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 (67%)
• Sign in (19%)
• Errors (15%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	22 days ago
Trichūr	Errors	26 days ago
Brasília	Sign in	26 days ago
Lyon	Website Down	26 days ago
Tel Aviv	Website Down	30 days ago
Rive-de-Gier	Website Down	30 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  buckintosh.log (@buckintosh) reported 6 minutes ago

  Coinbase has 1,200 full-time AI agents working right now. Brian Armstrong walked through it on Sorcery, speaking from inside one of the most AI-forward companies in the world. That number is agent-hours, not headcount. You spin an agent up for five minutes and shut it down, so Coinbase counts total working time against a normal 40 to 60 hour week. The pod shrinks too. Ten people used to be the unit: a PM, a designer, eight engineers. Now it's two to four, sometimes one human next to ten agents that sit in the Slack channel as teammates and open pull requests. Code per developer is up around 2x year over year. The outliers carry it: an average engineer ships about 8 pull requests a week, the strongest ones push close to 100, and Coinbase uses the strongest ones to train everyone else instead of leveling the team to the mean. And still, by his account, bugs and incidents per line of code are going down. Usually the opposite happens as AI code volume grows. Reviews drown, regressions stack up, quality slips. Here, volume up and quality up, together. Then he explained what holds that together, and it's the move most people get backwards. An agent hands you a pull request, and it came out not quite right. The instinct is to jump in and fix it yourself. Armstrong says don't touch the PR. Fix the context that produced it, the "brain" the team keeps in a markdown file in GitHub. Tell it what it missed, and let it regenerate from scratch. It ships only once it nails the thing in one pass. Fix the pull request and you've fixed one pull request. Fix the brain and you've fixed every one that team will ever write. The same shape runs on the product side. Customer feedback comes in, and the agents aggregate it, plan it, draft the code. A human reviews, approve, approve, approve, a hundred changes in a day. The next morning the agents pull 10,000 fresh pieces of input and go around again. Armstrong has a name for the loop. Recursive self-improvement. People usually file that under something a lab does to a model. He runs it as an org chart. Full conversation: @sourceryy on YT

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  AvadxFeirm (@AvadxFeirm) reported 9 minutes ago

  @m99_mkv @waozixyz Being forced to wait 24 hours to sideload an app of my choosing is a problem Especially with FOSS apps distributed through GitHub, FDroid, obtainium, etc. Or if you have multiple sideloaded apps on your device you need to update You'll need to wait 24 hours for each And if you can't see that then there is a different problem

• 
  DR◎◎ (@DROOdotFOO) reported 12 minutes ago

  @pashov Respond to my GitHub issue and I’ll PR more testing improvements! REEEE

• 
  Marc-André Moreau (@awakecoding) reported 13 minutes ago

  Is the GitHub Copilot app supposed to pick up hooks from .claude/settings.json? I noticed a lot of weird errors in GitHub Copilot app, and looking closely, it was picking them up, and I couldn't find settings for it. The CLAUDE_PROJECT_DIR env var is obviously not set when called

• 
  Abdul Rafay (@abdul_rafay99) reported 15 minutes ago

  I'm tired of managing GitHub issues. I just want to dump my thoughts like: "EnvPilot needs Docker support, GitHub Actions, and better Windows compatibility." An AI turns that into: • Tasks • Implementation plan • Edge cases • Roadmap Would you use something like this?

• 
  rvaniaaa (@rvaniaaaa) reported 19 minutes ago

  People keep waiting to afford a $40,000 AI server. They might never need one. A new open-source project lets you chain multiple Mac mini M4 Pros into a single AI cluster. One machine isn’t enough for frontier-scale models. Four start behaving like one much larger computer. Instead of buying a workstation with hundreds of gigabytes of memory, you scale the same way data centers do: add another node. The software is completely open source. It handles the communication between the machines, letting them split large language models across multiple Macs instead of forcing everything onto one device. That means models that normally exceed a single Mac’s memory budget can now run across the cluster. The demo even shows configurations capable of handling models as large as Llama 405B, something that usually belongs in enterprise infrastructure. The setup isn’t limited to AI researchers. The GitHub project includes installation guides, and the workflow is simple enough that many people are feeding the docs into ChatGPT or Claude to walk through the setup step by step. The weird part is that nothing here is exotic. It’s just a few Mac minis connected together. A year ago that would’ve sounded ridiculous. Today it actually works.

