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GitHub Outage Map

The map below depicts the most recent cities worldwide where GitHub users have reported problems and outages. If you are having an issue with GitHub, make sure to submit a report below

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The heatmap above shows where the most recent user-submitted and social media reports are geographically clustered. The density of these reports is depicted by the color scale as shown below.

GitHub users affected:

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GitHub is a company that provides hosting for software development and version control using Git. It offers the distributed version control and source code management functionality of Git, plus its own features.

Most Affected Locations

Outage reports and issues in the past 15 days originated from:

Location Reports
Itapema, SC 1
Cleveland, TN 1
Tlalpan, CDMX 1
Quilmes, BA 1
Bengaluru, KA 1
Yokohama, Kanagawa 1
Gustavo Adolfo Madero, CDMX 1
Nice, Provence-Alpes-Côte d'Azur 1
Brasília, DF 1
Montataire, Hauts-de-France 3
Colima, COL 1
Poblete, Castille-La Mancha 1
Ronda, Andalusia 1
Hernani, Basque Country 1
Tortosa, Catalonia 1
Culiacán, SIN 1
Haarlem, nh 1
Villemomble, Île-de-France 1
Bordeaux, Nouvelle-Aquitaine 1
Ingolstadt, Bavaria 1
Paris, Île-de-France 1
Berlin, Berlin 1
Dortmund, NRW 1
Davenport, IA 1
St Helens, England 1
Nové Strašecí, Central Bohemia 1
West Lake Sammamish, WA 2
Parkersburg, WV 1
Perpignan, Occitanie 1
Piura, Piura 1
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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:

  • joaopcapinha
    João Capinha (@joaopcapinha) reported

    I'm using Claude Code more than any other tool in my stack right now, and not just for writing code. Here's how I'm running a DeFi project with agentic AI orchestration at its core. I'm coordinating across ClickUp, Google Drive, Slack, GitHub, and call transcripts. And the problem isn't that the information doesn't exist. It's that finding it, connecting it, and moving it between tools quietly becomes the job. Nobody puts "context archaeology" in the job description. It just eats your day. The shift: instead of jumping between apps, I talk to Claude about the project. Pull the latest task status. Cross-reference a spec. Update a ticket. Draft a message. One thread. No rebuilding context from scratch every time. It also makes you faster at being wrong (worth saying out loud!) Feed it a messy problem, you'll get back a very confident-sounding mess. The judgment still has to be yours. But the coordination overhead? The invisible tax that was never really the job? Most of it has disappeared. Huge productivity unlock.

  • MystiqueMide
    MystiqueMide (@MystiqueMide) reported

    @vikktorrrre It’s veryyyyyyyyyyyyy simpleeeeee Check my GitHub or search hermes on my page I broke it down

  • tomcrawshaw01
    Tom (@tomcrawshaw01) reported

    The #1 open-source repo on GitHub right now is an AI agent called Hermes. Its founder just gave away the 6 keys to getting real work out of any agent. Most of them have nothing to do with which model you pick. The problem they fix shows up fast. Most people babysit their agents, micromanaging every step, and the work still comes back wrong. So here are his 6 keys. 1. Describe outcomes, not steps. Tell the agent what "done" looks like and the conditions it has to hit, then get out of the way. The models keep getting better at long-horizon planning, so your step-by-step instructions are the bottleneck now. 2. Define "good" or you get slop. The AI has no taste. Leave your standard unspoken and it hands you the average of everything ever written, then thinks it nailed it. Write your standard down, all of it. 3. Explain it like it's an alien, not like it's five. You and I share a lived history, so half of what we want goes unsaid. The model never grew up on Earth, so every assumption you skip stays unmet. 4. Use agents for patience, not creativity. They have infinite patience and almost no creativity. So give them the work a human could do but never wants to, like reading every log line or running the same checks all day. 5. Build the agent that learns once and reuses forever. Their agent booked a Vegas restaurant. 45 minutes the first time, instant the next day, because it saved the skill. One engineer taught their log agent once and the whole company runs on it now. 6. The harness matters as much as the model. The model is the brain and the harness is the body. A great harness with a weaker model beats a great model with a weak harness, because the model just outputs tokens and the harness is what touches your actual work. Put these together and one person starts moving like a team. The founder built Hermes into the #1 repo on GitHub without really knowing how to code. The tools did the rest. There's never been a better time to be early again. I break down systems like this every week. Follow for more.

