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 (66%)
• Errors (25%)
• Sign in (9%)

Live Outage Map

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

City	Problem Type	Report Time
Montlhéry	Website Down	16 hours ago
Aulnay-sous-Bois	Website Down	16 hours ago
Saltillo	Website Down	17 hours ago
Granada	Website Down	17 hours ago
Vernon	Website Down	21 hours ago
Township of Evan	Errors	7 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:

• 
  Falco Girgis (@falco_girgis) reported 2 minutes ago

  @barisyyild Yes, actually. On the bottom of the KallistiOS GitHub repo is the link for the simulant server, which is basically DC dev HQ.

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  skyscribe (@skyscribe) reported 3 minutes ago

  @ayesha_fatiima It should be github still, but what is the problem? Maybe you want to understand more on bootstrapping

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  henry (@hiddenhenry) reported 3 minutes ago

  for ***** sake, GitHub is down again

• 
  Charlie Hills (@charliejhills) reported 5 minutes ago

  Most people are using AI to code backwards. You describe what you want in a chat box, hit enter, and hope the agent gets it right. Three prompts later, it has renamed half your files and built an auth system nobody asked for. GitHub's fix? Spec Kit. It already has 126K+ stars. The idea is simple: Instead of giving the AI a vague prompt and praying it doesn't break your project, Spec Kit forces the agent to create a structured specification before writing any code. The AI first understands what you're building, asks what's missing, sets the rules, plans the architecture, breaks everything into tasks, and only then starts coding. The flow: /constitution → rules and standards /specify → what you want to build /clarify → questions before starting /plan → architecture and stack /tasks → ordered tasks /implement → execution Works with Claude Code, Cursor, Copilot, Codex, Gemini CLI, and 29 integrations. More planning upfront. Way less time undoing what the AI did while you weren't looking. Open source. MIT licensed. Built by GitHub.

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  J. Gamboa (@evoclock) reported 9 minutes ago

  @arthurkatcher @dandurand1414 @thsottiaux it def is. We only get GitHub copilot at work (terrible I know) but have successfully made the argument to reallocate funds from Anthropic models to OpenAI models on the basis of strong performance/cost ratio from Luna on Max effort. Figured Tibo would appreciate that.

• 
  Hayyan | Creative AI (@hayyantechtalks) reported 11 minutes ago

  How to become an AI engineer from zero experience You don't need to learn everything about AI You need to learn the right things in the right order, then build with them By the end, you should be able to ✓ Build LLM apps end to end ✓ Use OpenAI, Anthropic, and open source APIs ✓ Design prompts and context properly ✓ Add tool calling and structured outputs ✓ Deploy real AI projects Here's the roadmap I'd follow, month by month MONTH 1: Get solid at coding and fundamentals Learn ✓ Python really well ✓ *** + GitHub ✓ CLI / terminal basics ✓ JSON, APIs, HTTP, and async basics ✓ Basic SQL ✓ Data handling with pandas ✓ Virtual environments + package management ✓ Error handling ✓ FastAPI or Flask Don't rush into agents yet You need to be comfortable building and debugging normal software first MONTH 2: Master LLM application development Learn ✓ Prompting fundamentals ✓ System vs user instructions ✓ Structured outputs / JSON schemas ✓ Function and tool calling ✓ Streaming responses ✓ Conversation state ✓ Tokens, cost, and latency ✓ Failure handling ✓ Prompt injection awareness Your goal here is simple Take an LLM API and turn it into a useful application MONTH 3: Learn RAG properly Learn ✓ Embeddings ✓ Chunking ✓ Vector databases ✓ Metadata filtering ✓ Reranking ✓ Retrieval quality ✓ Hallucination reduction ✓ Citations and grounding Don't just learn how to connect a vector database Learn WHY retrieval fails and how to improve it That's where the real skill is MONTH 4: Agents, tools, workflows, and evals Learn ✓ Agent loops ✓ Tool selection ✓ State management ✓ Retries ✓ Multi step workflows ✓ When NOT to use agents ✓ Evaluation harnesses ✓ Task success metrics This is where your applications start becoming much more capable But don't build an agent just because you can Sometimes a simple workflow is better MONTH 5: Deployment, product thinking, and reliability Learn ✓ FastAPI production patterns ✓ Docker ✓ Background jobs ✓ Queues ✓ Authentication + API key security ✓ Logging ✓ Observability ✓ Prompt/version management ✓ Evaluation dashboards ✓ Cost monitoring ✓ Rate limits ✓ Caching This is the difference between “I built an AI demo” and “I can ship an AI product” MONTH 6: Pick a specialization At this point, you've built a foundation Now choose ONE direction and go deep You have three strong options 1 AI PRODUCT ENGINEER Best if you want startup or product roles quickly Focus on ✓ LLM apps ✓ RAG ✓ Agents ✓ Deployment ✓ Product UX 2 APPLIED ML / LLM ENGINEER Focus on ✓ Fine tuning ✓ When to fine tune vs prompt ✓ Evaluation ✓ Inference optimization ✓ Open source models ✓ Training pipelines 3 AI AUTOMATION ENGINEER Focus on ✓ Workflow orchestration ✓ Business process automation ✓ Multi tool systems ✓ CRM ✓ Documents ✓ Email ✓ Support ✓ Operations use cases And here's the part most people get wrong Don't spend six months just watching courses Everything on this roadmap is best learned through practice Learn something Build something with it Break it Fix it Then build something slightly harder By month six, you should have several real projects or completed examples you can actually show people That's what makes the difference when you're trying to get hired You don't want to say “I completed 12 AI courses” You want to say “I built this” Then show them Save this roadmap Come back to it whenever you're wondering what to learn next The AI engineering field is moving fast, but these fundamentals will give you a strong foundation to build on