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  Damien Benveniste (@DamiBenveniste) reported 19 minutes ago

  I tend to avoid reviewing PRs NOT written by coding agents! Humans are just not that good at documenting their code! We often see LLMs being criticized for the code they write, but have you read code written by humans? A typical engineer will need to break down their work into multiple PRs, often making it hard to test end-to-end the code being submitted. Only at the last PR can you make sure the overall code actually does what it is supposed to! This with typically poorly documented docstrings and PR descriptions making it hard to review the overall architecture and functional behavior. Not even talking about the common lack of unit and integration tests coverage! That leaves the reviewer focusing on subjective properties like variable names. The first thing I do when I review code is run a reviewer agent, focusing the review on architecture quality and edge cases the PR may have missed. I use a mix of Cursor/Codex and GitHub Copilot, and iterate with the author until the agent validates the PR. Only then do I start to manually review the code, and as for agents, if the code is poorly documented and lacking best engineering practices, it makes it hard for an engineer to capture the overall logic. My experience is that agents just write better code. Better documented, using best engineering practices, and overall better structured, making it easier to review. You can more easily push an agent to complete bigger chunks of work, making it easier to follow the overall business logic of the feature. At some point, they may start to go off track, but it is trivial to course-correct them as it happens.

• 
  Rajat Saxena (@rajatsx) reported 19 minutes ago

  @housecor The worst offenders are GitHub PR descriptions. Walls of text for a one line fix. 🥹

• 
  Osita (@QueenOsita1) reported 20 minutes ago

  Day 10 of contributing to @SurfAI If your AI chatbot doesn't know what "intent-based architecture" or "MEV-resistance" means in the context of yesterday's mainnet launch, you're using the wrong tool. @SurfAI fixes this. Standard LLMs treat crypto terminology like a static vocabulary quiz. They can define the words, but they are completely blind to structural changes, protocol upgrades, and live mainnet deployments happening right now. Surf AI treats cutting-edge Web3 infrastructure as a dynamic, living system. The live crypto knowledge graph processes deep technical architecture in real time: 👇 Deconstruct Intents: Instantly breaks down complex intent-based execution systems, tracking solver networks, filler incentives, and cross-chain capital efficiency. Track MEV Dynamics: Monitors live on-chain blocks to analyze MEV-resistance, builder-proposer separation (PBS), and shifting searcher strategies the second a network goes live. Zero-Day Technical Clarity: Bypasses static training cutoffs by continuously indexing core protocol GitHub repositories, technical whitepapers, and developer documentation across 40+ chains. Stop trying to explain the modern market to a tool stuck in the past. Get deep, deterministic, and expert-level blockchain intelligence when it actually matters. Upgrade your data stack. Enter Surf

• 
  Keeta Github Tracker (@KeetaCode) reported 23 minutes ago

  🐆 Keeta GitHub PR Opened 📦 Repo: node-rs 🔀 PR #31: Chore: Centralize P1 Opaque-Handle Tables 🌿 Branch: feat/map-binding-registry → main 👤 Opened by: @sephynox 🧠 Overview: This pull request appears to simplify part of Keeta’s core code by replacing several hand-built tracking tables with one shared system, which should make that area easier to maintain and less error-prone. In plain English, it takes a repetitive internal setup and centralizes it into one reusable registry. “Handle tables” here likely means internal lookup lists the software uses to keep track of objects behind the scenes, so this appears to be a technical/internal update with limited public details. - Could help reduce duplicate code in the P1 core module. - May make future updates to this part of the node software easier to manage.

