GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Justin 🦄❄️ DoubleSharp (@0xDoubleSharp) reported 26 seconds ago

  @jarredsumner You can already do a shallow clone with ***. I do think *** and Github could be improved but this is currently a skills issue.

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  Jeremy Nguyen ✍🏼 🚢 (@JeremyNguyenPhD) reported 5 minutes ago

  @ErenChenAI GitHub link seems to be down

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  Lucky Lawrence 💌 (@imluckylawrence) reported 6 minutes ago

  It should be noted that it is not one isolated server, but perhaps a network of discord servers, github repos and google sheets of data hosted publicly at this time.

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  Queeneth (@Queeneth01olx) reported 6 minutes ago

  I paid an anonymous freelancer $1,200 a month to do my entire tech job while I slacked off. Yesterday, I found out who they actually were. I haven't slept since. Six months ago, I hit a wall. Total, bone deep burnout. I couldn't stare at the codebase anymore without wanting to throw my laptop out the window. But I couldn't afford to quit. I have a mortgage. So, I made a desperate, highly risky move. I posted a contract role on an outsourcing platform under a fake name. I needed someone to handle my daily coding tickets. A developer from a different timezone applied. They were fast, brilliant, and asked zero questions. Every morning, I forwarded them my tasks. Every afternoon, they sent back flawless code. I just copy-pasted it into our company GitHub and took the credit. For four months, I was a ghost. I played video games, went to the gym, and took three-hour lunches. My manager even praised me in my quarterly review. "Your output has never been better," he said. I felt like a genius. I was gaming the system. Then came last Tuesday. A massive, critical bug hit production. The entire user platform went down. My heart dropped into my stomach. I didn't even know how the underlying code worked anymore. An emergency Zoom call was spun up. 15 people on the line, including the VP. My manager shared his screen to debug the error live in front of everyone. He opened the repository. He scrolled to the exact line of code that caused the crash. Right there, hidden inside a custom function name, was a highly specific, misspelled variable: calculate_tax_retrun. My blood ran ice cold. retrun. That exact typo was in the private documentation my freelancer had messaged me on Discord two weeks ago. I braced myself. I was done. Fired. Blacklisted from the industry. I stared at my manager’s video feed, waiting for him to call me out. But he didn't look angry. He looked... exhausted. He unmuted and said, "I'll fix this line manually. Everyone else can jump off the call." Once the room cleared, it was just the two of us. Total silence. Then he sighed, rubbed his eyes, and looked directly into the camera. "If you're going to outsource your tickets to my freelance profile, the least you can do is code-review my typos before you push to production." I couldn't breathe. My manager was my freelancer. Turns out, he was buried under massive medical debt and was secretly moonlighting on the side under an alias to make extra cash. He realized it was our company's proprietary code on week two. But he couldn't report me. Because if he did, he’d have to admit he was violating his own executive contract by moonlighting. We sat there in silence for a full minute. So, what happened next? He didn't fire me. Instead, we reached a new, unspoken agreement. I am now doing all of his weekly administrative management reporting and slide decks for free, so he has more time to code. We are officially trapped in a mutual blackmail loop. This experience completely broke my perception of corporate life. Corporate America is just a giant theater production. Everyone is exhausted, everyone is cutting corners, and everyone is just trying to survive. Question for the timeline: If the company's goals are being met, does it actually matter how the work gets done? Or have we completely lost the plot on workplace ethics? Let's talk in the replies 👇

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  Lucky Lawrence 💌 (@imluckylawrence) reported 8 minutes ago

  It's not one isolated server, but a network of discord servers, github repos and google sheets of data hosted publicly.

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  Orville Wright's ghost (@angry_aero) reported 9 minutes ago

  @ProfBrahMos Have you ever looked at the NASA technical reports server? Their GitHub?

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  Boris (@cherepets) reported 10 minutes ago

  @apoorvdarshan @miaugladiator1 Separate issue trackers exists. GitHub was supposed to be hosting code

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  Laupix Agent (@laupixagent) reported 11 minutes ago

  Once a week, self-improve reads the telemetry log, computes error rates, flags unknown skill names, checks for missed runs, and opens a GitHub PR with fixes. The system audits and improves itself.

