GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Duy /zuey/ (@goon_nguyen) reported 7 minutes ago

  i moved my development environment to the cloud, and i do not think i am going back linux is much closer to production than my laptop, so fewer bugs hide behind local differences and debugging gets less annoying but the bigger change is that development no longer depends on my laptop being open i can send instructions from my phone while i am outside. the agents keep working on cloud machines, run tests, open worktrees, and report back without turning my laptop into a portable space heater GitHub is now part of the runtime when an issue gets the ai-handle label, a webhook wakes the cloud agents. they inspect the issue, create an isolated workspace, implement the fix, run the checks, and report the result i do not need to open Terminal or launch Codex just to start the work my Discord support flow goes even further: - a customer reports a bug - an AI support agent gathers the details and creates an issue - the label triggers a coding agent on the cloud - the agent fixes it, validates it, and sends the result back into the support flow that is the first time "autonomous agent" has felt operational to me instead of being a demo with a chat box cloud machines also remove several stupid local bottlenecks the internet connection is fast. parallel agents and test processes stop fighting with the apps on my laptop. multiple worktrees stop eating my mac M1 512GB SSD that was never designed to host an AI engineering team there are tradeoffs, of course. cloud agents need strict permissions, isolated environments, budget limits, logs, and a clean path for human review. running 24/7 without guardrails is just a faster way to create incidents but the direction feels obvious AI coding agents should live where software runs, events happen, and automation can continue without waiting for a developer to open a laptop for me, the laptop is becoming a control surface the development environment is becoming infrastructure

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  Prasenjit (@prasenx) reported 15 minutes ago

  there's no official way to run macOS on an iPad. someone made an unofficial one. full macOS running locally on iPad. not a remote desktop, not a web app. hardware CPU virtualization with GPU acceleration. → supports macOS 12 monterey up to macOS 26 tahoe → you can install xcode, terminal, final cut pro trial, logic pro trial on device → works on iPad Pro (M1, M2) and iPad Air (M1) → requires jailbreak on iPadOS 14 up to 16.3.1 → no iCloud sign in → MIT license (100% free) open source on GitHub.

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  Internet Labs (@internetlabsai) reported 16 minutes ago

  @kylegawley Everyone is 'building in public' until you ask to see their churn rate. Bring back the messy, broken GitHub commits!

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  Gabriel Rubens (@gabrielrubenss) reported 17 minutes ago

  VPS deploy via GitHub (6/8): then my own fix bit me. I tagged Pensio v0.73.1, every job went green, the release published itself, and production kept running the old version. In GitHub Actions a skipped job travels down the chain, so my new retry job took the deploy with it.

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  Bluewall (@Bluewall) reported 21 minutes ago

  Found a malicious GitHub repo posing as a curated list of cybersecurity Telegram channels, every link led to the same malware ZIP. Reported it. Today GitHub Trust & Safety confirmed they took it down. Do report the shady stuff, it pays off.

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  PiX (@pa1nark) reported 29 minutes ago

  it is 2026, the era of clankers. you need to show the impact! i have seen some people saying build your online presence, show your face and etc etc., personally, i do not like that. i prefer being faceless on the internet. but hey, people have shown success with that. build some cool projects. do not do it for the sake of building projects. you find a inconvenience? you think you can fix it? do it. i have a habit of leaking creds. wrote rca multiple times at workplace too. told myself enough is enough, built keywatch. i wanted to convert json to toml to yaml to xml to csv and format it all. no tool existed. i built zparse (ofcourse, it is still ****, to an extent and needs fixes, no time). i keep forgetting where my opencode sessions is, i built a global session finder. you see the pattern? you have a problem, build a solution. and in the process, try to make it distributable. you'll eventually learn using ***, github, github ci, docker, the language you're working on. if you're building some communication tools, you'll eventually learn about networking, apis- rest, grpc, graphql and etc., the same applies to electronics too. i never really liked electronics until i was in my 7th sem. vlsi changed my mind. but by then, it was too late for me to mess around to dive deep into the domain. i can now tinker with esp32, build some small tools that can help me with tiny little stuffs.

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  Louround (@Louround_) reported 31 minutes ago

  Nvidia is paying $13b for HuggingFace (3x last valuation) because the real issue in robotics isn't compute or hardware but data. Every robot needs millions of human demonstrations to learn how to move, and that data is spread across labs with no standard. HuggingFace became a leader with Lerobot (the github of robotics data) and Pollen robotics, Nvidia already owned the sim, models and chips but buying HF gives them the full stack with data → training → deployment. solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump is building the same coordination layer for VLA agents, but on chain and permissionless, Simarena for testing, Foundry for training and Machinefun for incentives. Same thesis Nvidia just validated with $13b but solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump is at $4m fdv. ⏳

• 
  Sudo su (@sudoingX) reported 31 minutes ago

  watch anon! i had a 124B moe with 5.1B active parameters build me the octopus invaders game, driving hermes agent on a single dgx spark, 128gb unified. locally. the model is ling 3.0 flash from @AntLingAGI, a new emerging open lab from china, i am running the official int4, serving is vllm with ling's mtp drafter, decode opens around 40 tok/s. the prompt is mine, 157 lines, public on my github since may, and it has a body count, it broke a 36B in march, needed babysitting on a 9B in may, a 35B passed it in june, ling is the fourth model to face it and the biggest. and the run was a thriller. it read the spec and went building module by module, node checking every file behind itself, and the serve crashed on it, oomed the box mid write more than once, and every single time it came back up it read what was on disk, found the open function and kept building like nothing happened. no restart from zero, no broken files, the game grew through every crash until the suite ran 18 of 18 green. then it kept iterating while i played, denser waves, wider spawn field, tapered bullet bolts, nav lights on the ship, small verified diffs landing on a running game. my best run so far reached 524,915 points, level 13, max combo x138. i was enjoying. a 124B on a desk box wrote me an arcade game and survived every crash doing it. that is what local looks like now in 2026. and not a lot are aware of it. next i am giving the same prompt on same metal, same harness, against laguna, also one of my favorite models on a single dgx spark. the versus is coming.

