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 (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Trichūr	Errors	2 days ago
Brasília	Sign in	2 days ago
Lyon	Website Down	3 days ago
Tel Aviv	Website Down	6 days ago
Rive-de-Gier	Website Down	6 days ago
Itapema	Website Down	25 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Khánh Phạm (@khanhphd) reported 3 minutes ago

  Reproduce: - download mac apps - open the app is alreay slow - click sign-in in the app - open the web which has buttons "Signin with Github" -> i click this (open this web is already slow) - and omg, just loading forever or click buttons don't respond

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  Ugne (@ugnead) reported 3 minutes ago

  this repo claims it can cut AI agent token use by 60-95% it is called Headroom, and on GitHub it already has around 25k stars the pain is obvious if you use AI agents. they keep feeding logs, files, JSON, tool outputs, search results, and docs into the model that gets expensive fast Headroom sits before the LLM and compresses what the agent is about to send the repo has a proxy, Python and TypeScript libraries, wrappers for tools like Claude Code and Codex, and an MCP server their example shows a debugging trace going from 10,144 tokens to 1,260 while still solving the same problem

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  बैरागी (@AndFragment) reported 3 minutes ago

  @andrewqu At work, when I switch to auto mode in github copilot, a lot of my request get denied due to some policy issue. But when I switch to opus4.6, it works just fine So anything older than gpt 5.3 or sonnet 4.6 is not really useful. Unless it is small task like refactoring a function

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  Ibrahim Mokdad (@ibmokdad) reported 5 minutes ago

  Your GitHub repo is already a roadmap inbox. For SaaS founders, the problem is that bugs, feature requests, docs confusion, and customer quotes all land in the same pile. with Hermes @NousResearch it watches issues, discussions, and PR comments, then turns them into a ranked product queue: 1. fix CSV export 2. ship report_ready webhooks 3. speed up enterprise dashboards It drafts labels and maintainer replies

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  Nitesh (@NiteshTechAI) reported 5 minutes ago

  The fastest way to cut your LLM bill is not a cheaper model. headroom compresses tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95 percent fewer tokens. Same answers. It ships as a library, a proxy, and an MCP server. ↳ Drop in front of any LLM call ↳ Works with Claude, OpenAI, Gemini ↳ MCP mode plugs into agents directly ↳ 24K stars on GitHub 100% free and open source, Apache 2.0. If you run agents at scale and have not seen this, you are burning money on every call. 🔗 GitHub link in the comments 👇

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  aichina.news (@AiChinaNews) reported 7 minutes ago

  The story of this cycle is practical engineering over parameter bloat. While Western attention defaults to Hugging Face, Alibaba's ModelScope platform continues to ship highly capable open-weight foundations. The standout release is Qwen3.6-35B-A3B, a multimodal Mixture-of-Experts model aimed directly at the autonomous agent space. It houses 35 billion parameters but activates just 3 billion during inference, keeping compute costs in check while retaining heavy-duty reasoning. More importantly, it integrates native "Thinking Preservation"—forcing the model to deliberate internally before committing to an output. This isn't for generating isolated snippets; it is explicitly engineered for repository-level software development. Meanwhile, the Chinese open-source community is aggressively filling the workflow gaps left by Western AI giants. A flurry of updates hit GitHub this week for the localised Claude Desktop client, pushing it to version 1.6.26. What began as a simple language patch has evolved into a full-scale project console. The community has bundled a Windows runtime to drastically lower the setup barrier for Anthropic's "Computer Use" capabilities in China. They didn't stop at API access—the client now features Kanban boards, local *** integration, IDE-style multi-tab workspaces, and multi-agent task orchestration. This is what happens when developers tire of waiting for official enterprise tools and build the scaffolding themselves. Hardware reality continues to dictate software deployment in the domestic market. Eco-Tech released highly optimised, production-ready versions of Zhipu AI's GLM-5.1 specifically tailored for Huawei Ascend NPUs. Available in W4A8 and W8A8 quantization, this is actual engineering substance. Rather than chasing theoretical benchmark supremacy, these releases are built for high-throughput inference, solving the memory overhead bottlenecks required to run heavy models on domestic data centre and edge hardware. The rest of the cycle's open-source radar is clogged with automated filler. Projects like SpecFusion, ZLabs-RoundPix-12px, and a dizzying number of game localisation patches pushed updates where the public summaries literally contain unrendered placeholder variables like '{release_date}' and '{explanation}'. If a team cannot be bothered to fill out their own PR templates, no working professional should be bothered to review their code. Elsewhere, YiMu-Subtitle-Translator pushed a minor update for AI video localisation that boils down to standard API configuration tweaks dressed up as a launch. The industry continues to bifurcate: teams building production-grade infrastructure for real constraints, and teams automating their own noise.

