GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  ꓘodingIsFun (@KodinglsFun) reported 9 seconds ago

  @skibumtrading ChatGPT because it can handle .zip files so it's unlimited usage just a little slow & I have to manually test. Workspaces for the extra reasoning is nice & Codex for testing in a real environment is cool but not enough usage. I miss VS github, but I use it up in a few days

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  Gyomei (@Gyome1_) reported 1 minute ago

  CLAUDE CODE SPENT WEEKS DESTROYING MY APP. ONE FREE GITHUB FILE FIXED THE REAL PROBLEM i was building an X post studio the app was supposed to collect relevant tweets, sort them by writing pattern, then turn one raw idea into a finished post Claude Code and Cursor were already open so i did what everyone does i dropped a three-page prompt into the chat and waited for the product to appear the first version looked promising then the sub-agents stopped working Claude patched them a new error appeared it fixed that too the generator finally produced a post, but the chat interface broke then the UI shifted then the typography collapsed after almost 100 hotfixes, the codebase looked like a house where every repaired pipe had cracked two more walls weeks disappeared the product was still half-built and the problem was not that Claude could not code the problem was that it started coding before it understood what it was building then i found one file buried inside the obra/superpowers repo: skills/brainstorming/SKILL.md the first rule was brutal: do not write code until the design has been presented and approved Claude now has to inspect the project, ask questions one at a time, propose multiple approaches, explain the trade-offs, write the design into a file, and wait for approval before touching the terminal even for one button even for one config change because “small” changes are where the model makes the assumptions that poison everything later that single skill changed Claude from a hyperactive junior developer into something much closer to a senior architect it stopped trying to impress me with fast code it started finding the decisions i had not made yet people spend $500 on prompting courses trying to make Claude write better the better move was teaching it when not to write the full Superpowers setup is below ↓

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  Bart Ilg (@bart_ilg) reported 3 minutes ago

  @rivdb Yep, most people simply don't have a bunch of machines that need identical configurations. Even if they want to copy parts of their setup across multiple machines, they end up being pretty distinct in roles and thus have alot of unique configurations. Its still amazing though, and when you do need to replicate those machines there isn't anything else comparable. I recently used it for a personal project where I wanted to deploy some small servers for family members. Mostly simple functionality like DNS level ad blocking. Once I got the config set up it became super simple to bootstrap a new server and have it pull updates directly from my github repo, its a dream.

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  Anushka Shandilya (@Anushka62255679) reported 6 minutes ago

  optimising performance today and this is episode 8 of me building in public what am i building? RAG for github by retrieving context not just from code files but also from prs, issues, readmes and discussions. Why fetching github data was taking a lot of time? Why can't we parallelize the waiting? Why Small-to-mid repos ingestion was still not possible? Fetch less hurts quality The N+1 request problem — yes, it's still there for everything except code files. never trust one LLm api, add callbacks cached aggressively What I tried (and what happened) Reduced the GitHub API delay This was the easiest win. I dropped the delay from 700 ms to 100 ms, immediately cutting a significant amount of idle waiting during repository fetching. Tried switching the embedding model I considered moving to a smaller embedding model for faster indexing, but that would have meant changing embedding dimensions, updating the vector database schema, and regenerating all existing embeddings. The migration cost wasn't worth it right now, so I decided against it. Tried GPU embeddings I expected GPU inference to speed things up, but on my setup the overhead ended up making embedding generation slower than expected. After testing it, I switched back to the CPU. Instead of making hundreds of REST API requests, I rewrote the GitHub fetcher to use GraphQL. Replaced REST's N+1 request pattern. Reduced roughly 140 API calls down to about 5 GraphQL queries. Unified repository ingestion into a much cleaner and faster pipeline. There are still plenty of optimizations left, but this was one of the biggest architectural improvements I've made to the project so far. the good part is I have achieved the version 1 of the MVP which was ingestion and chat with self healing layer. I am open to ai engineer roles, dms are open. i'll see you in the next episode with more failures and optimizations.

