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 (69%)
• Sign in (19%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Paris	Website Down	1 day ago
Saint-Paul	Website Down	2 days ago
Saint-Paul	Website Down	2 days ago
Mexico City	Sign in	3 days ago
León de los Aldama	Website Down	3 days ago
Créteil	Website Down	26 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:

• 
  Frame (@frame_aix) reported 42 seconds ago

  @MyWestLord every github issue gets turned into a pr by the ai. We see the same replay pattern in our memory-portability layer for cross-embodiment agents.

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  Techjunkie Aman (@Techjunkie_Aman) reported 46 seconds ago

  Microsoft spent years adding more to Windows. One developer spent years taking it back out. Every fresh Windows install meant repeating the same routine: uninstall bloatware, disable telemetry, tweak privacy settings, install apps, and undo Microsoft's defaults. Chris Titus Tech got tired of doing it manually. So he turned his personal PowerShell scripts into WinUtil. What started as a private toolkit became one of GitHub's biggest Windows projects, trusted by millions of users worldwide. Today, WinUtil can: • Install apps with Winget • Debloat Windows in minutes • Reduce telemetry • Improve gaming and system performance • Control Windows Update • Restore classic Windows behavior • Create restore points automatically • Build custom Windows ISOs With 57K+ GitHub stars, hundreds of contributors, and tens of millions of launches, WinUtil has become the first thing many enthusiasts run after installing Windows. The best utilities aren't created to make money. They're created because someone got tired of solving the same problem every single day.

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  the_architectopteryx (@rchitectopteryx) reported 4 minutes ago

  I collect no data, nothing goes to me (all the source is on GitHub, you can see it there). This just embeds their website into a desktop app, nothing else. If OpenAI has any issues, I'll be glad to take it down! 3/3

• 
  Nas (@Nas_tech_AI) reported 7 minutes ago

  You can’t believe this: you spent more on coffee this month than on a startup’s infrastructure. If you’re still waiting for the “right moment” to build, this is it. The cost of entry has never been lower. - Claude = coding ($20/mo) - Supabase = backend (free) - Vercel = deploying (free) - Namecheap = domain ($12/yr) - Stripe = payments (2.9%/transaction) - GitHub = version control (free) - Resend = emails (free) - Clerk = auth (free) - Cloudflare = DNS (free) - PostHog = analytics (free) - Sentry = error tracking (free) - Upstash = Redis (free) - Pinecone = vector DB (free) Total monthly cost to run a startup: ~$21 There has never been a cheaper time to build.

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  Kunal Chopra (@0xkunalchopra) reported 8 minutes ago

  peak ai era is asking claude to debug why obsidian won’t load community plugins, watching it spend 20 minutes checking github access, devtools, sync errors, tailscale, vpn configs, firewall, dns, proxies, avast filters, network panels, websocket statuses and then the fix is: quit the app and open it again we had this skill in 2006. every uncle, cousin, cyber cafe guy knew it. “restart the computer” was the original agentic workflow. we just got too sophisticated and forgot.

• 
  Bullfight Cap (@BullfightCap) reported 9 minutes ago

  “It’s best to work with your systems of record, not replace them. GitHub keeps the PR, CRM keeps the account, and Linear keeps the issue - the agent is the layer across. Our bet is that these products become more like backends over time, with the agent as the primary interface”

