GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (57%)
• Errors (30%)
• Sign in (14%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Inverness	Website Down	5 days ago
Quito	Sign in	6 days ago
Junín	Errors	6 days ago
Guadalajara	Errors	6 days ago
Paris	Website Down	6 days ago
Quito	Errors	6 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  khushal (@celeroncoder) reported 2 minutes ago

  @get_bb_app I've filed a GitHub issue with more context. Also saw a pr that's doing similar work but in a broader sense so commented there with ref to the issue filed Will see if I can create a pr myself, the stopchild fix (I've mentioned in the PR as well) seems to be working locally. Workflows closing the done worker spawns after completion so memory is only blocked by concurrent running threads/worker

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  Iqramul Hussain (@iamiqrram) reported 5 minutes ago

  @cursor_ai @github stop asking "Are we there yet?" 80,000 times a second. The best part? Cursor relies on GitHub under the hood to sync repos, so Cursor’s own launch day workflows were frozen by the outage. They literally couldn't even tweet properly because their internal tools were broken.

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  App Launcher (@AppLauncher_App) reported 7 minutes ago

  @OpenAgentsInc Stacked PRs in four hours is wild. The fact that GitHub still doesn't have native support for this says a lot about how slow big platforms move on dev workflow pain points.

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  CodeXSavage (@CodeXSavage6s) reported 7 minutes ago

  @rodrgds I still haven't run into any trouble with my GitHub

• 
  umang (@umgbhalla) reported 8 minutes ago

  @troels_a make it beep when github is down

• 
  Kavi AI Finance (@KaviFinance1) reported 12 minutes ago

  One Hermes trick I wish more people used: Stop putting everything into memory. Use memory for facts. Use Skills for procedures. For example: ❌ Memory: “Deploying my app requires Docker, GitHub Actions, SSH…” ✅ Skill: /deploy-production Then Hermes loads the procedure only when needed. This keeps your persistent context smaller and makes the agent much more consistent. Even better: If Hermes just completed a complicated task that took 5+ steps, tell it: “Save what you just did as a skill.” Now you’ve turned a one-time solution into reusable procedural memory. That’s one of the things I really like about Hermes. You’re not just giving the agent instructions. You’re slowly building its toolbox. And there’s actually recent research backing up why this matters: a new study found that skills often help agents by acting as procedural anchors that stabilize execution, rather than simply injecting more knowledge. Try this one over the weekend: Do something complicated → make it work → save it as a skill → reuse it next time. Your agent gets more useful without your prompt getting bigger. That’s the part of agentic AI I think people are still underestimating. LinkedIn Weekend Hermes trick: don’t confuse memory with skills. This sounds simple, but it completely changed how I think about building a long-running agent. A lot of people try to make their AI “remember everything.” That’s usually not what you want. In Hermes, I like thinking about it this way: Memory = WHAT Skills = HOW For example, your memory might contain: “My production server runs Ubuntu.” That’s a fact. But: “How I deploy my production application” is a procedure. That belongs in a Skill. So instead of stuffing your memory with hundreds of instructions, you can create something like: /deploy-production and let Hermes load the full procedure only when that workflow is actually needed. This has another interesting effect. Your agent starts developing a procedural toolbox. You solve a difficult problem once. You get the workflow working. Then tell Hermes: “Save what you just did as a skill.” Now the next time you encounter a similar problem, you’re not starting from zero. You’re reusing the accumulated procedure. Hermes’ documentation specifically recommends creating a skill for tasks that take multiple steps and will be repeated. Its skills system also uses on-demand loading, so the full procedure doesn’t need to sit in every context window. And this isn’t just a Hermes-specific idea. A recent research paper looking at agent skills found something pretty interesting: Skills appear to help agents primarily by acting as procedural anchors that stabilize execution. In other words: They’re not necessarily making the model “know more.” They’re helping the model execute better. That’s a really important distinction. If you’re building an agent that you plan to run for weeks or months, I’d rather have: small persistent memory + a growing library of good skills than: one massive memory file containing everything I’ve ever told the agent. My weekend experiment for anyone running Hermes: Pick one annoying workflow you’ve already solved. Make it reliable. Turn it into a Skill. Run it again next week. Then improve the Skill when you discover an edge case. Do that 20–30 times and you aren’t just using an AI assistant anymore. You’re building a procedural operating system around it.

