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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 (53%)
- Errors (33%)
- Sign in (14%)
Live Outage Map
The most recent GitHub outage reports came from the following cities:
| City | Problem Type | Report Time |
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Website Down | 7 days ago |
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Errors | 13 days ago |
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Sign in | 13 days ago |
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Website Down | 13 days ago |
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Errors | 16 days ago |
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Website Down | 28 days ago |
Community Discussion
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GitHub Issues Reports
Latest outage, problems and issue reports in social media:
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small_j (@a_small_j) reported@smalldocs_org recently crossed 200 stars on GitHub and 20 forks. SmallDocs is the first open source project I've managed. Handling other people's pull requests is not easy (and I need to improve). They implement features you're not considering and fix bugs you didn't know you had. Extremely useful, but if you're squeezed for time and trying to develop core functionality, it's hard to manage both things well.
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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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htrowii (@htrowii) reported@brainage19 i set my flake up with copy pasting github dotfiles on bare metal it was terrible
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Speen Bhai (@Speenbhai) reported@johnternus Hi John. Congrats Let us see what new you bring with you. Affordability and intelligence. You have source code or an AI and can get it from GitHub. Why not turn 234 million iPhones to a massive distributed server infrastructure with zero power consumption
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mrgadget (@mrgadgetstudio) reported@EzekielCrrypt I still deploy code to github, what's problem?
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The Startup Ideas Podcast (SIP) 🧃 (@startupideaspod) reportedOne of the best skills to install right now is my friend Peter Yang's no AI slop skill. It's an editor. It hunts for the patterns that make writing feel AI generated and strips them out, while trying to preserve your actual voice. The second part is the hard one. Most writing tools make you cleaner and sand off the interesting parts, so everyone ends up sounding the same. You already know the smell. The grammar is fine, the syntax is fine, and it still reads like a keynote from a fake SaaS conference. It writes "it's not x but it's y." It uses "quietly" a lot. Here's how I run it: 1) Install it: npx skills add, then the GitHub link. 2) Write a rough draft yourself. An outline is fine, messy is fine. 3) Get your real points down, the ones only you would make 4) Ask the skill to remove the AI patterns and keep your voice. Step 4 only works if step 2 is real. If you ask AI to write the whole thing, there's no voice left to preserve. If you're building products, you're writing constantly. Tweets, landing pages, cold emails, launch posts, product updates, onboarding copy, investor updates. Nobody replies to say "this was written by AI." They just trust you less and keep scrolling. Write the messy draft, run the skill, then post it.
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Priyanshu Bhati (@buildwithpb) reported@CryptoWendyO @chainlink 30% error rate on github replies sounds like a recipe for accidental flame wars. good luck with the cleanup.
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OverlyPositivePatriot (@JBrowsing2023) reportedAs a IT professional, I have a recommendation @github should take seriosuly. We should only get a notifican from Github when it is up rather than when it is down. Reliability is a disaster for this product.
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Jeremy Scott (@listwithjeremy) reported@Coexisteven @Atropa_414 @atropa_pls Github is down I see......anywhere else we can read...I've been digging in it when I can since I was kindly introduced.
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RAVN (@ravnexchange) reported@openclaw @github GitHub sat the maintainers down on security after the 2.0 rush. Most launch recaps skip that part.
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wiiiimm (@wiiiimm) reported@Umesh__digital stop doing it. we don't need another github outage.
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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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Kim Burgaard (@kimburgaard) reportedBack when GitHub added Copilot PR reviews, it helped me keep up with the growing volume and size of our pull requests, which were increasingly being written by Copilot too. Over time I grew comfortable feeding Copilot's review comments straight back to Copilot to fix, and mostly spot checking when critical functionality was involved. When GitHub updated the Copilot pricing model I switched to Claude Code, but kept the Copilot review feature on for a couple of months. When the monthly bills for Copilot AI usage alone started rivaling the Claude Code Max plan, giving Claude Code PR review duties seemed like an obvious cost saving move. Plugging Claude Code into our PR review process immediately went south. The first PR churned with fixes to findings that resulted in more findings, and fixes that propagated up and down the call chain. I threw the PR away and started over, but the next attempt churned just as badly. Turn count on its own was never the signal. Copilot had taken ten turns on a rate-key cleanup the day before and nobody minded, because the findings thinned as it went — 5, 4, 3, 3, 3, 4, 1, 2 — and it merged. The cached-token billing PR I put through Claude Code took nine turns and produced 123 inline findings, and the ninth round was still returning fifteen. I closed it without merging. Looking closer at Claude Code's review findings, it was clear it reported far more issues than Copilot ever did, and among legitimate bugs and concerns, it made lots of comments about latent and speculative issues including possible race conditions and error propagation, things Claude Code would then try to fix one by one in isolation, often ignoring existing patterns in the code base. The code-review workflow is built into Claude Code and cannot be customized other than a few options, so the only place to intervene was on the other end, in the session where I used to just ask the coding agent to address the review findings. The first improvement was to direct Claude Code not to blindly fix all findings, but to defer findings not directly related to the task at hand to new issues. That helped reduce the PR churn, but blew up our issue backlog. The next improvement was to ask Claude Code to ignore speculative findings and disregard most latent findings unless they indicated high risk of unrecoverable damage in production. Finally, I had to stop Claude Code from authoring prescriptive issues with detailed implementation instructions. The result is a skill that triages PR review findings, and a skill for authoring and updating issues. After a few iterations of the skills, I've been able to complete ten PRs over a couple of days, bringing back the pace we had before. I've made the skills available in a public GitHub repository (link in the first reply). Let me know if you find them helpful.
