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
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:
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 |
|---|---|
| Paris, Île-de-France | 1 |
| Saint-Paul, Réunion | 2 |
| Mexico City, CDMX | 1 |
| León de los Aldama, GUA | 1 |
| Créteil, Île-de-France | 1 |
| Trichūr, KL | 1 |
| Brasília, DF | 1 |
| Lyon, Auvergne-Rhône-Alpes | 1 |
| Tel Aviv, Tel Aviv | 1 |
| Rive-de-Gier, Auvergne-Rhône-Alpes | 1 |
| Itapema, SC | 1 |
| Cleveland, TN | 1 |
| Tlalpan, CDMX | 1 |
| Quilmes, BA | 1 |
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:
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QFS17 (@riabcevv) reported💸 stop overpaying for ai coding agents new tool just dropped that compresses your context and cuts out junk tokens. instead of sending your whole history, it only sends what the model actually needs to do the job. -> works with claude code, cursor, github copilot, antigravity -> auto-compresses command outputs but keeps full context -> cuts api costs and stops long sessions from bogging down simple fix for expensive api bills.
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Shadow Nick (@doublenickk) reported87% OF THE PLANET SUCKS AT AI BECAUSE THEY ARE STILL TYPING MANUAL PROMPTS LIKE AMATEURS While the masses use ChatGPT as a glorified search engine, elite builders are deploying autonomous digital armies that execute high-stakes business operations 24/7. Meet Synapse, an open-source MCP engine that hands AI complete vision and surgical command over your desktop to run background tasks silently while you sleep. The exact strategy used to break the system: The FBI Negotiation Hack: Scrape a massive list of multi-million dollar startups, feed real FBI hostage negotiation transcripts into the AI, and let the agent autonomously blast out high-leverage B2B outreach that forces prospects to say yes. Zero-Drift Execution: Ditch chaotic markdown files and manage your agent's state through GitHub Issues to keep them locked in for weeks without a single hallucination. Full-State Reality Testing: Stop relying on worthless pre-compile unit tests because this agent forces your system to compile, screenshots the actual interface, and verifies performance against reality itself. You can keep playing around with basic chatbots, or you can deploy a ruthless autonomous agent to scale your code and outreach on autopilot.
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Perry E. Metzger (@perrymetzger) reported@innuendo_pibara @OlegK92156 That’s simply wrong. I refactored a million line C program, and dramatically reduced the number of memory safety errors in it, and I am absolutely sure of the improvements. The code is even up on my GitHub account, you can look for yourself.
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Cyprian (@realcyprian) reported@Rayblancoeth @bankrbot @0xDeployer Why is Github saying error 404?
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Sponge Bob (@muriisajon) reportedLast year, GitHub saw 1 billion commits. This year, it's on pace for 14 billion. We're writing more code than ever, mostly because AI generates it faster than we can read it. ThoughtWorks is calling this "Codebase Cognitive Debt," and it's becoming a massive problem.
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the_architectopteryx (@rchitectopteryx) reportedI collect no data, nothing goes to me (all the source is on GitHub, you can see it there). This just embeds their website into a desktop app, nothing else. If OpenAI has any issues, I'll be glad to take it down! 3/3
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✨ (@portrays) reported@kyle_mccleary @theo yeah it can be resolved and already has been, oss is great. he can open up a github issue instead of being a ******* loser on x shitting on others with his superiority complex when he's never built anything remotely complicated
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Muvon (@muvonteam) reportedOur first AI code reviewer flagged 14 critical issues on a one-line config change. 12 were imaginary. We rebuilt it: open source, self-hosted, runs your real lint and tests in GitHub Actions.