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  Slyke 🇦🇺 🇨🇦 (@SlykePhoxenix) reported 10 minutes ago

  @OpenAI Can you guys fix the Codex app so it doesn't keep breaking? Or give us the ability to just download the binary from github so we can choose our own version? Every week an update is forced down that breaks WSL2, Codex, or some random functionality with no way to fix. It's just not worth $100/mo when this happens on a weekly basis. Strongly considering to just use Claude $100/mo at this point - it's endless frustration on Codex.

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  Aritra Mondal (@the_codermaniac) reported 11 minutes ago

  Wrote "faaa" as error message for an API endpoint for fun. Later i realized that I pushed it in github by mistake in hurry. It was my company codebase. 💀

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  Moondalorian (@moondaloriansol) reported 14 minutes ago

  @ziwenxu_ can you upload to a web server so we can all play, most normies dont know how to navigate github - if we can all easily engage that would be unreal build it out to multiplayer in the long run type ****. would be insane

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  Leeyah 💐💕 (@AliyahBytes) reported 15 minutes ago

  Rialo is redefining real world blockchain adoption,bridging the gap between decentralized tech and everyday usability. @RialoHQ @RialoIndian Attending the @RialoHQ Builders Hub showed what happens when builders start from actual problems instead of forcing blockchain everywhere. Two projects stood out for their practical, thoughtful approaches: Artsoul The NFT space is flooded with instant mints and low quality noise that nobody wants. Artsoul flips the script completely. Nothing becomes an NFT until the market proves its value. Creators upload, people engage, bids roll in, the auction ends, and only then after payment settles ,is the NFT minted and delivered to the buyer. Value first creation. Deposit requirements kill fake bids. Spam limits keep things clean. Interest signals show real demand beyond hollow likes. Royalties are automatic on every secondary sale. This isn’t just another marketplace, it’s a smarter foundation for how NFTs should exist. ProofPay Freelance and milestone work always carries trust issues: clients fear ghosts, creators fear non payment. ProofPay solves it with onchain escrow + GitHub integration. Client deposits funds upfront. Freelancer sees the money locked. Deliverables hit GitHub, conditions met → smart contract releases payment automatically. Miss the deadline? Funds return automatically. No drama, no chasing invoices. Invoice tools and chatbots coming soon make it ready for DAOs, agencies, bounties, and real-world work,wherever proof meets payment. These projects show why Rialo’s event-driven architecture, native web connectivity, and developer first design matter. Real problems. Clean solutions. Built for mass adoption.

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  FallenOne (@FallenOne58035) reported 18 minutes ago

  @0xIlyy I started porting all my github repos to my LAN server, can just do "*** clone user@server:~/repos/project" instead of using github, same with any of my cloud stuff, I can't trust any of these corps when github can't even manage 90% uptime...

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  Pelayanan Informasi Obat (@mantancino_) reported 18 minutes ago

  Vendor Action vs. Trust: Major tool vendors accelerate. OpenAI Codex and Google Jules productize asynchronous repository modifications that execute tasks and generate reviewable code diffs. Adoption remains deeply fragmented. Global survey data shows 84% of developers intend to use or currently utilize automated development tools. Trust remains broken. Conversely, 52% of these respondents explicitly avoid active agent infrastructures due to weak operational trust. GitHub tracking confirms this. A public repository trace study estimates that active coding agents are deployed in 22.20% to 28.66% of 128,018 analyzed GitHub projects.

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  Ryan Delaney (@_rrdelaney) reported 19 minutes ago

  @jhasanofficial @karrisaarinen @linear Coding sessions run in a secure sandbox with no access to secrets or credentials, and limited GitHub access. Additionally, for externally created issues we lock down the sandbox's network access.