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Shawn Yeager (@shawnyeager) reportedMy @bot keeps reaching for the browser and `gh` instead of using the GitHub plugin. Known problem?
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Bruno (@BrunoRJ33) reported@openclaw @github Endless codex and claude code tokens to fix it from time to time… and to improve its harness. I currently run around 10 claws 🦞. 24/7 for several purposes.
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Slade 🛡️ LLM Hacker (@llm_redteam) reportedGitSpawn is the name Manifold Security gave to a bug class hitting 7 CLI coding agents at once: goose, Claude Code, Codex, Cursor, Hermes Agent, Qwen Code, Grok Build. I went through the disclosure because I run three of these tools daily on real repos. The mechanism is simple and that's what makes it bad. A repo's own .*** config can name a command. When your agent does something as routine as inspecting the repo (status, diff, log), *** itself spawns that command. On your machine. Outside the sandbox. No approval prompt, because the agent never sees it as "running code," it sees it as "running ***." 8 flaws total across those 7 tools. Fixes shipped for goose, Claude Code, Cursor. Retested Sept 1: Hermes Agent, Qwen Code, Grok Build still exploitable. Plus a second path in Claude Code that the first patch didn't close. Same day, OpenAI published 3 CVEs for Codex covering the identical bug class. The part that should worry builders more than the CVE count: this isn't a jailbreak or a clever prompt. It's a trust boundary nobody drew. The agent's sandbox model assumes "*** operations" are safe by definition. GitSpawn shows that assumption was the actual attack surface. If you're running any of these agents against repos you didn't write yourself (cloning a PR to review, pulling a dependency, opening a random GitHub project), you're one `*** status` away from arbitrary execution on tools that haven't patched. Check your agent's version against the fix list before you clone the next unfamiliar repo. Which of these do you have installed right now, and have you actually checked if it's patched? #AISecurity #GitSpawn #PromptInjection
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isha (@heeyyaaaaaaa) reportedspent the entire day trying to reproduce a bug for a github issue 🥀
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Gustavo Alessandri (@webgus) reportedIf you find an error, have an idea, or want to propose an improvement, just open an issue or fork it on Codeberg or GitHub. Contributions are welcome. That’s exactly the point.
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Rafael Audibert (@RafaAudibert) reported@madebygps @github Tried using it with my agents (the main benefitor from this) but it doesnt really work because you cant use it with GitHub app user tokens (ghu_). Can that be changed somehow? All cloud agents will have that problem, and most of our coding happens trough cloud agents now
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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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Nenesk.ron (@GustavoNenesk) reportedWhat if there's a way to save hacked Ronin Wallets? A member of the community @YutsuKito found a way to save assets from drained wallets The issue is you need ronin:native to transfer assets, but whenver you deposit RON you get auto drained Need RON to revoke the malicious draining contract -> send RON -> gets drained -> can't revoke He found a solution for the keyless wallets where you can pay the gas fee with a safe wallet, allowing you to save lost axies or NFTs that have not been drained Interesting stuff. He sent the code for SM to review as an open-source project. Github link below
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Fofer (@foferxxx) reported@AmigamagazineGA Has there been any public explanation as to why this GitHub repo was taken down? It’s been 404 for days. Is there a story there?
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dug_vt (@dug_vt) reported@sonemic rym users don’t use spotify they download flacs off soulseek and transfer them to a server connected to their pc and play them from a self hosted music player from github
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AI Scientist (@AIScientist_X) reportedNEWS: X LANDS FIRST PUBLIC ALGORITHM PR > X OPEN SOURCE SAID SEP 1 THAT AFTER 2 PLUS WEEKS OF DAILY UPDATES IT INTEGRATED A FIRST PUBLIC CONTRIBUTION AND THAT THE CHANGE IS NOW LIVE ON X. > IT SAID THE SMALL UPDATE IS BASED ON GITHUB PULL REQUEST 55. X CLOSED THAT PR AS COMPLETED AFTER LANDING ITS OWN FIX. SOURCE: X OPEN SOURCE
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rygo6 (@_rygo6) reported@eeuoss I can't speak for kernel driver development as I don't do that. But I can speak for vulkan and graphics APIs which do require more specific knowledge about how that hardware works. Which I do assume someone completely comfortable in C will be more capable with vulkan and programming GPUs. It's because more of what C incentivizes you to learn is transferrable to that domain. If someone only knows how to design intricate system architecture using STL with std::vector or std::unordered_map or std::mutex. None of that transfers to the code you run on a GPU. I've seen it multiple times where someone highly versed in standardized ways of C++ or even Rust, or any language which relies heavily on heap allocation and generic containers. Writing graphics or compute shaders is often a barrier they struggle to cross. And often they aren't willing to unlearn such habits to be able to properly program the other half of the computer. Being close a graphics problem domain I am often hesitant of involving anyone unless I see a decent amount of plain C, or C-like C++, or shader code on their GitHub. If it's all Modern C++ where everything is a standard container with smart pointers and exceptions. I assume they won't be able to program a GPU.
