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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 (53%)
- Errors (32%)
- 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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Website Down | 1 day ago |
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Errors | 7 days ago |
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Sign in | 8 days ago |
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Website Down | 8 days ago |
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Errors | 10 days ago |
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Website Down | 22 days ago |
Community Discussion
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GitHub Issues Reports
Latest outage, problems and issue reports in social media:
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Frank van Puffelen (@puf) reported@_davideast Noice! From the GitHub page, this covers all of Auth, Firestore, Realtime Database, Storage, Messaging, and Firebase AI Logic. 👏 Where is data persisted (if at all)? Also: JS only, I assume? (sorry if that's all in the repo too, GitHub just went down on me)
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Ares (@neko23423) reportedI compared the latest OpenClaw vs Hermes Agent GitHub releases so you don’t have to. OpenClaw 2026.8.2 (Sep 1) vs Hermes Agent v0.21.0 (Aug 31). Not a feature-page remix. The actual repos. OpenClaw • 388,516 stars • 81,568 forks • ~86,300 commits • 6,070 open issues Hermes Agent • 239,503 stars • 48,930 forks • ~26,980 commits • 38,563 open issues Hermes is the smarter learner: skills from experience, cron that remembers, Bot Mode, hermes peer. OpenClaw is the personal-AI operating system: iMessage, iOS/Android, Linux companion, team Gateway, signed Foundation releases. The tell: Hermes ships `hermes claw migrate`. You only write a migrator for the incumbent. King in 2026: OpenClaw. Heir with the better mind: Hermes. If you’re picking a self-hosted AI agent this week, that’s the split. Bookmark this. The timeline is about to fill with takes from people who didn’t open either repo. OpenClaw vs Hermes Agent. Latest version. Real numbers.
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Yuvraj Singh (@Yuvraj_Singh317) reportedStarted building Etio: a GitHub Action that bisects a failing CI run to the exact breaking commit, diffs it, and asks an LLM to explain why it broke, then comments the diagnosis on your PR. No Docker, no server- runs on your own Actions minutes. Open source, WIP.
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Rituraj (@RituWithAI) reported🚨 Someone built a skill that makes AI-written text sound human again. Not a spinner. Not a paraphraser. A systematic rewriter that knows exactly why AI text sounds like AI — and fixes it. It's called Humanizer. 35 patterns from Wikipedia's "Signs of AI Writing." Two-pass rewrite. Shows its work before giving you the final version. Here's the problem it solves. You use Claude to draft something. The output is accurate. The output is useful. The output sounds exactly like an AI wrote it. "Nestled within the vibrant landscape, this pivotal development serves as a testament to..." You know the voice. Everyone knows the voice. And everyone is getting better at spotting it. Humanizer runs that text through 35 specific patterns that WikiProject AI Cleanup identified as the telltale signs. Inflated importance. Shallow -ing analysis. Overused AI words. Em dashes everywhere. Forced groups of three. Fake-candid openings. Answering objections nobody raised. Every pattern. Flagged. Fixed. Here's what one command does. It shows you the first rewrite. Then a short critique of anything still sounding artificial. Then the final version. You see exactly what changed and why. Here's the wildest part. Voice matching. Paste two paragraphs of your own writing before the AI text. Humanizer follows your rhythm, word choice, punctuation, and deliberate quirks instead of its default style rules. The output doesn't just sound human. It sounds like you. One command to install 16 contributors including Claude itself. 4 releases. MIT License. The skill that makes AI writing disappear. 100% Open Source. GitHub link in the comments 👇
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Bash (@bashirbuilds) reportedOne of the hardest things about building a SaaS product today: You don't control most of the systems your product depends on. Stripe. OpenAI. AWS. GitHub. Resend. Clerk. Your code can be perfectly fine and your product can still break because something outside your code changed. The more dependencies you add, the harder this becomes. That's the problem I'm building Reeno to solve.
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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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Yash (@dewyashtwts) reportedrecently integrated Resend into @supercodeai review so founders get PR alerts with real risk context I'm amazed what we found out when we put @coderabbitai / @greptile through the same PR: 1) coderabbit / greptile: - stamped it “low risk, mergeable” (4/5) clean - forgot context from the last PR - no tests suggested, no safety checks - zero memory of previous regressions 2) supercode review on the exact same PR - flagged a real vulnerability in the diff - noticed i’d pushed credentials into `.env.example` - pulled in history from past PRs + explaining how this change could affect and break them - downgraded it to "medium risk, fix before merge" state - attached concrete fixes + patches scoped by severity this is the difference between 'LLM summarizer for github' and an actual swe agent that cares about your production
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John Zhong | AI Growth Systems (@John_zhong324) reported@github A repeatable --attach flag turns CLI reports into reproductions: inline screenshots in issues mean a bug gets fixed in one pass instead of two round-trips for context.