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  Harish (@im_harish_hari) reported 7 minutes ago

  a github star is not memory. a cloned folder is not memory either. you have 30+ repos sitting in a directory you haven't opened since the month you saved them. no context. no status. no idea which three of them do the exact same job. here's the part nobody on ct wants to hear: the problem was never finding tools. you are drowning in tools. the problem is that you never wrote down why you grabbed them. claude reads the readme, checks your actual projects, and writes the note you were always going to write and never did. > one markdown file per repo > status: in-use, shelved, duplicate, unclear > overlap detection across the whole collection > stale deps flagged before they blow up a build > everything in plain text inside obsidian the graph in the dashboard i'm showing right now has 31 nodes. 9 are duplicates. 7 are shelved. 4 are flagged stale. that leaves 11 repos that actually deserve space on your machine. you didn't need more tools. you needed one loop that audited the ones you already had. the vault doesn't just store the repo. it stores the reason. and the reason is the only part that ages.

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  vladutxo (@vladutxo) reported 7 minutes ago

  one of the more productive things i did this week was decide not to build something. there's no commit for it and nothing to announce. just one less thing to maintain six months from now. terrible for the github graph. probably the right call.

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  G (@gilbertsanchz) reported 7 minutes ago

  What cloud breaches actually look like, because it is rarely the provider failing. The most common pattern in cloud security incidents is misconfiguration: a storage bucket set to public, an admin account without MFA, an access key accidentally committed to a public GitHub repo. The Capital One breach in 2019, roughly 100 million records, came down to a misconfigured firewall setting in the customer's environment, not AWS being hacked.

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  Nick (@nickbarton) reported 11 minutes ago

  @Rasmic I don’t give any of the privately hosted models access to my email or data, that’s a huge mistake for any of the hosted tools out there. I do use Claude and chatgpt for coding/app/agent work with a privately hosted Forgejo gut server not GitHub. Now those labs are still getting and using context data to train, learn, etc. But it’s not going to China

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  Paul Sant · Telecodex (@YouPulseX) reported 11 minutes ago

  @hxyden During the July 19–20 GitHub Actions outage, would a one-stack record of upstream cause, status-page lag and blast radius have changed your deploy decision—wait, reroute or proceed—or was GitHub’s status page already enough?

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  HRH Prince Sven Olaf of CyberBunker - CB3ROB (@cb3_rob46858) reported 15 minutes ago

  @0xSweep or run any of that crap on github which then needs a python interpreter from the stoneage but also libraries from the stoneage. basically goes for all of that stuff. even the stuff created to 'fix the problem' lol. that itself is already too old to still run haha.

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  Asethon (@setho_asethon) reported 18 minutes ago

  @artsinni @Grxit We are not bombing countries with nuke-scale weaponry, so no. We don't. Also, you all have no problem using Windows, 30% of which is AI with large amount of gen probably getting trained on private GitHub repo's.

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  𝗮𝗰𝗶𝗱𝘃𝗲𝗴𝗮𝘀 (@acidvegas) reported 20 minutes ago

  @zombodb @github A platform with almost 200M user's on it had a little bit of down time? HOW DARE THEY. You sound like the people who start crying as soon as Claude drops to 98% reliability.

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  Lord Bean (@lifeisameeme) reported 22 minutes ago

  Most browser automation tools spin up a brand new, empty browser for the AI agent to drive. chrome-cdp-skill does the opposite. It connects to the Chrome you already have open. Same tabs, same logged-in sessions, same page state mid-workflow. No re-login, no cookie exports, no separate profile. Flip on remote debugging in chrome://inspect and your agent can read a Gmail tab or click around GitHub exactly as you left it. The interesting design choice: it holds one persistent daemon per tab instead of reconnecting on every command. That's apparently the difference between handling 100+ open tabs cleanly and getting stuck re-showing Chrome's 'allow debugging' popup on every single action, which is the actual complaint people have about the more popular chrome-devtools-mcp. 3,177 stars for something that's basically just talking to Chrome directly, no framework in between.

