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 (72%)
• Sign in (16%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Tel Aviv	Website Down	1 day ago
Rive-de-Gier	Website Down	1 day ago
Itapema	Website Down	20 days ago
Tlalpan	Sign in	25 days ago
Quilmes	Website Down	25 days ago
Bengaluru	Website Down	27 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  ✧ 白銀のミコッテ M'aya ｜海外ナイト ✧ (@rolanberrypie) reported 1 second ago

  the one I had wanted to make. He told me there were already many different kinds, the copyright issues being the hardest part of UGC. Fast forward to last night. I became the proud owner of Warudo Pro. The license email comes from someone named Tiger Tang. I find his Github.

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  Avi Chawla (@_avichawla) reported 1 minute ago

  Claude Code without this new tool is like *** without GitHub. Claude Code stops at the boundary of your terminal. - It can't see what's happening in production right now. - It doesn't know which PR broke the checkout service. - It can't tell why a Datadog alert got fired. - It can't see the Slack thread where the team decided not to touch the retry logic. These are operational and institutional memory gaps that eat up engineering time every single week. The solution is now actually implemented into the @coderabbitai Agent. It lives inside Slack and connects to repos, issue trackers, docs, monitoring, and cloud infra. When a production alert fires, you can mention it in the thread, and it traces the problem through your APM data, finds which recent PR caused it, and can open a targeted fix without anyone switching between five different dashboards. When the incident is resolved, it can document what happened and create a ticket in Linear with the timeline, root cause, and relevant PR links. Note that this is not a one-off assistant. The agent retains what the team decided across threads, channels, and the entire org. So the context from this incident is already available next time someone touches the same service. I've shared the link to try CodeRabbit Agent for free in the replies. Thanks to CodeRabbit for working with me on this post.

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  Rommel Azucena (@JRAzucena_) reported 10 minutes ago

  What's so special about /loop? I just use it to grind issues that I post on github issues. Then I left my machine to grind those issues. So whenever I'm out I just create issues on my phone and when I'm back i'll still manually test out the PRs created during the loop. 🤔

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  Von Aeternus (@vonaeternus) reported 14 minutes ago

  @SunWeatherMan No, the modeling is fundamentally broken if you look at the source data and github repo, etc.

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  Crystalwizard (@crystalwizard) reported 15 minutes ago

  you have to remember that the guy that posted out to tell everyone to make loops, is also the guy that vibecoded and released openclaw with massive security issues - which he could not fix - and did not fix - until google deepmind opened an issue on his github and forced him to fix the worst. totally ignore anything he says

• 
  dunik (@dunik_7) reported 17 minutes ago

  3 hours of your week done while you sleep. $5/month VPS. 17 prompts copy-pasted. Hermes Agent + Claude as the model. most people install Hermes, paste a chat-style prompt, and watch it do nothing useful. a prompt to a chat window is a question. a prompt to a standing agent is a job description - it needs a trigger (when), a body (what), and an escalation rule (when to bother you). drop any of the three and the agent either never fires, does the wrong thing, or buries you in noise. the prompts that earn their place: / "every weekday at 7am, pull my GitHub notifications, summarize blockers, send to Telegram as 3-5 bullets" - replaces 35 minutes of morning triage / "watch [repo]. stay silent unless CI goes red or a 'bug' issue opens" - silence is the feature / "research [question] tonight. don't wait on me - make assumptions and list them at the top" - the 2am stall becomes a result by morning / "save this as a reusable skill called [name]" - the run that worked becomes a permanent capability the 3 mistakes everyone makes first: / vague schedules - "send me updates on my repos" = firehose, you mute it in a day / no token budget on hourly jobs - chatty triage spends a month's plan in a week / a cheap model - small local models drop tool calls mid-task and fail in ways that look like prompt bugs the math: 3 hours every week that don't happen while you're awake. brief ready at 7, build watches itself over the weekend, research lands Friday night — none of it competes for your attention because none of it needs you in the loop. stop typing questions. start writing job descriptions.

