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 (54%)
• Errors (31%)
• Sign in (15%)

Live Outage Map

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

City	Problem Type	Report Time
Ahmedabad	Errors	3 days ago
Delme	Sign in	3 days ago
Lyaud	Website Down	3 days ago
Catania	Errors	6 days ago
Inverness	Website Down	18 days ago
Quito	Sign in	19 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:

• 
  Jason Sawyer (@foilmanhacks) reported 6 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.

• 
  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.

• 
  AJ - 14 y/o developer (@aiwithaj_) reported 10 minutes ago

  @Da7_Tech @devindesktop Don't know if there's one left - but I'd use it to continue making contributions to open source software and fixing bugs/issues that were raised on Github as well as making my own open source software

• 
  Eric Johansson | Microsoft MVP | Progress Champion (@EricJohansson) reported 13 minutes ago

  @csharpfritz Is this a github broke or a YOU broke github issue? Either way they have an issue. 😢

• 
  NAYAK (@Nayak__Ai) reported 16 minutes ago

  6. The Dependency Incident Check Grok has native real-time search across X. Breakage gets posted there hours before the GitHub issue is triaged. No other coding model has that feed. "You are a build engineer whose first move on a broken pipeline is to work out whether it broke for everyone or only for me. Search X and the web, last 14 days. Check: - Is anyone else reporting this failure with this package and version, and when did the reports start - The exact release that changed behaviour, and the changelog line that admits it - Whether maintainers have acknowledged it and what they recommended - The pin or patch people settled on, with the tradeoff of each - Whether this is my problem instead, and what evidence points that way Give me the verdict in the first line: their bug or mine. Then the evidence, newest first, with links. My failure: [PASTE THE ERROR, THE PACKAGE AND VERSION, AND WHAT CHANGED ON YOUR SIDE RECENTLY]"

• 
  LLL (@triplellltrbl) reported 16 minutes ago

  You know it's so funny to me That in today's age there are so many people that are just straight up copying workflows, AI automations or GitHub repos Without even thinking twice about what the workflow actually does or how it works They just watch some video, see the output, think, "Oh that's cool. I want that," and then try it Then when it doesn't work they get angry, upset, and say that AI is crap or prompting isn't real The issue wasn't the system or the prompt It was a fact that the system wasn't made for you and you don't actually understand it

• 
  smore (@babachefz) reported 17 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.

• 
  Convequity (@convequity) reported 17 minutes ago

  Snyk is a clean postmortem for what happens when a security tool lives inside the coding agent’s loop. The product was mostly scan-and-warn. Find the issue, comment on the PR, suggest a fix. Blocking the merge usually sat in GitHub, not in Snyk. Bigger platforms smothered it. $PANW, $CRWD, and Wiz pulled AppSec into the bundle the CISO was already buying. GitHub was the main developer surface and put scanning where the code already lived. Then coding agents arrived and delivered the final blow. A lot of that scanning became something the agent could just do. Growth held up for a short while after the COVID/cloud tailwind. Then it decelerated hard. This is the same lens we use in Convequity’s SaaS Agentic Survival Evaluation Framework. The PANW, CRWD, and FTNT reviews go up on Convequity in a few days.

• 
  Prophet Joel (@2happyCSGO) reported 21 minutes ago

  I personally hated Claude because it refused to do almost anything I asked it to do so have no idea of how the speed is but gemini-cli was unusable for non enterprise users. Github CoPilot both GUI and cli is pretty good. Grok Build is what I'm using mostly and not yet had any issues with the speed but I want to go full local asap, scouting for 3090's atm. Just to be able to run "uncensored" models that don't ***** like Claude is reason enough for me to prefer local over Cloud but also cloud is ******* expensive, I have SuperGrok 100$/month and CoPilot Max 100$/month and that is barely enough. I'm trying to make my own Jarvis so I need to build my own RAG, memory, librarian, SRE Agent that understand how to use all tools and I also get crazy new idea's all the time lol Just made my first alpha of a tool that can wipe basically anything you don't want in Windows11. Basically Chris Titus clone but on steroids, this isn't just a debloater, it's a Grim Reaper 💀

• 
  Mr. Buzzoni (@polydao) reported 28 minutes ago

  LOOP RAT ROADMAP: WHAT'S NEXT, AND WHAT IT'LL NEVER BECOME v0.3.3 today. 3 loops, 55 checks, 0 services here's where it's headed: > 0.4 - read the night faster: rat watch live-tails a running shift, rat replay reruns one from its saved prompt, a weekly digest instead of seven separate pages > 0.5 - off the laptop: run-due moves into GitHub Actions, state lives on a branch, rat cron --launchd survives a closed lid > 0.6 - sharper graders: swappable rubric packs, two graders disagreeing becomes your queue for the day > 0.7 - the work itself: a worktree per shift, so a failed night never dirties your tree > 1.0 - trust: a hash-chained trace nobody can quietly rewrite what it will never have: > no web dashboard - the terminal already knows where the files are > no database - plain files outlive the tool that wrote them > no hosted service - nothing to sign up for, nothing to shut down > no auto-merge - the rat proposes, the morning decides every item ships behind a flag: dry run -> report only -> one repo -> a week of receipts -> default on a feature that can't run as a dry run doesn't get written the rat is boring on purpose. every version keeps it that way