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  spect (@spectnfa) reported 22 minutes ago

  A GITHUB REPO WITH 45,000+ STARS IS THE ONLY LIST OF CLAUDE CODE TOOLS YOU ACTUALLY NEED open it and you get a curated map of everything built around Claude Code: skills, hooks, slash commands, agent orchestrators, full applications, plugins. not a random dump, a filtered list with an emphasis on code quality, security, and originality. instead of digging through scattered repos and Discord threads to find a working setup, you get one place that already separated the solid tools from the noise. install what fits your workflow and skip the trial and error everyone else is still doing. 1,150+ commits and a community that keeps shipping new entries as Claude Code ships new features, so the list stays current instead of freezing at launch day. bookmark it before your next Claude Code setup takes an afternoon it doesn't need to 👇

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  Marcus Le (@marcusleovn) reported 24 minutes ago

  The smartest developer I know makes exactly $0 on the internet. The worst coder I know clears $40,000 a month. If you think you need to be a genius to build a profitable SaaS, you are just looking for an excuse to avoid doing the actual work. Talent is the biggest trap in indie hacking. My smart friend is a technical wizard. He writes beautiful, scalable code that belongs in a museum. He can build a complex micro-SaaS over a single weekend. He launches on Product Hunt, gets 300 upvotes, and lands five paying customers. Then week two hits. The dopamine wears off. Users start finding bugs. He realizes he actually has to do customer support. He gets bored. He spots a new trend on X. He shuts down the server and starts building an AI wrapper. He has repeated this exact cycle twelve times in three years. He has 12 dead GitHub repos, a massive AWS bill, and zero monthly recurring revenue. Now look at the other guy. He is a terrible programmer. His codebase is a complete disaster. He uses a spaghetti PHP backend from 2015 that would make a senior engineer cry. But he is stubborn as hell. Three years ago, he built a simple scheduling tool for local gym owners. It was brutally ugly. It barely worked. When he launched, nobody cared. He got zero upvotes. Zero customers. A smart founder would have pivoted. He just went to work. He cold-emailed 50 gym owners a day. Every single day. Most ignored him. Some yelled at him. A few agreed to a Zoom call. He listened to them complain. He fixed the ugly software. He added the exact features they begged for. He didn't rewrite the app in a new framework. He didn't chase the crypto pump or the AI hype. He just kept emailing gym owners. Month one: $0. Month six: $500 MRR. Year one: $3,000 MRR. Year three: $40,000 MRR. He won because he understood the basic math of the internet. Math doesn't care about your IQ. Math cares about volume. If you are a 10x genius but you quit after two weeks, your score is zero. If you are painfully average but you swing the bat 500 times, you win the game. Look at how this plays out in marketing. The talented founder writes one viral thread, gets 5,000 followers, and then goes silent for a month waiting for inspiration to strike. The consistent founder posts two average tweets a day. Every day. For three years. They build a massive audience through sheer brute force. It is the exact same with SEO. The genius spends three weeks writing the perfect, definitive guide to their niche. They hit publish and wait to get rich. The average founder publishes one decent blog post every Tuesday. Fifty-two posts a year. Google rewards the machine, not the masterpiece. Being too smart actually hurts early founders. Smart people are used to getting things right on the first try. They went to good schools and passed hard tests. Business gives you an F for the first twelve months. When a smart person gets an F, they panic. They assume the idea is flawed. They pivot to avoid feeling stupid. Average people are used to struggling. When an average person gets an F, they just put their head down and grind until it turns into a C. The truth is, building a business is highly repetitive manual labor disguised as innovation. You don't need a groundbreaking idea. You don't need perfect code. You don't need a viral marketing campaign. You need to pick one boring, painful problem. You need to build a simple solution. And you need to show up every single day for two years, long after it stops being fun. By simply refusing to quit, you mathematically eliminate 90% of your competition. They will get bored and leave the market to you. Stop trying to be the smartest person in the room. Just be the last one standing. Are you overthinking your current build? Be honest below. 👇