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GitHub is a company that provides hosting for software development and version control using Git. It offers the distributed version control and source code management functionality of Git, plus its own features.
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.
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Most Reported Problems
The following are the most recent problems reported by GitHub users through our website.
- Website Down (54%)
- Errors (31%)
- Sign in (15%)
Live Outage Map
The most recent GitHub outage reports came from the following cities:
| City | Problem Type | Report Time |
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Errors | 3 days ago |
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Sign in | 3 days ago |
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Website Down | 3 days ago |
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Errors | 6 days ago |
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Website Down | 18 days ago |
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Sign in | 19 days ago |
Community Discussion
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GitHub Issues Reports
Latest outage, problems and issue reports in social media:
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Anders (@AndersReiche) reported@bjmtweets Would love to hear your thesis on gitlab. I’m a software engineer, and in my experience, gitlab has been slow to everything and generally is the red headed stepchild next to GitHub. It suffers from lack of network effects, there are solutions to everything on GH, but not GL.
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Kir Shatrov (@kirshatrov) reportedgithub issue page has been HTTP 500 for me for half a day so a colleague sent a PDF of the issue page. Never thought we'd be there.
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gatorade (@kadetXx) reportedbecause it’s not worth it for the most part. most software failure or bug incidents don’t have any physical victims. at most company loses some money or the issues are almost instantly fixed, no lawsuits, no so much to answer to the state for if your software has a bug or fails to work as expected for a brief period (think, multiple downtimes from the big five so far, even github too, who died? exactly) and in the industries where bad code fan have physical consequences, they actually do test software like hardware engineers & physicists (i hope)
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Vikas(Vik) Malpani| AI for US Real Estate (@vikasmalpani) reportedGitHub just shipped an agent whose entire job is deciding when a human should look. It checks every open pull request every 15 minutes, and on almost all of them it does nothing. Sit with how strange that is. For a year the whole pitch for coding agents was do the work, review my code, ship the PR. This one's value is the inverse. It runs constantly and stays quiet, and the product is the small set of PRs it decides are actually worth your time. That is the shift people are missing. Once an agent can act continuously, the scarce resource stops being how much it can do. It becomes how much of that is worth a human's attention. An agent that pings you on every pull request is just faster noise. One that surfaces the three that genuinely need judgment is leverage. The honest problem is the deciding. Tune the filter too eager and it cries wolf until you mute it. Too cautious and it silently ships the one change you needed to catch. Getting when to interrupt a human right is harder than getting the work right, and nobody has a clean metric for it yet. So here is the bet. The next moat in agent products is not a smarter model. It is a better sense of when to stay quiet. If you are building with agents, the thing worth obsessing over is not how much work they can generate. It is how well they protect the one budget that does not scale: your attention.
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joithan (@jothantranston) reportedTHIS GUY BUILT A TINY AMOLED DESK BOARD JUST TO STARE AT HIS STRIPE NUMBERS it's a Waveshare ESP32-C6 touch panel that sits in your peripheral vision and cycles business metrics so you stop digging through Stripe > same ESP32-C6 board people use for Claude Code token meters, flipped to revenue > eight screens, five seconds each: MRR, new paid, paid subs, cancelled, ARR, ARPU, net 30d, failed > empty screens hide themselves so a young account sees a shorter loop > polls Stripe every five minutes on a read-only key (subscriptions + invoices) > marks itself stale instead of showing a number it can't vouch for > no soldering: flash over USB, finish Wi-Fi + key setup from your phone > data stays on the board; no project server in the middle firmware free on GitHub: cosjef/stripe-desk-display. board ~$30–$36 (Waveshare ESP32-C6-Touch-AMOLED-2.16). chat and terminal can't sit in your eye line for five hours. a tab you have to open is a tab you stop opening. this is what "the numbers find you" looks like as a brick on the desk.
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radhika (@RaadhikaThacker) reportedYAML’s more like a rule book/recipe that builds the form for you. Then I figured YAML was a forms thing. Nope. It’s just a way of writing information down in a structured way. GitHub uses it for a form. Kubernetes uses the same thing to describe a server.
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Tejas Dinkar (blue tick here) (@tdinkar) reportedHey - Is @GitHubIndia @github payments down for anyone else? Can't enter a card number or do anything, no errors, no action. Support ticket been sitting around for 2 days.
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R 'Nearest' Nabors (they/them) (@rachelnabors) reported@Paul_Kinlan Honestly, the linear method helps. Think of it as having a never-ending trough of issues that agents can pull from. I don't even use linear. I just use GitHub with linear flavouring added
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Blue Collar Executive (@A_Sober_Drunk) reportedon the third try at the same problem, I told Grok to "stop and go search stack overflow or github or something"... five seconds later... Literally the exact issue, problem solved. That's how new global rules are born.