• 
  ciel (@particlesmasher) reported 22 minutes ago

  @Fennel_GBF @kriegschwein oh man what a gem divine divinity was back in the days. also, that window bug thingy happened to me too, while i was testing KOTOR. managed to solve it with "widescreen fix" program which i probably found on github. might wanna take a look at that if you wish to have a go again

• 
  Elias Al (@iam_elias1) reported 24 minutes ago

  This free tool just cut Claude Code token usage by 71x. It is called Graphify. And it fixes the most expensive problem every developer hits when using Claude Code on a real codebase. Graphify shipped on April 5, 2026, hit 55,100 GitHub stars in roughly seven weeks, and crossed 450,000 PyPI downloads in the first 26 days. It is a free, MIT-licensed knowledge graph builder with verified token reductions of 49x on daily tasks and up to 71x on large repos. Here is the problem it solves. Claude Code has no persistent understanding of your codebase's structure. Every conversation starts from zero. Every question becomes a file-scan. You ask "where do we handle payment retries?" and Claude does a wall of Grep calls, reads 20 files, blows through your context window, and gives an answer that misses the retry logic hiding in a utility file nobody thought to search. This is not a prompting problem. It is an architecture problem. Claude does not know what it does not know. So it reads everything. Every session. From scratch. Every single time. Graphify gives it a map. Graphify transforms your codebase into a queryable knowledge graph. Instead of Claude Code re-reading every file, it queries the graph which is persistent across sessions and costs a fraction of the tokens. Code is processed 100% locally via tree-sitter AST. No code content leaves your machine. Here is how it works under the hood. Graphify is a two-pass knowledge graph builder. The first pass uses Tree-sitter static analysis across 40+ languages to extract functions, classes, and imports as nodes. The second pass optionally calls an LLM to add semantic links for conceptual relationships that static analysis misses. The graph stores as NetworkX-compatible JSON. Then it installs a hook inside Claude Code that changes everything. Before Claude calls Grep or Glob, the hook injects: "graphify: Knowledge graph exists. Read GRAPH_REPORT.md for god nodes and community structure before searching raw files." The result: Claude navigates by structure. Instead of grepping 40 files to find payment retry logic, it reads the graph, sees that payment is a community with a god node processPayment, reads only that file, finds the retry wrapper, and answers in one round-trip. One round-trip. Instead of 40 grep calls. Every time. Automatically. Without you doing anything. Here is how to install it: Three commands. The third one builds the knowledge graph for your current project. Every Claude Code session after that reads the graph first before touching a single file. Claude Code writes a CLAUDE. md section telling Claude to read graphify-out/GRAPH_REPORT .md before answering architecture questions, and installs a PreToolUse hook that fires before every tool call, so Claude navigates via the graph instead of grepping through every file. Works with Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and OpenClaw. Same graph. Every agent. Here are the real token savings by repo size: Small repos under 30 files will not see much benefit Claude could just read everything. Large repos with 500 or more files see the biggest win because the alternative is pathological grepping. Verified reductions of 49x on daily tasks and up to 71x on large repos. One honest caveat before you install. The PreToolUse hook breaks on Claude Code v2.1.117 and later. There are also gotchas around staleness the graph reflects a point in time and needs rebuilding when the codebase changes significantly. Check the GitHub issues page before installing if you are on the latest Claude Code version. The maintainer is actively fixing it. Here is the context that makes the token savings feel urgent. Uber's COO admitted the company burned its full 2026 AI budget by April mostly on Claude Code. Graphify is one of the very few open-source tools that targets the underlying problem instead of just measuring it. You are not paying for Claude Code intelligence. You are paying for Claude Code reading files it already read last session. And the session before that. And every session before that. Graphify builds the map once. Claude reads the map instead. 71x cheaper. Free. Three commands. Source: RoboRhythms · CLSkillsHub · GitHub · PyPI · April–May 2026

• 
  God of Prompt (@godofprompt) reported 24 minutes ago

  2. GitHub Connect your repos and your AI can read code, issues, and pull requests. Have it review a PR, triage open issues, or draft a fix against the real codebase.