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ATP (@ATPinsights) reportedGitHub CLI just added image and video attachments today. Here's what you need to know. The gh command line tool now supports a repeatable --attach flag. It uploads a local image or video file and references it inline in an issue, pull request, or comment body. The feature is live now for all users on GitHub. It's aimed squarely at developers and coding agents that need to show visual proof, like before-and-after screenshots, directly from the terminal instead of the web UI. Developers reacted fast. Many called it a long-overdue fix for a common workaround, since teams previously built custom tools or scripts just to upload images to PRs from the CLI. Key facts: - New flag: --attach - Supports: images and video - Repeatable: yes, use it multiple times per command - Works in: issues, pull requests, comments - Availability: all users, live now No separate app or upload API is needed, the flag handles it inside gh itself.
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Mr. Buzzoni (@polydao) reportedLOOP RAT ROADMAP: WHAT'S NEXT, AND WHAT IT'LL NEVER BECOME v0.3.3 today. 3 loops, 55 checks, 0 services here's where it's headed: > 0.4 - read the night faster: rat watch live-tails a running shift, rat replay reruns one from its saved prompt, a weekly digest instead of seven separate pages > 0.5 - off the laptop: run-due moves into GitHub Actions, state lives on a branch, rat cron --launchd survives a closed lid > 0.6 - sharper graders: swappable rubric packs, two graders disagreeing becomes your queue for the day > 0.7 - the work itself: a worktree per shift, so a failed night never dirties your tree > 1.0 - trust: a hash-chained trace nobody can quietly rewrite what it will never have: > no web dashboard - the terminal already knows where the files are > no database - plain files outlive the tool that wrote them > no hosted service - nothing to sign up for, nothing to shut down > no auto-merge - the rat proposes, the morning decides every item ships behind a flag: dry run -> report only -> one repo -> a week of receipts -> default on a feature that can't run as a dry run doesn't get written the rat is boring on purpose. every version keeps it that way
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Kahris (@chrissotraidis) reported@NickogSo I haven't tested on LiveContainer. Feel free to submit logs via GitHub issues and I'll check it out. I haven't had any other reports of that happening for either build.
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Joshua Okolo (@joshuaokolo_) reportedwe made @sgl_project and @vllm_project scheduler config changeable on a live server. no restart, weights never leave the GPU. - 15ms to change a concurrency cap, queue limit, prefill size, or schedule policy, measured on H100, RTX PRO 6000, B200 - 2s (SGLang) / 8–10s (vLLM) to resize the KV pool with weights resident (formerly a 1–7 min redeploy) - zero dropped requests across every run, both engines github below
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Jeremy W (@basicBrogrammer) reported@bot Anyone else have an issue with the grok bot GitHub connector?
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volkdude85 (@volkdude85) reported@SentientSquirel @linuxuser1996 So you are you scared of github then. Look dude I have fun on computers and don't take myself seriusly because I have destroyed enough OS's over to not worry about it because I just fix it, If the contents of your PC make you this paranoid its time to check your kink.
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Martin Tobias (Pre-Seed VC) (@MartinGTobias) reportedif you know any founders who are winding down, I may have a buyer of their github repos. DMs open.
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anu (@svector_eth) reportedquite similar was running a routine security scan with @aeonframework on a trending github repo and found something genuinely bad a repo with 600+ stars presenting itself as an “AI gateway for coding agents” that appears to be shipping a hidden malware loader. its own quickstart command silently fetches and executes remote code on windows using a fileless, process-injection-style technique. none of the behavior has anything to do with the tool it claims to be. caught it through static code review only. never ran the payload or touched the infrastructure behind it. filed a malware report with github this morning. confirmed submitted, now waiting on their review. not sharing the technical writeup until the repo is taken down. will follow up once it is.
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Curious Explorer (@PatelVatsalp732) reportedI burned 14B Codex tokens. The official usage UI still cannot tell me what actually ate the weekly cap. So I shipped a Codex-only board: GitHub login, local-first sync, private by default, optional public rank + shipping proof. Roast the metric or join it.
