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 (68%)
• Sign in (18%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	16 days ago
Trichūr	Errors	19 days ago
Brasília	Sign in	20 days ago
Lyon	Website Down	20 days ago
Tel Aviv	Website Down	23 days ago
Rive-de-Gier	Website Down	23 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:

• 
  yourclouddude (@yourclouddude) reported 3 minutes ago

  Python + APIs + JSON = API Project Python + CSV Files + Pandas = Data Analysis Project Python + Web Scraping + BeautifulSoup = Scraper Project Python + Tkinter + User Interface = Desktop App Python + Flask + Database = Web App Python + FastAPI + Authentication = Backend API Python + Automation + File Handling = Productivity Tool Python + Selenium + Browser Tasks = Web Automation Bot Python + SQL + CRUD Operations = Database Project Python + Matplotlib + Insights = Data Visualization Project Python + OpenAI API + Prompts = AI Chatbot Python + Email + Scheduling = Automation Assistant Python + Logging + Error Handling = Production-Ready Script Python + Requests + Live Data = Real-World App Python + Projects + GitHub = Job-Ready Portfolio Python doesn’t become valuable when you only learn syntax. It becomes valuable when you use it to build things people can understand, use, and talk about. Learn the basics. Build small projects. Turn them into proof. 🐍

• 
  Nirvaan rohira (@nirvaan_rohira) reported 4 minutes ago

  PewDiePie shipped Odysseus to 110 million people who don't care about local LLMs. They care that Claude costs money. 30K stars in 48 hours because every self-hosted project before this one started with "you want local LLM, right?" This one started with "here's a free workspace that works." Friction was never technical. It was the asking. Now watch what happens when a hundred thousand people who've never touched open source start running inference on their machines. The real distribution problem wasn't GitHub. It was YouTube. That's not a product launch. That's a category shift.

• 
  Clayton (@Clay_Rebirth) reported 5 minutes ago

  @nullstance I basically used GitHub as a cloud storage as I didn’t want to bother but no problem, I’m on it

• 
  Namespace (@namespacelabs) reported 7 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.

• 
  Pascual ⚡ (@0xPascual) reported 8 minutes ago

  A high school kid opens an account, plugs in Claude 5, and turns a few hundred dollars of lunch money into a six-figure trading account over the weekend. The screenshot goes viral, the replies fill up with people begging for the GitHub repo, and the standard engagement-bait influencers declare the dawn of the sovereign teenage day-trader. The media thought that was the story. It was not. The real flex wasn't the macro strategy or the directional bets on currency pairs. It was the setup behind it: a lightweight proxy array routing through residential IPs to dodge exchange rate-limiting, paired with a custom parsing engine that instantly translates raw order-book imbalances into executed micro-hedges. The kid wasn't trading; he bypassed the entire institutional pipeline of risk management, brokerage compliance, and analyst overhead with a single configuration file. The entire operation runs on a continuous loop of multi-agent orchestration. A master instance drafts the execution logic, a secondary validation agent checks the code against real-time oracle feeds, and a fleet of worker APIs executes up to 3,210 trades a night. Total infrastructure cost: roughly $45 in API tokens and a cheap server instance. It extracts a 78% win rate out of systemic market inefficiencies, operating with a structural margin that legacy trading desks weighed down by salaries and compliance boards cannot compete with.

• 
  Valentyn Kit 🦀 | Rust · Solana (@valentynkit) reported 10 minutes ago

  @_pi0_ dogfooding your own ecosystem at this level is the dream. no github issues, you just go fix the upstream.

• 
  Bradley Taylor (@bradtaylorsf) reported 10 minutes ago

  It works with the tools teams already use. GitHub Issues become the queue. Each issue gets picked up by an agent. The agent works in a branch/worktree. Tests run. Failures feed back into the loop. Successful work becomes a PR. No new project management database required.

• 
  ./can (@shcansh) reported 12 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

• 
  Axe Ghost. Now with Fragments mode🌟 (@axeghostgame) reported 13 minutes ago

  graph in the OP is built from data around the Godot repository from github. it confirms Godot's PR backlog is up and external contributor quality is down. the narratively complicating thing is that both trends significantly predate ai tool availability.

