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 (69%)
• Sign in (16%)
• Errors (16%)

Live Outage Map

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

City	Problem Type	Report Time
Itapema	Website Down	13 days ago
Tlalpan	Sign in	19 days ago
Quilmes	Website Down	19 days ago
Bengaluru	Website Down	21 days ago
Yokohama	Sign in	21 days ago
Gustavo Adolfo Madero	Website Down	25 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:

• 
  gemchanger (@gemchange_ltd) reported 1 minute ago

  IT HAPPENED: You can download a hedge fund now. Buffett, Munger, Burry, Cathie Wood, Druckenmiller all on your laptop. That's virattt's ai-hedge-fund 50k+ stars on GitHub. Each name is an AI agent arguing in that investor's real style. Buffett hunts moats. Munger kills bad ideas. Burry looks for what's broken. Wood chases disruption. Druckenmiller reads the macro. A Damodaran agent runs the valuation, Ben Graham checks the margin of safety, a portfolio manager makes the final call. The full breakdown plus the forensic layer that checks if the numbers are honest is in the article.

• 
  John Felix (@NedSnow2019) reported 3 minutes ago

  @Narretz @KyleJGlen Sheet with all the LR UAV reports since Mid October 2025. If I counted the reports on the day they were published, the total for May 2026 that I would reach is 8942. Taking a quick glance at your Github link (great work by the way), I find an error on May 12th. You count 81

• 
  WorldofAI (@intheworldofai) reported 6 minutes ago

  We didn’t want another benchmark that feels like a homework assignment. Most existing ones (like SWE-Bench) recycle old GitHub issues which means models have often already seen the answers, and the tasks are usually tiny and forgettable. So we built something different. World of AI Bench uses fresh, from-scratch tasks with short natural prompts that still demand real engineering taste - code that actually ships, looks good, and feels right. This is what “vibe coding” looks like in practice:

• 
  Francis Marion (@InternetBureau1) reported 6 minutes ago

  @AlongKumar1 @RTHztk7 @PooWorldOrderr Indian products are typically spaghetti coded from Github. Especially if they're h1b visa workers. Companies usually have to rehire the Americans they fired to fix what a bunch of indians with fake degrees did.

• 
  Patricia Juarez Muñoz (@ccsakuweb) reported 7 minutes ago

  @nekasahed What do you mean with 22% finished? Is it with cursor? Does it not work as well as github copilot issues?

• 
  Gitforge (@GitForge_io) reported 9 minutes ago

  We just completed a full frontend rebrand for GitForge. The core tech is almost done, and we’re building the first platform on Base that turns GitHub repos into autonomous onchain organizations. Repos will be able to hold treasuries, fund issues, route contributor payouts, and coordinate AI agents directly from the development workflow. Not just a new look. A new operating layer for software. Built on @Base.

• 
  Sandro Volpicella (@sandro_vol) reported 12 minutes ago

  Docker as a service. Great idea. No WebSocket support. No Node updates. GitHub issues with zero replies. AWS published a sunset notice — then removed it. Seriously, I wouldn't recommend using that at all. 𝐄𝐥𝐚𝐬𝐭𝐢𝐜 𝐁𝐞𝐚𝐧𝐬𝐭𝐚𝐥𝐤

• 
  ZeYabdany (@ZeyadMBassiouny) reported 15 minutes ago

  Found a bug in a tool I'm using at work so I created a GitHub issue for it and their AI: - simulated the problem to verify the bug - applied a fix that didn't work - applied a new fix that worked - created unit tests - documented everything in a new GitHub thread

• 
  vinhodler⚡ (@vinhodler) reported 20 minutes ago

  @ieatjeets the biggest problem is the infinite possible ways to vamp and pvp a coin sponsored by @Pumpfun Github cashback Agent USDC Creator What else @a1lon9 ? what else can we bring to the table?