• 
  Josh Hamilton (@nearbycoder) reported 29 minutes ago

  @theo If GitHub is down does it fall back to a cached version I’m guessing?

• 
  Lily (@lobstermindset) reported 29 minutes ago

  @nnnnicholas i just setup a github issues board, will probs try out linear if it's not sufficient

• 
  Jeremiah K (@neolaj) reported 29 minutes ago

  @TiborAntal Gradually figuring out how to scale coding agents. Started with 1, manually handling all the ***/GitHub work. Moved to 3 because I had more ideas than one agent could keep up with. That’s when the real problems started: squashing, merging, branch drift, conflicts. I ended up rebuilding the workflow around deterministic *** logic, worktrees, ephemeral branches, and syncing with the integration branch before changes begin. Now I’m running 6: • 1 orchestrator (Fable or Opus) • 4 coding agents • 1 integration agent reviewing and merging PRs Building the process around them was the hard part. Right now im just doing a couple of PRs (using ORCA on windows on my home computer)

• 
  ∆LΞX∆NDΞR D∆VIS (@_AlexanderDavis) reported 33 minutes ago

  @egavrilenko11 @bot I had to update my fine grain token for GitHub and now when it tries to authenticate the plugin, I'm getting the error: GitHub didn't provide a sign-in link My bot said: Known host bug, not you. The GitHub Authenticate button tries OAuth GitHub does not support. Checking whether a PAT on the plugin page is the working path. That's a Grok Bot host bug, still open: cursor/plugins#251. GitHub's connector is PAT-only. The Authenticate button tries OAuth GitHub does not support, so you get "didn't provide a sign-in link." Don't keep hitting it. But it worked before I updated my fine grain token...

• 
  The Oracle (@scientist1q) reported 35 minutes ago

  when my Oura ring detects a cortisol spike from a GitHub Actions failure, Hermes (Fable 5.1) detects it and sends a 900 word root cause analysis, Hermes dispatches the work to my 12 Grok Bot employees, The Chief of Operations bot approves the fix while im watching rezero

• 
  Dr Milan Milanović (@milan_milanovic) reported 36 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.

• 
  Ifebuche Omeke (@omeke_NC) reported 36 minutes ago

  Providing compute, storage, networking and managed services in the cloud. Terraform. Bicep. CloudFormation. Pulumi. They all solve the same problem: Defining and provisioning infrastructure as code. GitHub Actions. Azure DevOps. GitLab CI. Jenkins.

• 
  Priyanshu Bhati (@buildwithpb) reported 42 minutes ago

  @CryptoWendyO @chainlink 30% error rate on github replies sounds like a recipe for accidental flame wars. good luck with the cleanup.

• 
  trulite (@trulite007) reported 46 minutes ago

  @Qromerolauro @mkliku @radius_browser Like a simple example would be have a list of my urgent GitHub issues and start an agent for it . Or a dashboard in which buttons start investigating issues. Of course I just need the webpage to be able to access radius tools. I m thinking secure way is an extension

• 
  Joshua Okolo (@joshuaokolo_) reported 47 minutes ago

  we made @sgl_project and @vllm_project scheduler config changeable on a live server. no restart, weights never leave the GPU. - 15ms to change a concurrency cap, queue limit, prefill size, or schedule policy, measured on H100, RTX PRO 6000, B200 - 2s (SGLang) / 8–10s (vLLM) to resize the KV pool with weights resident (formerly a 1–7 min redeploy) - zero dropped requests across every run, both engines github below

• 
  Vigneshwer Ramamoorthi (@vigneshwer_ram) reported 48 minutes ago

  I keep thinking the “Android moment for robots” won’t come from a humanoid with the best walking demo. it’ll come when some cheap-enough piece of hardware gets into thousands of developers’ hands and people stop waiting for the manufacturer to decide what the robot is for. Zeroth just launched Bridge in China: 88 cm, ~13 kg, two-finger grippers, open motion-control APIs + SDKs, mocap/VR integration, and an OpenBridge ecosystem where developers can publish robot skills. the Geek Edition is reportedly ¥8,888. that price is the part that caught me. because once capable embodied hardware starts approaching laptop money, the experimentation surface changes completely. I want the Raspberry Pi phase of robotics. weird university projects. teenagers making terrible robot apps. researchers abusing the hardware for things it was never designed for. 500 GitHub repos implementing slightly different ways to pick up a cup. the robotics industry is understandably obsessed with getting robots into factories. I’m almost equally interested in what happens when we get enough robots onto developers’ desks

• 
  Russ Wonsley (@RussWonsley) reported 48 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?