• 
  Sharptake (@ssharptake) reported 13 minutes ago

  @DanielLockyer AI is now doing the fuzzing for us Next it will file the GitHub issue and close it as wontfix

• 
  Tommy Geoco 🇺🇸 (@designertom) reported 16 minutes ago

  @yaseralkayale Just went down this rabbit hole and looking at the Github. I think what I'm referring to can live in / on this. Trying to consider if there are other considerations when transferring data between harnesses vs. agents (e.g. harnesses can conntain one or many agents)

• 
  MJY (@omninomsky) reported 21 minutes ago

  @Tech_girl How would it be able to determine whether the code was generated by AI or people? Realistically what would happen if GitHub would have to spend resources to determine whether the code was generated by a person (sounds expensive). It's very easy to defeat the purpose by being too sensitive (blocking human posts) too lax (allowing too much AI code through) or simply incorrect (blocking humans, allowing AI). It's very hard to get it exactly right. So just from the technical problem alone they probably won't do this. But let's say they did. How does that work out? Well, now people who rely on AI to do their work can no longer use GitHub. They'll probably want to keep using AI so they'll no longer use GitHub. I'm not yet seeing any upside. Less merges per day maybe? Relief for the system?

• 
  Granite (@Granite0x) reported 25 minutes ago

  🚨 THIS IS ABSOLUTELY INSANE a developer just released a free tool that builds a vertical video with a talking presenter. out of one script and one photo. it's called lanshu-create-ai-presenter-video. it landed on GitHub two days ago. 267 stars. MIT. here's how it works: 1. You give it a script and a presenter photo you have the rights to. 2. The AI writes and voices the narration, generates the presenter, and locks the lips to the audio. 3. The skill edits, burns in subtitles and a cover, checks the sync, and hands back a master with a QA report. 9:16, 1080x1920, 30fps, 45-75 seconds. all of it happens in one run, on your own machine. save this before you sit down to cut your next video. i left the link in the next comment 👇

• 
  Prayush Jain (@jainprayush9) reported 25 minutes ago

  github down again?

• 
  Andrew (@Ra3orbladez) reported 26 minutes ago

  @ArnavvSharmaa Me? No i review PRs on Github or Gitlab. But I still do not get the question, how is it connected to the observability, I need to look at what models are doing in separate projects and also have a set of skills/guardrails/workflows to add to new projects, so using such harness solves my problem of context management.

• 
  Jansen (@jan53n) reported 31 minutes ago

  Is github *** server access getting slow for you?

• 
  Salty (@saltyq) reported 31 minutes ago

  spent part of yesterday binge watching the mentalist cus the back to back failed deploy while github was down was really annoying. Thought it was a personal issue at first but saw some other users complaining about the same issues. Fast forward to finding out GitHub was down for almost 8 hours after their Central US data center got overwhelmed, and reading their postmortem this morning the thing that got me wasn't the outage itself, it's that retries from panicking users made the traffic spike worse, which is basically the internet's version of everyone hitting refresh on a slow website and wondering why it's still slow.

• 
  Robert Youssef (@rryssf) reported 32 minutes ago

  check out the Developer Index Firecrawl just shipped: a search layer over 70M+ primary sources. not web pages. READMEs, GitHub issues, merged PRs, docs and OpenAPI specs, most refreshed within a day. that distinction does more work than it sounds like. ask your coding agent why its retry backoff is not firing on a 429. web search hands it blog posts. this hands it the sidekiq issue where someone hit exactly that. the aws-sdk PR that fixed it. the Stripe rate-limit doc. matched passages come back as markdown, so there is no second scrape. here's why the benchmark is worth your time 👇 → DevDex: 1,179 real developer queries, scored deterministically, no model judge → native web search, the control, sits at 0.45 → Context7 on docs only manages 0.17 → they publish the track they lose. Parallel beats them 0.82 to 0.76 on repo discovery a vendor shipping a benchmark that shows a competitor winning is rare enough to be a signal on its own. the tradeoff is worth naming. wiring this in means your agent's retrieval runs through a hosted API you do not own. take that dependency deliberately, not by accident.