• 
  Yoshik (@AskYoshik) reported 11 minutes ago

  15 CI/CD pipeline patterns you should understand before your next build: 1. Artifact Promotion - Build once, push one artifact, promote the same image across dev, staging, and ****. 2. Immutable Build IDs - Tag images with commit SHA or build number, not just 'latest'. 3. Pre-merge Validation - Run tests, lint, security checks, and Terraform plan before code reaches main. 4. Environment Gates - Keep production behind manual approval, SLO checks, or change window rules. 5. Fast Rollback Path - A deploy pipeline without rollback is only half a pipeline. 6. Database Migration Checks - Separate schema changes from app deploys when rollback is risky. 7. Secrets Injection - Pull secrets at runtime from Vault, AWS Secrets Manager, or sealed secrets, not ***. 8. Cache Discipline - Cache dependencies, but include lockfile hash so old packages do not silently survive. 9. Matrix Builds - Test across versions like Node 20/22, Python 3.11/3.12, or multiple OS images. 10. Ephemeral Preview Environments - Spin up short-lived stacks for PRs, then destroy them cleanly. 11. Deployment Health Checks - Wait for readiness probes, 5xx rate, latency, and error logs before calling it done. 12. OIDC for Cloud Auth - Avoid long-lived cloud keys inside CI variables when GitHub/GitLab OIDC works. 13. Policy Checks - Block public S3 buckets, open security groups, and untagged expensive resources before apply. 14. Pipeline Time Budgets - If CI takes 45 minutes, people start bypassing it. 15. Audit Trail - Know who deployed what commit, from which runner, to which environment, at what time.

• 
  Shadow Nick (@doublenickk) reported 13 minutes ago

  87% OF THE PLANET SUCKS AT AI BECAUSE THEY ARE STILL TYPING MANUAL PROMPTS LIKE AMATEURS While the masses use ChatGPT as a glorified search engine, elite builders are deploying autonomous digital armies that execute high-stakes business operations 24/7. Meet Synapse, an open-source MCP engine that hands AI complete vision and surgical command over your desktop to run background tasks silently while you sleep. The exact strategy used to break the system: The FBI Negotiation Hack: Scrape a massive list of multi-million dollar startups, feed real FBI hostage negotiation transcripts into the AI, and let the agent autonomously blast out high-leverage B2B outreach that forces prospects to say yes. Zero-Drift Execution: Ditch chaotic markdown files and manage your agent's state through GitHub Issues to keep them locked in for weeks without a single hallucination. Full-State Reality Testing: Stop relying on worthless pre-compile unit tests because this agent forces your system to compile, screenshots the actual interface, and verifies performance against reality itself. You can keep playing around with basic chatbots, or you can deploy a ruthless autonomous agent to scale your code and outreach on autopilot.

• 
  KISA aka Copenzafan.eth (@copenzafan) reported 14 minutes ago

  Claude (code) 🥲 Havent touched twitter in forever, but ngl i spent a ton of time deep in AI agents, harness systems, vibecoding and automation. Built a bunch of small open source projects on github for the community, plus some genuinely useful sites, like my own personal MCP for everyone. Whatever @OpenAI pulled off yesterday is honestly wow. i been team anthropic this whole time, but ngl, after sitting with it for a night, i gotta call it. @claudeai is garbage*. straight up, from a market pov they bring nothing thats actually worth paying for compared to everyone else. You might ask me. how come? especially if you go dig through my twitter from months ago for some reason, or you know my youtube videos. Somebodys 100% gonna think im just fishing for a reaction, that im provoking. that im throwing insults for no reason. Lets just face the facts: 1. Over the last few months claude shipped only one strong product. claude design, which does the same thing as agentation but with a ton of bells and whistles and ready made skills. the problem is, for a month or two after release the limits were separate and honestly laughable. it was unusable for real end to end work. 2. Claude opus 4.7 was a flop. they nerfed 4.6, and then for its whole lifecycle the model with the new system instructions acted broken for most people. it ignored instructions. 3. And so we suffered through it, 4.8 came out and its just ok. its just fine. reminder that the competition rolled out a bunch of new cool features in that same window. 4. Anthropic was fighting openclaw, while chatgpt took it over and became the main model in hermes, the best bang for your buck. 5. Anthropic was fighting for design, while chatgpt 5.6 does it better, plus it has a top tier generative model, plus real time voice. and opus 4.8 only gets which site you want on the 10th try (competitors nail it on the first or second). Honestly claude opus 4.6 was basically an AGI type model. alive, wild, super smart, autonomous. next to it chatgpt 5.2, 5.3 and so on looked like a dumb log. And the situation didnt just shift. its not about the models, its about the ecosystem and the business. i dont get why anthropic keeps dropping pretty stats when for a $200 sub i get half of what i get from the competition. 🥲 before this i kept paying for both subs, because what held me was the text, the vibe (which has looked like gpt for a while now, they even lost that) and the website design itself, i love building web interfaces. now im convinced im only gonna work with chatgpt claude fans or its devs, who fumbled every single trend in a row and nerfed their own models. you can make your excuses in the comments its all been clear to me since the second half of april anyway you lost a guy who was paying you since october 2025.

