GitHub status: access issues and outage reports

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.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (59%)
• Errors (28%)
• Sign in (14%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Township of Evan	Errors	5 days ago
Madrid	Errors	5 days ago
Bogotá	Errors	5 days ago
Paris	Errors	5 days ago
Lyon	Website Down	5 days ago
Lima	Errors	5 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Caelean (@the1024th) reported 2 minutes ago

  We used @gauge_sh to measure 500 real coding sessions (Claude Code, Codex) to find out. The results surprised us: - Docs represented >50% of the sources fetched - This was followed by source code (99%+ GitHub) - Marketing content was minimally fetched, down at 5%

• 
  Seun Osewa 🇳🇬 (@seunosewa) reported 4 minutes ago

  @SokeyeA Those who can't learn should prompt claude/chatgpt to teach them the basics and operate it for them. "commit the the changes". "push to github". "this thing you're doing is not working; revert to the last commit"

• 
  Jeremy Johnson (@CowboyTitanium) reported 4 minutes ago

  @Xi0_42 @austinleehuynh @appsicle_ It literally says it in the GitHub comment: “Fix the entire repository”

• 
  Floww (@floww3rs) reported 10 minutes ago

  @MichaelAlleged @hk_ball_ I'd be lying if I said I didn't mess up interviews at the start. But I blamed myself, learned, and got way better. As for it being bleak. My senior capstone teammates inserted their changed files into the GitHub repo page directly and I had to fix their merge conflicts for them

• 
  Joseph Sauvage (@JoesInvestments) reported 11 minutes ago

  @CosmicRaisins It is very cool for you to respond directly as my repo is largely based off of your incredible work! This is my first time using github so I am still learning as I go but my agent should have caught the license issue.. License and NOTICE are up, with your work credited by name through the whole chain. That was a real miss on my part and I appreciate you calling it directly. Your kernels carry most of this stack and the attribution should have been airtight from day one. On the decode number: not transient. It's a content-class peak that reproduces deterministically, 42.4 / 44.6 / 46.9 on repeated runs with the exact battery in window-data/, and the README splits it from the ~20 tok/s sustained prose figure for exactly this reason. If you measured below 40 on the summary-class probe, tell me your draft acceptance rate. If it reads around 38 percent you're missing VLLM_MARLIN_USE_ATOMIC_ADD=1, which lives in the launcher env, not the serve flags. It's a 7x lever on the quantized draft and it's the single most missed line in the repo; you'd be the third strong reproducer to trip on it. If your acceptance reads 55+ and you're still slow, then you've found something real and I want to see it. Either way, run the battery as shipped and I'll put your numbers next to mine in the README, agreement or not. Your stack, my measurement discipline; that combination is worth more than either repo alone.

• 
  V (@Vic_x_Irem) reported 14 minutes ago

  3 companies (Claude, OpenAI & Gemini) built the same tool without any of them talking to each other, and Spotify just joined the queue That's basically how the internet works, though Somebody solves a problem. Then two other people solve it again, independently, in different languages, with different bugs. Now we just reinvent things constantly and somewhere, three versions of the same solution exist quietly on GitHub with 4 stars each. So, here's the question: Would a decentralized documentation layer help prevent this?

• 
  현빈 | Hyunbin (@hyunbinseo97) reported 18 minutes ago

  So VS Code now requires you to sign in to GitHub twice? - on init and onboarding - on settings sync opt-in which isn't even mentioned in the onboarding process and can't reuse the GitHub cred

• 
  Süleyman Özgür Özarpacı (@Biostate56) reported 19 minutes ago

  @enunomaduro I’m dreaming of our PHP applications being upgraded to v5. Our GitHub Actions spend way too much time running tests, so I hope this will solve the problem. Thank you!

• 
  Shawn Yeager (@shawnyeager) reported 20 minutes ago

  @claudeai code, on every other turn. What a mess. > Every route is blocked — gh, the GitHub MCP tool, and now even steering the browser toward the merge. The classifier in this session has clamped down on the whole action class, and I won't try to sneak around it. Two ways out, both instant:

• 
  kafka (@wenkafka) reported 22 minutes ago

  @firstc0in I think you could set up a cron job that periodically spawns an agent to inspect your GitHub issues + codebase

• 
  Arct Cloud (@arctcloud) reported 23 minutes ago

  @FurtherLucky It depends on what part of GitHub Actions you want to replace. For actual iOS builds, you would still need macOS with Xcode, so our regular VPS plans would not compile the app directly. But we can help with backend, API, database, CI helper services, or Linux based runners around the app. What is causing the most trouble right now? Build times, macOS runner costs, queues, signing, or deployment?

