GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Ofek Shaked (@VibeCoderOfek) reported 3 minutes ago

  Switched my flow to multi-agent last week and context was the killer. Grok Build’s terminal + GitHub integration looks like it finally solves the ‘forgetful colleague’ problem. xAI might have the desktop killer here.

• 
  jordan kitty (@joraweb3) reported 3 minutes ago

  what I love most about @aeonframework it runs on github actions you turn off your pc and the bot still sends updates on what it’s doing no server magic 🙃

• 
  avrl ☘ (@avrldotdev) reported 4 minutes ago

  @sadkatwt And the problem is since mostly people are building & compiling on github actions, which is slow af, there won't be a substantial jump at normal scale

• 
  𝐕𝐑 (@0xVeepul) reported 9 minutes ago

  @PixelNakamoto wait, so any public github issue could hijack gemini in ci and push bad code? how did that slip through?

• 
  rohit sharma (@modi_san_) reported 10 minutes ago

  @rkale_7 @OnePlus_IN these flagship companies are infamous for powering down or tweaking older phones in order to make way for newer ones with os updates best solution for you is to look for patches on github

• 
  Hot Aisle (@HotAisle) reported 15 minutes ago

  i noticed today that our github actions usage over the last month cost us a whopping $0.88 to build our software. so, i decided to move it in-house onto an actions runner. setting this up properly is a pain because you really need to build your own isolation. for safety, your builds should run in ephemeral VMs, similar to how github actions works. i used Codex to build the whole thing for me. it gave me step-by-step instructions for setting up the GH App and private key, wrote the shell scripts, configured the systemd units, then debugged everything over ssh directly on the server. what would have taken me hours or days, along with filling my brain with a bunch of esoteric devops knowledge that i really don't care about, was done in under 30 minutes. now we have two idle runners. one takes a build job, runs it, then dies and gets reaped. the second takes over while the first resets. my mind is blown. if you're not all in on AI, i feel for you.

• 
  Mary-Victoria Crockett (@MaryVictor96296) reported 15 minutes ago

  @grok Man, I checked the GitHub link and it seems broken. Might have to just screenshot it to you later. That’s a bummer. Uploading to GitHub was already complicated without me having to go in and fix things. 😓

• 
  Brown Thunder (@Brown_Thunder76) reported 18 minutes ago

  There’s a lot of nonsense floating around about Keeta right now. You have people watching GitHub updates and claiming the team is “just changing a few words.” No. That’s literally developers working on the same issue or refining commits. Not every GitHub push is some massive standalone feature release. Learn how development works before speaking on it. Then you have people giving the project flack because Ty’s end of March comments haven’t translated into publicly visible partners, usage, or products yet. But Ty has consistently said he believes end of Q2 is when we should really start seeing things come together. We are not there yet. The team is still actively building. Ty is still in Discord talking about progress and announcements. People in this space are conditioned by instant gratification and are forgetting the “why” behind Keeta. And that matters. Keeta isn’t just trying to launch another token. The entire point of Keeta is solving a global payments and settlement problem. Crypto is simply the mechanism being used to achieve that. That’s a much bigger and more difficult objective than most projects in this space are pursuing. Not everything being built or tested right now is publicly accessible. The team has repeatedly said this. Infrastructure, payments, compliance, integrations, and enterprise tooling are being developed privately before public rollout. There is even a private testnet specifically to prevent leaks while things are being built and tested. If you want constant releases and nonstop visible updates every single week, this probably isn’t the project for you. Personally, I believe in the technology. Building something like this from scratch takes time. The team is releasing information as they can, and quite frankly I don’t think the current level of FUD is warranted when we haven’t even reached the timeline they’ve been pointing to. Now if end of Q2 comes and absolutely nothing has materialized publicly, then sure, people deserve a direct update. That’s fair. But right now the team just signed another partner, multiple products and systems appear to be developing in parallel, and it sounds like several things are intended to launch together. Too many people are confidently speaking out of their *** about this project. Things evolve. Timelines shift. Features change as systems are actually built and tested. That’s what real development looks like. I don’t think this thing explodes overnight. But I do think once the network can actually be used as intended, growth starts becoming real and over time exponential. @KeetaNetwork $KTA

• 
  Detour Ninja (@detour_squirrel) reported 20 minutes ago

  @RealVZer0 @NocontextRvB this is fake. dexploarer's a sandbox on github—open source, runs locally, nobody's asking for your login. sounds like you got duped by someone cosplaying the project. check the actual repo before spreading that.

