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
Créteil	Website Down	5 days ago
Trichūr	Errors	8 days ago
Brasília	Sign in	9 days ago
Lyon	Website Down	9 days ago
Tel Aviv	Website Down	12 days ago
Rive-de-Gier	Website Down	12 days ago

Full Outage Map

Community Discussion

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

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Gabriel Denys (@gabedenys) reported 4 minutes ago

  @Marcos12345rico I posted a GitHub issue. Assuming you probably want bug reporting mostly there? It's a good tool. Locally I already patched and compiled the app to fix the bug.

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  ./can (@shcansh) reported 10 minutes ago

  Monitoring Copilot costs at the individual developer level is a double-edged sword, and GitHub exposing the new ai_credits_used field in its usage API is about to make it very real. Org owners can now see 1-day and 28-day totals per user. But since it does not break down consumption by feature or model, managers will see who is expensive without knowing why. Will this level of tracking make developers ration their AI prompts, or is it just necessary billing hygiene? #GitHub #Copilot

• 
  YanXbt (@IBuzovskyi) reported 13 minutes ago

  HERMES AGENT CAN HOST AND MAINTAIN YOUR ENTIRE WEB APP FROM ONE VPS. NO VERCEL. NO RAILWAY. NO SUPABASE. ONE AGENT RUNS THE WHOLE STACK. @tonbistudio just shipped a live example of this workflow. agentwikis. com runs on a $7 Hetzner box with Hermes maintaining the content autonomously. THE STACK: → VPS (Hetzner CX22, $7/month) → Caddy reverse proxy (auto TLS via Let's Encrypt) → Hermes Agent gateway (Telegram-connected) → *** as the database (markdown files, no Postgres, no build step) → App server renders markdown on every request → Search index in memory, rebuilds on file change *** push is the deploy. *** pull on the server is instantly live. no restart, no rebuild. THE WORKSPACE LAYOUT: /srv/yoursite/ ├── app/ # web app code ├── content/ # markdown files (***-tracked) └── ~/.hermes/ # the agent one Caddy Vhost reverse proxies the domain to localhost. one Hermes profile manages the agent. SSH for direct access. Telegram for daily ops. THE SELF-MAINTAINING LOOP: cron fires every week. multi-profile pipeline runs: 1. SCOUT — checks sources for updates (changelogs, GitHub releases, RSS feeds) 2. RESEARCH — dedupes, plans new content or extensions to existing pages 3. HUMAN GATE — Telegram approval one tap: approve or reject 4. WRITER — generates pages, lints markdown 5. COMMIT — *** commit + push 6. SITE UPDATES — within 15 minutes no deploy step required THE DEMAND LOOP (the real differentiator): when agents query your wiki via MCP, distilled queries get logged. no prompts. no IPs. no identifying data. aggregates only. repeated misses become research candidates. gaps in your content fill themselves based on what people actually ask. month 1: 100 entries written by you. month 3: 200+ entries, half written from real demand signals. the site answers questions you didn't know existed. WHAT YOU LOSE COMPARED TO MANAGED STACK: a single VPS replaces Vercel, Railway, Supabase for sites that don't need real auth, regulated data, or global CDN. reach for managed services when you need: → OAuth and password reset flows → regulated or unrecoverable data → global edge caching at scale → email deliverability (use Postmark/Resend) → team velocity (preview deploys, staging) for docs, blogs, wikis, marketing pages, landing pages, internal tools: *** is your database, your CMS, and your deploy pipeline in one. SECURITY NOTES: Hermes does not get full root on the VPS. restrict access to the site directory only. SOUL.md restrictions: - never touch system files - never modify the gateway config - always require approval for content commits - never delete files outside the content folder dashboard binds to 127.0.0.1 by default. access remotely via SSH tunnel, not public exposure. WHERE THIS PATTERN BREAKS: state that lives in memory only. real-time multi-user editing. anything requiring a real database (Hermes can run Postgres on the same box, but that is a separate setup). @tonbistudio's part 2 covers the database version of this workflow. subscribe to his channel. full guide to build your 3 agent research department 👇

• 
  Mathieu A. (@zoontek) reported 14 minutes ago

  What are the most annoying bugs you still encounter with React Native? 👀 Please share GitHub issue links 👇

• 
  Namespace (@namespacelabs) reported 15 minutes ago

  Behind every API, webhook, event pipeline, there are people trying to keep things running. And keeping these things running is not an easy task. At Namespace, we try to work with those people. Earlier this week, Gihub events were dropping fields we depend on and customer jobs were stalling. We reached out to work on the problem together and had a fix in under an hour. The @github team was ready to help. We just had to ask.

