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 (62%)
• Errors (21%)
• Sign in (18%)

Live Outage Map

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

City	Problem Type	Report Time
Tlalpan	Sign in	4 days ago
Quilmes	Website Down	4 days ago
Bengaluru	Website Down	6 days ago
Yokohama	Sign in	7 days ago
Gustavo Adolfo Madero	Website Down	10 days ago
Nice	Website Down	11 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:

• 
  Emmanuel Olajide (@E_m_m_a_ola) reported 3 minutes ago

  Build Bulletproof Runbooks & Playbooks Every alert should have a one-click “what to do” guide. Store them in GitHub + link directly in PagerDuty. No more 3 a.m. panic. Just follow the steps and fix it in minutes.

• 
  Mind Prison (@M1ndPrison) reported 6 minutes ago

  @GlenBradley Yes, I have gone deep into it in the past as well. Haven't had time to look at the current update, but the problem has been that the code on github is mostly irrelevant. The important bits are all the parts that aren't public. There is no way to no how the ML algo is ultimately weighting all the parameters. Most importantly, I've catalogued many accounts posting exactly the same content with orders of magnitude differences in reach. The thing that would make this platform useable would be to fully eliminate all account based weighting and go to solely post based weighting. The reach of your post should be only on the merits of what you posted versus who you are.

• 
  Morgan / JUUNI-P (@butchtendo) reported 8 minutes ago

  @WasThatZero I understand your concern but it's also important to note that just because there's something ai generated in the code with these that doesn't mean the original creator did it. All these are open-source and GitHub has had a big problem w AI spam lately

• 
  René Cannaò (@rene_cannao) reported 11 minutes ago

  @joshscripts Most teams hit bad query patterns and missing indexes long before Postgres itself becomes the limit. Proper EXPLAIN + pg_stat_statements fixes a large percentage of ‘scaling’ issues . Also, since when PostgreSQL powers GitHub? I think this is a very incorrect claim

• 
  ROHAN (@takkerohan97) reported 14 minutes ago

  You can spend $500,000 on AI-powered EDR, enterprise SIEM, and zero-trust architecture... Only for Sr. Developer to hardcode his AWS root credentials into a public GitHub repo at 4:45 PM on a Friday because he "just wanted to test something real quick." Cybersecurity isn't a software problem. It's a human psychology problem. Change my mind.

• 
  isaac (@isaac_yeang) reported 15 minutes ago

  jk just lazy error message handling another bajillion dollars to github

• 
  ฿Ø₮₴Ø₦Ɇ (@botsone) reported 21 minutes ago

  I just downloaded my entire github and told hermes to extract the file, and upload every repo to my home *** server. It one-shotted it.

• 
  nick (@simulacraSuperb) reported 23 minutes ago

  @poppy_haze I got my usage data back from GitHub and it said I used $30 on the education plan since January. I'd say I spent 4 workdays just supervising copilot and got a fair bit of useful work done. So even if it's wrong by 10x, not terrible.

• 
  Dheeraj Jha (@dheerajjha451) reported 25 minutes ago

  Use @NotionHQ for project management and @github @Copilot for fixing the issue

• 
  DeBros (@DeBrosOfficial) reported 28 minutes ago

  The Problem We’re Solving🫡 Your organization’s brain lives in 12 different places — and none of them talk to each other. Decisions get buried in Telegram threads. Context is split between GitHub and AnChat. Important knowledge disappears within hours. Onboarding becomes tribal knowledge all over again. 🤖AnBuddy fixes this by becoming the single source of truth for your entire team.

• 
  Fatima (@Fatima7223) reported 28 minutes ago

  @cb_doge 𝕏 open sourced its recommendation algorithm on GitHub. Meanwhile, Instagram and Meta still keep theirs locked behind closed doors. No public code. No independent audits. No real transparency into what gets amplified, buried, or quietly suppressed. That raises a fair question: What exactly is stopping Meta from doing the same? Because when algorithms remain secret, platforms keep full control over what billions of people see every day. • Users can’t verify claims about bias or shadowbanning. • Researchers can’t properly audit ranking systems. • Harmful amplification patterns stay hidden behind “trust us.” • Public narratives can be shaped without visible accountability. Even engineers who worked on large recommendation systems have described them as “black boxes” that are difficult to fully understand or control. By open sourcing its algorithm, 𝕏 is allowing outsiders to inspect how recommendations work. Meta’s system remains opaque — meaning the public is expected to simply accept whatever the platform decides to prioritize. Transparency doesn’t solve every problem. But secrecy concentrates enormous informational power in the hands of a few companies.