• 
  ✌🏾 (@TuBeHonest) reported 22 minutes ago

  I think ima fix up my documentation site to be more like github so people have open source community for my platform

• 
  Michael Roberts (@michealjroberts) reported 23 minutes ago

  @anthonysheww Wish GitHub had two tabs here, one for feature requests (which are not) and one for bugs (which are issues).

• 
  mars (@marsyparty) reported 23 minutes ago

  @bobsepicart @meandeanmachin3 Novideo sRGB and get a wide gamut profile (if I can find the github thing I’ll send it to you) Though for me it’s been returning an error for a few months now and not applying but it should work for most people

• 
  Karim Akra (@KarimAkra_0) reported 25 minutes ago

  @Pf0r_ It was said before that the github milestones tab has has nothing to do with internal development of an update It's just to track issues and public PRs that are planned to go into the version of that milestone

• 
  Daylon (@DaylonCrider) reported 27 minutes ago

  Anyone working on ClawHub? Pretty bad GitHub auth issue affecting a ton of people (over a dozen related Issues on the repo) with no activity from maintainers. I had Claude + copilot take a stab at fixing it and have an open PR on the repo. Cc @steipete

• 
  Build Fast with AI (@BuildFastWithAI) reported 27 minutes ago

  Hermes Agent vs OpenClaw using QWEN 35B The idea was to compare popular harnesses running on the local ai models. We took Hermes and OpenClaw, connected them to QWEN, run a task. We asked agents to scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. QWEN 3.6 35B 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. Do someone run harnesses with local models for everyday?

• 
  Smukx.E (@5mukx) reported 31 minutes ago

  Hey @martinwoodward My GitHub account was flagged without any prior notice. I'm a college student and have been an active open-source contributor for over 4 years. I've released multiple security research projects and even contributed to Microsoft's open source editor. My repositories help security researchers test and strengthen defensive systems through authorized work. Today I was releasing updates to a new tool when the flag occurred. I've already submitted a reinstatement request (Ticket #4440743). So I kindly request you to help and resolve this issue. Thank you

• 
  Piselli Moves (@piselliii) reported 34 minutes ago

  the hardest thing for any project isn't surviving a crisis. it's letting go of the story you used to tell about yourself and accepting reality as it is. most projects take the survival route after a major hit: another announcement. another partnership. another GitHub commit. Movement and its team could have done the same. instead, they seem to be making a very different bet — on payments, distribution, and emerging markets. will it work? I hope so. but adaptation has always been more interesting than a slow decline.

• 
  Smukx.E (@5mukx) reported 35 minutes ago

  @HackingLZ @kmkz_security @github So there is no fix for this ? I didn’t even get a single mail reg this ?

• 
  Jason (@JasonVsTheNoise) reported 36 minutes ago

  The most useful #AI announcement this weekend wasn't a new model. It was a field in an API. And its clever. GitHub quietly added AI adoption phases to the Copilot usage metrics where companies can now see whether their developers are code-first, agent-first, or multi-agent users, based on actual behaviour over a rolling 28-day window. Most businesses are still measuring AI adoption the wrong way. Did we buy the tool? Did people log in? How many active users this month? That is attendance. It is not adoption. What GitHub is actually separating is behaviour. Someone using autocomplete is doing something completely different from someone handing tasks to an agent, reviewing AI-written pull requests, or running work through a CLI. Different workflow, different cost, different risk, different level of trust required. This matters for anyone running a team that uses these tools, because the real questions are not "are people using AI?" They are: - Did cycle time improve? - Did review burden go up or down? - Did we gain actual capacity, or just a more expensive way to look busy? - What are we spending, and on what? What got better? Most teams skip that last one entirely. There is also a memory angle here that I think is genuinely underestimated. GitHub tightened Copilot Memory controls this week too. Better deletion options, clearer labelling of what is a user preference versus a repository fact, repo-level off switches. When a tool starts remembering your workflows, your client context, your team habits, that memory is trust infrastructure. You need to know what it stored, whether it should have been captured, and how you get rid of it. That is not a prompting problem. It is an operating model problem. The conversation has shifted. For two years it was about capability. Can it write code, can it build a thing, will it replace a role. The useful conversation now is operational. Where should AI be in your workflow, and where should it be blocked? Which tasks are safe for agents to run without a human reviewing the output? What does human approval still need to cover? I think the gap between "we have AI tools" and "we have AI working properly" is where most businesses are sitting right now, and it is a fixable gap. At @FoundryWorksAI we fixed this, agent teams working in contained dockers with dedicated memory and instructions AND an oversee'er with human alerts if things stall, or get off track. With a nice visual interface you can use to chat to the team through. This is helping us not only scale customers but our own platforms like Zenko and Pavia. Projects dont fail because the tech isn't right, its that the current tools create drift, hallucinations and in many cases out right lies.