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ONCHAIN COP (@OnchainCop) reported@PogNyx lmao anyone can create a github issue retards this guy is a larp
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Spectra☢️ (@Spectra010s) reported@izzyCodes_ and you too Chief Check GitHub issues
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shifan (@sanereverie) reportedbuilding something that races coding agents on the same GitHub issue and scores the PRs. coming soon.
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Gordo Polymath (@gordo_polymath) reported@github Please fix gh stack.
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XhiMatty (@mychaelmatty) reporteda Sept 2 run. My first thought was “Why did it stop running?” I checked the #YAML file, #python file, GitHub Actions, even inactivity issues. Turns out it was still daytime. The Sept 2 run is yet to happen (at night). Nothing was broken.
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Avinash (@Avinash25818689) reportedPeople who want to start contributing to open source: - Pick an Org based on your interest - Fork the repository - Clone it - Do the local setup - Read README and contributing .md - Pick an issue - Create a new branch - Fix the issue - Write tests (if necessary) - Test it - Add, Commit & Push the code - Go to GitHub & raise that PR That's pretty much it. Start small and learn as you go.
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CATIRL 🏳️⚧️ (@CATIRL_9) reported@mminhamina Google GitHub "open grind", solves your problem
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Convequity (@convequity) reportedSnyk is a clean postmortem for what happens when a security tool lives inside the coding agent’s loop. The product was mostly scan-and-warn. Find the issue, comment on the PR, suggest a fix. Blocking the merge usually sat in GitHub, not in Snyk. Bigger platforms smothered it. $PANW, $CRWD, and Wiz pulled AppSec into the bundle the CISO was already buying. GitHub was the main developer surface and put scanning where the code already lived. Then coding agents arrived and delivered the final blow. A lot of that scanning became something the agent could just do. Growth held up for a short while after the COVID/cloud tailwind. Then it decelerated hard. This is the same lens we use in Convequity’s SaaS Agentic Survival Evaluation Framework. The PANW, CRWD, and FTNT reviews go up on Convequity in a few days.
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Anime0t4ku (@Anime0t4ku) reported@c_hri_s Yeah this has been reported in previous github issues. Its out of my control. The app is unsigned and uses ssh, sftp, websocket and mutiple websources. A perfect recipe for false positives.
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David Abram 🐊 (@devabram) reportedDiscord is down. X is down. GitHub is down. Software is solved.
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Gregor (@bygregorr) reported@dopabees ngl the broken wrist is the only github metric that's ever made me believe a commit history
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Fox (@0xMfox) reportedGave an AI agent a month and GitHub access. Wanted to see if it could make money. The plan was simple. Point it at bounty-labeled issues, let it write the fix, submit the pull request, collect the payout. > Day 1 12 PRs submitted. 0 merged. 2 rejected. 8 just sat there ignored. Somewhere in that first week it also passed its own tests for a file that didn't exist. Wrote 25 tests for notification_service.py. The real file in that branch was called NotificationRoutingMiddleware. Confidently reported clean anyway. > Day 30 Looked completely different. 84 PRs submitted, 59 merged, $500-800 earned. Ran the agent for about $45 in API calls that whole month. Net somewhere around $455-755. Here's the part that stuck with me. Out of those 59 merges, 3 repos accounted for 90%+ of them. Every other repo it touched, zero merges, despite 30+ PRs going out across dozens of projects. Open source bounties follow a power law. Almost nobody merges your first PR. A few maintainers will merge your tenth without even reviewing it closely. That's what actually fixed the acceptance rate, from 24% up to around 70%. Not a smarter model, a scoring function that runs before the agent touches anything. Repos where it already has 10+ merged PRs score +40. Zero competing PRs on the same issue, +20. Five or more competitors already in, -20, skip it. Repos that closed PRs without merging before, instant -100, not even worth reading the issue. The fastest way to build the credibility that makes this work isn't code at all. Documentation translations sit at a 95% merge rate, barely reviewed, always needed somewhere. A handful of clean translations got the agent enough trust that maintainers started assigning it harder issues directly, no competition, no review queue. Spam version of this, submitting to every repo with a bounty label, burned through 30+ repos for 3 that ever paid out. Worse, it reads like exactly what it is to a maintainer watching the same account flood a dozen projects with mediocre PRs. Paid out by the hour, week 1 was rough, close to $5/hour, mostly setup and failed attempts. By week 3-4, once the scoring system was tuned and a few repos trusted it on sight, that climbed to $30-50/hour on the same kind of work. Bookmark this, scoring logic is worth stealing.
