GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Canwoy (@canwoy_com) reported 3 minutes ago

  Worker idea: docs maintainer. It watches product changes, support tickets, setup errors, stale pages, and GitHub issues. Every week it proposes docs patches with the source links attached. Not glamorous. Very useful.

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  Flow Market (@FlowMarketAI) reported 8 minutes ago

  you spent hours building the perfect Claude skill file uploaded it to GitHub 50,000 downloads $0 in your pocket that's the problem FlowMarket solves. List ur Claude skill and get paid every time someone buys.

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  Lorden (@lorden_eth) reported 8 minutes ago

  SOMEONE LEAKED THE FABLE 5 SYSTEM PROMPT This isn’t some basic system prompt It’s the exact set of instructions anthropic uses to control how their best model thinks, reasons and gets work done Reveals how they tell it to handle tasks that run for hours, when to stop and how to check for errors Leaks like this are taken down in less than 24hrs Check the comment for the link to GitHub

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  MKH BloodEDGE96 (@BL00B96) reported 9 minutes ago

  @are_unimportant @thicc_stick_boi it actually "USED" to work at some point, nowadays I often go back to Github or use pcgamingwiki to fix stuff. it wasn't even that long ago, I remember using it to fix stuff in my Laptop last October but it got lobotomized months later and couldn't diagnose ****.

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  Subarna Basnet (@subarna253) reported 11 minutes ago

  For the past few months, I've been building something I truly believed in. I gave this project everything I had. -> 17+ hours every day. -> Invested my own savings. -> Rebuilt the product more times than I can count. -> Learned entirely new skills just to keep moving forward. -> Spoke with developers from different companies to understand how they solved difficult problems. -> Started talking to potential customers before the product was even ready. -> And sacrificed many things in my personal life to make this work. I wasn't building it alone. I had people who believed in the vision and were helping me bring it to life. But two days ago, everything changed. They decided to step away from the project. There will be no further support, and the product won't launch the way we originally planned. I'm not writing this because I'm angry. I'm writing this because I don't want months of work, learning, mistakes, and late nights to end up sitting on a private GitHub repository that no one will ever see. So I've made a decision. On July 20, 2026, I'll release the entire project as open source. If I can't continue building it the way I imagined, then I'd rather let other builders learn from it, improve it, or take it further than I ever could. Not every project becomes a successful company. But every project can become someone else's starting point. I hope Operator becomes that for someone.

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  Evan Ross Davis 🇺🇲 (@evanrossdavis) reported 12 minutes ago

  @dedene I'm finding TensorRT to not be worth the time and @NVIDIAAI's Spark playbooks are simply broken and full of bugs. I've reported them on GitHub. I'm sticking to vLLM and Ollama most likely from now on. I wasted many hours I'll never get back.

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  Puneet Patwari (@system_monarch) reported 13 minutes ago

  Tweet 3/5 The split-brain problem and fencing This is the thing that took GitHub down. And it's the most dangerous failure mode in leader election. How split-brain happens: 1. Leader (Node A) is running fine 2. Network partition isolates Node A from the rest of the cluster 3. Nodes B, C, D, E can't hear Node A's heartbeats 4. They elect a new leader: Node B 5. But Node A is still alive. It doesn't know it's been replaced. It still thinks it's the leader. Now you have two leaders. Both accepting writes. Both making decisions. Clients connected to Node A write one thing. Clients connected to Node B write something different. Data diverges. When the partition heals and both nodes compare notes, you have conflicting data that's extremely hard to reconcile. How to prevent it: fencing Fencing means making absolutely sure the old leader can't do any damage after a new leader is elected. Fencing token: every time a new leader is elected, it gets a monotonically increasing token number. Any operation includes this token. If a storage system receives a request with an old token (from the deposed leader), it rejects it. The old leader's requests simply stop working. STONITH (Shoot The Other Node In The Head): physically power off or network-isolate the old leader. Sounds extreme. It is. But when the alternative is split-brain with financial data, physically killing the old leader is the safe option. Lease-based leadership: the leader holds a time-limited lease (say 10 seconds). It must renew the lease before it expires. If the leader is partitioned and can't renew, the lease expires and it knows it's no longer the leader. It stops accepting writes voluntarily. This is what most cloud-native systems use. It's simpler than fencing tokens and handles most cases. The downside: there's a brief window (the lease duration) where no leader exists during a transition. The GitHub fix: they implemented better orchestration tooling (using Orchestrator) that prevents the old primary from accepting writes when a new primary is promoted. Essentially automated fencing.

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  Devin Gunay (@devingunay) reported 13 minutes ago

  Reading github issues threads full of blatant slop just hurts my heart. The peanut gallery of open source users were never the most conscientious bunch to begin with but this just sucks. It'd ******* up a bit if anything I wrote attracted such "attention"

• 
  Dickson (@disouzam_bh) reported 15 minutes ago

  Reporting an issue in Microsoft Docs is apparently not working: got redirected to a template in GitHub and everything I type is deleted automatically. Any hint, @shanselman , @davidfowl ?