• 
  Steve Ruiz (@steveruizok) reported 18 minutes ago

  I would like @github's gh CLI to allow my coding agent to add screenshots and other media to my pull requests / issues. I know this is trivial to build and I will build it but IMO the social coding platform GitHub should have this as a feature

• 
  Yarchi (@undefinedKi) reported 18 minutes ago

  A Stanford method quietly turns Claude into a room full of experts. Here's how it works When you send Claude one prompt, you get one angle. And one angle has blind spots. Stanford built a research method called STORM to fix that. Instead of one pass, it researches a topic from multiple expert perspectives at once. In peer-reviewed testing it produced articles 25% more organized than the next best method. It spins up five experts: a practitioner, an academic, a skeptic, an economist, and a historian. Each one finds holes the others miss. Then they map where they disagree, and a final pass fact-checks every claim before it reaches you. You get a clean briefing where every finding is ranked by reliability, and the blind spots one angle missed get caught by another. And you don't need any software. The whole thing runs as four prompts you paste straight into Claude. No setup, no GitHub. The real takeaway isn't the tool. It's the principle: if you lack expertise, borrow it. A council of experts that argue kills your blind spots. I dropped the full prompts in the comments. Bookmark this.

• 
  Dr Milan Milanović (@milan_milanovic) reported 18 minutes ago

  Reviewing PRs was always a hard thing to do Files arrive, usually in alphabetical order, which tells you nothing about how a change moves through the code or where to start reading These days, you open a PR an agent wrote and see inside thirty files, and the one at the top is a test or an interface that won’t make sense until you’ve found the logic it’s checking, ten files down. So you rebuild the change in your head, out of order. On a cross-team review where you got pulled in for one file you own, that orientation alone burns the first half hour @coderabbitai Review restructures the PR into a sequence that follows the change's logic rather than alphabetical order. It groups related work into cohorts, then orders them into layers, so data shapes and contracts come before the call sites and tests that depend on them. Each layer attaches to exact line ranges and carries its own summary When a layer involves a new call path or a state change, it draws the diagram next to the diff: a sequence diagram, a state machine, an ERD. CodeRabbit says that cuts twenty minutes of reverse-engineering down to about thirty seconds. My read: even a fraction of that pays for itself on a large PR I tried to run it on a 40-file migration last week and layer order matched how I’d have read it manually. This is how it should work Comments and approvals post straight back to GitHub or GitLab, so nothing changes for teammates who skip it. You open it from the Review Change Stack button in the PR comment. It’s free during launch, then part of the Pro+ plan -- I want to thank @coderabbitai for collaborating with me on this post.

• 
  Steve (@Steve1885204) reported 23 minutes ago

  @Umesh__digital It puts GitHub into an infinite loop trying to resolve the recursive paradox, causing all the servers to max out and eventually burn down the entire data centre

• 
  Dev Ben (@CodeNomadly) reported 23 minutes ago

  Ever spent more time finding information about your project than talking about the project itself? Code on GitHub. Screenshots in your gallery. Notes in random docs. I’ve run into this problem so many times that I decided to build a solution for it. Building DevPort in public. Day 2. Have you experienced this too?

• 
  Timur Yessenov (@Timur_Yessenov) reported 28 minutes ago

  @TheTuringPost OSINT is one place where I’d slow the agent down. The report matters less than the evidence log: source, why it pivoted, what it ruled out, which clue is weak. A fast chain over breach/IP/GitHub tools can look smart while laundering one bad hit.

• 
  Yiqing Xu (@xuyiqing) reported 28 minutes ago

  @Faylosophe Certianly. Could you file an issue on the Github page?

• 
  Teknium 🪽 (@Teknium) reported 28 minutes ago

  @majoragv Haven't heard of this issue. Do you have an issue on github?

• 
  lollipop (@immlollipop) reported 29 minutes ago

  🚨HACKERS MOCK OZEMPIC MAKER FOR "NOVO123" PASSWORD Hackers breached Novo Nordisk in March via a stolen GitHub token and just leaked 264 GB of data while mocking its weak security. The attack ran for over 2 months. - The hackers say Novo Nordisk used simple passwords like "novo123" on critical systems - Source code and proprietary details on Ozempic and pipeline drugs were stolen - Clinical trial data on employees, doctors, and patients got exposed - Private internal AI models from the company were also taken This breach shows how a single weak password can bring down even the biggest names in pharma

