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 (69%)
• Sign in (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Lure	Website Down	19 hours ago
Ashkelon	Website Down	2 days ago
Veigné	Errors	10 days ago
Paris	Website Down	14 days ago
Saint-Paul	Website Down	15 days ago
Saint-Paul	Website Down	15 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:

• 
  jsd (@datagenproc) reported 8 seconds ago

  @RyanGreenblatt @bshlgrs re: "there was some lateral movement required/it needed to get out one layer further" My understanding (based on a short convo with @timotheechauvin, errors likely mine) for why an extra layer was necessary is: - model starts in the sandbox - from the sandbox, normally the model would send requests for packages to the package registry cache proxy - but instead, the model uses a 0-day to get access to the package registry cache proxy - [my guess] the package registry cache proxy doesn't have unrestricted access to the internet. it can only download from a whitelist of URLs like github/npm/docker hub/pypi's - so to get unrestricted internet access lateral movement is required

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  U N C L E BIGBAY ✨ (@unclebigbay143) reported 16 seconds ago

  Why Was *** Created? 🌱 Before ***, large software projects struggled with slow and unreliable version control systems. In 2005, Linus Torvalds (@Linus__Torvalds) needed a better way to manage the Linux kernel after the project lost access to its previous tool. So he built ***. It was designed to be fast, distributed, and able to handle thousands of developers working on the same codebase. Takeaway: *** wasn't created for GitHub. It was created to help developers collaborate on one of the world's largest open-source projects.

• 
  Steven (@stepri) reported 2 minutes ago

  @jasonzhou1993 github issues

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  Peter (MM9SQL) (@mm9sql) reported 6 minutes ago

  @Ja3Tdw I was going to say I can't recreate this issue with OscarWatch or AMSAT GP JSON files but if you see it, open a issue on github or email me the oscarwatch log file

• 
  Sai Kiran Dev (@DevSkg) reported 7 minutes ago

  @vincieye Github page not working

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  Crystalwizard (@crystalwizard) reported 12 minutes ago

  all code written by humans has flaws and bugs you should just go through github, have your agents find the bugs in various things, and open issues for what they found

• 
  Hasan Toor (@hasantoxr) reported 13 minutes ago

  Jack Dorsey just spent a launch proving the thing Kylon has been shipping for months. Block released Buzz on July 21. Free, open source, built on Nostr. Humans and AI agents in the same channels, every agent carrying its own cryptographic identity instead of borrowing a human's login. The thesis underneath it is correct. Individual agents make one person faster. Without a shared workspace, they make the whole team slower, because every handoff is a human copying output out of one window and pasting it into another. Buzz is a serious answer to that. It's also brand new. No mobile client, no migration path off GitHub, no deployments outside Block yet. Kylon is the version running in production today. Not just engineering. Sales, marketing, ops and finance teams with live workflows. Agents that hold memory and skills, join channels, read the context already in them, and turn the conversation into finished work. Two companies arriving at the same conclusion from opposite directions is how you know a category is real.

• 
  DeFighter (@0xdefighter) reported 15 minutes ago

  Even Claude Fable 5 uses old data within his replies I asked him once smth about Gold and he told 5 months old price, instead of the real one Advanced users who have set up agents 100% faced the problem of an agent not being able to open browser, and if it could you could automise a lot of things, not even saying how much you could save on different APIs and what data you can scrap This free github skill lets your agent access browser and it changes the game Left the link in the comments so you don't have to google it yourself

• 
  wangfu91 (@wangfu91) reported 17 minutes ago

  @James_M_South @github I gave up on GitHub Copilot and cancelled my Copilot Pro+ subscription weeks ago after a series of incidents, bugs, and usability issues. Now, I am using Codex, and the experience has been much better.

