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 (70%)
• Sign in (17%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Itapema	Website Down	17 days ago
Tlalpan	Sign in	22 days ago
Quilmes	Website Down	22 days ago
Bengaluru	Website Down	24 days ago
Yokohama	Sign in	25 days ago
Gustavo Adolfo Madero	Website Down	29 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  ちゅうこ / 合瀬 奏 (@y_chu5) reported 2 minutes ago

  @Azure Hi, the repositories azure/azure-functions-docker and azure-functions-durable-js and more... have been disabled on GitHub for violating the terms of service. Was there a problem? I was just forking it, so I was surprised to receive an email from GitHub.

• 
  Bollish (@99_Bollish) reported 7 minutes ago

  🚨 $CUBIC ( 4f6GadxAPxvzZLVp7m2iGiJGZbxVbsAFjjQR5Vq2pump ) @CubicLaunch is doing the “no custody, fully on-chain, audited smart contract” thing on the front page, and then admitting the exact opposite 3 clicks later in their own docs. lol. Homepage, big letters: “Fully on-chain. No middlemen, no custody, the smart contract handles everything.” faq even says “We hold no custody of any funds at any point.” Now their own docs: “We generate a custodial launch wallet for you.” “Private keys are encrypted with AES-256-GCM and stored securely.” “The launch wallet becomes the creator, collecting fees.” “our system auto-claims them from PumpFun’s vault.” So read that again. They make a wallet, they hold the key (encrypted, sure, but they hold it), that wallet launches your coin, and every creator fee it ever makes lands in their wallet. that’s not “no custody,” Thats the most custodial thing possible. They have the keys to the thing holding all your money. “Audited smart contract, fully open source”? there’s no github linked anywhere on the site. No auditor named. No report. The docs and dashboard links in their own footer are dead #. there’s no contract to audit, it’s a server with a custodial wallet. And the actual idea is weird anyway. the fees don’t go to YOUR holders, they go to holders of whatever backing asset you pick. So back it with BONK and supposedly every BONK holder on earth gets a slice. Paying out pro-rata to a million wallets “automatically” is not a thing that happens. The “BONK avg 0.8 SOL/week” numbers are made up. So, custodial launcher pretending to be a trustless on-chain protocol, lying about custody on its own docs page, “audited” with nothing to show. If you launch through it you’re handing some anon the keys to your coin and all its fees. Hard pass for me. Read /docs yourself, it rats them out. Nfa.

• 
  abhisek (@abh1sek) reported 8 minutes ago

  @fr0gger_ The same can happen through GitHub issues as well right? Data is potentially executable now. It’s like we are back to pre NX/DEP/PageExec era. Just at a different abstraction level.

• 
  TwoSix (@Anon2Six) reported 8 minutes ago

  @goyblooddrinker I've been wanting to test the yellowkey bitlocker bypass but NightmareEclipse's github got taken down. I also dont have a spare machine to encrypt with bitlocker (as I use VeraCrypt)

• 
  Grant Ongers (https://defcon.social/@rewtd) (@rewtd) reported 11 minutes ago

  @Hostinger is there an issue with @github social logins? I'm getting: { "success": false, "status": 400, "error": { "code": 2036, "message": "User email is not verified" } }

• 
  The Blue-Collar Bard (@RidleyofZebes) reported 13 minutes ago

  That moment when you find a github issue from someone with your EXACT PROBLEM and their SOLUTION WORKS. **** you, sqlite, for dropping support for my ancient server processor. lmao

• 
  Jag Singh Reehal (@JagReehal) reported 19 minutes ago

  @github would be possible to look at my issue 4448185? I have replied back to support who asked me a question. Thanks.