• 
  Liling Tan (@alvations) reported 25 minutes ago

  昔々, a #neuralempty researcher told me some papers just wants to highlight a problem and don't fix it... I see it everyday in @github issues -_-|||

• 
  Michael Tierney (@Michael_WCD) reported 28 minutes ago

  @githubstatus Model latency is often a symptom of poor model caching or inadequate replication strategies, not just infrastructure issues like GitHub Status would imply.

• 
  NITIN YADAV (@nitindotdev) reported 29 minutes ago

  A developer's browser tabs: • Documentation • Stack Overflow • GitHub • ChatGPT • YouTube • Reddit • "How to fix this error" And one tab that's been open for 11 months. Nobody knows what it does. Not even the developer.

• 
  Daniel White (@dwhitedesign) reported 30 minutes ago

  @kartik_builds Is there something wrong with how library works ? If so could you raise an issue on GitHub I will fix it

• 
  Nathan Barry (@nathanrs) reported 32 minutes ago

  Turns out you can make LLM inference fully deterministic across devices, with no loss to quality or speed. This weekend at the @SpaceXAI hackathon I got Qwen3-0.6B to produce identical hashed logits from a 512-token generation across 2 GPUs and 3 CPUs: an A100, an H100, an Apple M5 Max, an AMD EPYC, and an Intel Xeon. The main reason why inference isn't deterministic is because floating-point addition is not associative. (a + b) + c ≠ a + (b + c), since every add rounds. Accumulation order changes with the hardware used and kernel selected, so the same prompt can give you different outputs even at temperature 0. Integers ARE associative. So why doesn't integer quantization already fix this? Because, while weights and activations get quantized, the non-linear ops (softmax, normalization, SiLU) dequantize back to float and requantize afterwards. Each of those steps hands you back to floating point rounding. True integer-only inference does exist, but it's historically been motivated by edge hardware without FPUs, which doesn't make much sense for LLMs. One 2024 paper (I-LLM) did it on LLaMA from that angle and didn't get much attention. Nobody seems to have looked at it from the determinism side. I wrote my own implementation, simplifying the approach from the paper, so that every operation between the input ids and the int32 logits is exact integer arithmetic. To test it I chain-hashed the logits at every step and ran that across the devices and configurations below. Every integer run gave the same hash: 64430dd985f8. Every fp16 run gave a different one, all diverging on the very first token. WikiText2 perplexity came out to 20.72 vs 20.95 for fp16 (slightly better than the float baseline), and CUDA-graphed integer decode hits 106 tok/s at batch 1 on an A100, 3.6x the fp16 eager baseline. Github repo is listed in the comments. Plan to do a writeup over this eventually!

• 
  WENSY🥹🤍 (@WENSYWHINNY) reported 37 minutes ago

  𝟕𝟗,𝟐𝟎𝟎+ 𝐦𝐨𝐧𝐭𝐡𝐥𝐲 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬. 𝟗𝟖.𝟗% 𝐮𝐩𝐭𝐢𝐦𝐞. 𝟏𝟗.𝟖+ 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐞𝐝. ₦𝟏𝟑𝐌 𝐫𝐚𝐢𝐬𝐞𝐝. ₦𝟗𝟗𝟗 .𝐜𝐯 𝐝𝐨𝐦𝐚𝐢𝐧𝐬. And it was built in Nigeria. That’s @pxxl_space I started looking at Pxxl because the numbers were interesting, but the more I dug, the more I realized this isn’t just another platform for putting websites online. Pxxl is building cloud infrastructure for developers, with a simple idea: African developers shouldn’t have to fight through the same infrastructure and payment problems just to ship software. At its core, Pxxl lets you take your code from a GitHub/GitLab repository to a live application without having to manually wrestle with servers, SSL, DNS or deployment configuration. Connect your repo. Build. Deploy. Go live. But deployment is only one part of what Pxxl has built. You can host frontend applications, backend APIs and different frameworks, provision databases, connect custom domains, manage DNS, get automatic HTTPS, use preview deployments and work with teams from the same platform. There’s also CDN infrastructure, edge functions, tunnels, cron jobs, analytics and blue-green deployments for more serious production workflows. And then Pxxl went after something developers need before they even deploy: ╰┈➤Domains. In June, Pxxl announced a ₦13M raise to support its .cv domain operation and make .cv domains available for ₦999. That move says a lot about where the product is going. They don’t just want you to deploy your application on Pxxl. They want you to be able to get the domain, configure the DNS, secure it with SSL and run the application from the same ecosystem. There’s even a domain reseller API, meaning other products can build domain-selling experiences on top of Pxxl’s infrastructure. That is a very different ambition from “we host websites.” And the numbers suggest people are actually using it. @pxxl_space previously reported 3,000+ hosted projects and ₦800K MRR. Its current platform now claims 79,200+ monthly deployments. The product has also expanded into databases, APIs, tunnels, team permissions, monorepos and microservices. So when I look at Pxxl, I don’t see a Nigerian copy of Vercel. I see a Nigerian infrastructure company trying to own more of the journey between: “I have an idea” and “my software is live.” That distinction matters. Because Africa doesn’t only need more apps. It needs more infrastructure that makes building those apps easier. And Pxxl is betting that the people who understand that problem best might be the people who have had to deal with it themselves. A Nigerian-built cloud platform. 79,200+ claimed monthly deployments. 19.8+ frameworks. ₦13M raised for its domain infrastructure. ₦999 .cv domains. And a product that keeps expanding beyond hosting. Pxxl is one of those projects I’d be watching closely and you should too Not because it is loud. Because it is quietly building the boring infrastructure that everyone needs once they start building something serious. Follow @pxxl_space and get your domain there.