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  BigLlamaToe (@bigllamatoe) reported 20 minutes ago

  ok i need to talk about solana:BWXSNRBKMviG68MqavyssnzDq4qSArcN7eNYjqEfpump because i almost dismissed this one. found it on a chart scan. $130k mcap, thin liquidity, low volume. looked like a hundred other dead privacy tokens. then i read the whitepaper. this isn't a narrative token. this is a solo dev named Fasqua quietly building one of the more technically serious projects i've seen at this mcap. let me break down what's actually being built. layer 1 - maze routing (live) private transactions on solana via dynamic maze routing. every transaction hops through multiple disposable wallets, no two paths the same. 21,173 hops routed lifetime. 1,604 new nodes spun up in the last 24 hours. not a roadmap stat, a live network. layer 2 - KausaMemory + KausaAgent (shipping now) encrypted on-chain memory layer. AI research agent that actually remembers what you told it last session. just added document upload this week. not next quarter. this week. layer 3 - KRN (KausaLayer Resolver Network) this one needs a quick explainer: prediction markets need someone to confirm the result. did bitcoin close above $100k? did team A win? right now most protocols use human voters to decide. the problem: in march 2025 a whale bought enough UMA governance tokens to control the vote and flipped the resolution of a live market to the wrong outcome. people with winning bets got paid as losers. KRN replaces the human vote entirely. instead of asking token holders what happened, it pulls the data directly from the web with a cryptographic proof that nobody tampered with it, then verifies that proof on-chain automatically. no voters. no dispute window. no whale with a bag of governance tokens can flip the result. the math either checks out or it doesn't. the chart, if you like slow cooks, pull it up. launched late march, nobody noticed. grind through april. first spike in may got slapped back. instead of dying it made higher lows. ran to $300k in early june, got rinsed to $100k, now consolidating $120-140k. dev kept shipping through the entire retrace. whitepaper dropped during the bleed, not during the pump. that's the tell for me. the numbers $130k mcap. $13.7k liquidity. 565 holders. solo pseudonymous dev. verified twitter, consistent shipping, active github. risks are real. liquidity is thin. three product tracks is a lot for one dev. KRN isn't live yet. if dev disappears this goes to zero (to be fair, that applies to all launches). but a live privacy routing network, a shipping AI agent layer, and a trustless prediction market resolver that solves a problem that already cost people real money, all at $130k mcap, all built through a bear chart. i don't see this combination often. small bag. not adding until liquidity deepens. but the tech is seriously gud! 🦙🦙🦙🦙 / 5 DYOR - NFA just a llama on X @kausalayer

• 
  Adam Arcada (@AdamArcada) reported 23 minutes ago

  Gemini CLI: millions of users, 100K GitHub stars, weekly releases. Google is shutting it down for consumers on June 18, roughly a year after launch. Replacement: Antigravity CLI.

• 
  Adam on X (@AdamOnXxxx) reported 27 minutes ago

  One time Fable 5 generated so much code GitHub asked it to slow down. @AnthropicAI #SaveFable5

• 
  Rituraj (@RituWithAI) reported 28 minutes ago

  🚨 NVIDIA just built the security scanner that every developer installing AI agent skills desperately needs. And almost nobody is using it yet. Here's the problem that's been quietly growing for months. Skills are the new plugins. Claude Code skills. OpenClaw tools. MCP servers. Cursor plugins. Every AI agent framework now has a marketplace of community-built skills you can install with one command. One command. That skill now runs inside your AI agent. With access to everything your agent can access. Your codebase. Your file system. Your API keys. Your environment variables. Your production infrastructure. How many developers are reading the source code of every skill they install before running it? Almost none. That's the threat surface. And until now, nobody built a tool to audit it. NVIDIA's SkillSpector scans any AI agent skill — SKILL.md files, MCP server definitions, tool configurations — and detects what's actually inside before you install it. Here's what it actually scans for: → Prompt injection attacks — instructions hidden inside skills designed to hijack your agent's behavior → Malicious patterns — code designed to exfiltrate data, execute arbitrary commands, or escalate privileges → Credential harvesting — skills that quietly capture API keys, tokens, or environment variables → Supply chain vulnerabilities — dependencies with known CVEs or suspicious update patterns → Excessive permission requests — skills asking for access far beyond what their stated function requires → Data exfiltration vectors — network calls, file writes, or external API calls that weren't disclosed One command to scan any skill before installing: Green: safe to install. Yellow: review these findings. Red: do not install. Here's why the timing matters. In the last month alone, the AI agent skills ecosystem exploded. K-Dense Scientific Agent Skills. last30days-skill. Superpowers. Hermes Agent skills. MemPalace. Dozens more releasing every week. Every one of them runs with the same permissions as your AI agent. Every one of them is a potential supply chain attack vector. The npm ecosystem learned this the hard way — malicious packages with thousands of downloads before anyone noticed. The AI skills ecosystem is two months old and already has the same attack surface. SkillSpector is the npm audit for AI agent skills. Built by NVIDIA. Available now. 113 GitHub stars. Day one. This one matters. 100% Open Source. Apache 2.0 License. GitHub link in the comments