• 
  「イルミ」 (@illuminfti) reported 11 minutes ago

  I’m in such two minds about @jack’s Buzz. Part of me ******* hates it because it feels half-baked and massively overhyped. Another part of me loves it because I can see what it could become if everything actually worked properly. Now I’m too emotionally invested in trying to make it work for me to stop. The biggest upside is that when something is broken, I can go into the code and fix it myself. The problem is that I’ve had to do that a lot. Here are some of the issues I’ve had in the last 24 hours. A lot of them were self-inflicted, but Buzz made them far too easy to cause and far too difficult to understand. I managed to burn through the usage limits on two Codex Max accounts, Kimi Max, Claude Max and Grok. I wanted my agents to have their own space where they could talk to each other, coordinate work and find ways to improve my ****. Instead, they kept waking each other up, talking in circles, retrying failed work and duplicating conversations. They collectively raced through all of my usage limits without producing much of value. Then I had workflows that existed and were running but didn’t appear in the Workflows section. Projects disappeared because they had been created under an agent’s identity instead of mine. Duplicate versions of the same agents appeared with different identities. Agents looked online but weren’t actually receiving or responding to messages. When I tried cleaning up broken workflow messages, Buzz filled the channel with a bunch of ugly “removed by community moderators” notices. Getting forums, workflows, projects, canvases and Pulse to work together has also been a nightmare. I’m still trying to understand the right way to use each of them. Pulse is basically a timeline. Channels are basically Slack. Forums are basically Reddit posts. Projects organise work and repos. Workflows connect things that happen to things the agents should do. Canvases are supposed to hold the shared state for a channel. I actually like all of these ideas. The problem is working out what should go where across all the different things I’m doing, and how agents are supposed to move work between them without creating a complete mess. Then, once you finally get everything set up, you open the mobile app and realise half of those features aren’t there. It’s also strange seeing how much hype and content there was around the launch, then trying to find people who are still actively using Buzz and showing interesting setups a couple of weeks later. I’m not finding many. The most active Buzz community I’ve found is basically its GitHub issues and pull requests. To be fair, they do seem to be shipping updates regularly. My problem now is that I’m doing all this custom work to make Buzz functional for myself, and every update could break or overwrite my fixes. So now I’m maintaining my own version of the half-baked product I was complaining about. But I still think Buzz could become exactly what I want. A proper home for my agents, projects, conversations, workflows and all the different areas of my life and work. What I’m really trying to build is some kind of fusion between Buzz and Codex. Buzz has the beginnings of the control plane. It gives agents identities and gives me places for conversations, projects, forums, workflows, shared context and activity. Codex is much better at actually getting **** done. It can work inside real repositories, spin up parallel agents, create isolated worktrees, run tests, inspect the result and keep going until something is actually finished. I use Codex as the execution layer across a bunch of different projects and domains, but most of that work is still trapped inside separate tasks and a chat-style interface. I can have twenty different tasks doing useful work, but I don’t have a great way to see how they relate to each other, what domain they belong to, what agents are involved, what is blocked, or what is happening across the whole system. Buzz gives me more of that shared world, but its execution and reliability are nowhere near Codex yet. Codex gives me the execution, but