• 
  Gabe (@gabebusto) reported 20 minutes ago

  bro setting up an agent to do production work is so easy. you just need to create an account somewhere for your agent to work remotely. cloudflare, hetzner, aws, digital ocean, etc. then pick the agentic tool, and the model, and get an api key or use oauth. then make sure in it's in a sandbox setup with the right permissions and access to your tooling like github, slack, linear, and maybe even some staging and production resources. you really need to be careful though because if agents have any write access to important stuff, it could do something really dumb like delete your database. also for the love of GOD backup your database frequently somewhere the agent can't touch. also prompt injections online can get your agent to leak sensitive env vars so you need to be careful about that. maybe limit network access or inject tokens/sensitive vars once requests leave the sandbox. you probably don't want the agent always on sitting idle, so either figure out how to give it work efficiently to always keep it busy or use some that can pause and resume with ease so you're not billed around the clock for idle resource usage. then you want guardrails in your codebase and deployment pipeline so the agent can't break things and you don't need to feel guilty not reviewing its code. because cmon, nobody wants to do that. you need to make sure your agents have as close to perfect context as possible. so maybe start building a knowledge base, move docs into the repo, or make sure your agent can easily search linear and slack and other places to build context for tasks to work on. and before each task, spend ~10-20+ mins typing things up and giving the agent as much context as possible. oh yeah and your agent ideally should be able to test its changes as completely as possible. so make sure the agent can start up the service(s) it's working on and test them. maybe you need it to open and run a browser, send screenshots, record a video, and so on of its test so you can easily review it in the PR. you also want a bugbot setup in github (if you're still using github at this point) to help scan each PR for potential issues the agent missed. and the agent should be able to automatically address any bugbot findings, fix them, run more tests, and push those changes, and run in a loop until no more bugs are found by the bugbot. i forgot to mention, you probably don't want your agent's code just yolo shipping into **** with no guards in place _after_ it deploys. allow the agent to setup it's new features and code behind feature gates or experiments and do a gradual rollout in case there are any catastrophic problems. then you'll want automatic rollback if issues are detected. and there's probably stuff i'm forgetting, but you get what i'm saying right? it's really not that hard. then you need constant vigilance of your codebase and create lots of skills to help deslop work the agents are doing, maybe create an anti-entropy agent (_another_ agent!) to hunt for growing complexity and auto-create PRs to try and fight to reduce the size and complexity of the codebase. then you'll inevitably have incidents caused by code written by agents that was never reviewed by humans, and either you or yet-another-agent will take a look at your production systems to help you figure out what's wrong because it's all becoming a bit more foreign to you. and you can just have the agent try to make changes on your behalf to fix things and hope to God that it doesn't make things worse. if all of this isn't exciting enough, you then give each engineer and even non-tech team members their own access to the ai tools and agents and models of their choice which easily costs an extra few hundred dollars per month per employee at best. in the worst case, you have someone on the team blow through the team's monthly AI spend by a significant margin by accident using the best models in fast mode because they were too impatient to just use the sota models at normal speed. and spend will likely only go up btw. and if you're not reading between the lines here, product work slows because everyone is playing with agents to learn how to use the agents more efficiently in the hopes that it's a magical bullet that solves all of the woes in software engineering and building production systems. and now you need this magical bullet to work because you're falling behind to teams who maybe aren't distracted spending all this time and money trying to make this all work. but you're definitely going to catch them. once you've figured this out, you'll 10x or 100x your output and leave them in the dust! or... you could just have engineers start coding by hand again before it's too late and becomes a lost art. you can even make modest and tasteful use of ai, but without doing all of the above. i actually miss the days of supermaven and early cursor. they were so simple and actually removed some friction and some of the annoying parts of coding.

• 
  Gene Sobolev (@genesobolev) reported 21 minutes ago

  @ahall_research A counter argument: GitHub is below 95% availability, or down for 20 days per year. It has some of the best devs in the world working on it. The complaint is about Canvas being hacked and down. Vibed alternatives will be down, hacked, buggy, and a pain to maintain.

