GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Charles McDowell (@charlesmcdowell) reported 5 minutes ago

  @openclaw @github I still just want to know why there was even a new release of OpenClaw with nothing new that could compete with Hermes Agent? I was really excited for the release. Then, just like what seems like everybody else, incredibly let down.

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  Ravi Prasad (@ravikp7) reported 6 minutes ago

  Big NO to Github hosted CI runners for personal projects now. I have setup a self-hosted github CI runner on a spare laptop running ubuntu server. Been running it for 10 days and I did some calculations, for my usage if I run it on Github runners, it'd cost me around 200$ vs < INR 100 on electricity (local setup) monthly.

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  shifan (@sanereverie) reported 8 minutes ago

  building something that races coding agents on the same GitHub issue and scores the PRs. coming soon.

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  Asterix (@Asterix54907294) reported 9 minutes ago

  end-of-summer snapshot for @QFEX : -~$222M in open interest -CLI v0.3.12 shipped in August with improved installation docs and a go.mod fix -GitHub activity continued through late August not a flashy launch recap, just a quick look at how the exchange is closing out the summer: more markets, meaningful liquidity, and active work on the tooling side still early, but the infrastructure is clearly moving

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  Dr Milan Milanović (@milan_milanovic) reported 10 minutes ago

  How 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.

• 
  Jason Sawyer (@foilmanhacks) reported 11 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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  HeroGamer⚡ (@herogamer21btc) reported 14 minutes ago

  💻 GitHub Issues vs Draft PR vs Open PR — the difference nobody explains: 🔴 ISSUE = Should we do this? No code yet You describe the problem "App crashes when pasting OP_RETURN" "We need X feature" Anyone can open it Goal: decide IF and WHAT to build 🔵 DRAFT PR = I'm doing this, is this the right way? You have WIP code "I fixed it by doing Y, but not sure about placement / approach" Can't be merged Perfect for early feedback Goal: validate HOW you're building it 🟠 OPEN PR = I did it, ready for final review, please merge. Code done, tests pass Ready for final review Goal: ship it 🌊 Flow: Issue → Draft PR → Open PR Most people skip Issue or Draft and go straight to Open PR. Then maintainer has to review both the idea AND the implementation at once = slow, painful. Start Draft when unsure.

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  Kevin Minnelli (@minnelli) reported 15 minutes ago

  WTF - Grok Bot can't fire on schedule to save it's life. The scheduled routines are just broken and at best unreliable. I want to love this product. When you set the cron job it doesn't work. It tells you try Cloudflare, sure let's set that up and burn tokens, then that doesn't fire to wake them. Oh, let's try GitHub now and use that....all failed. I had to wake it again this morning before the market opened. Anyone else feeling frustration in this regard?

• 
  Åsa-Nietzsche (@AsaNietsche) reported 17 minutes ago

  @peterb0yd @burkeholland @github It's every ******* model. I'm getting whiplash from all of this everything changing forever society being turned upside down every two weeks.

• 
  small_j (@a_small_j) reported 19 minutes ago

  SmallDocs 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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  Harsha Kotcherlakota (@DPortkey) reported 20 minutes ago

  Awesome Codex non-coding usecase: I had 1-2 TP Link Kasa smart outlets that always ended up falling off the network, and it drove me nuts. I set Codex on it. It found a github library for these devices, carefully examined them on my network and watched them fall off, and told me that even though they look identical, 2 of them were previous generation models that had *slightly* lower total wattage load support. It told me exactly how to tell them apart, and sure enough, that was that. 2 replaced outlets later and my connected devices have bene flawless. Months and months of irritation, gone because of 30 seconds of curiosity. Just try, you never know what you could fix! @victornunez

• 
  Straggler Liu | AI & Semis (@StragglerLiu) reported 20 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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  volkdude85 (@volkdude85) reported 21 minutes ago

  @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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  Russ Wonsley (@RussWonsley) reported 22 minutes ago

  My @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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  smore (@babachefz) reported 24 minutes ago

  @ZixuanLi_ @huggingface asking support questions in someone's hype thread is a crime. check the docs, check the github issues, it's probably not listed yet because it dropped like 6 hours ago.