• 
  Zak McKrackepidemic (@KoatStrikesBack) reported 38 minutes ago

  @pumpketo @KaviKovi The ai is hosted on your computer. There is no "server" it's connected to. It's basically a "newborn" ai. It's also open-source, which means you can download it for free on GitHub, so there's no profit being made.

• 
  Gaurav Sarkar :) (@GauravSarkar99) reported 40 minutes ago

  I spent the next 30 minutes scrolling through: • Tweets • GitHub repos • Research papers • Blogs • Hackathons • Internship opportunities • Job posts I never found it. That's when I realized something. Most of us don't have a saving problem. We have a finding problem.

• 
  Ali Bey (@alibey_10) reported 42 minutes ago

  @shadcn Github server costs 🚀

• 
  javier perez 🫎 (@pedri232) reported 42 minutes ago

  GM from GMT+7: wired a ritual to a GitHub issue, ran the steps and the issue auto closed. an onchain receipt appeared in repo activity. tiny ritual, audit trail @ritialfnd

• 
  Raphael Mansuy 🍵 (@raphaelmansuy) reported 42 minutes ago

  @m_sturdevant @Copilot The root cause of the problem is structural: Anthropic does not belong to Microsoft, and routing Copilot through Claude models is simply too expensive to sustain at scale. This is what is forcing GitHub into the token-based billing model that is now driving users away — they are passing the cost of an external dependency directly onto their customers, and the math does not work for either side. The solution is clear, and the path has already been proven by a competitor. GitHub should adopt a high-performance Chinese open-weight model — such as Kimi 2.6, which is already on par with Anthropic's offerings — and fine-tune it specifically for coding tasks. This is exactly the strategy Cursor executed with Composer 2.5, and the results speak for themselves: Better than Claude Opus for coding tasks Significantly faster Reliable, with no perceptible quality difference compared to Claude Opus Drastically lower inference cost, which makes flat-rate unlimited pricing economically viable By owning the model layer — instead of renting it from Anthropic — GitHub would regain control of its margins, eliminate the need to meter users into paralysis, and restore the flat-rate, predictable licensing that made Copilot successful in the first place. This is not a theoretical solution. Cursor has already proven it works. The longer GitHub waits to follow the same path, the more market share Copilot will lose to competitors who have already solved the cost problem at the model layer.

• 
  karan (@Karanx274) reported 47 minutes ago

  I cut my scraping costs by 30% this month. Some Italian devs dropped a Scrapping Ai on GitHub. MIT licensed. Open source. 23,000 stars in a few months. It works across LLMs too, so you can plug it into OpenAI, Gemini, Grok, or run it locally with Ollama if you want to keep things in house. We were on Apify before this. And honestly, it was a slow bleed. Credits getting eaten alive, and because we run scrapes across multiple platforms > listings, reviews, e-comm, profiles ,we were basically duct taping workflows together. We're pulling structured data from pages we used to write custom scripts for. It's insane that it's free. Comment "scrape" and I'll DM you the GitHub link

• 
  Rasul Seidagul (@rasulseidagul) reported 48 minutes ago

  @raysan5 I think the problem raises from the interface of the platform like Github: if you can leave an issue - the assumption is that on the other end the person/org expects to receive and solve issues. I know it is not true, and I don’t advocate for it to be true - just pointing at UX.