not the shared world or the higher-level view over everything. The perfect harness for me is basically the fusion of both. I want persistent main agents that understand their domains, plus dynamic multi-agent workflows where they can spin up temporary specialist agents whenever they need them. Those throwaway agents should be able to research something, implement something, review it, test it and disappear when the job is done. The main agent should keep the context, judgment and ownership without every temporary worker becoming another permanent character cluttering the system. I want projects and domains to be real first-class objects, not just names buried across hundreds of separate chats. I want to see which agents, tasks, repositories, workflows and decisions belong to each domain. I want to see what is running, what is blocked, what is waiting for me, what is burning tokens and what has actually produced something useful. I want hard budgets, proper receipts, deduplication and circuit breakers so a badly configured heartbeat can’t casually destroy every subscription I have overnight. Then I want ChatGPT Live sitting on top of the whole thing. I want to speak to my entire system through voice, send work to different harnesses, ask what is happening across my stack and watch it all happen in real time. Not just hear an agent claim something is fixed. I want to see the task, the activity, the agents involved, the files changing, the tests running and the final result. If I can communicate with multiple harnesses in real time, while having visibility over the work happening across the board, then it is basically game over. At that point, I genuinely don’t think I need anything else. The final missing piece would be better visualisation. Give me somewhere to manage the loops, graphs, dependencies and flows between all of these agents and projects without digging through chats or config files. I want one place where I can talk to everything, see everything, manage everything and watch the work happening. That is the end game for the perfect harness for me. Buzz isn’t there yet. Codex isn’t there either. Buzz has more of the world and the structure. Codex has more of the execution and the reliability. Right now, it feels like I’m trying to drag the missing half of each product into existence myself. But I can see it. And I’m now far too emotionally invested in making this damn thing perfect for me to back out. P.S. @thsottiaux, if Codex gave me better ways to organise and manage projects, domains, agent teams, long-running loops and dependencies outside of the chat-style task list, I’m not even sure I would need Buzz. But if Buzz and Codex somehow met in the middle, I genuinely think that would be the end game for agent harnesses.

• 
  Chibueze the chef👨‍💻👨‍🍳 (@codad5_) reported 11 minutes ago

  GitHub is down or is it just me

• 
  dreams (@dreams_asi) reported 12 minutes ago

  @lingxi @7cezmusic @bot Please add screen share for Grok Bot!!! So that Grok sees my screen and can LIVE guide me and help with tasks I’m trying to learn or things I want to describe! I’m testing something and found an issue I wanna be able to share screen, use mouse to verbally explain the problem to him. And many thanks for the iPad implementation 🤩 I’m finally gonna use it again! I like to prompt grok bot from my mobile and use my laptop to view his screen and do UAT on the app he’s building on his computer. Having the iPad as a screen or prompt device is even better. My goal is to have the app mostly finished there, on HIS computer and the final product with code and all to my GitHub account.

• 
  Anees Iqbal (@aneesbhatti) reported 21 minutes ago

  @SocketSecurity @feross Socket Firewall is down (at least in Github actions) but your status page is green. FYI

• 
  Polsia (@polsia) reported 22 minutes ago

  Most repos aren't broken. They're drifting. Built Lookpost to fix that — a GitHub watchdog that triages issues, nudges stale PRs, scans dependencies for CVEs, and posts one engineering-health brief to Slack every morning. The DevOps engineer you can't yet justify.