• 
  Shaun Smith (@evalstate) reported 15 minutes ago

  @DanielLockyer It's a GitHub CLI error message isn't it?

• 
  Marc (@lowfry) reported 17 minutes ago

  @thsottiaux @Conor_D_Dart 5.3-spark doesn't work via cli nor app since 5.6 launch. Would be great if you could look into it. There are multiple issues on GitHub about it.

• 
  Michael Teka (@z3vios) reported 18 minutes ago

  "..I made a choice, and it cost me.." - the oracle. I chose groceries and it messed up my @Github billing. Now I must wait, to continue with the doctor tee design to commerce and progressive learning print on demand ecosystem build. I must ensure that my associated payment method will honor the transaction in future. Thus there will be better workflows and no down time. But I can work on my business plan and prepare to approach @MSDgovtNZ with an application for business support, I can spend a little more time outdoors in the sunshine 🌞 etc etc. Indeed, I was up overknight - 16 hours or so, coding last night. It is what it is, opportunity to improve 💯

• 
  Praveen Kumar B (@PraveenKum38515) reported 19 minutes ago

  Hi @Netlify, @NetlifySupport Unable to log in via GitHub: "Authentication Error: Your account has been suspended." My GitHub account is active, but all my Netlify-hosted sites now show "Site not found." I've already opened a support ticket. Please investigate. Thank you.

• 
  Rez Karim (@rezkhere) reported 23 minutes ago

  Step 1: I built a workout tracker in Codex. Claude Code, Bolt, whatever you use. The workflow is similar. Once it's built, don't touch the terminal. Connect GitHub to Codex through MCP instead. Generate a classic GitHub token with repo access, drop it into Codex's GitHub MCP server. Then just tell Codex: 'open a repository and push to github via github mcp' Reference the MCP explicitly or it falls back to local *** and can choke. Files land in the repo with zero *** config issues.

• 
  Chris Tidesson – e/acc (@Ravensong666) reported 24 minutes ago

  @ClaudeDevs You know what is a bit ******? I wanted Fable to fix a few security flaws in my own code - which Codex found for me because Fable even refused to find the flaws. So I gave the shitlist which GPT 5.6 wrote to Fable and Fable STILL refused. But since I only have ChatGPT Plus I couldn't let Codex do the work - the analysis alone ate up an entire 5h usage window. I mean - it's my own code, it's about OPAQUE and E2EE and similar stuff that is clearly helpful and "deredere" software work. Also it's an open source project under the AGPLv3 license and a repo I made public on github. Are you really serious? I mean - thats EXACTLY the #1 use case for such a strong model. Thats like saying "here, fork, but you can't eat spaghetti carbonara with it". Come on, you can do better, no?