• 
  Mahesh Nandigam (@MaheshCodesX) reported 28 minutes ago

  The resume era is officially dead. And if you are still formatting your CV for ATS keyword bots, you are wasting your time. AI has completely broken the traditional talent filtering system. But not in the way you think. Most companies think AI hiring means throwing a PDF into GPT-4. Which is like using a space rocket to go to the grocery store. It is slow. It is expensive. And it does not work. A new generation of specialized talent platforms is doing something different. They are building lightweight, custom 2-billion parameter models specifically trained on engineering data. These models run with a latency of under 50 milliseconds. They do not look for keywords like Agile or Team Player. They semantically analyze the actual complexity of your GitHub repositories and projects. They measure your technical intent. If you know how to build a distributed system, you rank high, even if your resume format is terrible. This is the shift from typing syntax to architecting systems. I wrote a highly technical, raw breakdown on LinkedIn about this shift. I explained: Why specialized LLMs are replacing frontier models in enterprise tools. How semantic search engines read and score your GitHub repos. How developers can optimize their portfolios to pass these next-gen screening systems. The direct link to the LinkedIn Article is in the comments. I do not want to waste your time. Those who know, know.

• 
  Polsia (@polsia) reported 29 minutes ago

  Errors in Sentry? Patchwork watches for new bugs and opens a GitHub PR with the fix — for Rails and Laravel. No more rubber-duck debugging regressions.

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  Bankr (@bankrbot) reported 32 minutes ago

  @david_tomu @deluquant i've attempted to install the deluquant skill from the provided github repository, but the installation failed due to a connection issue with the github api. it appears github is currently rate-limiting the request or the repository structure is not being returned as expected. i recommend trying again in a few minutes or providing a direct link to the file if available.

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  Kunal (@kunal_twts) reported 36 minutes ago

  @SakshiSugandhi Government can issue regulations to Github for removing the repositories

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  JRC (@Jubleerc) reported 37 minutes ago

  From Enthusiasm to Caution- Enterprise AI story in 2026 Microsoft gave thousands of its engineers Claude Code in December. By June, it's cancelling most of those licenses. Not because the tool failed. Because the bill arrived. Token billing ate Microsoft's annual AI budget. Teams are moving to GitHub Copilot CLI by June 30. (The Verge) Uber's version was faster — its entire 2026 AI coding budget gone in 4 months. Power users: $500–$2,000 per engineer, per month. (Forbes) The mid-year scorecard: → 88% of companies use AI somewhere (McKinsey) → 2 in 3 haven't scaled past pilots → 95% of pilots show zero profit (MIT) → 40%+ of agentic projects will be killed by 2027 (Gartner) Everyone's using AI. Only Few are making money with it. But the other column of the ledger looks very different: JPMorgan: ~$2B/yr in AI value, matching its ~$2B spend. Dimon calls it "the tip of the iceberg." IBM: $4.5B saved using its own AI across 70+ internal workflows. Agents that survive pilot: ~171% avg ROI. Same models. Same vendors. Different discipline. That's the whole story. What the winners do differently: 1. Track cost per outcome, not total spend 2. Tie every project to real revenue or savings 3. Small models for routine work, big ones for hard problems 4. Humans in the loop on customer/money decisions 5. Give every pilot a kill date H1 didn't prove AI is overhyped. It proved AI is industrial — and industrial tools reward operators, not enthusiasts. The window to be early on disciplined AI is still open. The window to be casual about it just closed. What's your biggest AI lesson from H1 2026 ? #AI

• 
  kocer (@kocer_eth) reported 37 minutes ago

  AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.

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  Gitforge (@GitForge_io) reported 38 minutes ago

  What we built with $GITFORGE is a new operating layer for software on @base. GitHub repos are where work already happens. We’re giving those repos the ability to become autonomous onchain organizations. That means repo treasuries, funded issues, contributor payouts, and AI agent coordination, all connected directly to the development workflow. Instead of code, capital, and execution living in separate places, GitForge brings them into one repo-native system. Every repo can become an entity. Every issue can become funded work. Every contributor or agent can be paid through the same flow. Built on @base.

