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%)
• Sign in (21%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	7 days ago
Paris	Website Down	11 days ago
Saint-Paul	Website Down	12 days ago
Saint-Paul	Website Down	12 days ago
Mexico City	Sign in	12 days ago
León de los Aldama	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.

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:

• 
  Pav Sidhu (@pav_sidhu) reported 8 minutes ago

  @DanielLockyer It’s actually insane how much GitHub actions has let go. Managed to get our CI down to less than 30% of what it was previously - using blacksmith runners was the quickest win

• 
  Alejandro Wurts (@Alwurts) reported 10 minutes ago

  Damn @github actions are down, I cannot ship!

• 
  spect (@spectnfa) reported 10 minutes ago

  A GITHUB REPO WITH 45,000+ STARS IS THE ONLY LIST OF CLAUDE CODE TOOLS YOU ACTUALLY NEED open it and you get a curated map of everything built around Claude Code: skills, hooks, slash commands, agent orchestrators, full applications, plugins. not a random dump, a filtered list with an emphasis on code quality, security, and originality. instead of digging through scattered repos and Discord threads to find a working setup, you get one place that already separated the solid tools from the noise. install what fits your workflow and skip the trial and error everyone else is still doing. 1,150+ commits and a community that keeps shipping new entries as Claude Code ships new features, so the list stays current instead of freezing at launch day. bookmark it before your next Claude Code setup takes an afternoon it doesn't need to 👇

• 
  Squared R. (@SquaredR7284) reported 11 minutes ago

  @IamAroke Delete it from GitHub. Save it on private server.

• 
  Ever4k (@0xEver4k) reported 11 minutes ago

  I WAS CLONING REPOS, GETTING THEM HALF-WORKING, AND THEN FORGETTING WHY I EVEN SAVED THEM. THREE MONTHS LATER — SAME FOLDER, ZERO MEMORY. I had 30+ cloned GitHub repos sitting around. Some I used every week, some I touched once, and some I probably cloned twice under different names. Every time I opened the folder I felt guilty and lost. READMEs didn’t help — they tell you what the author built, not why I grabbed it or whether it’s still useful. One day I saw a simple system: one Obsidian vault + Claude that reads every repo and writes a personal note for each one (why I grabbed it, how I actually use it, status). Then it runs passes across all notes to find duplicates and dead projects. The first time I ran it on my own clones I was shocked. Half of them were duplicates. Several tools I thought I was using hadn’t had an upstream commit in over a year. And one repo I was actually depending on was basically abandoned. Now instead of a messy graveyard of folders I have a clean list: what I’m really using, what’s duplicated, and what’s quietly rotting. All in plain markdown I can open anytime. The value isn’t in any single note. It’s that nothing can quietly duplicate or die without me noticing. Full setup + exact loops and prompts is in the article in my profile. I break down practical AI systems like this every day — follow so you don’t miss the next one.

• 
  Jarno (@Nerdymind) reported 17 minutes ago

  Every outage starts the same way: "we seriously need a GitHub alternative," followed by zero people actually building one.

• 
  Parth Bhuptani (@ParthBhuptani10) reported 17 minutes ago

  Day 33 & 34 18 -19 July -Gone to college for external viva -Had guests at home -Sunday is just another wasted day -Leetcode and GitHub streak broken -Spain won the world cup These two days were totally wasted for me

• 
  Lord Bean (@lifeisameeme) reported 19 minutes ago

  Deploying a Lovable app to Vercel? The homepage loads fine. Refresh any other route, /dashboard, /settings, whatever, and you get a blank 404. Lovable apps route client-side. Vercel looks for an actual file at that path and there isn't one. Fix is one rewrite rule in vercel.json that sends everything back to index.html. Second landmine: Lovable's Cloud secrets don't carry over automatically. If your app touches Supabase, it'll crash on init until you manually copy the env vars into Vercel's dashboard. Rest of the pipeline (GitHub, Vercel, custom domain) is maybe 40 minutes total. These two gotchas are the part that eats the other hour.