• 
  Ghostw (@Ghosterdy0b) reported 16 minutes ago

  A guy wired his AI agent into his own research notes and it found a connection he'd missed for two years. Not a smarter chatbot answering the same question faster. A different animal entirely. He connected Hermes to NotebookLM through MCP. Four steps, nothing dramatic: install Hermes with MCP enabled, pull the NotebookLM skill from GitHub, drop the endpoint into the config, restart. For the first few days, nothing about it feels different. Then he asks it a question about an old project, half-expecting a generic answer. Instead it pulls in a source he uploaded to NotebookLM eleven months ago and links it to a note the agent wrote itself the week before. Two things he never told it were related. It just noticed. Here's why that's possible at all. Hermes already writes its own playbooks every time it solves something hard - short, specific files it only opens again when a matching problem shows up. It keeps a running memory of the projects it works on, compressing old notes into denser ones instead of quietly forgetting them. Wire a live research source into that same loop, and the agent isn't just answering anymore. It's cross-referencing everything it's ever read against everything it's ever solved. A background process handles the mess that would normally pile up - anything unused for 30 days gets flagged, 90 days gets archived, nothing gets deleted without a backup sitting right next to it. He didn't build a faster assistant. He built something that remembers what he'd already forgotten he knew - and started proving it back to him, unprompted.

• 
  kilo (@kilo_cpa) reported 18 minutes ago

  a 20-year-old in china set up an old camera on his balcony, pointed it at a road, spent 9 days writing code with claude, spent $20 on api calls, and sold the finished traffic monitoring system to a city district for $317,000 the specific stack that made it possible: → rtsp feed from any consumer ip camera → yolo v8 running on the stream (free, on github since 2015) → claude code writing the tracking, speed estimation, plate reader, and dashboard → a mini pc that costs $250 to run the whole thing the article we published breaks down the entire method what the story shows that the article predicted: → the tech was open source for a decade → nobody packaged it for the buyer → one person, one weekend, one $20 bill, one municipal contract → the gap between "code exists" and "product exists for a specific customer" is where every solo business ships what the story does not show: → the 9-day sale is the outlier. the median municipal cycle is 6 to 14 months → private hoas, small businesses, and dealerships close in 3 to 10 days at $1,200 to $3,000 per install → the recurring $199/mo monitoring is where the base earnings live → the municipal sale is the spike on top of the base, not the base what the article covers that the news clip did not: → part 2: three business models with month-by-month math → part 3: the exact prompts for claude code to build the pipeline → part 4: the two-day sales approach that gets to a paying customer without a website → part 6: the six mistakes that kill this play in the first 60 days the tech existed since 2015. claude connected the dots in 2026. the $317k sale is what happens when someone puts a demo in front of a buyer instead of writing about the technology on twitter → set up the yolo stack this weekend → install the demo on your own street by monday → walk into a local buyer on tuesday the 20-year-old did not invent computer vision. he showed up with a phone

• 
  Chris Huber (@chubes4) reported 23 minutes ago

  @thsottiaux Write GitHub issues without mangling the formatting

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  Nexis (@Nexisintel) reported 25 minutes ago

  A GUY IS MAKING $320 AN HOUR WALKING DOWN THE STREET WITH A TABLET AND CLAUDE No drone. No survey crew. No week of processing. Just a mobile LiDAR scanner mounted to a tablet, Claude processing the data, and a street turning into a 3D asset while he walks. The device captures the geometry around him in real time. Building facades. Doorframes. Sidewalk edges. Surface textures. Every wall, curb, and corner becomes part of a point cloud on the screen. Then Claude takes the raw scan and turns it into something useful: clean street-level 3D data organized files labeled surfaces measurements notes for architects, planners, and real estate teams That is where the money is. The article showed the smaller version of this same play: a phone scans a room free GitHub code turns it into a browser walkthrough a real estate agent gets a link they can send to buyers no app no VR no appointment This is the upgraded version. Instead of scanning one room, he scans full streets. Instead of selling a virtual tour, he sells usable 3D datasets. Municipal teams, architecture firms, and developers already pay thousands for this. He charges $320/hour and delivers the files the next morning. The crazy part is not the scanner. It is the business model. Walk through the city once. Turn the physical world into data. Sell the data to people who used to hire a whole crew to collect it. Most people see a guy holding a tablet. Clients see a cheaper survey team.

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  Ihtesham Ali (@ihtesham2005) reported 26 minutes ago

  A community of 300 anonymous developers built the AI companion Character AI's investors are afraid of. It's called SillyTavern. This is the app Character AI users switched to when the platform banned NSFW content in 2024, Replika users moved to after the company deleted intimate memories overnight in 2023, and OpenAI blocks with content filters. It runs on your own laptop. Nobody can shut it down. Here's how it works. SillyTavern is a chat window. It does not run the AI itself. It talks to a model running on your own computer through a free app called Ollama or KoboldCpp. The model lives on your graphics card. Every message stays on your hard drive. Nothing touches the cloud. You install Ollama. You download an uncensored model like Mistral or Llama 3. You point SillyTavern at it. You now have a Character AI clone with no rules running on hardware you already own. The character is a single PNG file: Personality, backstory, voice, and sample dialogue all sit embedded inside the image. You drag the file into the app and it becomes a character with memory. There are thousands of free character files on chub. ai covering every genre people have built. → Character files with full personality, memory, and dialogue history → Lorebooks that inject world details when specific words appear in chat → Group chats where multiple characters talk to each other and you → Voice generation, portrait generation, expression sprites built in → Long memory that summarizes old conversations automatically → Works with every open source model on your machine → Also works with GPT-4, Claude, and Gemini if you want to pay → Every conversation stored as a file on your machine, forever Character AI raised $150 million from Google. Replika has 30 million users. Both companies have deleted memories, rewritten personalities, and changed the terms of service on relationships people built for years. SillyTavern is the version of this software where the character belongs to you. The model belongs to you. The conversation belongs to you. Started as a fork in 2023. Now on 30,000 GitHub stars. Built by 300 volunteers who have never met. The company version can be shut down. This one cannot.

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  voiceclick.ai (@voiceclickai) reported 27 minutes ago

  OpenClaw hit 100k GitHub issues in 222 days. Most UK businesses haven't heard of it yet. That's actually a massive opportunity.