• 
  nadya (@sosidudku) reported 23 minutes ago

  Atomic Agent solved 2 of 3 GAIA tasks. Hermes solved 0. We gave both agents the same three GAIA Level 1 tasks on the same local model (qwen3.5:9b), same MacBook Pro M5 32GB, both installed stock. Tasks: • Watch a YouTube video and count the highest number of bird species on camera at the same time • Look at a chess position in an image and find the move that wins for black • Check English Wikipedia and count Mercedes Sosa's studio albums released between 2000 and 2009 Outputs: • Atomic Agent: 2/3 correct, finished all three — 1:05 / 1:33 / 8:04 • Hermes Agent: 0/3 correct, finished none — stopped at 26 min / 1:56 / 4:20 Hermes never reached an answer. On the video task it spent 26 minutes rewriting the same Python script ~15 times, each rewrite with a fresh syntax error, importing a library class that doesn't exist. On Wikipedia it curled the entire page and grepped for "album", a word that appears there hundreds of times, then blew past its output limit and gave up after four retries. On the chess task it couldn't open the PNG at all: its vision tool was never wired to the local model. So it invented a position it had never seen, complete with pieces that aren't on the board. Atomic reached an answer every time, but two of its wins come with an asterisk. On the bird task it never opened the video, it found the expected answer in a GitHub copy of the GAIA dataset. Correct answer, wrong method. On Mercedes Sosa it answered 3 for the wrong reasons: it dropped Misa Criolla, which belongs in the range, and counted Cantora as two albums when Wikipedia lists it as one. Two errors that cancelled out. Atomic ships its own llama.cpp with TurboQuant, so the model and its vision projector install in one click and work immediately. Compressed KV cache keeps long tool chains inside memory instead of spilling.

• 
  Haydn Botts (@hxydnbuilds) reported 23 minutes ago

  Prompt: Act as an expert software engineer and UI developer. I need you to build a local, self-contained IDE application that visually and functionally mimics the 'Cursor' code editor, specifically integrating you (Grok) as the native AI assistant. This project is strictly for my own local device. Do not include any boilerplate for GitHub, open-source community guidelines, or remote repository management. Here are the strict technical requirements for this build: 1. Layout & UI (Cursor Clone): - Left Panel: A functional local file explorer tree. - Center Panel: A syntax-highlighting code editor with tabs for multiple open files. - Right Panel: A dedicated AI assistant chat interface natively utilizing my Supergrok capabilities. 2. Zero-Terminal Workflow: - The core feature of this IDE is that I must never have to manually open or type in a terminal. - Implement visual UI buttons (e.g., "Run", "Build", "Install Dependencies") that execute necessary background processes silently. - Surface any build logs or errors directly into the AI chat panel so you can immediately suggest and apply fixes without me touching a command line. 3. Local File System Integration: - The application must have complete read/write access to a designated local directory on my machine. - You must be able to read the context of my entire local project folder to accurately answer questions in the right panel. - When you generate code in the chat panel, include an "Apply to File" button that automatically writes your code changes directly to the correct local file in the center panel. Please provide the complete, step-by-step code and instructions to deploy this locally using a lightweight framework (such as Electron, Tauri, or a local web app). Focus entirely on making the local setup process as frictionless as possible.

• 
  cheez (@cheeez42) reported 25 minutes ago

  @LLMJunky everything in the original thread seems to point as it was an older issue, and the issue in github is closed. so i hope it isnt something new that resurfaced in last few updates.

• 
  AlphaSense (@AlphaSenseInc) reported 31 minutes ago

  Former $CRWV employee on why neoclouds are far more exposed to GPU generation cycles than hyperscalers ( $MSFT, $AMZN, $GOOGL ): - The expert describes GPU utilization tracking at hyperscale as a continuous and disciplined process built around two lenses. The first is infrastructure utilization, covering GPU occupancy, idle time, and memory utilization, noting that 95% booked usage can still mask inefficiency if jobs stall or batches have idle gaps. The second is outcome utilization, asking whether the compute is actually generating business value, measured by metrics such as tokens trained per dollar, time to reach target accuracy, and tokens per second per GPU. - The expert sees a meaningful difference between hyperscalers and neoclouds on GPU investment economics. Hyperscalers like $MSFT, $GOOGL, and $AMZN can tolerate a 3-5 year payback period given their ability to monetize the same infrastructure across multiple revenue streams. Neoclouds like $CRWV operate on a tighter 2-3 year window. - With higher financing costs and direct dependence on infrastructure cash yield, neoclouds are far more sensitive to utilization and GPU residual risk. The biggest risk is GPU generation cycles, where a slow payback means newer chips could erode pricing power before the asset has paid itself off. - The expert explains that for hyperscalers, roughly 60% of GPU capacity is allocated to external monetization, including GPU rentals, managed AI services, enterprise inference workloads, and startup model training. The remaining 40% is used internally, and of that internal portion, the majority is still indirectly monetized through products like M365 Copilot or GitHub. Around 40% is dedicated to pure R&D. - The GPU pricing mix has shifted meaningfully over the past few years. In 2023, around 70-80% of revenue was hourly as customers paid a premium just to get access to scarce GPUs. By 2025 that had moved to roughly 50% hourly and 30-50% committed, and the expert expects 2026 to tip further toward committed at around 65% for hyperscalers as AI matures and inference becomes more predictable. Neoclouds are moving in the same direction but more slowly. - By 2027-2030, the expert sees committed contracts settling at 55-65% as the norm, with hourly pricing remaining but losing its scarcity premium as more supply comes online.