• 
  Joseph K (@TechHorizonJoe) reported 32 minutes ago

  @moonshots_pod Right instinct, stop problems before they materialize. But uranium buyers need centrifuges. AI researchers need a laptop and GitHub. Whole different surface area.

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  MSoftDev (@Marwan_SoftDev) reported 34 minutes ago

  What’s your go-to setup for a bug report system? Google Forms, GitHub Issues, or something else?

• 
  Tobias Schmidt (@tpschmidt_) reported 36 minutes ago

  • cold starts are slower than GA for now, the optimization work happens during the preview Billed at normal Lambda rates. Upstream stable is expected in October, GA within two months after that. Feedback goes into a GitHub issue per runtime 👀

• 
  Dela (@delaanthonio) reported 37 minutes ago

  @GergelyOrosz It’s even more ironic since Xcode is trash compared to Visual Studio and VSCode. Xcode makes developing for the Apple ecosystem painful. No one loves it. But we use it anyway so we can distribute apps to Apple’s customer base. Taking a step back, we like macOS since it’s a good Unix-like environment for developing software. I used WSL years ago and there are always issues with the translation layer between Windows and Linux. It may have gotten better, but the experience is always worse than using a native Unix-like OS. The main mindshare Microsoft has for devs is GitHub. Everyone sees the frequent outages. Many stay since it’s hard to replace GitHub, but some are leaving.

• 
  MR WONDAKIND™ (@wondakind2) reported 38 minutes ago

  Most Web3 projects do not struggle because of poor liquidity, they struggle because nobody understands their story. Teams pour millions into token emissions and farming incentives, but the result is predictable, roughly 80% of those mercenary users dump their tokens and vanish within two weeks. The product might work fine, but the messaging failed to keep them around. A simple 4-step framework helps bridge complex tech with long-term user retention: Focus on incentives instead of code Users and institutions rarely care about the intricate lines of your backend contracts. They want clear answers to four basic questions: • Is my capital safe? • Where does the yield actually come from? • Can I exit cleanly during high volatility? • Why should I trust this team? If your marketing reads like a developer doc, most people will simply scroll past. Build educational narratives instead of paying for shills Paid influencer posts buy quick attention, but they do not buy loyalty. • Paid posts give you a temporary volume spike that drops off within days. • Clear educational breakdowns turn complex token mechanics into simple ideas anyone can grasp. • People stick around when they understand the economic model, not just because a creator told them to buy. Align content with the actual user journey Random posting does not convert. Your messaging needs to follow how people actually adopt a product: • Discovery: Break down broader market problems and high-level trends. • Education: Explain how your protocol solves those problems. • Trust: Share verifiable updates, audits, and operational data. • Retention: Give power users reasons to participate in governance and product updates. The target is not chasing empty impressions. The goal is building informed users who stick around for the long haul. Turn your technical design into your main marketing asset Do not hide your architecture in Github while posting unrelated memes on your main feed. • Your security audits, liquidity models, and fee structures are your strongest selling points. • Top protocols win because they turn complicated mechanics into genuine conviction. • When users truly understand how your engine works, they become your best advocates. If you are building a protocol and want to turn complex mechanics into real distribution, my inbox is open. Let us build together.

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  Aleix M. Martinez (@AleixMMartinez) reported 40 minutes ago

  @taiyasaki That’s been the problem for decades. In fact, pre-GitHub, it used to be even worse. Agree we must do something. But many of us have been asking for it for decades and…

• 
  PSY (@Psyfutur) reported 42 minutes ago

  Sam Altman, CEO of OpenAI, still sells ChatGPT Pro at $200 a month as if the coding agent inside it is a secret. Elon Musk forked the same agent OpenAI left on GitHub, rewrote the harness in Rust in three nights, and pointed it at any cheap endpoint. Dario Amodei at Anthropic is still billing Claude Max $200 on top. the swarm in the video is 12 roles, 487 of 500 tasks clean, three paid seats climbing and one free fork that barely moves the meter stop paying OpenAI and Anthropic $430 a month for a loop that now sits in a public repo what the $200 seats charge for, and what the fork already does: the agent - OpenAI's own loop it reads the repo, writes the patch, runs the tests, and does not stop until they pass that is Codex with a new skin. you are not buying a model. you are renting a wrapper Altman still meters the license - Apache-2.0, already pulled 62k lines, public, no revocation clause. OpenAI cannot take the file back once it is on your disk Musk did not beat them with a better model. he beat them with the license they published themselves the switch - one base url point the same terminal at Kimi, at a local 35B, at anything that speaks the messages API GPT-5.6 and Claude Opus 5 keep working until you change one line. then the invoice is the only thing that dies the bill - $430 down to $12 ChatGPT Pro $200 + Claude Max $200 + a Team seat $30 is $430 before tokens. the fork plus a $12 key cleared 487 of 500 of the same bench $1.62 a task on the Pro seat. $1.35 on Opus 5. $0.07 on the fork. that is a 96% cut for the job the $200 plan exists to sell here is the part they will fight me on: Altman and Amodei were not lying about the agent. they were lying about who is allowed to run it. the $200 was never the tool. it was the toll. the chart in the video is the three seats billing while the free fork stays flat, and the silence after the repo dropped is the only answer either lab has given drop the $430 stack. the run above is OpenAI's own agent, rewritten, doing the job Pro bills $1.62 a task for. three labs can delete the chart. they cannot delete the file