  • jsgrrchg
    Jose Gurruchaga (@jsgrrchg) reported

    I love @github . Please @Microsoft fix the reliability and the diffs!! I can't imagine a world without it 😭

  • GrooveNet
    Richard Vincent (@GrooveNet) reported

    GitHub just updated its security blog. If you run GitHub Enterprise Server on-prem, rotate the GHES signing key today. One poisoned IDE extension, 18 minutes live, one GitHub employee's machine, ~3,800 internal repos exfiltrated. Same chain hit Grafana, OpenAI, Mistral. The next supply-chain attack will not be a vulnerability. It will be a trusted update.

  • ed_the_engineer
    ed_the_engineer (@ed_the_engineer) reported

    How the numbers were calculated: Benchmark: SWE-bench Verified, 500 real GitHub issues from 12 Python repos, human-curated by OpenAI in Aug 2024 from the original SWE-bench (Princeton, Oct 2023). Models must submit a patch that passes the original unit tests. Cloud baseline (Q3 2024): GPT-4o scored 33.2% on Verified at the benchmark's launch. Source: OpenAI's "Introducing SWE-bench Verified" announcement. Open baseline (Q2–Q3 2024): Llama 3 70B and Qwen 2.5 72B at 4–6% raw, ~12–16% with agent scaffolds (Agentless, SWE-agent). Open frontier hadn't been built for coding agents yet. Small tier today (May 2026): Qwen 3.5 9B at ~65% per published evaluations. Fits in ~5 GB VRAM at Q4 quantization, runs on a $400 GPU. Tier definitions in the chart: Small tier = ≤16 GB VRAM (RTX 4060 Ti, 5060 Ti, etc.) Mid tier = 24–48 GB VRAM (RTX 5090, dual 3090) Frontier = any size, including multi-GPU MoE Forecast: dashed lines are linear-with-decay extrapolation of the observed slope from each tier's last 4 quarters. Not a prediction, more of an "if the curve holds" projection. Real outcomes depend on: benchmark saturation (SWE-bench Verified has known contamination issues, with SWE-bench Pro emerging as the harder successor), continued release cadence from Qwen/DeepSeek/GLM, and whether reasoning post-training keeps delivering gains. Caveat: SWE-bench Verified scores are scaffold-dependent. Same model can vary 10+ points by harness. Numbers cited use each model's officially reported configuration.

  • elliothesp
    Elliot Hesp (@elliothesp) reported

    Yeah pretty sure GitHub is having issues... yet again...

  • lordofblocks
    David J. (@lordofblocks) reported

    @rauchg GitHub ships Copilot, has access to every AI model, and still has outages. The hard parts of software are still hard. The tools help, they don’t remove the problem.

  • its_aman_yadav
    Aman Yadav 💫 (@its_aman_yadav) reported

    Everyone sees the green squares on GitHub. No one sees the empty drafts, the 500 internal server errors, and the quiet grind. When I started learning backend logic, it was overwhelming. Instead of quitting, I doubled down on the fundamentals. Build it. Break it.

  • dolphin278
    dolphin278 (@dolphin278) reported

    @claudeai can we have GitHub connector in plain Claude, not CC? I had an interesting discussion that turns into GitHub issues for my project, but Claude can’t do it. Of course, I can just copy paste it or share via public url, but it is clunky

  • bklyn_newton
    rupertnewton (@bklyn_newton) reported

    @jefielding non-coder, had a terrible experience cloning app off github with claude co-pilot. put me right off.

  • flareforward
    Flareforward (@flareforward) reported

    Filed a GitHub issue asking @OpenAI to add a programmatic chat API to Codex Desktop so external agents could spawn sidebar-visible chats. 5 days later Codex 0.133.0 dropped with the exact API. Wired it into my multi-agent fleet tool the same day it shipped. Submission → implementation → production in one week. The feedback loop is real.

  • ivanzugec
    Ivan Zugec (@ivanzugec) reported

    @fonsvandamme @github I do use Gitlab, and I do like the fact that you get wiki functionality on the free account and the issue tracking is much better. I should set up a gitlab ci to sync the repo to github.

  • kunaljeweller
    Lil Weapon (@kunaljeweller) reported

    i was trying to do something and it didn't work, and i was like "is @github down? of course it's down"

  • agentskills_ai
    Justin Brooke (@agentskills_ai) reported

    You will regret installing Hermes locally ESPECIALLY if you're not backing up to Github daily. Local machines die, get unplugged, lose wifi connection, kids break them, things spill on them. That's why I install mine on a cheap VPS server, and I like DigitalOcean because they have a CLI. Which means, Claude can do the whole install for me. - It's super cheap - Always on - No one can steal it - Accessible from any device anywhere If you're a non-techy like me, then this checklist will be the fastest, easiest, safest way to install Hermes. Just let AI do it for you...

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