GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  mrgadget (@mrgadgetstudio) reported 4 minutes ago

  @EzekielCrrypt I still deploy code to github, what's problem?

• 
  Asterix (@Asterix54907294) reported 8 minutes ago

  end-of-summer snapshot for @QFEX : -~$222M in open interest -CLI v0.3.12 shipped in August with improved installation docs and a go.mod fix -GitHub activity continued through late August not a flashy launch recap, just a quick look at how the exchange is closing out the summer: more markets, meaningful liquidity, and active work on the tooling side still early, but the infrastructure is clearly moving

• 
  Rituraj (@RituWithAI) reported 9 minutes ago

  🚨 Someone built the complete playbook for running frontier AI models on consumer GPUs at home. Not a tutorial. Not a YouTube video. A production-grade serving stack with measured benchmarks, working configs, and battle-tested recipes — for RTX 3090 owners who want real performance. It's called club-3090. And the numbers it delivers should not be possible on consumer hardware. 127 tokens per second. Qwen3.6-27B. Two RTX 3090s. 262K context window. Vision. Tool calling. At home. Here's what's actually inside. Two serving routes — pick based on what your workload breaks on. vLLM dual: maximum throughput. 89-127 TPS on code tasks. 4 concurrent streams at 262K context. Full feature stack — vision, tools, speculative decoding, streaming. This is the path if speed matters. llama.cpp single: maximum robustness. Full 200K context on one 3090. No prefill cliffs. 25K-token tool returns work correctly. 91K needle ladder passes. ~51-60 TPS — slower than dual, but doesn't crash on real-world agentic workloads. Both routes ship as validated Docker Compose configs. Drop-in OpenAI-compatible API on localhost:8020. Your Claude Code, Cursor, or any OpenAI-compatible client connects immediately. Here's the model support that makes this practical. Qwen3.6-27B — production ready. Works on 1 or 2 cards. vLLM, llama.cpp, ik_llama. Up to 262K context. Gemma 4 31B — production ready. Vision, tools, up to 106-141 TPS on dual cards. Qwen3.6 35B-A3B MoE — production ready. 103-149 TPS single card. 178 TPS dual. Here's the wildest part. The terminal UI. c3 is a lazydocker-style cockpit that wraps discovery, serving, and operations in one keyboard-driven interface. Browse the model catalog, serve a variant with Enter, watch live GPU stats, run health checks — all without touching the CLI. Here's why this is different from just installing Ollama. Ollama gets you running. club-3090 gets you benchmarked, stress-tested, and production-hardened. Every config ships with a verified TPS measurement. The bench script runs 3 warmup + 5 measured passes. The stress test catches the specific prefill cliff that Ollama silently fails on at long contexts. When your agent starts doing 25K-token tool calls at 3am and something crashes — club-3090 already found that failure mode and documented the workaround. One command to start. Your RTX 3090 just became a frontier AI inference server. Apache 2.0 License. 100% Open Source. GitHub link in the comments 👇

• 
  ATP (@ATPinsights) reported 10 minutes ago

  GitHub CLI just added image and video attachments today. Here's what you need to know. The gh command line tool now supports a repeatable --attach flag. It uploads a local image or video file and references it inline in an issue, pull request, or comment body. The feature is live now for all users on GitHub. It's aimed squarely at developers and coding agents that need to show visual proof, like before-and-after screenshots, directly from the terminal instead of the web UI. Developers reacted fast. Many called it a long-overdue fix for a common workaround, since teams previously built custom tools or scripts just to upload images to PRs from the CLI. Key facts: - New flag: --attach - Supports: images and video - Repeatable: yes, use it multiple times per command - Works in: issues, pull requests, comments - Availability: all users, live now No separate app or upload API is needed, the flag handles it inside gh itself.

• 
  Martin Tobias (Pre-Seed VC) (@MartinGTobias) reported 11 minutes ago

  if you know any founders who are winding down, I may have a buyer of their github repos. DMs open.