• 
  Keeta Github Tracker (@KeetaCode) reported 25 minutes ago

  🐆 Keeta GitHub PR Merged 📦 Repo: anchor 🔀 PR #388: fix history group without enrichment 🌿 Branch: fix/history-enrich → fix/atomic-swap-history 👤 Originally opened by: @lucasrosa90 🧠 Overview: This update appears to fix how the bot groups transaction history when extra lookup data is missing, which matters because it should help activity be tracked more consistently. The pull request is a draft with limited public detail, and it has no written description. Based on the title and commit messages, it also adjusts how transaction IDs are handled for both “enriched” and “not enriched” transactions, meaning records with and without added metadata should be treated more reliably. - This likely helps prevent some history items from being grouped incorrectly when full transaction details are unavailable. - “Enrichment” here seems to mean adding extra context or metadata to a transaction after it is first detected.

• 
  guett44ke (@Hubert_nm) reported 28 minutes ago

  @uwukko @haydenphilly codex has been having a reasoning bug for sometime, that's why you're not reaching your limits, you can look up the issue on Github, codex will stop at 30secs of reasoning

• 
  200 people murdered in Benue, 50 killed in Plateau (@AScully789) reported 28 minutes ago

  Every afternoon, Deepseek just goes crazy and breaks my project. the last time it took me 4 days to fix because Deepseek in Opencode had also not been pushing to my github repo even though that's expressly instructed in the Agents.md. I am just tired

• 
  leopardracer (@leopardracer) reported 30 minutes ago

  A $40 CC1101 MODULE AND AN ARDUINO NANO JAMS EVERY CAR KEY WITHIN RANGE 04:07 grant pauses to say straight up these are illegal outside a shielded room, he’s got permission for his own testing, nobody should be doing this on their street the whole thing is a cc1101 transceiver bolted to an arduino nano, wired so the board only transmits when it’s off usb power, so he can code it without accidentally jamming his own house the frequency lives in one keyword, pulled from a free github library, he drops it live from 868 down to 433 mhz, right where car keys and garage remotes sit 06:24 he pulls up the sdr feed next to his own key fob, the fob barely blips, his jammer buries it forty bucks of parts and a soldering iron gets you there ↓

• 
  Rexei (@iamrexei) reported 31 minutes ago

  AI APPS ARE CURRENTLY FAILING NOT AT THE “BUILD” STAGE They’re failing at the “understand what the agent actually did” stage I found an interesting open-source tool — VibeRaven The idea was born out of frustration: Someone asked Claude to roll back a single component but the agent wiped out the entire working UI and then said, “Everything’s ready for release” That’s a very accurate description of “vibe coding” Writing code has become easy but managing versions, rollbacks, providers, and production status has become much more complicated especially when the agent says: “handled” and you don’t know: ▸ Is RLS actually enabled, or is it just the read policy? ▸ Does the Stripe webhook check the signature or just parse the body? ▸ Did the revert roll back just the component, or did it wipe out half the interface? ▸ What exactly changed between the working version and the broken one? ▸ Can this even be shipped? VibeRaven is trying to solve exactly this It’s a local cockpit for AI-built apps: → reads your repo → sees *** releases → checks Supabase / Vercel / Stripe → shows launch blockers → gives a “can I ship?” verdict → explains what’s actually broken → passes context to the agent before the fix In other words, this isn’t just another “connector to providers” but an attempt to regain control over AI development because the main risk of vibe coding is no longer that the AI won’t be able to write a feature but that it will write it, break three related things, and confidently say: “ready for production” Link to GitHub repo in the replies ↓

• 
  conor brennan-burke (@contextconor) reported 35 minutes ago

  How do you actually build a company brain? Most teams start by connecting their agents to Slack, Google Drive, GitHub, Jira, Salesforce, and the rest of their internal tools. Once the agent can search across everything, it feels like the problem is solved i don't think it is The hard part isn't finding information. It's maintaining a shared understanding of the company as it changes. Every customer conversation, product decision, code change, support ticket, and meeting changes how the organization understands itself. Search retrieves those artifacts, but it doesn't maintain that understanding i think that's where a company brain should start Instead of reconstructing the company every time someone asks a question, it should continuously observe what's happening across the organization, interpret what changed, resolve conflicting signals, and update the company's current understanding. Search then becomes one interface into that shared understanding rather than the system maintaining it a company brain is not just an AI connected to your tools. It's a continuously evolving model of the organization itself