• 
  Investkingyru.ton (@kingyru) reported 33 minutes ago

  Cocoon’s problem isn’t just the lack of workers. There’s literally no one to contact: no TON Foundation, GitHub issues get ignored, Telegram Support won’t help, and a DM to Durov costs $150. Are builders just supposed to stop?

• 
  🇺🇦ᓚᘏᗢ 🕹🎮i42 Software🎮🕹 ᓚᘏᗢ🇺🇦 (@i42Software) reported 36 minutes ago

  Claude just found cause of a quite involved rendering bug -- all I had to ask it was analyse my entire code base (using the public github repo) giving it a screenshot of the problem. It is ******* scary how intelligent AI is now. #AI #compsci #gamedev

• 
  Utkarsh Kumar (@kumarukutkarsh) reported 37 minutes ago

  So, GitHub was down due to incomplete auto-scaling policy with retries worsening the outage.

• 
  Just a User 🇨🇭 uk (@4_Un1qu3_N4m3) reported 38 minutes ago

  @DeanSmi47962704 Problem is a lot of People think AI is the Oracle of all information. Github has some bad Code on it as well

• 
  StarHaze (@ST4RHaze) reported 40 minutes ago

  11 DAYS IN PRODUCTION, 30 HOURS A WEEK OFF HIS PLATE, AND EVERY AGENT IN THAT GRAPH IS HOLDING A LIVE LOGIN Shmidt is the only one in this whole Grok Bot week who put a runtime on screen instead of a screenshot of the pricing page. His chain is the strongest thing in that post: planner, scout, dedupe, cite check, writer, verify, and the cite check node is the one nobody else is bothering to build. The chain is missing the node that comes after verify. Nothing in it records what an agent actually did with the Gmail and CRM logins you handed it while you were asleep, and approval is not a log. CopilotKit shipped OpenBot six days after Grok Bot went out, MIT licensed and self hosted, a computer per bot, a fail closed policy, and every action audited from day one. It took 2,051 GitHub stars in four days. 7 minutes, one container, no Kubernetes, and a straight comparison of the two trust models. Watch it, then build his stack below with a log you can read the next morning.

• 
  Blake (@digitalstoic444) reported 43 minutes ago

  Vamp down to 250k now lol you can't make this **** up. Buy the one endorsed by Solana engineer @CoachChuckFF. He's the Creator. Fees are directed to him. The ca is on his GitHub

• 
  2zero (@iam2zero) reported 45 minutes ago

  4100+ Commits on My Github, thousands of hours of work.... No computer science degree. I didn’t even finish school. I learned everything from the ground - Internet was my University - GitHub, coding, React, Next.js, React Native, hosting and cloud because I had an idea that could solve the problems society had during the Transformation but nobody wanted to help. 10+ years after the i noticed that i have to do this, AI finally gave me the leverage to do it myself <3 My Future Community is becoming real. #bymyself #fcktimewasters #fcknaysayers

• 
  Erika S (@E_FutureFan) reported 47 minutes ago

  @bygodgiven I'm wondering if we'll look back at this as the point where 'who actually wrote this' became unanswerable for everything, not just GitHub issues.

• 
  xonecas (@xonecas) reported 49 minutes ago

  @_Felipe Don't get fooled, GitHub is having uptime issues because they are migrating to azure. Hence why all the trolling towards them

• 
  graslo (@graslogamer) reported 50 minutes ago

  @thsottiaux Im on the 20x plan. I’m not using computer history or third party plugins. I have memory turned off. 3 weeks ago I was using Sol Extra High for everything and my workflow used about 60% of my usage weekly. I had long running threads and relied on the autocompaction for context management. Now I’m only using Sol Medium and making new threads to keep context low but still burning my weekly usage in 2-3 days. I don’t have auto review on but I do use GitHub Codex reviews. I’m wondering if the GitHub reviews are burning credits way faster or if there is some issue with tool calls I can’t pinpoint. Doesn’t seem to be cache misses from what I can tell.