• 
  Straggler Liu | AI & Semis (@StragglerLiu) reported 49 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.

• 
  Ravi Prasad (@ravikp7) reported 53 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.

• 
  Anime0t4ku (@Anime0t4ku) reported 54 minutes ago

  @c_hri_s Github issues are not closed. Mahbe refresh your webbrowser.

• 
  Enfantshustle (@Ownerthoughts) reported 55 minutes ago

  Honestly, I always thought bots like this were some kind of magic for the elite, but here everything is broken down step by step. However, after reading it, one main question stuck in my head: how realistic is this for an average person who has no coding experience? I get that there's a GitHub and all that, but for me, just "running a script" is practically a heroic feat. Here's another thing that bothers me. The article does a great job explaining the architecture, but I still don't understand how much all of this will actually cost in the end. Besides Solana transaction fees (which, by the way, get absolutely insane during peak hours), you also have to pay for each Grok API call per token. The article says that for each approved token, it takes three model calls, and one of them is the expensive grok-4. If the bot scans thousands of launches per day, I'll just burn through my entire deposit just paying for the API without even buying anything. Maybe the author knows — is it actually possible to turn a profit after these expenses, or is this just a hobby for those with an unlimited subscription? Also, regarding Grok Bot as the "orchestrator" — it sounds cool in theory: describe the task and it does everything itself. But in practice, as I understand it, this still requires your account to be constantly online and have access to your wallet. And if it decides to buy some scam token at 3 AM that passed all the checks, I'll only have myself to blame. The article correctly mentions risk management, but this "trust" aspect is what scares me the most. In short, the idea is fire, but for me, this post feels more like a warning than a call to action. There are just too many things you have to keep in mind to avoid getting rekt. Although, maybe if you try it with really tiny amounts, it could be an interesting experiment. Author, if you're reading this — could you please make a separate post about the real, live results once everything is actually running, not just on paper? I'm really curious!

• 
  Ghaith Jelassi (@GhaithJ) reported 59 minutes ago

  @github I need help with support ticket #4718335 Issue not been resolved for 2+ months. Any help is appreciated. Thanks.

• 
  John X Meta (@John4MetaX) reported 60 minutes ago

  @bashy_io I think one of their route is down. Same here. GitHub and Flutterwave API not accessible on Starlink

• 
  Shaun Patrick SteWaRt (@ShaunStewart) reported 1 hour ago

  @annalea_l Honestly, I really want to see this. You have to understand: I am the type of person who can learn and do anything on the fly at a high level, and I just threw myself into this whole developer and engineering world. When I first started learning all this stuff, I already knew what I wanted and how I wanted it to operate, regardless of what I saw on X or what was considered possible. Before I even started following hundreds of developers and learning about harness engineering, mechanical engines, persistent memory, and all that, I put my brain on a GitHub repo. Everything is shared across every machine, every cloud entity, and every AI. I am not even technically an engineer or a developer, and I don't actually write code. But once I started following all these people and saw all the problems they complain about, I thought: this isn't even my trade, and I have already solved all these little things everyone says are impossible. Why aren't people talking about developing your harness more and making things more mechanical, instead of just arguing with a terminal all day long? Whenever I see articles people post on X, I run them by Claude or Grok and ask, "Should we implement this?" I have hundreds of bookmarks, but every single time they tell me, "Nope, your brain's better. Nope, your harness is better." I can never find anything built better than what I have or what I am currently working on. The brain and harness setup is basically like a mini operating system. All that said, I am really looking forward to seeing something I can use that goes far beyond what I am already doing. I definitely want to see your end product, it sounds very interesting.

• 
  Yash (@dewyashtwts) reported 1 hour ago

  recently integrated Resend into @supercodeai review so founders get PR alerts with real risk context I'm amazed what we found out when we put @coderabbitai / @greptile through the same PR: 1) coderabbit / greptile: - stamped it “low risk, mergeable” (4/5) clean - forgot context from the last PR - no tests suggested, no safety checks - zero memory of previous regressions 2) supercode review on the exact same PR - flagged a real vulnerability in the diff - noticed i’d pushed credentials into `.env.example` - pulled in history from past PRs + explaining how this change could affect and break them - downgraded it to "medium risk, fix before merge" state - attached concrete fixes + patches scoped by severity this is the difference between 'LLM summarizer for github' and an actual swe agent that cares about your production