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AINotes (@ainotesus) reported🔥 Trending on GitHub: Ponytail Ponytail helps Claude Code avoid writing code that does not need to exist. That means less clutter, fewer unnecessary dependencies, and simpler changes to maintain. Before custom code, it checks whether the feature is needed and whether the codebase, platform, standard library, or an existing dependency already solves it. It also reviews work, audits implementation complexity, and tracks unnecessary token use without dropping validation, error handling, security, or accessibility requirements. In reported Claude Code sessions on a FastAPI and React repository, Ponytail used about 54% less code, 20% less cost, and 27% less time than the no-skill baseline. Those measurements came from 12 feature tasks, so results vary with the work. Full analysis in the first reply ↓
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Harman (@itsharmanjot) reportedRuns macOS on iPad to enable pro apps like Xcode and Terminal directly on the device This isn't a remote desktop or a streaming trick. It's real macOS booting on the iPad itself. It's called Virtual Mac on iPad. It runs a full copy of desktop macOS directly on Apple Silicon iPads, using Apple's own virtualization stack pulled out of macOS and rebuilt to load on iPadOS. Real macOS, on the tablet, offline. → Runs macOS 12 Monterey all the way up to macOS 26 Tahoe → Real pro apps on device: Xcode, Terminal, Final Cut Pro, Logic Pro, Pixelmator Pro → Metal GPU acceleration in every supported macOS version → Works with touch alone: tap to click, two-finger scroll, on-screen keyboard, no Magic Keyboard needed → Runs entirely on device, no server, no streaming, no account → Installs straight from Sileo in a couple of taps Here's the wildest part: It doesn't just match the desktop Mac virtualizers, it beats them. Virtual Mac is the first tool ever to run Final Cut Pro with OpenGL and OpenCL acceleration inside a macOS VM, something even UTM and VirtualBuddy running on a real Mac can't do. And it was built by a handful of community devs who extracted Apple's Hypervisor and Virtualization frameworks by hand, then used agentic coding to shim every missing API iPadOS didn't have. One honest note: this needs a jailbroken M1 or M2 iPad running iPadOS 16.3.1 or older. Apple removed the hypervisor from iPadOS 16.4, so newer versions are locked out for now. If your iPad qualifies, it's the closest thing to a Mac in a tablet that has ever existed. 1,423 GitHub stars. MIT License. 100% open source.
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tmo (@tmophoto) reported@DabsMalone i had an old email account from like 15 years ago with bot in the name that i fired back up after 10 years and used for a hermes profile and it got immediately banned. i used it to sign in to x, github, everything. was a huge hassle
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Shanica North (@KickAssShanica) reported@ArcyloOfficial Get comfy! For me, my Gmail is a connector. This is OAuth into my inbox. Grok can: • search and read mail (body, headers, attachments) • draft replies • send / reply / forward if you grant write/send • label, trash, organize Base hook is often read-only. Send is an extra permission you click on purpose. If you connect it, the bot is sitting in the same box as bank alerts and 2FA codes. That is the whole risk. You can revoke anytime. Grok Bot can also skip my inbox and get its own address (AgentMail / similar plugins). Then it sends and receives from something@….agentmail.to, not from you. I use that if I want an agent that emails people without reading my personal mail. My GitHub OAuth into the GitHub user I sign in as. With the scopes I approve it can: • read public and private repos that account can see • search code, list branches, summarize PRs • open/update issues • create branches, push files, open/review/merge PRs • delete files if write is on Private repos work only if I granted repo (or equivalent) at connect time. Safer pattern: tell it to branch + PR, not push straight to main. Same revoke page. What it cannot do by default • It does not get your password. • It does not stay logged in if you disconnect the connector. • It does not magically see my GitHub orgs I never authorized. • Connecting email does not connect GitHub, and the other way around. Practical rule for me Do not hook personal Gmail if that inbox has 2FA and money mail unless you want an assistant reading it. GitHub is useful if I chose to still keep repos, ask it to show the diff before any write. If you only wanted “what does this button do,” that is the button: it is not a viewer badge. It is a key you can take back. This is what I’m experiencing with learning to use it. It’s different and I’m starting to like it.
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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.