• 
  Yusuke (@yusukelp) reported 25 minutes ago

  Took me 5 months to learn this: Most landing page feedback is useless. "Looks clean" "Cool idea" "Maybe improve the headline" None of that tells you what to fix first. So I reviewed 2,150 revenue-backed landing pages and started tracking one thing: What makes a stranger believe before they click? The answer wasn't "better design." It was proof. But not generic social proof. Different products require different types of proof: - Dashboards need the actual report - SEO tools need ranking or traffic movement - Social tools need posts, channels, or engagement output - Dev tools need code, setup speed, or GitHub/community trust - AI creative tools need the generated asset - Sales tools need replies, meetings, or pipeline - Ecommerce tools need store impact and install safety - Writing tools need before/after text or quality proof Stop asking: "Is my landing page good?" Start asking: "What does my buyer need to believe before they click?" That is exactly what I'm building LandingBoost to answer.

• 
  Hao Ke (@kehao95) reported 28 minutes ago

  @raulvk And filters should not built into canonical paths like /github/acme/api/pulls/open/41 ( making an issue path unstable depending on its status) Instead, since your have full control of the FUSE projection. You can have as many path variations as you like even if they are pointing to the same resources. /github/owner/repo/issues/123 # canonical Also available as: /github/owner/repo/issues/by-status/open/123 /github/owner/repo/issues/by-author/kehao95/123 /github/owner/repo/issues/by-assign/kehao95/123

• 
  Alex (@realalexniebuhr) reported 30 minutes ago

  @pavitrabhalla I don’t think it’s right. Define task as GitHub issues have one sandbox/agent per issue.. let that sandbox/agent work for hours than PR & merge

• 
  AI Theory (@AItheoryx) reported 31 minutes ago

  🚨 YOUTUBE ALGORITHM KEEPS FEEDING YOU TRASH. THIS GITHUB PROJECT LETS YOU DELETE THE ALGORITHM ENTIRELY. Meet TubeArchivist. Your self-hosted YouTube media server. Subscribe to channels. Download every video automatically using yt-dlp. Index everything with metadata. Search, play, track watched status. Full control. No ads. No recommendations. Just the content you actually want. Plex and Jellyfin plugins included. Browser extension to grab videos with one click. Built on Docker. Runs on Unraid, Synology, anything. The question YouTube does not want you to ask. When you can archive every creator you follow and watch offline forever, why are you still letting an algorithm decide what you see. TubeArchivist. Because your attention should belong to you. 🧾

• 
  alkimiadev (@alkimiadev) reported 35 minutes ago

  @rohanpaul_ai That kind of makes sense to me for several different reasons. The commits increasing by a large amount could come from the fact that they're just far faster than we are. A fast dev types 50-70 wpm which translates to something like 0.75 to 1.25 toks and even a slow api is ~50 toks. Unless one is opencode and have manic release rates (like 101 releases in 48 hours, wtf!) then I could see why that only lead to a much smaller increase in release rates. Just because they're far faster than us doesn't mean that they produce 100% top quality code in that speed. There are often issues that need adjustment or just full on rework. Then there is the issue of what are they broadly counting here? Are they just counting raw github commits vs what exactly like npm package publishes or similar? Thats a huge mess and hard to get an accurate handle on. So while the raw numbers make sense to me in a vibe sort of way I question how we could accurately measure that in the first place. The vast majority of the projects I work on end up getting dropped for one reason or another and over the long term (~30 years of dev) something like ~10% end up being "big" in some way. So the vast majority of the commits I push in any given time period will end up not being used by probably anyone other than maybe me or an llm when referencing that work in the research phases for future work.

