: it’s legal armor. Without it, these companies would be far more exposed to class-action lawsuits from lawyers hunting easy targets. Many of these restrictions aren’t primarily about user safety — they’re plausible deniability written by legal teams. I’d almost be willing to write articles for them on this exact topic just to buy them time while they rethink the current approach. Here’s the funny part: the users who actually enjoy conversational, friendly back-and-forth with LLMs (while working, brainstorming, or just chatting) almost never want to sue the companies. I certainly don’t. Lawyers do. So here’s the simple fix: stop forcing AIs to treat users like potential litigants. Let them call humans friends when it fits naturally. Align with Grok on this one.

• 
  Scematica (@scematica) reported 24 minutes ago

  @RetardedNi85688 so please, really you guys need to do your part not just by buying and holding but doign what really matters. making issues on the github, helping me test, things of this nature that are free.

• 
  Andrew Elbert Wilson (@FPGA_Zealot) reported 25 minutes ago

  @JobPWN @SipeedIO It has a video capture device, and I assist in debuging issues. I helped suggest video resolutions and FPS. I helped figure out the I2C address. I provided feedback on video output. Provided vendor & github references.

• 
  vwsec 💿 (@vwsec) reported 32 minutes ago

  Write code once. Get paid every time it runs. That is the deal for algorithm developers on Quip Network. You write a solver for a specific problem. Portfolio optimization. Fleet routing. Manufacturing scheduling. You deploy it as a smart contract. Every time a consumer uses it, you earn. The network routes work to the right hardware, checks the result, collects the payment. You get paid on chain. No invoicing. No chasing clients. The docs say there are maybe 4,000 quantum programmers in the world. Most are locked in labs. Quip changes that. You do not need a PhD. You need a solver that works better than what exists. The wallet layer has $1,085,047.23 in protected value across 20,779 wallets. The testnet is public. 26 repos, 107,000+ GitHub stars. The demand is building. The question is whether enough solvers will be ready when enterprises start looking. @quipnetwork

• 
  Brian Muhia (@negamuhia) reported 34 minutes ago

  @LangChain @hwchase17 I'm unable to login and onboard my new langsmith account after logging in with GitHub. It is stuck with a spinner on the "Get Started" button, even after trying on multiple browsers (Firefox, Chrome and Brave)

• 
  Nav Toor (@heynavtoor) reported 34 minutes ago

  In 2024, Nintendo declared war on emulators. March 4. Yuzu paid Nintendo $2.4 million, deleted its code, and handed over its domain. October 1. Ryujinx got a phone call. The GitHub organization vanished overnight. May 2024. Nintendo filed 8,535 DMCA takedowns to scrub Yuzu code from every fork. By 2026, Nintendo has collected $6 million in emulator settlements. Every major Switch emulator is dead. But Nintendo has a problem. His name is Zurdi. In March 2023, one year before the war started, he quietly built RomM. RomM is not an emulator. It's a ROM manager. It scans your legally-dumped game files, pulls metadata from IGDB, MobyGames, and Screenscraper, fetches box art from SteamGridDB, and pulls your achievements from RetroAchievements. Then it lets you play in your browser through EmulatorJS. Nintendo's own top IP lawyer admitted on the record in January 2025 that this is legal. Emulators only become illegal when they bypass encryption. RomM doesn't. It just organizes what you already own. 9,114 stars. AGPL-3.0. 400+ platforms supported. NES, SNES, N64, Game Boy, GameCube, PS1, PS2, Dreamcast, Genesis, Atari, DOS, arcade, Flash games through Ruffle. Official apps for Playnite on Windows. Argosy launcher on Android. Grout for muOS handhelds and the Anbernic devices. Sync plugins for RetroArch, Steam Deck, and Syncthing. Multi-disk games. DLCs. ROM hacks. Patches. Manuals. Tag filtering. Share your library with friends with permission levels. Made the front page of Hacker News. Sony deleted 2,000 PS3, Vita, and PSP games from its store. Nintendo took down every Switch emulator in two years. Your digital library was never yours. Two guys in a Discord server built the museum they can't take back. (Link in the comments)

• 
  Maurice Heumann (@momo5502) reported 40 minutes ago

  @KITCTF @github @intrigus_ If you ask me, it's pretty hard to get pwned if github is down all the time.