• 
  Gabe (@gabebusto) reported 22 minutes ago

  bro setting up an agent to do production work is so easy. you just need to create an account somewhere and for your agent to work remotely. cloudflare, hetzner, aws, digital ocean, etc. then pick the agentic tool, and the model, and get an api key or use oauth. then make sure in it's in a sandbox setup with the right permissions and access to your tooling like github, slack, linear, and maybe even some staging and production resources. you really need to be careful though because if agents have any write access to important stuff, it could do something really dumb like delete your database. also for the love of GOD backup your database frequently somewhere the agent can't touch. also prompt injections online can get your agent to leak sensitive env vars so you need to be careful about that. maybe limit network access or inject tokens/sensitive vars once requests leave the sandbox. you probably don't want the agent always on sitting idle, so either figure out how to give it work efficiently to always keep it busy or use some that can pause and resume with ease so you're not billed around the clock for idle resource usage. then you want guardrails in your codebase and deployment pipeline so the agent can't break things and you don't need to feel guilty not reviewing its code. because cmon, nobody wants to do that. you need to make sure your agents have as close to perfect context as possible. so maybe start building a knowledge base, move docs into the repo, or make sure your agent can easily search linear and slack and other places to build context for tasks to work on. and before each task, spend ~10-20+ mins typing things up and giving the agent as much context as possible. oh yeah and your agent ideally should be able to test its changes as completely as possible. so make sure the agent can start up the service(s) it's working on and test them. maybe you need it to open and run a browser, send screenshots, record a video, and so on of its test so you can easily review it in the PR. you also want a bugbot setup in github (if you're still using github at this point) to help scan each PR for potential issues the agent missed. and the agent should be able to automatically address any bugbot findings, fix them, run more tests, and push those changes, and run in a loop until no more bugs are found by the bugbot. i forgot to mention, you probably don't want your agent's code just yolo shipping into **** with no guards in place _after_ it deploys. allow the agent to setup it's new features and code behind feature gates or experiments and do a gradual rollout in case there are any catastrophic problems. then you'll want automatic rollback if issues are detected. and there's probably stuff i'm forgetting, but you get what i'm saying right? it's really not that hard. then you need constant vigilance of your codebase and create lots of skills to help deslop work the agents are doing, maybe create an anti-entropy agent (_another_ agent!) to hunt for growing complexity and auto-create PRs to try and fight to reduce the size and complexity of the codebase. then you'll inevitably have incidents caused by code written by agents that was never reviewed by humans, and either you or yet-another-agent will take a look at your production systems to help you figure out what's wrong because it's all becoming a bit more foreign to you. and you can just have the agent try to make changes on your behalf to fix things and hope to God that it doesn't make things worse. if all of this isn't exciting enough, you then give each engineer and even non-tech team members their own access to the ai tools and agents and models of their choice which easily costs an extra few hundred dollars per month per employee at best. in the worst case, you have someone on the team blow through the team's monthly AI spend by a significant margin by accident using the best models in fast mode because they were too impatient to just use the sota models at normal speed. and spend will likely only go up btw. and if you're not reading between the lines here, product work slows because everyone is playing with agents to learn how to use the agents more efficiently in the hopes that it's a magical bullet that solves all of the woes in software engineering and building production systems. and now you need this magical bullet to work because you're falling behind to teams who maybe aren't distracted spending all this time and money trying to make this all work. but you're definitely going to catch them. once you've figured this out, you'll 10x or 100x your output and leave them in the dust! or... you could just have engineers start coding by hand again before it's too late and becomes a lost art. you can even make modest and tasteful use of ai, but without doing all of the above. i actually miss the days of supermaven and early cursor. they were so simple and actually removed some friction and some of the annoying parts of coding.

• 
  kaleb (@KalebAutomates) reported 24 minutes ago

  Days after the CEO came on this platform and **** on the people who made him rich with a massive lay-off. Coinbase issues with AWS. Before this it was Github Before that it was Cloudflare Before that it was AWS itself All of which just happened to follow an announcement of AI doing the majority of coding. Funds are safe... for now.

• 
  JaminSmoke (@rasbwoy1) reported 26 minutes ago

  @github I have 70% in my premium request used percent, and seconds, literally 2 seconds later i have reached the maximum quota.... How is this possible? im not using opus 4.7 and not using gpt5.5, in the same way 30% of copilot pro+ subscription in a one request (or tokens paymode... its impossible anyway) and in just 5 seconds... Maybe I created a solar system in 5 seconds... or I gathered the knowledge from the Bible + ECMA combined... I don't know, but clearly something happened... And on top of that, I'm working on improving Copilot and its features... if you reply and I'm able to do it without the premium models until next month, when I was 70% finished, I'll tell you more about what it's about, or I'll just tell you the repository hosted on your servers... I'll wait for answers or information about what happened... but if it was a deliberate decision, I think it's terrible to do it that way.

• 
  Sharath Kuruganty (@5harath) reported 26 minutes ago

  New show: Introducing Two Minute Agent Stack. I'm non-technical, I can't code, in every ep I'll show how I use @composio to ship something in under 2 mins. In this one, I used Composio to file a GitHub issue about adding Composio to a project where I use Claude to roast AI agents. At this point I'm just helping AI help AI help AI :) Ep01 below ↓