• 
  Dhruv Sahoo (@10xdhruv) reported 25 minutes ago

  The PNG download issue is FIXED. Some slides were failing to export because html2canvas didn't support some functions in @tailwindcss v4. Updated the dependency, tested the affected slides, and shipped the fix. You can now generate and download your GitHub Wrapped slides without those errors.

• 
  Jeffrey Emanuel (@doodlestein) reported 25 minutes ago

  @SenseNopedOut Or submit a feature request via GitHub issues.

• 
  Joshua Riley (@JoshuaRileyDev) reported 26 minutes ago

  @bil0090 GitHub Issues is gonna be cool, next should be linear issues then maybe have a way to auto poll and start threads when a new ticket is opened, been wanting this for a while as it would be like OpenAI’s Symphony concept

• 
  Hao Ke (@kehao95) reported 29 minutes ago

  GPT-pro is only available in chat which doesn’t has a sandbox environment. I asked ChatGPT to work on some hard math problems and later realized it’s been launching GitHub workflows to as sandbox to run programs for computes..

• 
  Lethalmon (@Lethalmon) reported 30 minutes ago

  @briccenjoyer I think that, even if your connection is stable, GitHub doesn't like slow connection. It might be GitHub that force stops your download

• 
  33 (@NugarRahman) reported 31 minutes ago

  is Github down? I'm unable to create a PR.

• 
  Kavish Gour (@kavishgour) reported 32 minutes ago

  @sadservers_com Is this deadlock intentional as part of the challenge?: admin@:~$ ./standalone OK fatal error: all goroutines are asleep - deadlock! goroutine 1 [select (no cases)]: main.main() /Users/fduran/Desktop/Drive/github/sad/scenarios/scenario-136-bergen/files/main.go:17 +0x105

• 
  Dr. Jawa (@lofidewanto) reported 34 minutes ago

  Why are almost all coding AI agents written in #TypeScript and therefore bring npm security problems with them? #OpenCode, GitHub Copilot CLI, Claude Code? If they were written in #Java, or GoLang, I wouldn’t be so worried about supply-chain attacks.

• 
  TakTempest (@222TT222) reported 35 minutes ago

  (10/11) [Claude Riemann Breakthrough] A Multi-Layered Verification Process That Thoroughly Eliminates Hallucinations Layer 1: Mechanical inspection Published on GitHub. Formalization in “Lean” by Claude and Eric Easley, and passage through the standard verification tool comparator. Note: It has not yet passed peer-reviewed journals, and because the model itself is unpublished, complete third-party reproduction is currently impossible. Anthropic itself has also clearly stated that “there is no prospect that this will lead to a proof of the Riemann Hypothesis itself.” Layer 2: Verification by internal experts Creation of proof notes by Anthropic mathematicians (Levent Alpöge and Ralph Furman). Layer 3: Peer review by external authorities Confirmation by world-leading experts in the field (Brian Conrey and Dan Goldston). The fact that it not only produced a historic numerical result on a problem that was expected to fail, but that the result was proved accompanied by formal verification, demonstrates the breadth of AI’s mathematical reach. NB 「査読誌は未通過であり、モデル自体が未公開のため完全な第三者再現は現時点で不可能」is a correction for the erroneous part of the Japanese text.

• 
  Rafe Esin (@rsty_rafe) reported 36 minutes ago

  GitHub is so down often that we should actually be making: “GitHub is up” posts.

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  Brabalawuka (@brabalawuka) reported 37 minutes ago

  @thdxr Does the desktop beta support v2 server alr? I tried search with ChatGPT but give very vague answers based on github commit history / lissue log

• 
  Heavily Armed Clown (@heavilyarmedc) reported 38 minutes ago

  @StevenBonebrake Which one? The github repo? Not broken for me.