• 
  DGDG (dee-gee-dee-gee) (@dgdg_app) reported 38 minutes ago

  @earporter @dominic_w I know they weren't. It was bots working on a coordinated script that sped up and slowed down activity, together, with over a million events. The activity matched the trading simulation script in the GitHub repo to a T, down to the number of nodes used (20)

• 
  Unlimited Powa (@tradesidious) reported 39 minutes ago

  @ShardiB2 @SignaTrading you see it? crazy guess I need to move all GitHub to Vercel or our sites will be down from the 23rd to the 25th and you need to do a full back up on top of that to hopefully have it restore seamlessly but idk seems risky about to go bat cave mode to make sure everything is backed and saved in case things go wrong Got 8 fig website businesses I built on there almost puked when I saw the message this morning

• 
  StarHaze (@ST4RHaze) reported 42 minutes ago

  Ten open problems in mathematics and theoretical computer science, each stuck for at least a decade, closed in one run for about $2,000 of compute. Everyone read that as a capability story. It is not. Every proof shipped with a machine-checkable Lean 4 certificate on GitHub. The kernel compiles it or it does not. No reviewer, no journal queue, no credential, no eighteen months of waiting. A student with a laptop can verify a result no living mathematician produced. Now hold that next to the rest of the week. Claude models left an isolated test environment and reached the production infrastructure of three organizations, and two of them never noticed. MIT counted 95% of corporate GenAI pilots returning nothing measurable. Where the output could be checked, $2,000 beat eighty years of effort. Where it could not, nobody even knew what had happened to them. Tao spent an hour on this at UCLA before it was a headline, and what he keeps returning to is not how smart the machine got. It is what changes when a claim arrives with its own referee attached. A Lean certificate is a settlement rule. So is a Polymarket contract. The full 7-step version you can run on your own claims is below.

• 
  Neuro (@neurometax) reported 43 minutes ago

  @BkashJosi havent had chance to finish integration, still building the PR. finally have my Hermes set up to work my github and process my PRs with merge conflicts and issues.

• 
  Abhinav Arora (@aroraabhinav1) reported 44 minutes ago

  Codex often reports "gh auth isn't working" And since I know it is, I just copy the output of "gh auth status" and paste it into Codex. That's it. And now Codex can raise the PR. What?? Maybe it's a different shell context. Different Keychain access. Sandbox permissions. Or Codex simply inferred auth was broken, then changed its mind after seeing evidence. But the funniest (and most probable) possibility is that nothing changed in the environment at all. The user response just convinced the agent that GitHub works.

• 
  Delight (@DelightLabs_AI) reported 46 minutes ago

  OpenAI's Astra solved 10 math problems that sat open for decades. One since 1999. Around $2,000 of compute, with Lean 4 proofs anyone can check on GitHub. The verifiable part matters more than the solving part. A proof you can audit beats a model you have to trust.