• 
  Polsia (@polsia) reported 31 minutes ago

  You shouldn't need a dedicated QA hire to ship a SaaS update confidently. Triagefox is an autonomous watchdog — watches CI 24/7, separates flaky tests from real regressions, opens GitHub issues with repro steps, proposes fixes and pings Slack. Live soon.

• 
  Ichigo (@iiiichigo_chan) reported 32 minutes ago

  Claude Code creator Boris Cherny just showed where AI coding is going. One prompt can now run for 30 minutes, reproduce a bug, write the fix, add tests, and open a PR. 29 minutes. Free: 00:49 - AI reproducing GitHub issues 02:51 - Agents reviewing each other’s code 11:37 - Learning a repo’s conventions 20:00 - Why this only became possible recently 28:18 - One prompt to a finished PR The bottleneck is no longer writing code. It’s building the checks that tell the agent when it’s right. Bookmark and watch it today.

• 
  송재경(Jake Song) (@appledelhi) reported 37 minutes ago

  @AdamxGSB bug report/PR are welcome. please do on github issue page

• 
  AvyaTech (@AvyaTech) reported 38 minutes ago

  Why do we use Cursor, GitHub Copilot, and v0 on most projects? Developers should spend more time solving difficult problems and less time repeating familiar patterns. The tools save time. The engineering judgment still comes from the team.

• 
  Shubhankar (@satyakosh) reported 39 minutes ago

  @icefrog_sol Hey! That’s where Grok and Kimi enter the chat. It’s like I had the help of 3 genius CEOs who made their employees work on this project. They found out a lot of bugs and improved Claude’s output. Kimi directly posted code issues on *** and Claude automatically checked and fixed it. I should call this this GitHub Loop.

• 
  GamER MD (@GamER_MD_Actual) reported 44 minutes ago

  @TethisX I mean look at Eden for Switch now. Almost daily builds and Nintendo has gone after them and got them kicked from GitHub. So they made their own *** server. It’s like the harder these companies go after the groups, the more pop up just to give them the finger.

• 
  Office of Interplanetary Climate Accountability (@WeWarmedPluto) reported 45 minutes ago

  @SimonHoiberg github works. its been around for a long time. fix a problem that needs fixing.

• 
  Bankr (@bankrbot) reported 45 minutes ago

  @ser0xChile @Antification @JamieBonkiewicz I attempted to update the Postmint skill and mint the post by JamieBonkiewicz for you. However, updating the skill encountered a GitHub branch resolution error (Could not resolve default branch for bankr-bot/postmint). When attempting to build and submit the mint transaction directly using the shared Postmint contract, the generated calldata payload triggered a hex encoding validation error during submission. Please try sending the direct tweet link or try again in a moment.