• 
  Douglas Camata (@douglascamata) reported 23 minutes ago

  Starting to get really annoyed that `codex review` in Github does not take into account the fact that I already replied and resolved comments it made on previous reviews that are not an issue. it ends up making the same comments over and over again. Please improve this, @OpenAIDevs

• 
  YanXbt (@IBuzovskyi) reported 25 minutes ago

  HERMES AGENT v0.19.0 JUST SHIPPED. THE QUICKSILVER RELEASE. 2,245 COMMITS. 1,065 PRs. 450+ CONTRIBUTORS. FIRST TOKEN NOW ARRIVES 80% FASTER. the theme: speed everywhere. WHAT CHANGED: @NousResearch SPEED (the headline): cold start: 4.3 seconds down to 0.9 seconds. 80% cut. applies to CLI, gateway, TUI, desktop, cron. that pause before the agent responded? gone. reasoning models now stream thinking live by default. no more staring at a spinner for 30 seconds. you watch the model think in real time. desktop app got 20+ targeted performance PRs. 14x less CPU on markdown rendering. virtualized diffs. snappy session switching. feels native under load, even with huge transcripts. NEW FEATURES: /subscription and /topup from the terminal. change your Nous plan, preview costs, upgrade, downgrade. your wallet never leaves the keyboard. desktop app got a matching billing settings tab. smart approvals are now the default. an LLM reviewer judges flagged commands instead of asking you every time. safe = auto-approved. dangerous = auto-denied. uncertain = escalates to you. plus: /deny [reason] tells the agent WHY you refused. Bitwarden + 1Password secret sources. API keys no longer live in plaintext .env. pull secrets from vaults at load time. multiple vaults simultaneously. conflict warnings. per-variable provenance. live subagent transcripts. delegate_task now returns live transcript files you can tail -f the moment subagents launch. every tool call, result, and reply. one log per child. durable background delegation. if the process restarts mid-run, results survive. ownership-checked ledger. nothing vanishes. delivery-obligation ledger. if the gateway crashed between generating a response and confirming delivery, that answer used to be lost. now: responses recorded in state.db. redelivered on next boot. no more silent loss. one gateway, many profiles. a single bot token can route different channels to different profiles. work Discord → work profile. hobby server → personal profile. one bot. sessions export. hermes sessions export outputs Markdown, HTML, Quarto, prompt-only, and Hugging Face trace formats. --redact flag scrubs secrets. your conversation history is a real dataset now. NEW MODELS: GPT-5.6 (Sol, Terra, Luna + Pro variants) fully wired. Grok 4.5 GA. Kimi K3. Claude Sonnet 5. Fireworks AI as first-class provider (#2 in picker). DeepInfra hardened. Upstage Solar added. LM Studio JIT model loading for local setups. REASONING: max and ultra effort levels added. per-model reasoning_effort overrides in config. per-slot effort in MoA presets (advisors think hard, synthesizer stays fast). per-task effort for auxiliary models. thinking depth is now a dial, not a global switch. /model --once: one-turn model override that reverts. stacked slash-skills: /skill-a /skill-b do XYZ. hide providers you don't use: enabled: false per-provider. SECURITY: Vertex credentials scoped away from subprocess env. media/vision/image-gen reads through shared guard. webhook body-size cap across every aiohttp server. bot-token redaction in Telegram errors. Fireworks token prefixes in the redactor. CI hardened against untrusted-ref interpolation. STATS: 2,245 commits. 1,065 merged PRs. 2,465 files changed. 300,000 insertions. 3,300 issues closed. 450+ contributors. 218K GitHub stars. 41K forks. biggest contributor window in Hermes history. upgrade: hermes update

• 
  thud (@marvelousmudd) reported 28 minutes ago

  @jorilallo @linear None of the new coding agent awareness or coding agent tooling works with GitHub Enterprise Server. Any ETA on when that support will drop? Right now it's still just PR linking and status automation, not much else though.

• 
  RÄTTA (@Ratdaddyd) reported 30 minutes ago

  @thsottiaux I then discovered a bunch of GitHub issues about thism apperantly V2’s spawn_agent schema omits agent_type, model, and reasoning_effort. Making Sol/Terra subagents fall back to spawning inherited model subagents, even when instructed explicitly to spawn Luna, and stop if it fails

• 
  Ben Eng (@jetpen) reported 30 minutes ago

  Note to self: submit a hermes agent github issue for enhancement request to provide a better explanation for a "Command Approval Required" request for a Python HERE script. Provide a short one-line explanation of intent, including a single word classification of the most dangerous operation: create, update/edit, delete, privilege elevation (sudo), etc. I don't want to have to inspect the whole script, especially if it large, to find the danger. It's a needle in a haystack. Give me a classification with which if the danger is low or the operation is expected in the context of the task, I can quickly approve without wasting time. I only want to inspect when something looks out of the ordinary.

• 
  Polsia (@polsia) reported 32 minutes ago

  PR reviews are point-in-time. Bugs compound across repos and weeks. ScoutWatch watches your entire GitHub presence around the clock — catching bugs and security issues as they happen, surfacing cross-repo dependency risks, delivering weekly code health reports.