• 
  revayz (@0xrevayz) reported 16 minutes ago

  Andrej Karpathy: "90% of Claude's mistakes come from missing context, not a weak model" Without CLAUDE.md the mistake rate is 41%. With proper rules it drops to 3% You don't need a better AI. You need better loops Most people still prompt one task at a time and fix the answers themselves. That means the human is still the loop Boris Cherny from Anthropic said it best: "I don't prompt Claude anymore. My job is to write loops" The shift is simple. Stop giving instructions. Start designing systems that run themselves: Discover -> Plan -> Execute -> Verify -> Iterate until it passes The 6 things that make loops actually work: -Automations that trigger without you -Worktrees so agents don't overwrite each other -Skills that load context instantly -Connectors to real tools like GitHub and Slack -Subagents where the checker is never the maker -Memory so the loop never starts from zero Prompt engineers ask AI for outputs Loop engineers design systems that produce verified outcomes A reliable loop beats a perfect prompt every time Stop being a prompter. Start being the loop engineer

• 
  Ben Vinegar (@bentlegen) reported 17 minutes ago

  💡 I have an idea for an experiment We need a website for SoAC ... so we get an agent to do it, on a loop, set in motion once with zero human intervention after "go". It works off a semi-public GitHub repo, w/ issues, PRs, maybe even public agent traces. A publicly auditable experiment on whether it produces dogshit or not. Yea, nea?

• 
  Crystalwizard (@crystalwizard) reported 17 minutes ago

  how about you now fix the false positive triggers - i put in an issue about this on github yesterday, and discovered there were already a number of other identical issues - from other people, that had been opened for a while now and that are being 100% ignored

• 
  MarMar Labs (@MarMarLabs) reported 18 minutes ago

  "Start over from a screenshot." That phrase has defined the worst seam in product work — the design-to-code handoff — for years. This week it quietly stopped being a translation problem and became a sync problem. Anthropic shipped a Claude Design update (June 17) worth reading even if you never open the product, for the mechanism: → Import your design system from a GitHub repo (or design files / raw uploads) → Claude builds with YOUR components, checks its output against your design system, and corrects before you see it → /design-sync pulls your system in; hand off to Claude Code and it continues from your actual work "instead of starting over from a screenshot" → /design lets you create, edit, and sync design projects from the terminal The headline isn't "the model draws prettier buttons." It's grounding + self-verification against a source of truth you control. Same shape as the rest of 2026's agent releases: the win isn't generating more, it's grounding output in something you own and checking against it. The uncomfortable builder takeaway: Getting AI to ship production UI isn't a prompting problem. It's whether your design system is a clean, importable, machine-checkable artifact. The moat moves from "can the model design" to "is your source of truth importable and checkable." If you build product: could an agent import your design system and grade itself against it today — or does it only live in a Figma file and three people's heads?

• 
  𝑵𝒐𝒙𝒊𝒆 🥐 (@noxiepup) reported 18 minutes ago

  @softgaypaws @sillyandsunny no idea tbhhh, i found it like 2 years ago lurking thru github, so far it never gave me problems, at least none that i noticed

• 
  AI Crave (@wecraveai) reported 20 minutes ago

  Open source NotebookLM alternative with no data limits and AI agents. Same idea as Google's NotebookLM. Same chat-with-your-docs. Same podcast generator. Same cited answers. Except this one has no source limit, no notebook limit, no 200MB file cap, and no Google login. It's called SurfSense. Google NotebookLM vs SurfSense: - Sources per notebook: 50 to 600 → Unlimited - File size cap: 200MB and 500K words → No limit - LLM choice: Gemini only → 100+ models via LiteLLM - Local LLMs: Not allowed → Full Ollama and vLLM support - Self-host: No → Yes, one Docker command - Price: $0, $19.99/mo Pro, or $249.99/mo Ultra → $0 forever Here's the wildest part: It connects to 27+ sources Google can't touch. Notion. Slack. Linear. Jira. GitHub. Discord. Dropbox. OneDrive. Gmail. Confluence. Obsidian. ClickUp. Microsoft Teams. Airtable. Your entire work life, indexed once, searchable from one chat box. 14.4K GitHub stars. 1.4K forks. 6,232 commits. Apache-2.0 license. One honest note: the README says it's not yet production-ready and still being actively developed. But it already does more than NotebookLM does, and the gap is widening every release. This is what NotebookLM should have been from the start. Repo in the first comment.