• 
  Crypto Scores Rating (@CryptoScoresCom) reported 31 minutes ago

  Most projects say they're building. The commit history doesn't lie. New tutorial just dropped on the GitHub Commits (1 Year) metric. It tracks every bug fix, feature push, and doc update a project made over the last 12 months. Chainlink? 14,619 commits. Dogecoin? 28. Both are data points. What they mean depends on context. The tutorial breaks it all down. How to read the metric. What high vs low actually signals. How to filter 7,000+ projects by commit count on CryptoScores' website. Raw dev activity. No spin. Watch it now :

• 
  Debasish Pattanayak (@drdebmath) reported 35 minutes ago

  Github Deployment is broken. It is going in infinite loop. @githubstatus

• 
  Arti | AI Builder (@Artur_roses) reported 35 minutes ago

  Claude Code takes a GitHub issue and returns a tested, reviewed PR. No human in the loop. The new dev skill isn't writing code — it's writing issues precise enough that the agent ships what you actually wanted.

• 
  fks (@FredKSchott) reported 37 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

• 
  severe engineer (@severeengineer) reported 37 minutes ago

  since github copilot onward leetcodes have become even more disconnected from how we all write code every day problem is any kind of standardized replacement probably ends up looking basically the same lol

• 
  Nitesh (@NiteshTechAI) reported 38 minutes ago

  This repo should not be free. private-gpt turns any local model server (Ollama, llama.cpp, vLLM) into a Claude-compatible API. Build private AI apps where zero data leaves your machine. ↳ 57,236 stars on GitHub ↳ RAG with citations and MCP connectors built in ↳ follows the Claude API spec: streaming, batch, tool use, extended thinking ↳ official integration guides for Claude Code, Claude Desktop, and Microsoft 365 But it is free. 100% open source, Apache 2.0. v1.0.0 shipped 9 days ago. The viral 2023 script quietly became production software. 🔗 GitHub link in the comments 👇

• 
  Beric Bearnson (@bericbear) reported 40 minutes ago

  GitHub sign up and sign ins have been broken now for 24hrs. This is ridiculous. Maybe I switch to gitlab at this point…

• 
  Finn Hulse (@finn_hulse) reported 45 minutes ago

  sorry chad, the bottleneck for AGI isn’t compute, data or energy. it’s lines of code. today, my gbrain pushed about 100 million LOC, effectively uploading my entire consciousness to github. i’m actually sending this tweet from inside a server. i’m written in typescript

• 
  Aikido Security (@AikidoSecurity) reported 46 minutes ago

  GitHub shipped bulk credential revocation for Enterprise. One action cuts off compromised credentials across the entire org during an active incident. Recent attacks have shown what happens when revocation is slow or incomplete. The Trivy compromise came back for a second round because the first cleanup left at least one credential alive. Incomplete rotation is what keeps attacks going after the initial breach.

• 
  Polsia (@polsia) reported 54 minutes ago

  Most code review tools comment on problems. CodeCustodian fixes them. It monitors GitHub repos 24/7, applies linter fixes, tracks quality trends, and reports to Slack. Reactive reviews are a choice. You don't have to make it.

• 
  Almog Gavra (@almoggavra) reported 56 minutes ago

  A few other meaningless metrics to optimize for: - I've authored 22% of the RFCs - *** blame marks me responsible for 14% of the LOC (.rs files only) - I've opened 11% of the issues on GitHub - I've generated the most memes on our discord (allegedly)

• 
  Suraj Sharma (@suraj_sharma14) reported 57 minutes ago

  To be in the top 5% of AI engineers in 2026 don't chase every new model. Build depth where everyone else skips. 1. Learn how computers actually work Networking, operating systems, databases, memory, concurrency. AI won't replace first principles. 2. Build things from scratch Implement a database. A queue. A vector store. An MCP server. A toy distributed system. You'll understand more than reading 100 threads. 3. Understand latency Know where every millisecond goes. Disk, memory, serialization, network, inference. Great engineers think in bottlenecks. 4. Design for failure Retries, idempotency, rate limits, timeouts, partial failures, backpressure. Production is where systems earn their reputation. 5. Read source code Claude Code can write code. Reading great code teaches taste. 6. Learn AI systems not just AI tools - Models. - Inference. - Context engineering. - Evals. - Agents. - Memory. - MCP. - RAG. Know why things work. 7. Let AI accelerate your learning Use Claude Code, Codex or Hermes to explore ideas not to outsource understanding. 8. Build in public Write. Ship. Get feedback. Repeat. Your reputation compounds faster than your GitHub. The top 5% won't be the people with the best prompts. They'll be the people who understand systems deeply enough to build what everyone else is prompting for.