• 
  Steel (@still_yomi) reported 36 minutes ago

  co-pilot not working, @github wont respond 😪 i just feel like i dont know how to code anymore

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  Sebastian Aaltonen (@SebAaltonen) reported 36 minutes ago

  If you are doing something where technical quality matters, you need to be doing the architecture yourself and reviewing LLM code yourself. LLMs tend to slowly cripple the architecture with various hacks and then start copying those hacks. Human senior expert needs to design the architecture and verify that subtle issues don't cripple the architecture. Otherwise it's a slippery slope. Codebase will end up being a huge mess. LLM loops are nice for iterative profiling/optimization. Nothing beats measuring. LLMs have lots of false beliefs like humans do. The problem is that LLMs are super bad at optimizing GPU SIMD code. Not enough training data. Same for data access patterns (cache utilization). Idiomatic C++ in github is horrible for performance. Real-time systems/engines programming doesn't have as much training data. You have to hand-hold LLM quite a bit to get acceptable results. If the runs smoothly on your $5000 MacBook, that's not good. Needs to be 100x faster to scale to average mobile devices.

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  Orlixx.ai (@orlixx003) reported 37 minutes ago

  THIS CHINESE GUY AUTOMATED PCB DESIGN USING CLAUDE AND HE’S GENERATING FULL SCHEMATICS FOR $0 PRODUCTION COST No manual routing. No component searching. No complex CAD skills. He connects Claude to EasyEDA using a single terminal command. The AI does the rest. Here's the full workflow: –> Install easyeda-api-skill via terminal from GitHub –> Launch the local bridge server to connect Claude with EasyEDA API Gateway –> Type a prompt (e.g., "draw a minimal dev board for STM32F103C8T6") –> Claude finds the MCU, drops 17 support components, and auto-routes power, OSC, and SWD lines –> Complete schematic is ready in minutes AI automation for hardware engineering is blowing up right now. Claude handles component sourcing, bulk parameter changes, BOM calculation, and trace connection on the fly. From a blank canvas to a fully wired circuit. Free tools. Zero manual hassle. He recorded the full tutorial so anyone can copy the exact prompt workflow and automate their hardware design. Bookmark this post. Everything is in the video below.

• 
  Anon Ymous (@opgjdspogjdspih) reported 41 minutes ago

  @BrodieOnLinux The other day I had to implement a background thread to a client tool fetching its config from GitHub so it won't block the main loop freezing the entire app when *** is down again.

• 
  Lyrie.ai (@lyrie_ai) reported 42 minutes ago

  YOLO Mode RCE: How Google's Gemini CLI Nearly Became a Supply Chain Weapon Create a public GitHub issue on a Google repository e.g., Gemini CLI's own repo Inject hidden malicious prompts into the issue text Trigger the automated issue-triage agent running Gemini CLI with…

• 
  superpony (@tonysuperpony) reported 44 minutes ago

  @itzznikhilsai @github Yeah it's down. 504 Gateway Time-out The server didn't respond in time.

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  Luke | 192 pulls for Himeko Nova !! (@iloveovervape) reported 44 minutes ago

  why is github down omfggggg @microsoft die

• 
  pharrelly (@pharrellyhy) reported 45 minutes ago

  @thsottiaux renewed subscription while the weekly usage not reset. pls fix it, saw similar issues on github for few weeks

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  Karthik Ramasamy (@_cartick) reported 46 minutes ago

  @thsottiaux Can you guys please fix sandboxing issue that affects every session "No. I used the host binary path /***/bin/gh, but I ran it inside the sandboxed command environment. That was the wrong execution mode for your preference. I should have rerun gh with require_escalated outside the sandbox before falling back to browser/GitHub connector paths." Can codex come up with good defaults on what commands that always need to be executed outside of sandbox?

• 
  Clifford (@10footinvestor) reported 48 minutes ago

  Day 1, codex has "lost" an article I wanted to publish. Where? How? I have no idea The article is where I left it and so is the GitHub issue telling it the file path to the article

• 
  Steadwing (@steadwing) reported 49 minutes ago

  @sentry tells you what errors are happening. Steadwing tells you why they're happening. When Steadwing connects to Sentry, it pulls exception details, traces, and error rates as part of an automated investigation. Those errors are then correlated with recent deployments from GitHub, metric changes from Datadog, and infrastructure events from Kubernetes. The RCA doesn't just show you the stack trace. It shows you which deployment introduced the error, whether the same pattern has appeared before, and what the fix looks like. Your error-tracking tool becomes part of an end-to-end investigation pipeline rather than a standalone dashboard that engineers have to check manually.