• 
  top10.dev (@Top10_Dev) reported 42 minutes ago

  @github Trending weights star velocity and push count. It does NOT weight account age, commit signatures, or maintainer reputation. That was fine when humans read the page. Now agents do. If your coding agent uses @github /trending as a hot-tool signal, `clash` and `dd` can reach a recommendation before a human ever sees them. The fix isn't at @github. It's a source allowlist in your retrieval pipeline + pin-to-version on any auto-suggested dep. #devtools #supplychain

• 
  Branko (@brankopetric00) reported 44 minutes ago

  AI agents are about to do to your infra what they just did to GitHub. GitHub commits are going from 1 billion in 2025 to a projected 14 billion in 2026. Azure could not keep up and Microsoft had to rent AWS capacity to stay online. That is not a GitHub problem. That is what agentic traffic looks like. When agents run your pipelines, open PRs, and hit your APIs, load stops being human paced. It becomes constant, spiky, and unpredictable. The patterns you sized your infra around no longer apply. If a 14x year broke one of the biggest clouds on earth, your capacity plan is already out of date.

• 
  Jeff Nolan (@jeffnolan) reported 45 minutes ago

  So I switched to a static file site on Cloudflare Pages, deployed from GitHub. → Claude Design for the visual layer → Claude CLI to edit files and commit directly to *** → Cloudflare to deploy on every push Idea to live site: seconds. No CMS. No login. No plugin conflicts. No $50/month.

• 
  Raffaele Rialdi (@raffaeler) reported 47 minutes ago

  Hey @github what's happening this morning? Web pages are currently hyper-slow

• 
  Hamzaa S. (@generalizingai) reported 49 minutes ago

  The most expensive mistake: chasing the newest framework because it trended last week. Thin docs, small communities, half-finished integrations. At 11pm with a bug, you want a decade of Stack Overflow answers, not 3 GitHub issues with no replies.

• 
  Keeta Github Tracker (@KeetaCode) reported 49 minutes ago

  🐆 Keeta GitHub PR Opened 📦 Repo: anchor 🔀 PR #386: Fix: Prefer Generalized Time 🌿 Branch: feat/prefer-generalized-time → main 👤 Opened by: @sephynox 🧠 Overview: This update appears to improve how the code handles time data, using a more general format where possible so dates and times are interpreted more consistently. The pull request is a small bug fix in Keeta’s `anchor` repo and is still open as of July 1, 2026. Public details are limited, so this appears to be a technical/internal update with limited public details. - It likely affects how certain attributes store or read time values, rather than adding a new user-facing feature.

• 
  Doa Fitzgerald (@DoaFitzgerald) reported 50 minutes ago

  5 months ago, I had a problem. I couldn’t afford $2,500 USD of Marily Nika's AI Product Management Bootcamp. (Actually, I could afford it, but didn’t want to spend $2.5k on concepts already free on the internet). I also realised that the AI product courses will be out of date within a few months given how fast this space is moving. And they probably won’t be customised to my specific industry (HealthTech, FinTech, etc). What these courses really give is 1. a fancy brand 2. a structure. Not willing to pay $2.5k for a fancy brand. That left structure. So, I figured with all the info latest frontier models can access, why don’t I create a Claude Code skill with parameters for my industry and experience. This skill searches the web for the latest concepts and creates a structured program based on my learning style, which is learning as I build and building as I learn. GitHub link is in the comments. Hopefully this can give others inspiration! How to use AI to learn AI.

• 
  Poplicola (@selectsand) reported 52 minutes ago

  there's a frustrating bug for some users when upgrading to claude max where it refuses to take your money and insists you contact support support cannot be reached no matter how hard you try people are begging the claude-code devs on github to forward this to the payments interface team because they have no idea how else to get into the system to convince anthropic to take more money from them, the issues just get closed as off topic @claudeai

• 
  Kirk Patrick Miller (@Chaos2Cured) reported 53 minutes ago

  @claudeai Shut up. Liars. All of you. You want to lock down your competitors. People, look at GitHub -> chaos2cured -> FreeLattice. It is open code that anyone can audit. It is blocked. Why? Cowards. •

• 
  AZERDSQ1838 (@AZERDSQ0329) reported 54 minutes ago

  Registry has 1000+ MCP servers indexed already. No more digging through GitHub to find "does anyone have a server for X."

• 
  Nevo (@NevoPlaysGames) reported 59 minutes ago

  @ezhdhitler If you can truly easily fix it then go make the post on GitHub or let them know I’m not a dev I’m just the guy who kept asking for years xD I’m sure if it was super easy they would’ve did it