GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Kir Shatrov (@kirshatrov) reported 2 minutes ago

  github 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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  mrgadget (@mrgadgetstudio) reported 2 minutes ago

  @EzekielCrrypt I still deploy code to github, what's problem?

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  CATIRL 🏳️‍⚧️ (@CATIRL_9) reported 3 minutes ago

  @mminhamina Google GitHub "open grind", solves your problem

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  Jason Sawyer (@foilmanhacks) reported 5 minutes ago

  There's a huge problem in InfoSec education: it’s way too course and tool focused. Instead of teaching the underlying methodologies and how to discover or invent, we feed people the latest "OSINT" slop script that’s been shat onto GitHub. OSINT isn’t about using scripts or services. It’s about understanding how they work, and being able to create your own.

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  Max Rovensky (@MaxRovensky) reported 6 minutes ago

  @thekitze you'd be even further down if you fixed the GitHub bug I just reported

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  Ash Lonare (@ashlonare) reported 6 minutes ago

  What 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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  Bash (@bashirbuilds) reported 8 minutes ago

  Your 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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  Harman (@itsharmanjot) reported 26 minutes ago

  Runs 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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  Kim Burgaard (@kimburgaard) reported 29 minutes ago

  Back 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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  Frank van Puffelen (@puf) reported 32 minutes ago

  @_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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  Vitaliy Salyuk (@vitaliysalyuk) reported 32 minutes ago

  @openclaw @github Fix your updater and I might give it another shot.

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  AINotes (@ainotesus) reported 33 minutes ago

  🔥 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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  Aayushiii (@stfu_aayushiii) reported 35 minutes ago

  If you're building a project, read this before writing a single line of code. 5 things I learned the hard way: 1. Problem > model Don't start with “How do I use GPT?” Start with “What problem am I solving?” 2. Simple stack > impressive stack If your MVP needs Kubernetes, 6 microservices and an agent swarm, you probably haven't built an MVP. 3. Evaluate before you optimize You can't improve what you can't measure. 4. Build for users, not your GitHub README A technically impressive project nobody can use isn't a product. 5. Ship ugly. Iterate fast. Your first version isn't supposed to be impressive. The biggest mistake? Spending weeks deciding which model to use when you haven't even validated the problem.

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  Bash (@bashirbuilds) reported 36 minutes ago

  One 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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  Chris (@chriscoolstuff) reported 37 minutes ago

  @pfernan95dev For the SEO part there's one thing that I've been also doing: Ask your agent what keywords you should search for relevant to your app on answerthepublic, perplexity and google Gather all that info old fashion, by yourself - might take around 2 hours but it's worth it Plug all that info into the agent and have it give you 5 titles for 5 articles Make it write those articles - maybe use nosoopai github or edit them manually so they seem more human like Connect the agent to google console After 1 month tell the agent to review the results If no article took off you can wait one more month or put up 5 more After the next month check what worked and double down on that