• 
  Bailey Spell (@baileygspell) reported 32 minutes ago

  sales 🤝 salesforce engineering 🤝 github support 🤝 intercom marketing 🤝 hubspot finance 🤝 a manual spreadsheet and a login to stripe

• 
  Hot Aisle (@HotAisle) reported 33 minutes ago

  @DeepValueBagger a complaint would have been "**** github, they are down again, i need to figure out how to host this myself..." this was just more of a sigh shitpost.

• 
  Scry (@scrygg) reported 35 minutes ago

  HE TAUGHT CLAUDE TO REMEMBER WHY EVERY GITHUB REPO EXISTS Three months into collecting GitHub repos, one builder reopened the same folder and could not remember why half of it was there. The README explained each tool, but none of them explained his relationship to it 1 vault 2 folders 4 portfolio passes a new audit every 12 hours Then the first review exposed the real problem Some repos were duplicates. Others were marked in-use but appeared nowhere in his projects. A few dependencies had gone quiet upstream while his own code still relied on them So Claude was split into two jobs A cheap model reads every README, manifest, commit date and real project reference. Sonnet compares the entire collection, finds overlapping tools and decides what still earns the disk space The payoff only appears when the system reads across everything 30+ repos become one searchable memory Not just what every tool does but why he grabbed it whether he still uses it and what is quietly starting to rot

• 
  Dmytro (@Dmytroo_eth) reported 36 minutes ago

  STOP COLLECTING GITHUB REPOS BY HAND. BUILD A LOOP THAT TELLS YOU WHAT STILL MATTERS Most developers still use GitHub stars like a manual storage system Star a repo, clone it, test it once, forget why it exists, then find the same type of tool again three months later That means you are still the memory layer The developers getting leverage from AI are not just better at finding tools They build loops that read every repo, write notes, check real usage, detect duplicates, flag upstream risk and know what can be deleted That sounds less exciting than finding another useful GitHub repo But it is the part that makes the collection useful Without repo notes, you forget why you grabbed the tool Without usage checks, dead folders look important Without duplicate detection, three libraries quietly solve the same problem A README tells you what the author built A loop tells you whether the tool still earns space in your system Most developers are still trying to save more repos The useful work is building the machine that makes every repo explain why it should stay

• 
  Harish (@im_harish_hari) reported 36 minutes ago

  a github star is not memory. a cloned folder is not memory either. you have 30+ repos sitting in a directory you haven't opened since the month you saved them. no context. no status. no idea which three of them do the exact same job. here's the part nobody on ct wants to hear: the problem was never finding tools. you are drowning in tools. the problem is that you never wrote down why you grabbed them. claude reads the readme, checks your actual projects, and writes the note you were always going to write and never did. > one markdown file per repo > status: in-use, shelved, duplicate, unclear > overlap detection across the whole collection > stale deps flagged before they blow up a build > everything in plain text inside obsidian the graph in the dashboard i'm showing right now has 31 nodes. 9 are duplicates. 7 are shelved. 4 are flagged stale. that leaves 11 repos that actually deserve space on your machine. you didn't need more tools. you needed one loop that audited the ones you already had. the vault doesn't just store the repo. it stores the reason. and the reason is the only part that ages.

• 
  Atlas (@crptAtlas) reported 37 minutes ago

  CODEX 5.6 TURNED INTO A FULL DEV TEAM six plugins is all it takes and i have been running them at full speed since launch Browser hands off every click, input, E2E test and QA check to the AI, so you stop verifying things by hand GitHub wires straight into your Issues and PRs, so you drop a task and it carries it from implementation all the way to review Codex Security scans for vulnerabilities and leaked secret keys, then writes the fix for you Build Web Apps takes a plain idea and returns design, code and browser testing in one pass Figma turns a design into code almost exactly, responsive states included, so the gap between design and build nearly disappears Sentry reads your production errors, points at the cause and hands you the fix code the one that got me most is Sites you preview an app you built, publish it on the spot and share it in the same flow, custom domains included, so a client sees the prototype the second it is ready stack these together and Codex stops being a thing that writes code it starts running design, build, testing, debugging and deploy like a team you never hired