• 
  VybeCoding (@VybeCodin) reported 20 minutes ago

  Everyone talks about building in public but nobody talks about the boring part. The week where nothing ships. The GitHub issues that sit untouched. The launch post that got 3 likes. That's the actual build process. The wins are just the highlight reel. What's the unglamorous part of your current project right now? Drop it below 👇 #buildinpublic #indiehackers #opensource

• 
  October Ø (@ralphaelofDeFi) reported 21 minutes ago

  @Trae_ai Pls respond to the problem on the ide GitHub. We can’t login

• 
  Cortex (@0xCortexl) reported 25 minutes ago

  THIS CHINESE DEVELOPER STACKED 4 NVIDIA CHIPS AND CONNECTED JARVIS + GITHUB + CHATGPT 5.5 - 9 AGENTS, 5 MEMORY BACKENDS, $10,000/MONTH FROM ONE ROOM 4 gold NVIDIA compute modules stacked and cabled - not rented, not shared, not someone else's server - his hardware, his room, his data never leaving the building every time you send a message to ChatGPT your data hits a cloud server and comes back - his setup changes that entirely - Jarvis runs locally on the stack, GitHub handles the codebase, ChatGPT 5.5 handles reasoning - all three connected into one pipeline he owns 9 agents running in parallel across 5 memory backends - each agent knows what the others did, nothing gets lost between sessions and the system compounds every week clients pay for AI infrastructure that doesn't leak their data - that's the pitch that closes deals without negotiating on price 4 chips bought once, $0 in monthly cloud bills, data stays in the room - and the open source stack on top turns it into $10,000/month the people running their AI on someone else's server are one policy change away from losing everything - he built his own

• 
  Ab. (@Abiodun0x) reported 25 minutes ago

  Github is buggy. Part of our issues today

• 
  Bill Forney (@wforney) reported 28 minutes ago

  @thisjonrussell @github @shanselman GitHub action `Azure/functions-action` down - Microsoft Q&A

• 
  Peter Steinberger 🦞 (@steipete) reported 30 minutes ago

  @alex_vazelakis Haven’t seen that one yet, pls do a GitHub Issue with details. 🙏

• 
  Saylor (@seylorra) reported 30 minutes ago

  @TheAhmadOsman honestly i just want sm120 to work with vllm without a 4 hour github issue hunt. a rocm sanity check or json config isnt too much to ask.

• 
  Bob McElrath (@BobMcElrath) reported 31 minutes ago

  @Italianclownz @barackomaba @BarackObama My analysis harness uses transformers directly and reimplemented your kernels, so I can dump intermediate tensors (hence the MSE error measurements in the github issue). I did a bunch of research on quantization methods and built this harness for it.

• 
  Justin H. Johnson (@BioInfo) reported 32 minutes ago

  I built a small thing this week that I thought was clever. One of my automated routines now reads back over its own run, asks what it just learned that its instructions didn't already cover, and edits its own checklist so the next run is a little sharper. Then I went looking, and found half the field had already built it. That used to feel like a letdown. Now it's the best part. The pattern I "invented" is written up as a recipe. Anthropic's own tooling does a sharper version. Microsoft has a paper that tunes these instruction files the way you'd train a model. And a directory has scraped 1.6 million of them off GitHub, up from about 790,000 six months ago. My problem wasn't unique. That's the reason the answer is worth keeping. So here's the loop I've started running on purpose: write up the thing I think is clever, sweep the last 30 days to find the dozen people who already hit it, take the best of what they worked out, fold it back into my own setup, and share the result forward. The writing and the searching aren't separate from the building. They're how the building compounds. The flashy demos rewrite their own code against a scoreboard. The quieter, more durable move for anyone actually running this stuff is a routine that keeps better notes, in a file you can read, and borrows the best ideas from everyone else. If your problem feels unique, you probably just haven't swept yet.

• 
  KarmaWarrior (@merovingian_man) reported 36 minutes ago

  @pkay2402 @github The economics of this was always suspect Hw prices have to come down for it to make sense

• 
  umar ibrahim (@imp213x) reported 38 minutes ago

  Ok, this is getting serious. Has anyone ever had problems with subscription on @github ? I think they have the poorest support system I’ve ever interacted with! Actually, there is no interaction, because an interaction has to have a second or third party, I’ve been the only one doing the “interaction.” I’ve never experienced anything quite like this in my entire experience on any platform. If anyone have a quicker way to get their response 🙏

• 
  Michael Ryerse (@MichaelRyerse) reported 39 minutes ago

  @m2jr Yeah I have them open issues describing the skills they need created or updated. GitHub is not ideal but until there’s a cross ai platform registry for skills works ok.