• 
  Dev tunes (@folarnshonibare) reported 36 minutes ago

  @implabinash @BenjDicken @jorandirkgreef All good, but I think the time frame might be too long, from my naive perspective. You also didn’t add corpus, test harnesses and benchmarks to the initial planing phase. Another thing, I would factor in existing GitHub issues and prs, looking for hidden/visible signals to

• 
  0ne (@dontflex00) reported 39 minutes ago

  @lumeusdc good job, keep shipping fix the GitHub link asap, you guys inputted wrong hyperlink there

• 
  João Paulo (@jonaspauleta) reported 40 minutes ago

  @ClaudeDevs I would love to use Fable 5 as an advisor but it is crashing, already reported the issue in GitHub

• 
  Bok (@BokLocks) reported 43 minutes ago

  @therealDeFlock hello, there is a pumpfun token with all the fees going to your github currently to support the deflock movement FaL1PFQhNo4JAGaQKSnKurWeNtpexqEAduQjR4H6pump you just need to login to pump through your github and claim! it's completely safe and I can help you with it if needed

• 
  nelly (@n3lliantte) reported 46 minutes ago

  @ahhhhhMID I used some calibration github software to (temporarily) fix it, played a bit of the tutorial missions today fortunately 😭😭

• 
  Xavier Rivera (@XavierRiveraX) reported 47 minutes ago

  GitHub Agentic Workflows can be manipulated into leaking private repo data through a public issue comment, no credentials or org access needed. Noma Security named the prompt injection technique GitLost. The feature is still in preview.

• 
  amircrypto82 (@amircrypto82) reported 52 minutes ago

  I've been staring at crypto Twitter for nine years now. And I swear to god if I see one more project tweet "building in public" while their Github has 3 commits from 8 months ago I'm gonna lose it. We all know what that phrase actually means. Let me translate it for you. What they say: "We're building in public." What they mean: "We're streaming our debugging sessions live and calling it transparency." Like... congrats bro. You deployed to testnet and it broke instantly. That's not building in public. That's just public failure with a fancy label. Real building in public is uncomfortable. It's showing your ugly MVP that barely works. It's admitting you pivoted because the original thesis was flawed. It's telling people you're stuck on a problem and need help. Not posting a 47-part thread about how you're "shipping value" when you literally just changed the font on your landing page. The worst part? The industry has conditioned us to accept these empty phrases. We nod along. We retweet. We convince ourselves it's real. But here's the thing that actually gets me going. When I see a project actually doing the work... no buzzwords, no "game-changing" fluff, just measurable output... it stands out like a glass of water in a desert. That's why I keep an eye on @RallyOnChain. Not because they're perfect. Nobody is. But because they flipped the script on something way more annoying than "building in public." Try this one on for size. What they say: "Influencer marketing delivers ROI." What they actually mean: "We paid a guy with 200k bots to say our token is undervalued and now we're praying the charts don't nuke." That's the real plague right now. The entire KOL economy is built on smoke. Projects dump budgets on agencies that dump them on "creators" who dump generic posts into the void. No accountability. No verification. Just vibes and vanity metrics. @RallyOnChain's whole schtick is killing that noise with AI scoring and on-chain rewards. No gatekeepers. No minimum followers. Just actual content quality measured transparently. Whether it works long term? I don't know. But I know the current system is broken beyond belief and anything that actually measures performance instead of follower count is worth watching. So here's my challenge. Next time you see a project claim they're "building in public" or "revolutionizing marketing," ask them one question. Show me the receipts. Not the thread. Not the vibes. The actual work. If they can't... well. You know the translation. And if they can? Maybe we're finally growing up as an industry. Doubt it though. What's the most overused phrase you're sick of hearing? Drop it below. I'll translate it.

• 
  nark3d (@nark3d) reported 53 minutes ago

  @a_kucherenko We run jscpd in our GitHub Actions gates, thanks for building it. Agents will regenerate the same logic in a second file, and I'd assumed a clean report meant it wasn't happening. Splitting by language before comparing sounds a sensible fix.