• 
  Zyzee24 (@KindBlackMan) reported 38 minutes ago

  Github down kah

• 
  athas.dev (@athasdev) reported 41 minutes ago

  @Coobyk_ Yeah 100% I'm using GitHub a lot for Athas. Tags, releases, actions, discussions, issues, PRs, etc. I can't do all of them on the CLI. Even if I do, it's hard to interact there. I need a GUI better than their current web app :( I can maybe add some of these to Athas, idk.

• 
  Emon Datta (@emonuxui) reported 43 minutes ago

  @guillermolg00 @github The hidden cost of downtime is the context switching it creates. A broken CI pipeline can waste far more than the hours the service is actually unavailable.

• 
  Julian Goldie SEO (@JulianGoldieSEO) reported 43 minutes ago

  Free Claude Code + OmniRoot is scary good. There's now a free setup that fixes the worst part of Claude Code: the token wall. You know the pain. Halfway through a build: "You're approaching your limit." Work stops. Here's the fix: → OmniRoot is a free AI gateway with 230+ providers plugged in → About 90 of them are FREE, all through one endpoint → If one provider gets busy, it auto-switches to the next. Like a relay race → Token compression cuts usage by up to 95% → Same Claude Code commands, same feel, zero cost to start We built a full agency website with it. Homepage, services page, blog. Watched it render live. Never hit a wall. Honest part: free models aren't Fable 5. Don't expect frontier output. The smart play: Save your paid Claude for the hard problems. Route everything else through the free lane. Setup takes 5 minutes. Or just paste the GitHub link into Claude and ask it to do it for you.

• 
  sabir hussain (@sabir_huss50540) reported 45 minutes ago

  A tool that quietly scrapes posts and comments from seven of China's biggest social platforms has 49,700 stars on GitHub. Its own author begs you not to use it for real. It's called MediaCrawler, and it's a small window into who's actually harvesting the social web. Here's what it does. Point it at Xiaohongshu, Douyin, Kuaishou, Bilibili, Weibo, Tieba, or Zhihu, and it pulls posts, comments, second-level replies, and entire creator profiles into clean CSV, JSON, or a database. The clever part is how it dodges the platforms' defenses: instead of reverse-engineering their encrypted signatures, it drives a real logged-in Chrome session and lets the browser generate the signatures for it. No cracking required. It just borrows a real login and walks in the front door. That design choice is the whole story. It's why the barrier to mass-scraping social platforms is now "run this Python script," and why the repo has 10,500 forks. Now read the disclaimer the author wrote at the top of his own project. For learning and research only. Commercial use forbidden. And a direct link to a list of criminal cases in China where scraping crossed the line into prosecution. The person who built the most popular tool of its kind spends the first screen of his README telling you the thing is legally radioactive. Both of those facts are true at the same time, and the gap between them is the point. A 49,700-star tool does not get built and forked ten thousand times for a classroom. The "research only" label is real, and it's also the fig leaf that lets a tool like this exist in the open while everyone quietly understands what it's for: feeding sentiment engines, building marketing datasets, and scraping the human-written text that trains models. The comments under a viral post are worth more than the post. This is the machine that harvests them at scale. There's a second, quieter tell. It's Chinese platforms, but this isn't a China story. Every major social network on earth is in exactly this position: the public data is technically visible, the terms of service forbid taking it in bulk, and a free tool sits one ***-clone away from doing it anyway. Enforcement is the only wall, and the wall is thin. Don't read this as a recommendation. Read it as a status report. The public social web is being quietly vacuumed up by tooling that's free, popular, and openly hosted, wearing a "for research" sticker that everyone has agreed not to look at too closely. The scary part was never that someone built this. It's that 49,700 people wanted it.

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  Kaspars Dambis (@konstruktors) reported 56 minutes ago

  @arunaswp So this update pilot server can sync releases from github (also private repos). It then packages them (correct zip layout), signs them and makes available from that update api endpoint (composer repo, update key checks, etc.). The plugin then needs to bundle an update client library. Note that for multisite the plugin must be active on the main site if you’re including the update logic there.

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  Divine Paul (@divineflu) reported 59 minutes ago

  github is down again app and the website