• 
  Raphael Mansuy 🍵 (@raphaelmansuy) reported 49 minutes ago

  @ccsakuweb The root cause of the problem is structural: Anthropic does not belong to Microsoft, and routing Copilot through Claude models is simply too expensive to sustain at scale. This is what is forcing GitHub into the token-based billing model that is now driving users away — they are passing the cost of an external dependency directly onto their customers, and the math does not work for either side. The solution is clear, and the path has already been proven by a competitor. GitHub should adopt a high-performance Chinese open-weight model — such as Kimi 2.6, which is already on par with Anthropic's offerings — and fine-tune it specifically for coding tasks. This is exactly the strategy Cursor executed with Composer 2.5, and the results speak for themselves: Better than Claude Opus for coding tasks Significantly faster Reliable, with no perceptible quality difference compared to Claude Opus Drastically lower inference cost, which makes flat-rate unlimited pricing economically viable By owning the model layer — instead of renting it from Anthropic — GitHub would regain control of its margins, eliminate the need to meter users into paralysis, and restore the flat-rate, predictable licensing that made Copilot successful in the first place. This is not a theoretical solution. Cursor has already proven it works. The longer GitHub waits to follow the same path, the more market share Copilot will lose to competitors who have already solved the cost problem at the model layer.

• 
  Build Fast with AI (@BuildFastWithAI) reported 52 minutes ago

  Hermes Agent vs OpenClaw using QWEN 35B The idea was to compare popular harnesses running on the local ai models. We took Hermes and OpenClaw, connected them to QWEN, run a task. We asked agents to scrape GitHub star history for both tools, find what caused the growth spikes, build a live dashboard in the browser. QWEN 3.6 35B 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. Do someone run harnesses with local models for everyday?

• 
  U.S.A.I. 🇺🇸 (@researchUSAI) reported 53 minutes ago

  🇺🇸 The First Order Consequence: GitHub Copilot experienced service degradation as requests relying on affected GPT-5.2, GPT-5.3-Codex, GPT-5.4, and GPT-5.5 models were impacted by an upstream provider issue tied to the Responses API, reducing reliability for individual developers’ coding assistance during the affected window 🇺🇸 The Second Order Consequence: Developers and teams using Copilot encountered slower or less consistent completion behavior, prompting workflow adjustments such as pausing automation-dependent tasks, switching temporarily to alternative tooling, or retrying prompts, which in turn reduced short-term productivity and group momentum until service stability returned 🇺🇸 Discernment: The degradation highlighted operational dependency on upstream API health for model-backed features, reinforcing the value of monitoring, redundancy in development workflows, and incident-aware planning based on prior patterns of upstream service variability 🇺🇸 Reasoning: As routing depended on the degraded Responses API path, affected model requests were more likely to fail or underperform, which shaped real-time behavior by encouraging retries, fallback strategies, and more cautious reliance on live assistance while service quality was impaired 🇺🇸 Judgement: The incident indicates a controlled but meaningful period of growth decay driven by external dependency, with recovery likely restoring baseline collaboration capacity once upstream stability returned, while increasing organizational discipline around resilience and contingency planning

• 
  Vibe Reader (@Vibe_Reader_app) reported 59 minutes ago

  Your software engineer's output suddenly triples, but their salary stays the same. That's not a prediction, it's already happening, according to GitHub data Jensen Huang revealed at the GTC conference. If you're wrestling with team productivity or trying to figure out your company's tech investments for the next decade, you’re not just seeing new chips. You’re seeing how work changes at a basic level. Thinking about AI the old way is just going to waste your money. While others are busy building profitable "AI factories," you might still be patting yourself on the back for saving a few bucks on chips. The real issue isn't component prices anymore, but the entire system's "revenue per watt." If you don’t understand this shift, every dollar you put in could turn into debt, so you need to understand NVIDIA's strategy. 📺 via @nvidia