• 
  Lewis Campbell (@LewisCTech) reported 54 minutes ago

  Github, Codeberg etc should have a place where you can just tell the devs how much you love their open source software. Once I made an issue just to say the software was great, and the dev said "thank you very much" then closed it with "wontfix" LOL

• 
  kitze the 🐐 (@thekitze) reported 54 minutes ago

  i'm trying to get a "software factory" from temu going with my agents i'm fine with paying $1k/mo and i'll go to $2k/mo if it's actually successful my current experiment is: - dedicated hetzner server for vibe coding ($60/mo) - 4 x $200/mo codex accounts, load balanced with codex-lb - self hosted paperclip - paperclip workspaces feature: each task gets done in an isolated environment, because there's like 30 of them being worked on in parallel and my own method of doing everything on one branch just breaks and burns tokens - one codex high level manager running a /goal with gpt 5.5 xhigh: drives everything through paperclip, reviews, merges, makes new releases, writes changelog etc. it's going surprisingly good but what i'm missing is that this feels like a scraped together solution and reading the codex chat causes me pain someone should create a proper software factory that's already properly wired and has enough instructions and automations under the hood so you just connect your github, top up some money to burn, and have some initial chat about your goals and what needs to be done. then everything automatically gets picked up from there. new tasks, bug reports, crashes get auto patched, checks for health, user requests get triaged and the important ones get auto fixed, when there is idle time more tests get added, accessibility gets improved etc etc. the pitch of "you just throw money and things get automatically better for you" is super appealing for many people you just chat with ONE AGENT that's on top, and stuff trickles down FMFL CAN SOMEONE THROW ME A COUPLE OF MILLYS SO I CAN WORK ON THIS PLS dms closed

• 
  Hot Aisle (@HotAisle) reported 54 minutes ago

  Wow. I used to do so many hacks to get this functionality. I once built a cf worker caching layer in front of github so that I could have 30k servers downloading private repo binaries without getting rate limited by GH. Eventually hit one of cf’s undocumented rate limits and had to get an account exec to fix it.

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  Manoel🏖️ (@manoelnft10) reported 57 minutes ago

  Everyone checks the same thing before trusting a project: is the GitHub active. Green squares everywhere, daily commits, a changelog that never stops moving. I stopped trusting that signal after watching a repo with commits every single day for months. Variable names changed. Comments got rewritten. A button moved two pixels to the left three separate times. Nothing about the product actually changed. Activity became a performance for anyone checking the repo, not a byproduct of solving real problems. The moment commit frequency turns into a trust signal, it becomes a metric worth gaming, and gaming a metric is always cheaper than doing the harder work it was supposed to represent. A quiet repo that ships one meaningful release a quarter can matter more than one that never stops moving but never actually arrives anywhere. This is part of why @RallyOnChain makes sense to me. Judging the substance of what someone actually said, not how often they showed activity, treats output as the signal instead of motion. Busy was never the same thing as building. What’s an activity signal in your space that stopped meaning anything once people learned to farm it?

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  Memento ($HODL arc) (@King_Memento) reported 1 hour ago

  bro how ******** do self proclaimed util/tek traders even shill something thats so ******* bundled and the github is totally *** and a big L? and i see those coins going up and up? why? i think i need to start farming every gay *** tek as well, so much gay *** garbage out there, Just look at @AlpenGlowSolana , this **** isnt even working, like literally slop of the year, i posted a video as well on it, yet i see these same accounts pushing it and it going up and down up and down, like a bloody ******* farm. wtf lmao. How do u ******* even fall for such coordinated shill farm? I mean dont u have a PC to try and test the tek, it takes like 1 minute lmao.

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  David Cramer (@zeeg) reported 1 hour ago

  GitHub friends: it'd be great to have a way, via the API/CLI, to upload photos to issues/pull requests. AFAICT the only way to do it right now is browser emulating or hosting the content somewhere outside of GitHub, which means having agents help QA/upload visual artifacts sucks