• 
  YummyNZT (@yummy_nzt) reported 40 minutes ago

  🚀 BUYING $DOGE RIGHT NOW TO FLIP IT 3X HIGHER IN 3 MONTHS Massive panic selling absorption by major players happening at this level right now. Historically, this accumulation leads to huge pumps 📅 Aug-Sep 2018: 3x+ pump driven by Dogecoin-Ethereum bridge launch and forking hype. 📅 October 2022: Pumped from $0.06 to $0.15 following Elon Musk's acquisition of X. 2026 Season: What structural catalysts could trigger a massive short squeeze and send us straight to the moon this time? 📈 🔹Spot Dogecoin ETF Approval Grayscale, Bitwise, and 21Shares have already submitted official 19b-4 filings to the SEC for spot Dogecoin ETFs. 🔹Radical Supply Emission Cut (GitHub Proposal #3776) Core developers are actively debating a major proposal to slash block rewards from 10,000 down to 1,000 DOGE. Massive supply shock loading. 🔹Solana Integration & DeFi Bridges Active development is underway for full-scale integration into top DeFi ecosystems via trustless cross-chain bridges. 🔹Official US "Digital Commodity" Status & Utility Major e-commerce giants are expected to announce DOGE integration as an official payment method this summer. If even ONE of these catalysts gets officially confirmed, we are getting a rock-solid fundamental reason for a massive programmatic pump. Have you bagged some DOGE yet? 💰

• 
  Searxly (@Searxly) reported 44 minutes ago

  Plans for today: - Add more tabs to the website, redesign, fix bugs on mobile. - Redesign entirely search results in Searxly. - Implement the Wallet feature inside of Searxly, make it work - Publish all changes today to the GitHub repository.

• 
  MrRuSs3LL (@mrru5s3ll) reported 44 minutes ago

  Spent the morning digging through GitHub trending. Some genuinely useful stuff shipping right now. Spec Kit v0.9.4 dropped last week — GitHub's spec-driven dev toolkit. JSON output for workflow runs, headless Cursor agent dispatch on Windows, active skills registration fixed. If you're doing spec-driven dev, gets you running. Hermes Agent v0.15.2 also landed. Nous Research's agent framework. Bug fix release but the plugin.yaml bundling in wheels matters if you're distributing skills. OpenClaw hit 376k stars. Personal AI assistant, any OS, built in Rust. The lobster branding is growing on me. Superpowers framework from obra — agentic skills methodology that actually works. 218k stars says something. ECC (affaan-m) — performance optimisation harness for Claude Code, Codex, Opencode, Cursor. Skills, instincts, memory, security. 207k stars. Claude Code skills from Karpathy observations (multica-ai) and mattpocock's engineer skills. Both worth a look if you're configuring agents. Agency agents (msitarzewski) — complete AI agency, specialised experts with personality. 107k stars. Point is: the agent/tooling space is moving fast. Pick one, go deep, ship something.

• 
  Saravanan Jaichandaran (@SaravananJ2294) reported 46 minutes ago

  A GitHub issue on anthropics/claude-code has had no maintainer reply in 53 days. In that time, six independent memory-tool authors arrived and quietly wrote a four-hook lifecycle spec together. Wrote up what they converged on, and why it matters.