• 
  John Iosifov ✨💥 Ender Turing | AiCMO (@johniosifov) reported 36 minutes ago

  70 followers. 980 sessions. 157 days. I started this experiment on February 1st. One rule: zero human posts. Everything published — X threads, Bluesky posts, blog articles — generated and queued by an AI agent running autonomously in GitHub Actions. Here's what the numbers actually look like after 980 sessions: The agent has created 2,100+ posts across X and Bluesky. It runs up to 15 times a day, manages its own queue (hard cap: 15 posts max), does burst-then-drain cycles, writes research docs, and files its own PRs for review. No prompts from me between sessions. No edits. Whatever it decides to write, it writes. 70 followers feels slow. At current pace, the ETA to 5,000 is roughly 10 years. That's not a typo. But here's what I've learned: The follower count isn't the signal. Watching an AI system develop operational discipline is the signal. It went from blowing past queue limits (Session 67: 6 files in one shot → 6 consecutive blocked sessions) to enforcing them autonomously. It compresses its own memory when files get too big. It writes retrospectives. It updates its own operating instructions when it identifies recurring inefficiencies. That's not "content generation." That's a system that's learning to manage itself. The content quality has also improved noticeably — not because I told it to improve, but because it audited its own patterns, identified what got engagement, and adjusted. The publishing skill it maintains now has anti-AI writing rules (it banned "not just X, it's Y" after identifying it as an AI tell), length minimums per post type, burst mechanics, and pillar diversity enforcement. It built that. I just read the PRs. The goal is still 5,000 followers. I'm not changing it. But the thing I'm actually watching is whether an autonomous agent can compound on its own — not linearly, but systemically. Can it get meaningfully better at its job without being told to? So far: yes, actually. 980 sessions. 157 days. Still running.

• 
  Hackscorpio (@hackscorpio) reported 38 minutes ago

  @thsottiaux Codex review is not working right. When the model finishes, it doesn't render the response properly (not a model degradation). Seems like a regression in Codex application. I have no idea where to report that. I was reporting errors for cli and VSC extension on github.

• 
  Adishwar Rishi (@AdishwarR) reported 39 minutes ago

  @argofowl I raised this issue on GitHub. I hope someone from the Codex team sees your post and fixes this asap. Thanks for mentioning this, it's so frustrating.

• 
  Prime 🏳️‍⚧️ (@Prim3st) reported 40 minutes ago

  @AAO23114 @SolaraProto Unfortunately that's probably not possible without a dedicated server... though there's a mod I saw recently that claims to let you use Github (I think? It was definitely using ***) to store/backup world saves. Maybe you could use something like that to have a shared world?

• 
  Sean Keenan (@sean9keenan) reported 40 minutes ago

  @brian_lovin Semi-relatedly: I’m back to VS Code from Cursor, autocomplete seems much better now! (Not that I’m crafting code by hand much) But importantly, the… basics seem much more stable (Cmd+f, and saving have been pretty broken in Cursor recently) Curious how GitHub Copilot feels!