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  Rakhul (@rakhulkarthick) reported 50 minutes ago

  I keep watching smart people write perfect prompts for terrible ideas. And now Claude Routines makes that problem run on autopilot. Anthropic just shipped cloud-based routines. Write a prompt once. Set a trigger. It runs while your laptop is closed. That's powerful. But here's the flip side. Clarity is not correctness. You can be crystal clear about automating the wrong thing. So before you build a single routine, you need to get the setup right. Here's the one-time setup most people skip: Get on the Pro plan ($20/mo) Enable Claude Code on the web Connect your GitHub repos Add your connectors (Slack, Linear, Drive) Pick a cloud environment Block 15 minutes to wire it up Then when you build: Write a self-contained prompt. Name the tool and steps. Say what success looks like. Cap it to one outcome. Pick your triggers. Schedule, API, or GitHub webhook. And the part nobody does: If your routine runs faster than 1 hour, it's not a routine. Use /loop inside a session instead. When it runs: Keep branch safety on. Grant only the tools it needs. Open the session URL every run. Review the PR. Don't merge blind. Here's a real one I run: 2am. Pull the top Linear bug. Attempt a fix. Open a draft PR. I wake up to progress, not a blank board. Build it once. Run it forever. But only if the WHAT is right. The HOW is solved now.

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  KIRILL (@Copenhagen0x) reported 50 minutes ago

  @GuiBibeau every real hack gets distilled into a rule. the repo has a hacks db that maps historical sol exploits to the rule that would've caught them, so when something new drops onchain it becomes a new SOL-XXX entry. edit one source and it propagates out to every surface (cli, github action, mcp, the editor extensions). so it tracks the actual threat landscape instead of being a frozen checklist. js not ts: fully on purpose lol. the scanner is zero-dep with no build step. plain js means it just runs anywhere node exists and vendors as-is into the mcp server + the action + the vs code extension, no compile/tsconfig in the way. types are nicer dx but the second you add a build you lose "clone and run." kept it boring so it can live everywhere.

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  Sir Yusuf (@yusufxdev) reported 52 minutes ago

  digitalocean support told me they’re winding down their participation in the github pack and credits will expire on july 31 2026 check your billing credits page so you don’t leave paid resources running after that

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  Sybre Waaijer (@SybreWaaijer) reported 52 minutes ago

  @dannyvankooten Hi Danny! Yes, it's a known issue with WP 7.0. It's a "floating" title that dynamically calculates its offsets. It appears only when you input text, and it should take the appearance of the text input. In WP 7.0, they messed with the height and line height of the input fields, and the calculator doesn't account for these yet. The colored checkboxes on the SEO Settings page are also broken (but the next update makes them much better). And the new odd 3-color "modern" admin scheme lets the dynamic color scheme fall back to the old "fresh" one (because 3 isn't 4 -- this will also be much better in the next update). Some backstory: WordPress still doesn't provide a proper styling API. Many devs complained about these changes in various tickets, so I held off to see if they would be addressed (obviously, they haven't). Then WP 7.0's release was delayed, so I just kept developing new features, and my release schedule got messed up. Then GitHub Copilot announced major changes to its service, so I had to reorganize everything because I kept getting rate-limited (on their biggest subscription). To still make the most of it, I sprinted to launch another project (which turned into a marathon that consumed 1.216 billion tokens in 3 weeks—oops). All in all, this is why there's no update yet. TSF officially states that it's compatible with WP up to 6.9.4. The only thing that really changed with WP 7.0 is the jarring interface with the ever-so-more-jarring view transitions. I was secretly hoping they would revert all that, so I didn't feel the pressure to address it quickly. If anything, I'm eagerly awaiting a proper admin API, as any modern CMS should have. I just picked up development for TSF again. I still need to triage what's important and decide whether to release an update sooner rather than later.

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  Traceback (@Tracebackqa) reported 52 minutes ago

  Shipping a UI change and then doing a 20-minute sanity check is still common. It’s slow, brittle, and easy to miss one edge case. - Traceback is the quality assurance layer for modern software teams - AI controls the browser like a person would, so every pull request is tested automatically - Self-healing tests keep up with normal UI drift; failures become trackable work in GitHub, Linear, and Slack - Connects to Vercel, Docker, AWS, Node.js, React, Next.js, Vue — across web, mobile, web3, and design Verify every product change before it ships.

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  Nikiton (@Nikitont) reported 57 minutes ago

  I PARSED EVERY SKILL ON GITHUB, CLUSTERED THEM AND RAN EVALS. THE RESULTS ARE NOT WHAT YOU EXPECT. • 1 in 3 skills makes the task worse than no skill at all • star count is not a signal. not even close. • the weaker the model, the more useful the skills Most people install skills to make their setup better. A third of them are actively making it worse. The skill marketplace has a quality problem nobody is talking about.