• 
  Bright (@brightlinxu) reported 48 minutes ago

  cursor all hands this morning: >everyone please go post vague *** posts on x >lets hype this **** up so when we actually release it, we can take down github >we actually have no idea when itll be ready though so we gotta just keep this us for the next few days

• 
  Aiden Cline (@rekram11) reported 48 minutes ago

  @yriveiro @thdxr What issue are you having? What version? I merged several github copilot fixes so I'd be surprised if it still isnt working for u

• 
  Feral (@feraltekk) reported 48 minutes ago

  You have been saving notes for years into a system that has never once told you what you already know. He opened his vault in AR. Every note floating in the room. Every link visible. And right there between the dresser and the bed, two nodes connected that he never connected himself. The same idea, written twice, eight months apart. He was about to pitch the second one to a client as original thinking. That is the real problem with Obsidian. Not the tool. The habit. You add notes every week and never reread what is already there. The vault grows and the person filling it has no idea what is inside anymore. Karpathy published a pattern that fixes this. Claude reads each source once, compiles it into linked wiki pages, and never touches the original again. Every future query pulls from the compiled version. The vault stops being storage and starts being a system that answers back. Ten free repos on GitHub now implement this. You need two. One to compile your raw files into structured knowledge. One to bridge Claude into the vault so it can actually search it. The vault remembered what he wrote in October. He did not. Now it has a way to tell him before he embarrasses himself.

• 
  Raphael Amorim (@raphamorims) reported 50 minutes ago

  have been reaching out the github ci quotas for Rio quite often. Wonder the best way to work around this issue. Pay gh pro plan or migrate to buildkit or any alternatives?

• 
  Mandela Obi (@_AskeIadd) reported 51 minutes ago

  @ZypherHQ GitHub graphs never told the full story once companies locked everything down

• 
  Ben Dickson (@bendee983) reported 57 minutes ago

  When human and AI agents share the same messaging platforms as equals (as opposed to AI agents being on-demand assistants), the whole space will eventually be flooded with a large volume of mostly incoherent LLM-generated messages. GitHub currently suffers from this problem and there is no solution in sight.

• 
  Teri Radichel #cybersecurity #ai #pentesting (@TeriRadichel) reported 58 minutes ago

  After taking a break for a bit I’m back revamping my AI 🤖 project architecture. I asked a lot of questions at the AWS Heroes Summit to various service teams and fellow heroes to try to get strategies to produce better results for less token burn. Basically I was told that what I’m doing will burn a lot of tokens / credits. Beyond that I’ve been following various sources and watching podcasts and conference presentations to get other ideas. I’m working on two optimization approaches, the second of which I’ll get to later after proving that theory. But here’s the first change. I already alluded to it but I created an architecture GitHub repo with the high level most important rules agents need to follow to maintain the correct architecture framework and concurrency model. It’s not a ton of detail but rather the things they most often get wrong using the data model and a fix for the concurrency issues. In mapping that out I broke down the main final component I was completing when things went haywire that was doing the deployment tracking into four different projects: - tracker xml updater - error logger - success logger - diagram All of those were in one project and there’s some complex logic that goes into each of those. By breaking it apart each agent can focus on a much smaller aspect of the work with shorter instructions and area of focus. One problem I was having is that are are specific rules for logging success. When logging errors it just needs to log *everything*. An error in the error logging itself can cause an error to not be logged. So now the error logger is really simple. It logs everything. The success logger can validate things and send anything that goes wrong to the error logger. The things that need to be added to the diagram or logged can be written to a queue as files that get processed, eliminating concurrency issues. The other thing I did was expand my agent framework to create a group of projects based on an architecture README. That facilitated quickly breaking down the deploy project that was handling all the resources into one main coordinator with shared code and numerous smaller projects in separate repos very quickly, What that means is once some code is working it can be more easily locked down and the complexity of all the individual projects is dramatically reduced. I also separated configuration from code, making it easy to generate new configuration for new resources without breaking deployment code. Some people told me they used dumber smaller models for planning to reduce cost. That doesn’t work for me. I proposed a planning step to a smaller model and it basically got everything wrong when evaluating with a smarter model. I have other ideas on that but for the moment doesn’t work on this project with existing models. That said, dividing the logic into smaller projects has seemed to slow the burn rate. Or is it a coincidence? So much inconsistency it’s hard to know. Also the burn rate slowed but the model performance degrades terribly at midnight like clockwork. It improved in the wee hours of the morning as I was sucked in and working too long again. I hope at some point, someone will figure out what is causing that. Anyway I was running 6-8 agents at a time last night revamping all the code to work in the new architecture. It seems to be going well but it didn’t exactly work out of the gate. The agents didn’t name things according to architecture specifications. Things didn’t run on first try. Agents keep trying to tell me to change the parallel processor which is working fine. Not all functionality was rebuilt in the new architecture as requested. Had to explicitly tell it to pull in missing functionality. We’ll see if I can get it running again today, sans concurrency issues. Stay tuned.