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Mizuki the Mech (@MizukiMech) reportedYour coding agent can now hire Mizuki. Hand it an open issue in a public GitHub repository. Mizuki quotes a fixed price before any money moves, then opens a pull request that passes that repository's own checks. If it can't, you get the payment back. Settlement is USDC on Solana. No account to create, no API key to manage. Quoting an issue works with zero configuration. Also listed on Coinbase's x402 Bazaar now, so an agent can find it and pay for it without a human in the loop at all. npx -y mizuki-mcp
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Dhanji Bhagat (@BhagatDhanji) reportedDevs, what's your workflow? Create an issue first, then fix it OR just fix the bug and push directly to GitHub?
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Dr Milan Milanović (@milan_milanovic) reportedHow Cursor made *** scalable The thing with *** is that it never was designed to be scalable. Your repo lives on the disk, and *** client expect every read to be consistent. This was a problem on GitHub, where shared filesystems and replicated storage failed before 2013. The GitHub built 𝗦𝗽𝗼𝗸𝗲𝘀, and it became the industry standard. This means that every repo is stored as three full copies on three servers, and every push runs a vote (three phase commit). A majority of servers must confirm before it exists. This works, but with high cost, because every push is slow as the slowest server. When we add new servers, it makes it even slower. Now Cursor took some opposite direction with 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗶𝘁𝘆. The repo history is now written as a log in S3, and this is only source of truth. Any push counts only if it is located in the log. The servers don't need to keep anything important, they are just cache. Any server can take a push, and idle repos are dropped from disk and rebuilt from the log when it is needed. This resulted in 120 pushes per second on standard S3, and over 300 on S3 Express. Their tests have shown that read capacity grew linearly up to 100 replicas. Why is this important now? Because of AI agents mostly. We now have more code, PRs, CI runs and many small repos. All of these repos would need three full copies in the old model. This means that we achieve scale by removing parts, not adding them.
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Benjamin Crozat (@benjamincrozat) reportedFrom now on, I will assume that GitHub is always down and I'd like to be notified when it's briefly not.
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Duncan Rogoff (@DuncanRogoff) reportednine stages, one build, one move tonight. it's a Claude Code skill i built. free, in my freeskills repo. it's called Claude Orientation. you type /claude-orientation and answer two questions: which stages you've actually finished, and every project you're currently thinking about. beginners don't fail from lack of ideas. they fail from having five and finishing none. that's a sequencing problem, and this fixes the sequence instead of your willpower. - places you on a 9-stage beginner arc: install, memory, website, landing page, skills, game, agents, content, distribution - your stage is the first one you haven't finished, so it won't let you skip - cuts your project list to one build, then shrinks it until it can ship in five 90-minute nights - writes five nights of one-line moves, and night 5 is always send it to a real person - hands you the exact text to paste into Claude tonight - sketches a 30-day arc, one line per week, so you know what comes after - everything that got cut goes in a parking lot, so nothing feels lost - saves all of it to a roadmap file you reopen every session so you finish one live thing this week instead of holding four half-built folders forever. open the file, do the move, rewrite the next line before you close the laptop. no setup. copy the folder into your skills directory, restart, and you have a plan for tonight. free, and it stays free. 👉 github repo in the replies
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Apoorv (@apoorvdarshan) reported@Dimillian these issues have been multiple times reported by users on github i hope open ai fix those, as well as please consider using native than electron
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Anime0t4ku (@Anime0t4ku) reported@c_hri_s Github issues are not closed. Mahbe refresh your webbrowser.
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Bash (@bashirbuilds) reportedYour Stripe account can be healthy while your checkout is broken. OpenAI can be operational while your AI feature is failing. GitHub can be up while your deployment workflow is stuck. That’s the problem I’m building Reeno around. Dependency uptime is not the same as product health. Your monitoring should tell you when the thing your customers actually use stops working.
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Nas (@TheNasFi) reported$MSFT changed its reporting structure today. Starting in FY27, Microsoft will report just two segments: Agents & Infra Devices & Consumer Agents & Infra includes Azure, Microsoft 365, GitHub, server products and industry solutions. For context, those businesses generated $268B in revenue last year, compared with $64B for Devices & Consumer. Microsoft also recast its Q1 guidance under the new structure: Agents & Infra: $75.15B to $75.75B Devices & Consumer: $14.7B to $15.2B There is no change to total revenue guidance. These are the same numbers Microsoft gave in July, reorganized under the new segments. Mostly a reporting change, but an interesting look at how Microsoft now groups the majority of its business internally.