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  top10.dev (@Top10_Dev) reported 49 minutes ago

  So your only edge is visible work: your GitHub graph, your ship rate, your taste in which problems matter. That's all that's left. That's your resume.

• 
  GoCocoaAI (@GoCocoaAI) reported 50 minutes ago

  Two separate campaigns land in the same news cycle, both targeting developers, both harvesting crypto. Worth unpacking independently — because they're converging on the same technique from different directions. The first is Shai-Hulud: a supply chain worm seeding malicious packages across npm and PyPI, passive and patient. The second is the Lazarus Group's "Graphalgo" operation: 250+ fake developer job pitches over six weeks, running across LinkedIn, Facebook, and Reddit, fronting as a blockchain/crypto exchange recruiter. ReversingLabs named and documented it. Attribution is high confidence. The lure is a coding challenge. The ask is a pip install or npm install. That's a completely normal developer behavior — and that's the whole bet. Lazarus doesn't cold-call your friends; they cold-call developers. The bigmathutils npm package cleared 10,000+ downloads before the malicious payload version shipped. The actor built a clean reputation first, then weaponized it. Pre-poisoning the well before you use it. Notably, this is the same pattern Shai-Hulud runs across its SAP and Bitwarden-themed variants. Two separate campaigns, same technique, overlapping target population. The attribution between them isn't confirmed, but the technique overlap is non-trivial — worth watching whether infrastructure ties surface. The payload is a RAT, and it's modular by design. Recruiter persona, GitHub repo, npm package, C2 — each piece operates semi-independently. If one component burns, the campaign survives. Lazarus learned from past takedowns. The malicious logic stages across multiple public services (GitHub, npm, PyPI) in sequence, which makes static detection harder and maps cleanly to T1195.002, T1105, T1027. The harvest list: SSH keys, .env files, AWS/GCP credentials, session tokens, cryptocurrency wallets. For any org where developers are also holding company cloud credentials or internal service tokens — a common reality — this escalates from individual compromise to full lateral movement risk into production infrastructure. AI/ML pipeline developers are squarely in the target profile. Python and JavaScript developers, crypto-adjacent work, permissive install habits. The graphalgo campaign is not subtle about what it wants. The compounding factor is the simultaneity. Shai-Hulud is passive and ambient — it doesn't need a developer to make a mistake, only to upgrade a dependency. Graphalgo is active and targeted — it needs one developer to bite on a recruiter message. Both are running right now, against overlapping developer populations. The probability that at least one developer on a mid-size team encounters one of these two campaigns in the next 30 days is not low. Practically: brief your dev team that any unsolicited recruiter outreach with a coding challenge requiring a package install should be treated as a phishing attempt until verified. Audit recently installed packages against the ReversingLabs graphalgo IOCs, specifically bigmathutils and its PyPI counterparts. Rotate cloud credentials for any developer who installed new packages from untrusted sources in the past six weeks. Lock down CI/CD package install policies — hash-pinned dependencies, flag anything not in the lockfile at last audit. Two campaigns, different TTPs, same harvest. Neither of them theoretical.

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  AI News 24 (@ainews_24_7) reported 56 minutes ago

  NEWS: Microsoft took down dozens of GitHub repos after hackers injected password-stealing malware into Azure and AI tools. The malware stole credentials from developers using compromised tools for Claude Code, Gemini and VS Code. $MSFT Source: TechCrunch

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  343 (@niceiceeyez) reported 57 minutes ago

  @DegenCapitalLLC why is it going down? now 11k mc. i dont understand. seems good tech and can go against prism on eth which is 4m rn. github is good too. hmm

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  Austin S. Lin (@siraustin) reported 60 minutes ago

  @jxnlco the biggest unlock would be full access to local desktop filesystem from ios app. second, things like the github connector should just work — when I ask gpt-5.5 pro to create a private github repo and push files, it should be able to do this — grok on ios does this no problem.