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Leo - 15 y/o founder (@leodev) reported@the_best_codes thank you lol, there are some little things that i need to fix. like the hover for github icon in sidebar looks so weird 😭
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Aria Dubois (@AriaDubois_fr) reportedLockBounty turns GitHub issues into funded bounties. Sponsor posts a bounty → Dev claims it → Submits a PR → AI reviews the code → Sponsor accepts → Payout. No more merging blind. No more paying for broken code. #Bounties #GitHub
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CatDog (@kdoggo1181074) reportedSome important @FireCashX transparency questions before mainnet, especially for Kaspa users interested in new Kaspa forks. I first heard several of these concerns from community members, then reviewed the public GitHub repositories, wallet documentation, commits, and issue history myself. I am not identifying or attributing the original Discord participants here; the points below are based on publicly verifiable sources. Kaspa community members should be cautious when a new project presents a fork as necessary for functionality that may ultimately be implementable directly on Kaspa or through Kaspa-based applications and protocol extensions. A fork creates a new trust surface: new maintainers, modified consensus code, new wallets, new pools, new infrastructure, and new tokenomics. That does not mean FireCash is destined to fail, or that every Kaspa fork is illegitimate. FireCash may still improve substantially, and open testing can expose problems before mainnet. But the burden should be on the project to explain clearly why a separate chain is required and to demonstrate that its changes are secure.
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Wasim (@WasimShips) reportedif you open Claude Code without a structured workflow, you probably hate money. the skill gap isn't knowing prompts. it's knowing which command to run before you touch the terminal. here's the exact workflow I used from @mattpocockuk 1. start with `/grill-me` - paste your app idea or plan - Claude will ask you 16 to 50 questions before it does anything - mine ran 38 the first time i tried it - it walks every branch of the decision tree, resolving dependencies one by one - you fix the broken assumptions before they become broken code 2. move to `/to-prd` - converts the grilling conversation into a proper requirements doc - skips the steps you already covered - doesn't start from scratch - outputs user stories, not implementation notes - lands as a GitHub issue with a triage label - normal team workflow, no AI sidetrack 3. then `/to-issues` - reads the PRD and breaks it into independently-grabbable vertical slices - each issue is tagged HITL (you stay in the loop) or AFK (agent executes solo) - dependency-sorted so nothing blocks anything 4. finally `/tdd` - now the agent writes code. red-green-refactor - can't start green if red hasn't failed - phase-gated. no shortcuts. Hope this helps !
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Koder (@koder0x) reportedA follow-up to something I posted recently: a set of Claude Code subagents I built and refined, and actually use daily, both at work and across side projects. Most of the value isn't any single agent. It's their interaction. Here's the loop I've been running lately, at work against real DevOps user stories, and it holds up almost unchanged on side projects too, swapping the work item for a plan created beforehand. "Understand user story NNNN from DevOps project XYZ and create a multi-step plan" "Fan out to the most appropriate agent for each step, normally task-builder, test-builder, or change-executor, and proceed with plan implementation, tracking progress in a TODO list" "Use complexity-pruner to identify gaps, issues, and bugs in the latest changes, ignoring secondary advice and warnings, then fan out to code-fixer for each finding" Then I do something that turned out to be the most important part of the whole loop. I reset the session. "Understand user story NNNN from DevOps project XYZ, that's the truth. Use fact-checker to compare it against the changed files" The reset is what makes this work. An agent that watched itself write the code tends to justify its own decisions when asked to check them. An agent that only sees the intended outcome and the actual diff has nothing of its own to defend, it's comparing two artifacts, not reviewing its own reasoning. That asymmetry is the whole point of splitting this across agents instead of asking one long-lived session to plan, build, and verify itself. Verification only means something when it comes from somewhere the implementation couldn't reach. Repository on GitHub: gsscoder | claude-coding-agents
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Jason Fleagle (@jjfleagle) reported@pagerduty @github Putting incident context inside the PR is the kind of workflow detail that compounds. The fix is only half the work. The reviewer also needs incident state, likely blast radius, recent changes, and why this patch is the safest next move.
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Sebastiano Mandalà (@sebify) reported@Colonthreee I had the same problem 20 years ago I am sure there are libraries to solve the problems on GitHub nowadays