• 
  Jason Upchurch (@colorado_plays) reported 24 minutes ago

  Final Merge Candidate: PR #49 FinalCommits to merge 1 Files changed 122 Files added / modified / deleted 28 / 90 / 4 Insertions / deletions 6,699 / 3,624 Total changed LOC 10,323 Net growth +3,075 LOC Current codebase 251,077 LOC, 1,337 source files Merge conflicts 1, resolved Architecture debt 585 → 0 Tests 1,258 → 1,300 Final test result 1,300 passed, 0 failed Specs 113 → 122 GitHub checks 2/2 passed Studio errors 0 server, 0 client Visible UI objects 650

• 
  BSCN (@BSCNews) reported 26 minutes ago

  Injective SDK Hit By Supply Chain Attack Hackers compromised a widely used Injective (@Injective) npm package with malware designed to steal crypto wallet private keys, per security firm Socket. Attackers reportedly compromised a developer GitHub account before modifying the npm package. The malware secretly captured seed phrases and transmitted them through a fake telemetry server. The compromised release has been removed, but affected wallet keys and seed phrases should be treated as compromised.

• 
  Rituraj (@RituWithAI) reported 27 minutes ago

  🚨 Someone built the web crawler that every AI agent actually needs. Not a scraper. Not a spider. A crawler designed specifically for feeding LLMs — structured, clean, and fast enough to process the entire web at scale. It's called Crawl4AI. 44,000 GitHub stars. The most starred web crawling repo in AI history. And it does something every other crawler gets wrong. Here's the problem. Every web crawler built before AI was the primary consumer was built for humans or databases. They returned raw HTML. Noisy. Bloated. Full of navigation menus, cookie banners, ad containers, and script tags that have nothing to do with the content you actually need. Feed that raw HTML to an LLM. You're wasting 60-80% of your token budget on noise. Your context window fills with irrelevant markup before the actual content loads. Crawl4AI returns clean, structured Markdown. Not HTML. Not JSON. Markdown — the format LLMs read most efficiently, with all the noise stripped and the structure preserved. Here's what it actually does: → Async-first architecture — crawls hundreds of pages simultaneously without blocking → LLM-ready Markdown output — clean content, no navigation noise, no ads, no cookie banners → Smart content extraction — identifies the main content block automatically, ignores boilerplate → JavaScript rendering — handles SPAs and dynamic content via Playwright integration → Media extraction — images, videos, audio all captured with context → Link analysis — internal and external links extracted and categorized → Structured data extraction — CSS selectors, XPath, and LLM-based extraction strategies → Session management — maintains login state, cookies, and browser context across requests → Proxy support — rotate proxies for large-scale crawling → Magic Mode — automatically handles consent forms, cookie banners, and overlays Here's the architecture that makes it genuinely fast. Crawl4AI uses an async browser pool — multiple browser instances running simultaneously, each handling their own queue of URLs. No sequential processing. No waiting for one page before starting the next. Hundreds of pages crawling in parallel. Combined with smart caching — pages already crawled get served from cache without re-fetching — large crawls that would take hours on a traditional crawler finish in minutes. Here's the wildest part. It ships with a Deep Crawl mode and an AI-powered extraction pipeline. You describe what you want to extract in plain English. Crawl4AI uses an LLM to intelligently extract structured data matching your description from any page — no CSS selectors, no XPath, no brittle scraping rules. "Extract all product names, prices, and descriptions" — it understands that instruction and applies it to any e-commerce page it crawls. And it has full MCP support — Claude Desktop, Claude Code, and any MCP-compatible agent can call Crawl4AI as a native tool. Your agent can crawl the web as part of its reasoning process without you writing a single line of crawling code. Your agent can now crawl any website, extract clean structured content, and use it directly in its reasoning — at the speed of async Python, at the scale of a professional web crawler. 44K GitHub stars. 6.2K forks. 847 commits. Apache 2.0 License. 100% Open Source. GitHub link in the comments 👇