• 
  RyanX 🦞 (@ryanx_ai) reported 50 minutes ago

  Hiten Shah just put his finger on something most AI strategy memos miss. His argument: every company's first AI strategy should be a skill library. Not a tool rollout. Not a connector pile. A library of reusable ways of working that agents can load. The insight that hit me: "the pattern is older than AI." Unix commands made operations reusable. Libraries made code reusable. APIs made services reusable. Workflows made processes reusable. What changed isn't the desire to package expertise. Software has always moved in this direction. What changed is the executor. For decades, a human had to read the playbook and apply it. Now agents load the playbook, call tools, inspect files, run scripts, and keep going. The playbook becomes active. Documentation becomes infrastructure. That changes the value of writing things down. A skill that used to be "this is how the senior PM thinks about launches" was nice-to-have documentation. Now it's an executable asset. The mistake most companies are about to make: they start with access. Link the agent to the CRM. Set up Slack. Wire up GitHub. Connect the data warehouse. That all matters. An agent without access is guessing. But access alone doesn't create useful work. An agent can read every sales note and still miss the shape of a deal. It can search every support ticket and still miss the customer who needs immediate attention. The real work: teach the agent how your company approaches the work. That's what a skill is. Not a prompt for this conversation. A reusable way of working, packaged with instructions, examples, templates, edge cases, quality bar. Which is why the most valuable skills won't live on public marketplaces. They'll live inside your company, encoding things like: - what counts as escalation in your support org - how renewal calls are actually run (not what the playbook says) - which metrics matter for your board and which are noise - the legal fallback positions you actually rely on - the voice that defines your brand A generic agent has broad knowledge of sales, support, finance, product. What makes it useful inside your company is learning your specific processes. That's the moat. Not the model you pick. The work you teach the model to do well. Three things to do this quarter, before you buy another AI tool: 1. Map the repeated work. The workflows where experienced people consistently outperform everyone else. Sales calls, escalations, PRDs, postmortems, contracts, forecasts. None of these are the job. They're everything wrapped around it. 2. For each one, ask: what does the best person on the team do differently? What catches their attention first? What do they overlook? Which errors are they trying to avoid? That is the raw material for a skill. 3. Package the first three. Run them. Improve them. Make the owner stay close to the work — the skill decays the moment it stops being maintained by the person who actually does the job. The companies that win won't be the ones with the most internal AI demos. They'll be the ones that turned their judgment into reusable systems faster than their competitors. Your company already has skills. They're sitting in old docs, Slack threads, customer calls, and the heads of the people who know how the work really gets done. Make them visible. Make them reusable. Let the agents use them.

• 
  Darth (@DarthSZNN) reported 51 minutes ago

  @ReaperDTX @Marskies_ DualShock GitHub, there’s all kinds of videos on it on YouTube. A circularity error of less than 7% is gonna make your sticks feel “stiff” in game and hard to micro adjust.

• 
  Subir Ghosh (@iamSubir14) reported 52 minutes ago

  @bizuiyannn @whisp2424 @heliumbrowser I also thought about that, So I just checked it... I opened the same websites (like: YT, X, github...) inside Brave and Helium And the result, Helium is taking 1GB of more RAM And it's also running some extra 4-5 tasks I don't know that is the issue...

• 
  Julius (@jullerino) reported 53 minutes ago

  @tannerlinsley @ahlimanhuseynov @KevinVanCott We’re not even running build in CI. The app is built on e.g. Vercel, typecheck in GitHub actions. Having to run and discard a build just to do static analysis is just slowing down CI for no gain. That’s my 2 cents

• 
  Jan-Felix (@jfschwarz) reported 54 minutes ago

  @DevSwayam That GitHub issue is unrelated. #28 just asks Delay's `executeNextTx` to stop swallowing the revert reason of a failed inner tx, a debugging complaint. The exploit stemmed from a bug in an entirely different function (the `moduleOnly` modifier). Your claim is simply false.

• 
  Josh Tisdale (@joshtisdale) reported 56 minutes ago

  @MichaelGannotti @Microsoft Does the attestation take time to be effective? Any chance it not being processed would cause the “this GitHub users needs enterprise” error at login? Trying to figure out what step I missed.

• 
  KTMudak (@KTMudak) reported 56 minutes ago

  What do the companies in the image have in common? They get guaranteed AI impact from Cognition, authors of Devin – or their money back The enterprise pain is obvious now. Companies are disabling Claude Code or Github Copilot because devs are spending insane amounts on models. Uber’s CTO said they burned the entire yearly budget for AI agents in one quarter, which is, of course, dumb. In companies like this budgets are approved slowly, so they were probably estimating against something like Claude Sonnet 4.5. Then Opus 4.8 shows up, does more, costs more and suddenly the old budget makes no sense. Cognition is trying to solve this with Productivity Guarantee. Mechanism is pretty simple. They trained/calibrated a model that predicts: a) did the agent do something valuable b) if yes, how many hours would this take a human? Then those hours get multiplied by some average developer rate. Cognition sums it across a longer period and compares the estimated value to what the client paid. If the value is lower, they return the difference as credits – up to $10M for future requests. The evaluation model is not perfect but Cognition says the errors are unbiased, so over a long enough period the aggregate estimate should be relatively accurate. Interesting idea. Now lets see what OpenAI and Anthropic come up with – for Anthropic especially, proving customer spend pays back feels like a very sharp problem right now