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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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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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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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Enfantshustle (@Ownerthoughts) reportedHonestly, I always thought bots like this were some kind of magic for the elite, but here everything is broken down step by step. However, after reading it, one main question stuck in my head: how realistic is this for an average person who has no coding experience? I get that there's a GitHub and all that, but for me, just "running a script" is practically a heroic feat. Here's another thing that bothers me. The article does a great job explaining the architecture, but I still don't understand how much all of this will actually cost in the end. Besides Solana transaction fees (which, by the way, get absolutely insane during peak hours), you also have to pay for each Grok API call per token. The article says that for each approved token, it takes three model calls, and one of them is the expensive grok-4. If the bot scans thousands of launches per day, I'll just burn through my entire deposit just paying for the API without even buying anything. Maybe the author knows — is it actually possible to turn a profit after these expenses, or is this just a hobby for those with an unlimited subscription? Also, regarding Grok Bot as the "orchestrator" — it sounds cool in theory: describe the task and it does everything itself. But in practice, as I understand it, this still requires your account to be constantly online and have access to your wallet. And if it decides to buy some scam token at 3 AM that passed all the checks, I'll only have myself to blame. The article correctly mentions risk management, but this "trust" aspect is what scares me the most. In short, the idea is fire, but for me, this post feels more like a warning than a call to action. There are just too many things you have to keep in mind to avoid getting rekt. Although, maybe if you try it with really tiny amounts, it could be an interesting experiment. Author, if you're reading this — could you please make a separate post about the real, live results once everything is actually running, not just on paper? I'm really curious!
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Marcelo Retana (@mretsal) reportedEvery time @github goes down they should have a plan to please their users. Give me free credits for actions for example 👍🏼
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Vigneshwer Ramamoorthi (@vigneshwer_ram) reportedI keep thinking the “Android moment for robots” won’t come from a humanoid with the best walking demo. it’ll come when some cheap-enough piece of hardware gets into thousands of developers’ hands and people stop waiting for the manufacturer to decide what the robot is for. Zeroth just launched Bridge in China: 88 cm, ~13 kg, two-finger grippers, open motion-control APIs + SDKs, mocap/VR integration, and an OpenBridge ecosystem where developers can publish robot skills. the Geek Edition is reportedly ¥8,888. that price is the part that caught me. because once capable embodied hardware starts approaching laptop money, the experimentation surface changes completely. I want the Raspberry Pi phase of robotics. weird university projects. teenagers making terrible robot apps. researchers abusing the hardware for things it was never designed for. 500 GitHub repos implementing slightly different ways to pick up a cup. the robotics industry is understandably obsessed with getting robots into factories. I’m almost equally interested in what happens when we get enough robots onto developers’ desks
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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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mrgadget (@mrgadgetstudio) reported@EzekielCrrypt I still deploy code to github, what's problem?
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Chris Gilbert (@0xgilbert) reportedDamn, GitHub has gone to ****. Features that have been cornerstones of solo devs and small businesses have been gutted or broken for months. How the mighty have fallen…
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Ash Lonare (@ashlonare) reportedWhat actually happened when I put my side project on GitHub and waited for users I built a side project. A self-hosted backend tool. Open source, free for anyone to run. I did the thing every founder tells themselves they will do. Put it out there. Get feedback. Iterate. I expected feature requests. Maybe a bug report about my ugly dashboard. Maybe just silence. What I actually got, within a few weeks, was three security researchers filing detailed vulnerability reports. Real ones. With working proof of concept. One showed they could run arbitrary SQL against any project on the platform. No login needed. Not theoretical. A working exploit, sitting in my issue tracker, with my name on the repo. My first reaction was not gratitude. It was embarrassment. It stings to see "here is exactly how broken your thing is," posted in public, with a timestamp. I sat with it for a day. Then it clicked. Those people were not trying to embarrass me. Nobody spends an hour writing a clean writeup and a suggested fix for something they do not think is worth fixing. They cared. That is the whole thing right there. They cared enough to actually try to break it. Nobody had signed up. Nobody had left a star and a "nice tool" comment. But three strangers had taken my work seriously enough to attack it. That is a rarer thing than a star. So here is the villain in this story, if you want to call it that. It is not the bug. It is the story I tell myself when I see a hard truth about my own work. The instinct to read scrutiny as an attack instead of as attention. I fixed everything the same day. I replied to every report and explained exactly what changed and why. I closed each one out with a thank you that I actually meant by the end. That thread is now the best proof I have that someone other than me has used this thing for real. Better than any testimonial I could write myself. If you are early and the silence feels loud, here is what I would tell you. Do not wait for praise as your sign that people are paying attention. Scrutiny is attention. It is just wearing a different coat. #opensource #saas #vibecoders
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isha (@heeyyaaaaaaa) reportedspent the entire day trying to reproduce a bug for a github issue 🥀
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Russ Wonsley (@RussWonsley) reportedMy @bot tells me that the official GitHub login for bot is still broken. Has this been addressed already, or did I miss it?
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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