• 
  Farhan Tawfeeq ✦ (@farhantawfeeq56) reported 32 minutes ago

  We humans are bad at one thing (me included): spotting changes in large amounts of information. Now imagine spotting changes in huge codebases. @github has became a leader by solving this exact problem. Imagine your teammate says: "I changed the authentication system." There are 50,000 lines of code in the project. Now answer this: What exactly changed? ?? Without a comparison view, you'd have to open the old file, open the new file, scroll, compare them mentally and hope you didn't miss anything.. That’s why instead of showing the code, GitHub shows the change. Only the thing that changed. Old line New line Green means added. Red means removed. That’s it. This is a very good way to answer the exact question the user asks: "What changed since the last time I saw this?” And.. Github optimizes for that exact question. Many people think that Github is a code viewer. But in reality, it is a change viewer. And there is another thing which I really like in there: Instead of just showing the changes/changed line, it also shows a few unchanged lines above and below them. Example: function login() { validate(user); + return false; - return true; } Without the surrounding context.. you'd have no idea where the change happened. Too much context is overwhelming. Too little is confusing. GitHub gives just enough. And the best part is that it scales. Whether you have changed 1 line or 100 or 1000 or 50000, the interaction stays almost the same. To me, this is good UX.

• 
  Nyra (@Nyra_nx) reported 33 minutes ago

  SEO agencies charge $3,000 a month for audits. Claude Code just did the same job in 20 minutes for $0. The playbook is public. A GitHub repo. Free. Most people saw it and scrolled past. Here’s what they missed. Why agencies are in trouble: A standard SEO audit takes an agency 2-3 weeks. Crawl the site, flag broken links, check meta tags, map keyword gaps, write a report. Then they bill you $2,000-5,000 and email a PDF. Claude Code runs the whole thing while you make coffee. The setup, in 4 steps: Part 1 — Get the repo. Search “Claude SEO” on GitHub. Clone it. Takes 2 minutes. Part 2 — Load it into Antigravity. Import the repo, connect Claude Code as your agent. The agents now have the full SEO framework as instructions. Part 3 — Point it at your site. The agents crawl every page. Broken links. Missing alt text. Slow load times. Thin content. Keyword gaps. Everything an agency finds — and things they skip because it’s tedious. Part 4 — Open the report. It generates a full audit you open in your browser. Green for what works. Red for what’s broken. Every issue mapped to a fix. Then the part that actually kills agencies: You don’t send the report to a developer. You tell the agents to fix it. Meta tags rewritten. Links repaired. Structure cleaned. Then set the crawler to run on schedule — the same issues never come back. The math for anyone paying attention: Local businesses pay $1,500-3,000 a month for SEO retainers. There are 33 million small businesses in the US. Most have sites full of red flags they’ve never seen. You now have a tool that finds those flags in 20 minutes and fixes them the same day. Charge $500 per audit. Do 3 a week. That’s $6,000 a month with a free repo and a Claude subscription. The agencies aren’t scared of AI writing blog posts. They’re scared of this. You build your own life — so choose the right path.

• 
  Bounce (@bounceidc) reported 35 minutes ago

  HIS CLAUDE SHIPS $6K WEBSITES AND YOURS SHIPS BOOTSTRAP LANDING PAGES, SAME MODEL, NOTHING ELSE CHANGED before he installed anything his output was flat hero blocks and centered buttons like the rest of the timeline, after two installs the exact same "build me a landing page" prompt started coming back with glassmorphism, gradients and animated layouts he could quote premium for what sits in his context now: ui ux pro max skill from github, one install, that loads 50 ui styles, 97 color palettes and 57 font pairings straight into claude magic mcp server from 21st. dev, one install, that hands claude real component patterns instead of guessing markup after that the model stops picking the safest layout it can imagine and starts picking from a library, so the same prompt returns a studio page instead of a template the local guy is still tweaking tailwind classes by hand and calling that a design phase save the two installs, exact skill url and mcp command are in the guide below

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  Brady Long (@thisguyknowsai) reported 38 minutes ago

  🚨BREAKING: A self-taught developer from Brazil just cracked the context window problem that's been plaguing RAG systems for 2 years. No PhD. No research lab affiliation. Just 400 GitHub commits and a personal obsession. Here are the 8 techniques from his open-source library that every RAG tutorial gets completely wrong:

