GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  🦄Linus Shyu许发鑫高考去了不在 (@Linus_Shyu) reported 52 seconds ago

  Stop treating token rotation as a success path. x_bot: OAuth refresh token rotated, cache save failed, GitHub secret stayed old. Next cron died on invalid refresh token. Fix: save to secret BEFORE confirming with X, or write-after-rotation with retry. #DevTools #AI

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  tonis (@totovoto) reported 6 minutes ago

  @mittsh I was trying to find an open-source alternative for Tailscale when I first needed it. I guess AI suggested some OSS options, but they didn't have many stars on GitHub. AI didn't suggest Nebula. The Tailscale plan was free, so I just installed it and forgot about it. For Nebula, I think it is a distribution problem.

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  Curious Explorer (@PatelVatsalp732) reported 7 minutes ago

  I 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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  Ares (@neko23423) reported 8 minutes ago

  I 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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  Eddie Jaoude | DevRel | Open Source (@eddiejaoude) reported 15 minutes ago

  I have many tokens to burn before tomorrow after the Claude reset. Send me your GitHub issues with context 👇

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  Ash Lonare (@ashlonare) reported 15 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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  Kim Burgaard (@kimburgaard) reported 17 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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  David Abram 🐊 (@devabram) reported 18 minutes ago

  Discord is down. X is down. GitHub is down. Software is solved.

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  Vitaliy Salyuk (@vitaliysalyuk) reported 20 minutes ago

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

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  catman (@catmanyau) reported 23 minutes ago

  @sbilstein if GitHub is down, where does that push land first — and how do you handle conflicts when the repo comes back?

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  Straggler Liu | AI & Semis (@StragglerLiu) reported 24 minutes ago

  NVIDIA($NVDA ) Is Paying $14B for a Company With $150M Revenue. That's Not Financial Logic — It's Ecosystem Control. NVIDIA is in advanced talks to acquire Hugging Face for ~$14 billion ($12.9B acquisition + $1B retention), per Bloomberg. To put that in perspective: Hugging Face does ~$150M in annual revenue. That's ~86x revenue. Microsoft paid ~1.6x revenue for GitHub. Google paid ~3.5x revenue for DeepMind. NVIDIA is paying 20-50x more on a revenue multiple basis. The premium is not for revenue. It's for control of the AI developer ecosystem. What is NVIDIA buying? Hugging Face hosts 500,000+ models, 250,000+ datasets, and serves millions of developers. It is the single most important distribution channel for open-source AI. If you build AI, you use Hugging Face. That makes it the front door to AI development. Why NVIDIA is paying this premium: 1. The "NVIDIA triple lock." NVIDIA's hardware lead (GPU) is real. Its software lead (CUDA) is a moat. But the third lock — the developer workflow — was missing. Hugging Face is that workflow. Developers discover models on Hugging Face, deploy them, and optimize them. Whoever controls that discovery layer controls which hardware gets used. 2. The GitHub analogy, inverted. When Microsoft bought GitHub, developers were already using GitHub. Microsoft didn't need to capture them — it needed to prevent Amazon/Google from doing so. NVIDIA faces the opposite problem: developers are already using NVIDIA hardware. But they're discovering and deploying models through a neutral platform. NVIDIA is eliminating that neutrality. 3. The long game: inference, not training. NVIDIA dominates training. But inference is the bigger TAM — and it's more fragmented. If NVIDIA controls the model discovery and deployment layer, it can steer inference workloads to its own stack. That's a 10-year strategy disguised as a 14-billion-dollar acquisition. Who wins, who loses: NVIDIA (NVDA): Acquires the developer distribution layer. The most important strategic move since CUDA. Shifts the valuation case from "chip cycle" to "platform economics." Competitors (AMD, INTC): Lose neutral access to the primary AI model distribution channel. This is a structural headwind that no amount of hardware catch-up can fix. Cloud providers (MSFT, AMZN, GOOGL): Hugging Face was a neutral hub. If NVIDIA controls it, cloud providers risk being disintermediated from AI workload decisions. The open-source community: The platform that was built on openness is now owned by the dominant hardware vendor. Neutrality is the first casualty. The capital question: Can NVIDIA integrate Hugging Face without destroying its community value? If yes, the $14B is cheap. If no, it's a very expensive mistake. The answer will define whether NVIDIA becomes the AWS of AI — or just another hardware company with an expensive acquisition. Note: Acquisition details based on Bloomberg reporting; not confirmed by NVIDIA or Hugging Face. Revenue multiple comparisons based on publicly reported figures.

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  Yuvraj Singh (@Yuvraj_Singh317) reported 24 minutes ago

  Started 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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  Yeemio (@yeemio) reported 28 minutes ago

  owlrunkit is on github now. public corresponding source for the npm package. issues go here.

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  Bash (@bashirbuilds) reported 28 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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  Jessika Hyde (@dwajedentrzy7) reported 29 minutes ago

  @k2sbhai to all, u need to register via cn version (login with github). Pretty slow but usable as backup or something