GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Tolu Hunter (@tolu_hunter) reported 4 minutes ago

  Clone the repo and give it a shot, link below. Open a GitHub issue if there's a tool or retrieval method you'd want added. And if this is what your business needs built for real, my DMs are open.

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  great hylord cavey phd ∿ (@cavemanloverboy) reported 4 minutes ago

  centralized server cant handle 1000 tps? solana could be github lol (if all commits were under 4kb)

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  imam (@marbennaid) reported 5 minutes ago

  is github down again? Why is it so slow ?

• 
  Remyno (@JUSTRandomU) reported 7 minutes ago

  **YOU NEED TO LOGIN WITH A 10 MONTH OLD GITHUB ACCOUNT ONLY**

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  Rabnoor Singh (@RabnoorSingh10) reported 8 minutes ago

  @burkeholland @github Every tool in this category has that problem now. Reputation runs about a quarter behind the product.

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  Dominik Koch (@dominikkoch) reported 11 minutes ago

  Here is why (its 3am ill make a github issue tomorrow): I miss having a proper message queue system, every message seems to instantly be part of the chat and im not sure if the agent read it yet or not

• 
  ChrisM (@ChrisMasterton) reported 12 minutes ago

  @YINMELO @thsottiaux Omg, I’m saying that we’ve been told it’s safe to use all these features but it’s not. That’s where all OUR tokens are going. Geezus ****. I’m saying it DOES matter to US - I’m not saying it’s OUR fault, the opposite. OAI devs have infinite credits, they simply won’t see the same issues that you and I see. They will look for different answers because they don’t see the same thing we do. Root Cause Analysis is an underrated skill. I’ve been a dev for 30 yrs and it took me this long and a lucky accident to figure out the differentiator. I don’t think OAI have nerfed anything, they (and others) promoted features without understanding the ramifications to the average user (you and me). It’s not their “fault” but it is their responsibility to listen to their customers and not blow us off with nonsense about sub2api. It’s not that. It’s obviously not that. I started using agents because I was told it would decrease my token cost. If you have lots of skills; if you spawn multiple chats at once, and if they spawn agents you are suffering from a massive initial prompt that does not get cached until your second message - for every chat, for every agent, and if you have X minutes between chat responses. There are so many of us using codex we have wildly different usage patterns. Thank goodness for years of gamedev where **** goes wrong in the weirdest ways. That’s what turned me on to agents and large initial prompts. Btw, I asked codex about all of this - codex literally agreed and posted the github issue for me. Luna is great (I use it for lots of chatbots - love it!), but spinning up multiple small agents is costing all of us a huge amount of initial tokens. I’m on your side, our side, OAI’s side. I want o find a solution, and the lack of RCA on OAI’s side is really disappointing.

• 
  Shravani (@Shra_va_ni) reported 14 minutes ago

  what if GitHub charged $0.01 for every commit? would you finally stop making fix fix2 final fix final fix 2 😭

• 
  Michael (@Michael55698384) reported 16 minutes ago

  Is it just me, or does the @github website seem particularly slow today?

• 
  Dan Olson (@olson_dan) reported 18 minutes ago

  I did review this decision making in the GitHub issue when I was first burned by it. The normal thing if everyone agreeing with another in the first few posts of the issue and by the time someone comes in pointing out a problem that wasn’t considered adequately no one wants to “re-litigate” it. This one was more innocent than some but still. No good excuses for this.

• 
  Jesse Nickles (@jessuppi) reported 18 minutes ago

  Update: to anyone else experiencing this... after force revoking ChatGPT from both Authorized GitHub apps and Installed GitHut apps, logging out of ChatGPT, logging it to ChatGPT in private tab and starting new chat, I was able to get it working again, but slow af vs. before.

• 
  f4g (@f4gch) reported 22 minutes ago

  Disagree on that, codeberg is a somewhat proper non-profit that unlike others doesn’t have hard large sponsors (feel free to correct). Looking at the graph of new AI-base projects on GitHub and them slowly having more and more a problem with outages I see a pattern Codeberg doesn’t have MSFT budget and if it ends up expanding like it had that budget it’d either HAVE to submit to large investment group sponsors or become paid both of which potentially come with hard drawbacks

• 
  TechManTy 👌 (@TechManTy) reported 25 minutes ago

  @BlockStBoys they need to contact the github dev if they have an issue?

• 
  Yume_X (@yume_arasaki) reported 27 minutes ago

  Showing the true power of the DGX Sparks : The AI Cookshow. Two Sparks. One night. A model fleet wrote a playable roguelike from a single prompt, and then one of the models sat down and played its own game. No API. Zero cloud tokens. The setup: - Spark 1 runs Qwen 3.8 27B dense (NVFP4, DSpark speculative). The brain. - Spark 2 runs Ornith-1.5 35B-A3B (NVFP4, MTP). The hands. - 128GB unified memory each, roughly 100W per box. The 35B fans out parallel drafts, one game module per stream, up to 24 streams at once. The 27B judges every draft on the other Spark, scores it, picks the winner. Best-of-N with an honest referee. New rounds, new modules, the game assembling piece by piece across the night. Both boxes fully loaded, both models earning their keep. An bitmap tile-based dungeon game was produced in two minutes, it's not visually impressive but it works. The throughput, measured on my rig: Ornith (drafter): - 1 stream: 88.7 tok/s - 8 streams: 305.7 tok/s aggregate - 24 streams: 496.6 tok/s aggregate. 13 percent over the published recipe number. Qwen 3.8 27B (judge): - 1 stream: 45.0 tok/s - 8 streams: 141.1 tok/s aggregate. DSpark overdelivers against its own estimate. Concurrent streams across the whole project: - 24 parallel drafting streams — the original fleet run (8 scopes × 3 rollouts each), 24/24 usable drafts in 101 seconds. That's the peak, on one Spark. - 18 multimodal drafts (6 scopes × 3) in 95s — the ASCII edition rerun, references attached - 18 drafts in 119s — the HTML edition - 16 simultaneous tonight — 8 drafters on Spark 2 + 8 judges on Spark 1, both boxes loaded at once - c24 sustained on the bench — that's where the 496.6 tok/s number comes from That is 637 aggregate tok/s of generation across two boxes pulling about 200W total. And the fleet delivered. Full drafting waves landed with every module usable. The judge caught every truncation, every hallucinated import, every missing function, before anything reached assembly. Zero false alarms in the logs. When it flagged a draft 4/10 for a logic error, the crash was real. The output: a tile roguelike. Single 19KB HTML file, zero dependencies, runs in any browser. You download it, you double-click, you are in a dungeon crawler. Not the final game I want yet, it is v1, but it boots, it plays, it fights back. Then my favorite part. We handed the 27B a real Chrome window, pointed it at its own game, and said play. It screenshotted, looked, chose a key, pressed it. 60 moves, every frame recorded. It explored, it found enemies, it fought. The model that wrote the engine also played it, with its own eyes. Stay tuned for episode 2. Drop in reply, what would you like to see tested out on two DGX sparks? Recipes and github gist in reply

• 
  Delighful Derek (@traderphos) reported 28 minutes ago

  Did this idiot not read the root cause? AWS had horrible load balancer issues and would have been subjected to same outages given the high volume of vibe coded slop idiots like this guy keep pushing to GitHub