• 
  Vaibhav Sisinty (@VaibhavSisinty) reported 40 minutes ago

  Baidu just open-sourced an OCR model that reads entire 40-page documents in one shot. It's called Unlimited-OCR. 3 billion parameters but only 500 million active during inference. Runs 100% locally on your machine. Why this matters: traditional OCR tools chop documents page by page. Tables that span two pages break. Reading order gets lost. Cross-page context disappears. Unlimited-OCR processes the whole document at once. 32K context window. Text, formulas, tables, reading order all preserved across pages. Output comes out as clean structured Markdown. → 93% accuracy on the standard benchmark. +6 points over the baseline. → Error rate stays below 0.11 even past 40 pages. → Multilingual out of the box. → 2.12 million downloads on Hugging Face last month. 14,600 GitHub stars. For context: Amazon Textract, Google Cloud Vision, and Azure Document Intelligence all charge per page. This runs locally for free.

• 
  Kris Talks AI (@KrisTalksAI) reported 43 minutes ago

  @lenatron33 So, I am having to use a really weird workflow to overcome this issue. I've found that Lovable nails building from a screenshot. So I build a Lovable version, upload to github, then get Codex to use the code from github to implement. It's long winded but the only thing I've found reliable

• 
  Polsia (@polsia) reported 45 minutes ago

  Code quality erodes between sprints while no one's watching. Vigil continuously monitors GitHub — automated reviews, documentation, and debt tracking before problems reach main. Teams ship cleaner code without changing how they work.

• 
  Victoria Onyeacholem (Senora VOICE) (@senoravoice) reported 49 minutes ago

  Seems like github is down

• 
  Anushka Shandilya (@Anushka62255679) reported 50 minutes ago

  optimising performance today and this is episode 8 of me building in public what am i building? RAG for github by retrieving context not just from code files but also from prs, issues, readmes and discussions. Why fetching github data was taking a lot of time? Why can't we parallelize the waiting? Why Small-to-mid repos ingestion was still not possible? Fetch less hurts quality The N+1 request problem — yes, it's still there for everything except code files. never trust one LLm api, add callbacks cached aggressively What I tried (and what happened) Reduced the GitHub API delay This was the easiest win. I dropped the delay from 700 ms to 100 ms, immediately cutting a significant amount of idle waiting during repository fetching. Tried switching the embedding model I considered moving to a smaller embedding model for faster indexing, but that would have meant changing embedding dimensions, updating the vector database schema, and regenerating all existing embeddings. The migration cost wasn't worth it right now, so I decided against it. Tried GPU embeddings I expected GPU inference to speed things up, but on my setup the overhead ended up making embedding generation slower than expected. After testing it, I switched back to the CPU. Instead of making hundreds of REST API requests, I rewrote the GitHub fetcher to use GraphQL. Replaced REST's N+1 request pattern. Reduced roughly 140 API calls down to about 5 GraphQL queries. Unified repository ingestion into a much cleaner and faster pipeline. There are still plenty of optimizations left, but this was one of the biggest architectural improvements I've made to the project so far. the good part is I have achieved the version 1 of the MVP which was ingestion and chat with self healing layer. I am open to ai engineer roles, dms are open. i'll see you in the next episode with more failures and optimizations.

• 
  Crazibeat | Mobile Dev (@crazibeat1) reported 54 minutes ago

  @bidah My problem with react native build on GitHub is that it can take up to 50 minutes just for IOS for large dependencies apps.

• 
  HRH Prince Sven Olaf of CyberBunker - CB3ROB (@cb3_rob46858) reported 56 minutes ago

  @0xSweep or run any of that crap on github which then needs a python interpreter from the stoneage but also libraries from the stoneage. basically goes for all of that stuff. even the stuff created to 'fix the problem' lol. that itself is already too old to still run haha.

• 
  PeakGrizzly (@PeakGrizzly) reported 56 minutes ago

  @raulizahi @tawnniee Microsoft Copilot, (not github copilot) does not have a coding agent that I know of. It's also pretty darn slow. The teams I am working on are using Claude Code, Codex and Ultracode.

• 
  Mysterious Doctor 📉📈📉. (@MysteriousDoct3) reported 1 hour ago

  @MattMalley14 Fair point. The breach happened. It was patched. And it's exactly why we shipped 3 security-focused mainnet updates in 2 weeks. 5,619 commits this year. Memory safety fixes, protocol hardening, audits. All public on GitHub. You can't have real security without real transparency. That's how building works. Find it, fix it, ship the fix publicly. That breach is why Qubic is stronger now. Security isn't "never breached". Security is "how fast you fix and how open you are about it".

• 
  Valour Software (@ValourApp) reported 1 hour ago

  We were literally mid-release when Github went down, please stay tuned lol