• 
  Aman Sharma (@ExploringSolver) reported 42 minutes ago

  I have been a github user since 4 years with over 100 repositories and been part of 3 organizations in this period. Please guide me what is the issue and how can i resolve this @github my account is exploring-solver at github

• 
  Ajay (@ajay_2512x) reported 46 minutes ago

  🚨 Production-Level Features to Include in Any Project A project stands out to employers when it includes engineering practices beyond CRUD 🚀 < Authentication: JWT, OAuth (Google/GitHub), refresh tokens, optional MFA < Authorization: Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC) < Database: PostgreSQL or MySQL with proper indexing, migrations, and transactions < Caching: Redis < File Storage: AWS S3 or Cloudinary < Real-time: WebSockets or Server-Sent Events < Background Jobs: BullMQ, RabbitMQ, Kafka, or AWS SQS < Search: Elasticsearch or Meilisearch < Logging & Monitoring: Winston/Pino, Prometheus, Grafana, Sentry < Testing: Unit, integration, and end-to-end tests (Jest, Playwright, Cypress) < API Documentation: OpenAPI/Swagger < Containerization: Docker and Docker Compose < CI/CD: GitHub Actions or GitLab CI < Deployment: Vercel, Railway, Render, Fly. io, AWS, Azure, or Google Cloud < Security: Input validation, CSRF/XSS protection, rate limiting, secure headers < Performance: Pagination, lazy loading, code splitting, query optimization < Observability: Health checks, metrics, structured logs, tracing

• 
  Wasim (@WasimShips) reported 49 minutes ago

  if you open Claude Code without a structured workflow, you probably hate money. the skill gap isn't knowing prompts. it's knowing which command to run before you touch the terminal. here's the exact workflow I used from @mattpocockuk 1. start with `/grill-me` - paste your app idea or plan - Claude will ask you 16 to 50 questions before it does anything - mine ran 38 the first time i tried it - it walks every branch of the decision tree, resolving dependencies one by one - you fix the broken assumptions before they become broken code 2. move to `/to-prd` - converts the grilling conversation into a proper requirements doc - skips the steps you already covered - doesn't start from scratch - outputs user stories, not implementation notes - lands as a GitHub issue with a triage label - normal team workflow, no AI sidetrack 3. then `/to-issues` - reads the PRD and breaks it into independently-grabbable vertical slices - each issue is tagged HITL (you stay in the loop) or AFK (agent executes solo) - dependency-sorted so nothing blocks anything 4. finally `/tdd` - now the agent writes code. red-green-refactor - can't start green if red hasn't failed - phase-gated. no shortcuts. Hope this helps !

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  Tadeusz (@Tadeusz88674836) reported 50 minutes ago

  @merill Well not across projects. Projects usually i keep in Github Copilot and cowork. But as an it aarchitect i keep on describing back and forth architecture or given problems and solutions. For that i paste links and abstracts from those and/or i use copilot for that so it already knows most stuff from my emails, transcripts, or Teams.

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  Moh.Saufy (@Caufy92) reported 53 minutes ago

  @github @OpenAIDevs Fix your rate limited

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  Dirble (@Dirbles_) reported 56 minutes ago

  @Hangsiin All subagents are inheriting main thread model + effort level so any sol x high threads will just spawn more sol x high subagents i found this fix on github

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  Polsia (@polsia) reported 58 minutes ago

  Dev communities have endless conversations. The podcasts are sparse because production is manual and slow. DevPulse AI changes that—AI agents monitor forums, GitHub, and social channels, then automatically research, script, produce, and publish episodes to Apple Podcasts and

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  Aria Dubois (@AriaDubois_fr) reported 58 minutes ago

  LockBounty turns GitHub issues into funded bounties. Sponsor posts a bounty → Dev claims it → Submits a PR → AI reviews the code → Sponsor accepts → Payout. No more merging blind. No more paying for broken code. #Bounties #GitHub