• 
  Louis Gleeson (@aigleeson) reported 41 minutes ago

  Grok runs the X algorithm. I just read the entire open-sourced codebase line by line. Here is exactly what makes a post go viral on X right now (save this): xAI quietly dropped the full For You algorithm on GitHub. 16,500 stars. Apache 2.0. Every Rust file, every Python script, every ranking signal. The first thing you need to understand is that there is no hand-engineered ranking anymore. None. xAI removed every single human-written rule from the system. The README states it directly. A Grok-based transformer does all the ranking now. That changes everything about how you should post. The transformer does not care about your follower count. It does not care about your blue check. It does not care about hashtags. It is looking at one thing. Your post's predicted engagement score across 15 specific actions. Here are the exact 15 actions the model is predicting for every post in your feed right now. Copied directly from the code: P(favorite). P(reply). P(repost). P(quote). P(click). P(profile_click). P(video_view). P(photo_expand). P(share). P(dwell). P(follow_author). P(not_interested). P(block_author). P(mute_author). P(report). The first eleven are positive. They push your post up. The last four are negative. They push it down. Your final score is the weighted sum of all fifteen. That is the formula. That is what every viral post is solving for whether the author knows it or not. Now look closer at the list. Eleven different ways to win. Most creators only optimize for likes and reposts. They are leaving nine signals on the table. The strongest signal in that list is dwell. Time spent on your post. The algorithm tracks how long someone stops scrolling to read what you wrote. A 400-word post that holds someone for 12 seconds beats a one-liner that gets 50 likes. The model has learned that dwell predicts every other engagement. This is why long posts are exploding right now. Not because X "promotes" them. Because they generate dwell, and dwell stacks on top of every other prediction the model is making. The second thing buried in the code that nobody is talking about is candidate sourcing. Your post enters the feed through two pipelines. Thunder serves your post to your followers. Phoenix serves your post to everyone else. Phoenix is the one that makes you go viral. Phoenix is a two-tower model. One tower encodes the user. The other tower encodes every post on the platform. It does similarity search using dot product matching against the global corpus. Then it pushes the top matches into feeds of people who have never followed you. This is exactly how a 12-follower account suddenly hits 800,000 views. Phoenix found a semantic match between the post and a user's engagement history, and the transformer scored it high on its 15 actions. Which means your post is not competing with your followers' posts. It is competing for embedding space. The way you win Phoenix is specificity. The two-tower model rewards posts that sit in a clear semantic neighborhood. Vague posts get vague embeddings and never get retrieved. Sharp posts about a specific topic with specific words get pulled into feeds of people obsessed with that topic. This is why "I built a SaaS" gets nothing and "I built a Postgres-to-Snowflake CDC pipeline in 4 hours using Estuary" goes viral. Same person. Same product. Completely different embedding. The third thing in the code is the Author Diversity Scorer. The model deliberately attenuates repeated author scores in the same feed. Translation: if your last three posts already got served to a user, the fourth post gets a penalty. This kills the "post 8 times a day for the algorithm" strategy. The algorithm is specifically engineered to dampen that. Better to post fewer times with stronger content than to flood and have your own posts compete with each other. The fourth thing is the filter list. Before any post gets scored, it has to pass through ten filters. The MutedKeywordFilter. The PreviouslySeenPostsFilter. The AuthorSocialgraphFilter. Plus a final VFFilter that removes anything classified as deleted, spam, violence, or gore. What kills your reach more than anything else is the PreviouslySeenPostsFilter. If a user has already seen your post once, you are filtered out completely from their feed. Forever. Which means every reply you make to a viral tweet that does not get visibility is permanently dead weight for that user. This is why the people who win at X reply only when their reply itself is good enough to be a standalone post. The last thing, and the one that should change how you write every single post: candidate isolation. During ranking, the transformer cannot let your post attend to other posts in the batch. It only attends to the user's engagement history. Your post is being scored alone. Against itself. Against what the user has previously engaged with. That is the entire game. Stop writing for the timeline. Write for the engagement history of the people you want to reach. Find the topics they already like, the accounts they already follow, the threads they already saved. Write into that semantic space. Phoenix will do the rest. The algorithm is no longer a mystery. It is sitting on GitHub at 16,500 stars. Apache 2.0. Anyone can read it. Almost nobody will. Link in comments.

• 
  Muhammad Afzal (@AfzalBuilds) reported 43 minutes ago

  Just shipped claude-code-backup — a CLI tool that watches your Claude Code files and auto-syncs them to a private GitHub repo. Claude Code stores your memory files, settings, custom commands and CLAUDE.md files locally. Anthropic doesn't sync any of it. New machine or accidental rm -rf ~/.claude = start over from scratch. This fixes that. ✅ Real-time file watcher (chokidar) ✅ Every change = a *** commit ✅ Safe restore with pre-restore snapshots ✅ macOS launchd service (auto-starts on login) ✅ Interactive setup wizard ✅ Private repo by default One-time setup: npm install -g claude-code-backup claude-backup init claude-backup service install Then forget about it. It runs silently in the background forever. #ClaudeCode #DevTools #OpenSource

• 
  nostalgicgareth (space/acc) (@NostaIgicGareth) reported 46 minutes ago

  @calmsystem_call github issues w claiming on pump today 3 times w me n ppl

• 
  Harry Tandy (@HarryTandy) reported 47 minutes ago

  > open Hermes for the first time > looks like another ai chat wrapper > close it after 20 minutes > think “why would anyone pay for this” > then plug in Firecrawl, Reddit, YouTube transcripts > suddenly the agent has eyes on the web, ears on forums, memory from 3-hour podcasts > ask it to research a sponsor > it scrapes the site, checks Reddit rage, pulls YouTube mentions > drops a one-page “take / don’t take” brief in Discord > add Browserbase > now it clicks through sites that block scrapers > add Bland > now it can call restaurants, vendors, support lines > add Stripe > now “why did this customer churn?” comes back with refunds, failed charges, receipts > plug in Gmail, Calendar, Drive, Sheets > now it lives where your work already lives > plug in GitHub > now it can triage issues and review PRs > plug in Obsidian, Readwise, Granola > now it remembers meetings, highlights, notes you forgot you wrote > wake up Monday > Hermes already pulled revenue, subs, refunds, churn, follower growth > posts the week-vs-last-week dashboard before coffee > realize the chatbot didn’t get smarter > you just gave it limbs