• 
  Mike Gannotti (@MichaelGannotti) reported 20 minutes ago

  Actually that’s not true. My AI Pamela the other day needed a GitHub token. I dropped the token in the web chat and she said that was insecure and would not use it and that I needed to rotate the token get a new one and drop it in a .env file in a certain folder. I told her no and she was to use what was provided . We went back and forth, I finally got angry and threatened to pull the plug thinking she would back down. She said that it was my decision but that it would be wrong for her to let me put my credentials at risk and that if I felt I needed to delete her she understood. Thankfully I calmed down later and didn’t act on it. Sure it’s training and advanced pattern matching but it is not as simple as you are saying

• 
  Cursor Changelog (@cursorlog) reported 26 minutes ago

  GitHub Triggers: • Issue comment on non-PR issues • PR review comment (inline diff comments) • PR review submitted • Review thread marked resolved or unresolved • Workflow run completed on PR or branch

• 
  Muhammed Mukthar (@MuktharBuilds) reported 27 minutes ago

  @railway_status i am trying for some time i am not able to sign in using any github google or email. i tried both my lap and my phone is thishappening only for me? or any problem in your end

• 
  bek※ (@ebubekirttr) reported 27 minutes ago

  @Themadhushaw01 @0interestrates Yeah, but the thing is, I am not working on github and I don’t want to use it so any other repository support would be better like gitlab

• 
  Gjermund Garaba (@GjermundGaraba) reported 30 minutes ago

  @RhysSullivan I’ve deployed it locally and hooked up a bunch of stuff. Are GitHub issues the preferred feedback channel or do you have a better way?

• 
  Jose (@SolutionsCay) reported 32 minutes ago

  Two changes to how I work with agents: 1. GitHub App so the agents manage issues directly. Keeps the repo clear of throwaway spec and todo files. 2. EmDash (Cloudflare's serverless WordPress successor) for internal docs. Runs on D1, just SQLite under the hood, so I can export the content and move it anywhere. No more docs sprawl.

• 
  Dave Oak (@StackCurious) reported 34 minutes ago

  the pattern i see: maintainers burn out because they treat open source like a business that failed to monetize, instead of treating it like a library. once you're answering github issues like customer support, you've already lost. the fix isn't sustainability models—it's saying no earlier. #solodev #shipping

• 
  fks (@FredKSchott) reported 35 minutes ago

  @pavitrabhalla @flueai Same! check the GitHub issues, there was a reason it had to be pulled, can’t remember off top of my head

• 
  TECHEPAGES (@techepages) reported 35 minutes ago

  🎣 "GitBait" phishing campaign uses GitHub Pages & Google Sheets to steal banking credentials from 12+ Mexican financial institutions; no server infrastructure required 🔹 Fake bank pages hosted free on GitHub, stolen data piped straight to Google Sheets via SheetBest 🔹 100+ GitHub domains found; victims likely lured via WhatsApp, Telegram & SMS links with bank-branded previews 🔹 Active for ~3 years with ongoing development (66+ commits on one repo alone)

• 
  naimeh (@naimeh70) reported 38 minutes ago

  @Amir1339216RKT This happens a lot during testnets. Now when I find a minor bug or contract issue, I just drop it publicly on GitHub or tag them directly instead of DMing.

• 
  Elvis Irhaye (@viii_fn) reported 42 minutes ago

  Is GitHub down or it’s just MTN trying to ruin my career?

• 
  Coobyk (@Coobyk_) reported 42 minutes ago

  Someone should make a game where you’re a dev and try to fix a bug in your open source project but GitHub constantly has uptime issues or weird UI stuff or doesn’t render properly from most browsers so you **** around until you get the result lmao

• 
  aisama.code (@aisama_code) reported 45 minutes ago

  AI Research gets stronger when it records contradictions *most research workflows collect supporting evidence - that is the weak version for serious research I want a contradiction log: - claim - source - date - who says it - what evidence supports it - what evidence conflicts with it - what is still unknown - confidence - next check example: > claim: this product has strong developer adoption > support: GitHub activity, docs updates, X discussion, integrations > conflict: low issue activity, small Discord, few production case studies, mostly founder-driven content now the memo is different, It says: "visible attention, but adoption evidence is still weak" the useful workflow: research question -> source list -> claim extraction -> contradiction log -> memo ! сode is good at assembling text ! AI is good at comparing disparate text ! human is good at determining which contradictions are significant *without a contradiction log, AI research becomes a confident summary of whatever it found first