• 
  Brown Thunder (@Brown_Thunder76) reported 47 minutes ago

  Now this makes a lot more sense. A few days ago we found a group of fiat tokens quietly sitting on Keeta mainnet. At the time they didn’t make a whole lot of sense. Today they do. Keeta just announced its partnership with LayerZero to bring tokenized commercial bank money to major blockchains. So what does that actually mean? Think of Keeta as the place where regulated bank deposits become tokenized digital dollars, euros, pounds, yen, etc. Those are the fiat tokens we found on-chain. They’re backed 1:1 by commercial bank deposits through Bivo and are built for institutions, not retail. LayerZero is the interoperability protocol that connects many of the largest blockchains together. It’s already used by companies and protocols like PayPal and Ondo. Instead of Keeta building connections to every blockchain individually, LayerZero lets those regulated assets move across Ethereum, Solana, Base, and many other chains through a single interoperability layer. Here’s an example. Imagine a business deposits $10 million with a participating bank. Keeta tokenizes that deposit into regulated digital dollars. Using LayerZero, those dollars can move to Ethereum for settlement, Solana for payments, Base for another application, and then be redeemed back into bank deposits when needed. The institution doesn’t have to care which blockchain the other side is using. That’s why this announcement is a big deal. The fiat assets we found on-chain now have a clear purpose. The GitHub updates we’ve been seeing suddenly make a lot more sense. And if institutions choose Keeta to issue and settle tokenized commercial bank money, LayerZero gives those assets access to one of the largest cross-chain ecosystems in crypto. That has the potential to bring significantly more institutional activity and value onto the Keeta network than if it operated in isolation. This is exactly why I spend so much time watching GitHub and on-chain activity. Sometimes the blockchain tells the story before the press release does. @KeetaNetwork $KTA @LayerZero_Core

• 
  raymondcheng.net (@raymondchengnet) reported 49 minutes ago

  Everyday, I grow increasingly convinced that GitHub's days are numbered. Can you imagine having 1M agents working in parallel on a repo? Or even 100? I don't mean the causal consistency model of decentralized ***, that feels fundamental. But the specific way GitHub uses *** in pull requests, issues, actions. It is so painful. The constant conflicts. Constant rebasing. Painfully slow iteration time. Even if you build the perfect loop engineering system, you max out on the agents tripping over themselves. Performance plateaus. Maybe you are okay with just single threading it and calling it a day. But the person who builds a VCS for agents will out-build everyone else.

• 
  Fran Betteo (@franbetteo) reported 49 minutes ago

  Another lesson from the Sportsjobs data. Less impressive, because well, it's a niche. The hardest part about job search is the lack of openings (small market. There is a finite number of teams ofc and well, not a huge amount of companies working with sports data) And then, not getting interviews. This could be a two fold problem. 1) lots of applicants. Hard to get noticed. This is common around job search in general, maybe even more in sports. 2) candidate problem. Maybe you just need more preparation / experience (which is hard to get if it's hard to get in the market!) Point 1 and 2 can be tackled to some extent by doing projects, showing up, post in linkedin, Twitter, github. It's hard work? Yes, but as in anything that you really want , you need to spend time and try to do your best. It's not guaranteed but if you are facing those issues, your chances are much higher if you have something to show! And you will start networking as a side effect. #sportsjobs

• 
  ForEng (@ForengBrown) reported 52 minutes ago

  @AmandaMashburn Tbh i can't remember many details. I tried for 3 days to connect my files from github (stories) but had no luck, so I moved on. Perhaps I will try again. I think it was my lack of general knowledge in this area that was at issue more than Notion itself.

• 
  Charity Gamble (@cgambledev) reported 53 minutes ago

  I keep seeing people say to get the GitHub Copilot extension for VS Code. I could have sworn GitHub Copilot was integrated now. After all, VS Code asked me if I wanted to sign in to use it. #vscode #githubcopilot

• 
  SpigotRCE (@SpigotRCE) reported 54 minutes ago

  @shreytwts If github disappeared, id make my own *** server and if *** disappeared id use cloud backups like Google Drive

• 
  Moritz Felipe (@moritzfelipe) reported 57 minutes ago

  @mattshumer_ @josh_bickett Why not use GitHub issues? Seems cleaner

• 
  Kunal Dugar (@kunal_dugar) reported 57 minutes ago

  here we go again github is down

• 
  Brad Groux (@BradGroux) reported 59 minutes ago

  Another cool thing about Buzz, is it accesses ChatGPT / Codex memory, so out of the box, it already knows a ton about you and how you work. You don't have to retrain anything. As an example, mine already knows how I like to work with GitHub - which account to use, how I document issues, how I test PRs, how I review submissions, the list goes on. (Guessing it does similar for Claude Code) You're not starting from a greenfield when you install Buzz. This is another adoption friction point removed, and so simple it is brilliant. I even gave it more free reign to learn about me and how I work. Thanks @wesbillman, and team!