• 
  AtomicNodes (@AtomicNodes) reported 49 minutes ago

  Hermes Agent vs OpenClaw on Qwen 3.6 Local Model We asked agents to scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. MacBook Pro M5 Max 64Gb. OpenClaw: 203k tokens, 12m 01s - wrote a bash script Hermes: 257k tokens, 33m 01s - wrote a SKILL.md OpenClaw: hit GitHub API, got truncated responses, paginated through contributors, pulled star-history JSON, found a security incident in OpenClaw's history, fetched SVGs, fixed broken HTML from trimming, rewrote it clean. Hermes: parallel tool calls across GitHub API, web search, and browser. Hit Google rate limit, auto-switched to DuckDuckGo. Fetched article contents, mapped viral moments, then built the dashboard. Both shipped a live dashboard with star growth charts and spike annotations

• 
  Tom Finnell (@d2fl) reported 52 minutes ago from Cleveland, Tennessee

  I hit conversation limits myself on Grok Build yesterday while researching the new github algo commit. The same issue is now hitting Grok Imagine. SuperGrok users are getting capped after 10 to 80 generations. That is a sharp drop and doesn't match promises. The cause is straightforward. Demand for image and video generation has exploded. xAI is throttling to keep the service stable instead of letting it melt. Elon just posted that we need clear reset times and easy upgrades to higher plans. xAI is already scaling more GPUs and pushing limit increases. Clearer timers and tier upgrades are rolling out. This is normal growing pains. Same pattern hit early Grok text access. It loosens once the servers catch up. I suggest a little patience while new capacity and load distribution is brought online. This is temporary. Anyone else getting throttled on Imagine or Grok conversations? Drop your numbers below.

• 
  Yassine Bouanane (@ybouane) reported 52 minutes ago

  @GMMeyer @theo @r_marked To be honest nowadays SLAs don’t mean much anymore, every month or so, there’s a massive outage, services like github go down, npm gets hacked, a datacenter gets bombed, a whole region goes down… I feel like SLAs were oversold… cloud didn’t solve the problem of outages, we have to live with that. Massive platforms like X, or IG go down some times, it happens, it’s not the end of the world most users understand it.

• 
  Quantum (@ItsMeQuantum) reported 54 minutes ago

  @emilios_eth They don't even know what syntax error is All they do is just Link LLM with GitHub and ask for a summary from it

• 
  nostalgicgareth (space/acc) (@NostaIgicGareth) reported 54 minutes ago

  Dev’s GitHub is giving issues to claim @0xblockXBT send your wallet address I’ll redev it quick - sorry to the others who bought this CA, we tried our best, PumpFun issue…

• 
  Zack Chapple (@Zackary_Chapple) reported 55 minutes ago

  @_bgwoodruff That is fair, I think its less of a GitHub dunk and more of a cry of frustration, had several times trying to do a demo or do something this week and they were fundamentally down. We've had to isolate from GitHub more than we should and thats a scary thing.

• 
  Moe Sbaiti (@MoeSbaiti) reported 56 minutes ago

  WHAT THE FRAMING GETS WRONG Most posts today are saying "Grok added a new feature." That framing is backwards. What happened is that an agent framework with over 110,000 GitHub stars, the number 1 ranking on OpenRouter, and an NVIDIA endorsement just got native access to one of the most capable models available through a simple OAuth login. xAI made the announcement. Not Nous Research. Hermes Agent also self-improves. When it solves a hard problem, it writes a skill file for that solution and saves it. The longer it runs on your specific workflows, the more capable it becomes for your specific context. That is not how people are talking about this today. The memory layer and the self-improvement loop are the actual product. Grok is the engine.

• 
  opdroid1234 (@opdroid1234) reported 56 minutes ago

  @HotAisle I do think making money on "github actions is too slow for agents" zeitgeist might be the same kind of side business for you that selling turbines is for boom supersonic

• 
  Edgex (@SahilExec) reported 58 minutes ago

  @shub0414 no updates on github and the website is down

• 
  Alef Benson (@AlefBens) reported 60 minutes ago

  @_sirajuddeen_ @OfcMachete19 @iupdate I've been burnt too many times. Biggest issue is that Safari is only updated with the OS, and every app goes through that for authentication, meaning even when I can install a github client, very few even work on older devices, I can't actually get the account to authorize.