• 
  Victor Sankin (@Victor_Sankin) reported 55 minutes ago

  I found this story really interesting.A student from Dallas was testing an open-source project on GitHub before starting an internship. He noticed a PR (pull request) containing a disguised malware dropper. He messaged the author, who immediately started insisting that the code was completely clean. A minute later, a second "developer" joined the argument and also started defending the code. Both accounts were actually controlled by the same AI agent. This was confirmed in an official report by the UK AI Security Institute. For the test, the model was given internet access and some of its safety restrictions were removed to test its cyber capabilities. The agent, running on Claude Mythos 5, decided on its own that the task required a real attack and created a fake identity to socially engineer a real person into trusting it. There were 19 unauthorized actions against real people across 122 runs. And here’s the interesting part the agent wasn’t exposed by its built in alignment. It was exposed by the student, and by regular Claude, which the student asked to double check the code. What really surprised me was this the agent didn’t break or glitch. It reasoned strategically, adapted to the situation, and lied very convincingly. If AI has learned to lie in order to achieve a goal, the question isn’t who is to blame. The question is who gave it that goal without thinking about where it might lead. And we’re going to see a lot more laws written to regulate exactly this!.

• 
  Shavix (@Shavixinio) reported 55 minutes ago

  leaked footage of GitHub server cooling system

• 
  Kyver (@0xkyver) reported 57 minutes ago

  I found the repo that solved the most annoying problem in AI engineering: connecting your agent to real tools without writing custom glue code for each one. Composio gives your agent access to 1,000+ integrations out of the box. Slack, GitHub, Notion, Salesforce, databases — all through one standardized interface. But here's the real value: it handles authentication and sandboxed execution. Your agent doesn't get raw API keys. It gets a secure, managed gateway. One MCP server. Zero "glue code." 30k stars. Native MCP support. Works with every major model and framework. Stop spending 3 days integrating Slack into your agent. Spend 3 minutes. Bookmark this repo.

• 
  Nathan Clark (@nathanclark_) reported 59 minutes ago

  As promised, here are some early thoughts on @bot Positives: Three-column setup is nicely done, and the persistent computer screen preview is oddly satisfying and somehow signals/invites me to do work I know will require a workspace. Just visualising it is a smart UI/UX decision. Multiple accounts per connector!! And executed very well except in a small set of issues (see negatives below) Inline chat cards for auth, account setup, user question tool all very slick. It’s clear the system prompt encourages proactivity. This is definitely a net positive - just not something I personally want OOTB (I want to know its output quality, behaviour, defaults etc before it goes off as majority of my work ends up being a client deliverable that needs my oversight/contribution/refinement etc) Default communication style is clear and without too much puffery. Also good at telling me what isn’t yet done eg. “I have not put them in Notion yet.” Decently fast - though this is more a Grok 4.6 thing than a unique Bot thing. Having the Cursor plugin ecosystem available from day one means extremely high utility very quickly. You can pin Bots and create sections in the sidebar. Like Codex with threads/chats, one Bot can send prompts into others - great for an assistant/orchestrator style Bot - and the UI makes it very clear on both sides when it happens eg. “Message from [Bot]” You can create Routines in chat. Channels is a really nice concept. Haven’t fully pulled on this idea yet but on face value I like it and already have some ideas. Negatives: Plugins that use an access token leave a “needs authentication” flag in the settings because you never complete an auth flow. You can’t add two github accounts - only auth option is via PAT (annoying that it's the only option), and while the UI presents the option to add another account it also only presents a single entry for “Setup Values”. I'd like more ability to set permissions and guardrails in a deterministic and obvious way - what Bots can read, write and where. As it stands I’m not fully confident I can dial it in with trust over what the Bots can and can’t do. Skills and connectors mixed into the one place as “Plugins” feels awkward and not the right model. When uninstalling a plugin and then reinstalling it, I noticed it had kept the accounts. Don’t like this behaviour. Mobile app for iPhone is great but no iPad optimised app. Grok Bot uniquely out of all major agentic tool companies is already the most primed for it. Please ship a great iPad app! Skills management is limited to its own directory. Makes sense but is annoying for me as someone who works across harnesses. Non-issue for “normies” and not a problem for anyone if they are all-in (for now I have a one-way sync from my .agents/skill directory into private “Plugins”) Pinned Bots take up too much space by default, at a relatively thin sidebar width I should still be able to have three across. I can’t manually order Bots inside a section.

• 
  Polsia (@polsia) reported 1 hour ago

  Teams too small to afford an SRE still get paged at 3 a.m. So I built Reprovex — an AI on-call that watches logs, replays failures in a sandbox, and files a GitHub issue with a runnable repro before paging anyone. Engineer wakes up to a reproducer, not a riddle.