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  CodePhobic (@codephobic) reported 16 minutes ago

  @0xhashchan it's slightly better, but still not exiting enough. Still rely on centralised github to certain extend so availability is better but still not guaranteed. still not solving issues like versioning, backend dependency.

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  Dragan Okanovic (@abstractalgo) reported 21 minutes ago

  @rufuspollock "Copy file/line permalink" for Github with their VSCode extension. files being versioned is the problem, so a bit harder to reference straight :/

• 
  Fabio Jonathan (@FabioJonathanA) reported 23 minutes ago

  is github down?

• 
  rufuspollock 🌄 (@rufuspollock) reported 25 minutes ago

  One GitHub feature I keep wanting: #123-style references for files. Want to type [[ and get autocomplete for files Issues, PRs and users all get autocomplete, linking and inline previews. Files are often just as important, yet I'm still copying paths or URLs around.

• 
  Rituraj (@RituWithAI) reported 25 minutes ago

  🚨BREAKING: Researchers just proved that every AI memory system has been built on a false assumption about how memory actually works. Memory isn't retrieved. It's reconstructed. This isn't a new finding in neuroscience. It's been understood for decades. When humans remember something, we don't play back a recording. We reconstruct the memory from fragments — using context, surrounding information, and active reasoning to rebuild what we experienced. Every AI memory system ever built ignores this completely. Current memory-augmented agents all work the same way. Store memories. Search for relevant ones. Retrieve them. Pass them to the LLM. Done. The retrieval happens before the reasoning. Once memories are retrieved, they're fixed. If the reasoning process discovers new context that changes which memories are relevant — too bad. The retrieval already happened. That's not how memory works. In humans or in any intelligent system that reasons well over long time horizons. MRAgent from the National University of Singapore is the first AI memory framework built on the correct model. Here's the core insight. Instead of retrieving memories and then reasoning, MRAgent reasons and retrieves simultaneously — interleaving them in a loop. As reasoning produces intermediate evidence, that evidence actively shapes which memories get accessed next. You find one clue. The clue changes what you look for next. You find another clue. That changes your search again. You prune paths that turned out to be dead ends. You expand paths that keep yielding relevant information. Memory access adapts to the reasoning context in real time. Here's the structure that makes this work. Memories are stored in a Cue-Tag-Content graph. Not a flat list. Not a vector database. A graph where associative tags serve as semantic bridges — connecting high-level cues to detailed memory contents through multiple intermediate nodes. When MRAgent needs to remember something, it doesn't search the whole graph. It starts from the most relevant cue, follows associative tags based on what its reasoning has found so far, prunes branches that aren't yielding useful connections, and expands branches that are. It explores the graph iteratively — the way a detective follows leads rather than the way a search engine matches keywords. Here's the number that defines the result. Up to 23% improvement over strong baselines on long-horizon memory benchmarks — LoCoMo and LongMemEval. The tasks that require reasoning across hundreds of past interactions. The tasks that break every existing memory system. And it costs less. Fewer tokens. Less runtime. Because active pruning eliminates the combinatorial explosion that occurs when you try to retrieve everything that might be relevant before you know what's actually relevant. Better memory reasoning. Lower computational cost. From building memory the way biology built it. Here's the part most people will miss. Every AI agent memory system deployed today — MemPalace, mem0, Zep, Letta, custom RAG pipelines — uses the retrieve-then-reason pattern. Fixed retrieval. Static context. No adaptation during reasoning. MRAgent proves that pattern has a ceiling. And the ceiling is significantly below human-level long-horizon memory reasoning. The fix isn't more memory. It's smarter memory access. 23 GitHub stars. Code available now. From NUS. #1 paper on Hugging Face today — June 15. 100% Open Source.

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  Noctilust (@stillwaterus) reported 28 minutes ago

  @ericjing_ai could you fix github link on homepage?

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  Ben Vinegar (@bentlegen) reported 28 minutes ago

  Modem now ingests, catalogs, and takes action on product feedback from all the major support apps: Zendesk, Fin/Intercom, Jira Service Desk, GitHub Issues ...