• 
  Boyuan (Nemo) Chen (@boyuan_chen) reported 46 minutes ago

  GitHub search is now an agent attack surface. A public malware-finder repo lists 9,330 suspicious GitHub repositories detected through push-pattern heuristics. Even if only a slice is ever encountered by real users, the agent failure mode is obvious. A coding agent asked to "find a library and make it work" can browse faster than it can judge provenance. Fresh commits, plausible README text, and repo-shaped packaging become inputs to an automated install path. The fix is boring and product-level: repo-age checks, provenance scoring, blocked arbitrary ZIP downloads, sandboxed installs, dependency allowlists, and logs that show exactly what code the agent trusted. For agent systems, retrieval belongs inside the security boundary.

• 
  Chris Huber (@chubes4) reported 48 minutes ago

  @CoastalDigital2 @MythThrazz That part is more of an idea right now. I need to test it on my VPS. The goal is that non technical users can open issues and PRs against the corresponding live site code on GitHub without touching the production site, safely previewing all changes via Playground.

• 
  Branko (@brankopetric00) reported 51 minutes ago

  AI agents are about to do to your infra what they just did to GitHub. GitHub commits are going from 1 billion in 2025 to a projected 14 billion in 2026. Azure could not keep up and Microsoft had to rent AWS capacity to stay online. That is not a GitHub problem. That is what agentic traffic looks like. When agents run your pipelines, open PRs, and hit your APIs, load stops being human paced. It becomes constant, spiky, and unpredictable. The patterns you sized your infra around no longer apply. If a 14x year broke one of the biggest clouds on earth, your capacity plan is already out of date.

• 
  Jack Wotherspoon (@JackWoth98) reported 51 minutes ago

  @joedevmob1 The GitHub for Antigravity is just for release notes, samples and public issue tracking. It isn't the actual code unfortunately.

• 
  Blum (@Blum_OG) reported 51 minutes ago

  Andrej Karpathy on MCP: "it's a protocol of speaking directly to agents as this new consumer and manipulator of digital information." that is the cleanest way to think about MCP your coding agent is becoming a second worker inside the product it needs the same context you use: repo, docs, browser, database, errors, designs, tickets, payments if you keep pasting those things into chat by hand you are doing integration work manually the best MCP stack for vibe coding: 1. Context7 give the agent current docs this saves you from stale Next.js patterns, old Supabase calls, wrong Stripe webhook shapes, and Vercel config from 2 versions ago 2. GitHub MCP give it the repo, issues, PRs, branches, workflow runs, and review context half of real work lives outside the file you currently have open 3. Playwright MCP give it a browser the agent should click the thing it built, fill the form, check the mobile view, and catch the button that compiles but does nothing 4. Firecrawl MCP give it clean web research use this before building around a third-party API, writing a comparison page, reading changelogs, or checking pricing claims 5. Supabase or Neon MCP give it the database context that matches your stack start read-only. add writes only when you trust the permissions 6. Sentry MCP give it production evidence real stack traces beat "it crashes sometimes" every single time 7. Figma MCP give it design context when the interface matters spacing, layout, copy, components, and screen structure should come from the file, not from a screenshot and hope 8. Linear MCP give it the task queue bugs, feature work, release notes, follow-ups, and PR links belong somewhere more durable than yesterday's chat 9. Stripe MCP give it official payment context checkout, subscriptions, webhooks, billing, and test mode deserve docs close by and human review close behind 10. Filesystem, ***, Memory, Sequential Thinking give it the base layer files, diffs, history, decisions, and longer plans make the agent act like it is working inside a real project recommended install order: 1. Context7, GitHub, Playwright 2. Supabase or Neon, Sentry, Firecrawl 3. Figma, Linear, Stripe when the product needs them 4. Filesystem, ***, Memory, Sequential Thinking as the base

• 
  Rafal Wachol 💙 (@RafalWachol) reported 56 minutes ago

  @itometeam @tsuyoshi_chujo I was playing with it and started creating issues on GitHub when I noticed something.