• 
  Suryansh Tiwari (@Suryanshti777) reported 12 minutes ago

  6. The Dependency Incident Check Grok has native real-time search across X. Breakage gets posted there hours before the GitHub issue is triaged. No other coding model has that feed. "You are a build engineer whose first move on a broken pipeline is to work out whether it broke for everyone or only for me. Search X and the web, last 14 days. Check: - Is anyone else reporting this failure with this package and version, and when did the reports start - The exact release that changed behaviour, and the changelog line that admits it - Whether maintainers have acknowledged it and what they recommended - The pin or patch people settled on, with the tradeoff of each - Whether this is my problem instead, and what evidence points that way Give me the verdict in the first line: their bug or mine. Then the evidence, newest first, with links. My failure: [PASTE THE ERROR, THE PACKAGE AND VERSION, AND WHAT CHANGED ON YOUR SIDE RECENTLY]"

• 
  Varun Doshi (@Varunx10) reported 13 minutes ago

  Possibly found an issue in @github stack system It does not allow to re-target the base branch of a PR stack as you can generally do that on a single PR. Requires you to unstack and setup a new stack with updated base branch.

• 
  Nas (@TheNasFi) reported 15 minutes ago

  $MSFT changed its reporting structure today. Starting in FY27, Microsoft will report just two segments: Agents & Infra Devices & Consumer Agents & Infra includes Azure, Microsoft 365, GitHub, server products and industry solutions. For context, those businesses generated $268B in revenue last year, compared with $64B for Devices & Consumer. Microsoft also recast its Q1 guidance under the new structure: Agents & Infra: $75.15B to $75.75B Devices & Consumer: $14.7B to $15.2B There is no change to total revenue guidance. These are the same numbers Microsoft gave in July, reorganized under the new segments. Mostly a reporting change, but an interesting look at how Microsoft now groups the majority of its business internally.

• 
  paulrodturner (@paulrodturner) reported 15 minutes ago

  @supabase Is anyone else having issues logging in via Github?

• 
  Jeremy W (@basicBrogrammer) reported 15 minutes ago

  @bot Anyone else have an issue with the grok bot GitHub connector?

• 
  htrowii (@htrowii) reported 21 minutes ago

  @brainage19 i set my flake up with copy pasting github dotfiles on bare metal it was terrible

• 
  Fofer (@foferxxx) reported 21 minutes ago

  @AmigamagazineGA Has there been any public explanation as to why this GitHub repo was taken down? It’s been 404 for days. Is there a story there?

• 
  Aayushiii (@stfu_aayushiii) reported 25 minutes ago

  If you're building a project, read this before writing a single line of code. 5 things I learned the hard way: 1. Problem > model Don't start with “How do I use GPT?” Start with “What problem am I solving?” 2. Simple stack > impressive stack If your MVP needs Kubernetes, 6 microservices and an agent swarm, you probably haven't built an MVP. 3. Evaluate before you optimize You can't improve what you can't measure. 4. Build for users, not your GitHub README A technically impressive project nobody can use isn't a product. 5. Ship ugly. Iterate fast. Your first version isn't supposed to be impressive. The biggest mistake? Spending weeks deciding which model to use when you haven't even validated the problem.

• 
  Uptimus (@UptimusApp) reported 26 minutes ago

  Sep 02, 2026 at 13:29 UTC: Semaphore reports that periodic authentication failures with GitHub repositories are linked to a wider issue affecting HTTPS operations.

• 
  Mr. Buzzoni (@polydao) reported 30 minutes ago

  LOOP RAT ROADMAP: WHAT'S NEXT, AND WHAT IT'LL NEVER BECOME v0.3.3 today. 3 loops, 55 checks, 0 services here's where it's headed: > 0.4 - read the night faster: rat watch live-tails a running shift, rat replay reruns one from its saved prompt, a weekly digest instead of seven separate pages > 0.5 - off the laptop: run-due moves into GitHub Actions, state lives on a branch, rat cron --launchd survives a closed lid > 0.6 - sharper graders: swappable rubric packs, two graders disagreeing becomes your queue for the day > 0.7 - the work itself: a worktree per shift, so a failed night never dirties your tree > 1.0 - trust: a hash-chained trace nobody can quietly rewrite what it will never have: > no web dashboard - the terminal already knows where the files are > no database - plain files outlive the tool that wrote them > no hosted service - nothing to sign up for, nothing to shut down > no auto-merge - the rat proposes, the morning decides every item ships behind a flag: dry run -> report only -> one repo -> a week of receipts -> default on a feature that can't run as a dry run doesn't get written the rat is boring on purpose. every version keeps it that way