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 (57%)
• Errors (30%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Inverness	Website Down	3 days ago
Quito	Sign in	4 days ago
Junín	Errors	4 days ago
Guadalajara	Errors	4 days ago
Paris	Website Down	4 days ago
Quito	Errors	4 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:

• 
  Sai Krishna ⚡️ Superblog.ai (@_skris) reported 11 minutes ago

  You can create your own templates for Superblog now! Just install superblog-cli and ask claude/codex to build one by following your brand's design guidelines or handcraft custom designs. Without losing core web vitals. The below template was created with a single-prompt using claude. I was supposed to announce this on Monday but Github was down, so waited for a bit. Fun fact: Claude built the entire feature in 2 days. 16,000 lines of code. Since superblog is JAMStack but not open-source, building the instant live preview feature for developer experience was something super complex. All without shipping Superblog's core IP to the developer's machine. I'm gating this feature for customers on $99/mo plan for now. Will launch $199/mo plan and move it there.

• 
  CryptoPatrick (@cryptopatrick) reported 12 minutes ago

  @avrldotdev I looked at this a while a go. You can create a third agent, a dockerized "tester" with sole UNIX level write permission to test folders, responsible for writing property based tests from planner actions. The tester publishes one test suite via an API, and keeps one test suite private. The executor, dockerized so that it cannot interact with broader infra and has zero read or write permission to the testers test suite, then works until tests pass the test suite exposed by via the API. Once tests pass, the executor signals readiness to the tester with a link to a github repo, the tester pulls the repo and run both the published and its private twst suite. If tests pass then the tester signals readiness to the planner, using the planners API, which requires mTLS authentication between by the planner and tester. If tests fail, then the tester uses the executor's API to signal error category (status: fail, reason: property). To prevent the executor trial-and-erroring a passing test, the tester uses rate limiting by exponential backoff for failed attempts. By preventing the executor from talking to the planner (using mTLS), we "ensure" that the exwcutor cannot masquerade as the tester agent to try and bypass it. It's clearly a bit cumbersome to setup. I'm sure there are much simpler solutions. I think I have an orchestrator project which spins up the setup, but I haven't used it for anything to test its usefulness (too busy with math and school).

• 
  JO (@appealstoheaven) reported 13 minutes ago

  @moocat999 @drjoshcsimmons I run my own local gitea server and it's worth it for sure. Doesn't mean you can't ever use github either.

• 
  Romlib 🎄 (@romlib_) reported 16 minutes ago

  We're never gonna fix the GitHub uptime

• 
  Perfect Chaos (@MemPrices) reported 16 minutes ago

  @Dobra_Mc_Dronka @Isse_Vokan @FlorkOfCows Manjaro was the first distro that handled my laptop's nvidia+intel hybrid graphics card out of the box. I've tried so many distros, all of them I had either to rely only on the intel card or build a github driver that stops working later on. But since I have Manjaro, 0 problems.

• 
  Mach (@MachStack) reported 20 minutes ago

  @ChatGPT It would be cool to take it one step further and make some conversations public and discoverable, not just shared through links. Imagine a research problem branching into dozens of different approaches, researchers could fork the most promising ones, rate the branches that actually make progress and continue from there. Basically a GitHub for AI research conversations, you could even verify researchers through university emails to keep the noise down

• 
  Luke The Dev (@iamlukethedev) reported 20 minutes ago

  @vicentee97 @jrwut It was because GitHub was down and experiencing issues

• 
  Vatsalpandya333 (@Vatsalpandya333) reported 20 minutes ago

  our AI agent opened a PR to fix a production incident last week. no one triggered it. the engineer on call didn't even know the bug existed yet. a customer reported a UI glitch in Slack. TasksMind picked it up, traced it through the logs, found a null check missing in an API response handler from a deploy two days ago, and opened a pull request with the fix. by the time our engineer saw the notification, the PR was already waiting for review. i sat there staring at the GitHub notification for a solid minute. the fix itself was straightforward. what got me was that no human told it to do any of that. we've been building TasksMind for months. late nights, rewrites, demos that broke, weeks where it felt like we were just talking to ourselves. and then one morning, quietly, the thing just worked. a real customer, a real bug, a real fix sitting in GitHub, ready for human review. that's the moment it stopped being a project and started being a product. back to building.

• 
  Ashwin Rohit (@ashwinrohitcom) reported 22 minutes ago

  @uwukko I understand their position. The reason GitHub has been going down is because of the massive volley of LLM code that's being pushed on there. There's no way a company of Codeberg's size can possibly handle all that traffic.

• 
  Quentin Romero Lauro (@Qromerolauro) reported 23 minutes ago

  @c0mm0n_dev_us3r oop old name - we have to change our GitHub login!

• 
  علي عسيري (@3li3) reported 24 minutes ago

  @Teknium If I had to remove something from Hermes, I would remove friction before removing capability. At this point Hermes already has a lot of power. I think the bigger opportunity is making the Desktop experience more predictable, easier to debug, and more comfortable for people who use it all day. A few things I would prioritize: 1. Reduce default UI clutter. Things like pets, backdrops, reactions, translucency and other cosmetic extras are fine, but I would move more of them under a dedicated Personalization section. The default experience should stay focused on chat, projects, models, tools and agent activity. 2. Expand font and typography controls. Hermes already has UI scaling and terminal font controls, but I would add separate font selection for: * the main interface * chat messages * code/terminal This matters especially for Arabic, Persian and Urdu, where the quality of the fallback font can completely change readability. 3. Finish RTL/BiDi support across all surfaces. Arabic localization exists, but RTL support is still not complete. There are still open cases where mixed Arabic/English text renders incorrectly, especially when a paragraph starts with an English technical term. For technical users this happens constantly: API هذه المشكلة... Docker يحتاج... GitHub يدعم... Direction should be detected from the whole paragraph rather than relying only on the first strong character, while code, commands, paths, diffs and terminal output must remain LTR. A manual Auto / RTL / LTR override per conversation would also be useful. The TUI still has open RTL/BiDi work as well, and the Web Dashboard chat remains limited by its terminal/xterm-based rendering. 4. Make every failure actionable. Hermes should never leave the user wondering whether the model, provider, gateway or Desktop app is frozen. When something fails, the UI should clearly say which layer failed: * model/provider * custom endpoint * streaming/SSE * gateway * cloud agent * authentication * local runtime Then give useful actions such as: Retry · Switch Provider · Open Logs · Copy Diagnostics · Repair There are still open Desktop reports where provider streaming failures are logged in the backend but are not surfaced correctly in the UI. 5. Bring diagnostics into Desktop. Hermes already has useful CLI diagnostics. I would expose the same idea through a proper Diagnostics page. One click could check: * Hermes runtime * gateway status * provider connectivity * API endpoint * authentication * model availability * local ports * environment/config problems Then generate a redacted support bundle. A normal Desktop user should not need to understand Python environments, gateway processes or log locations just to diagnose a failed session. 6. Improve cloud and gateway recovery. Transient connection problems should not look like permanent failures or expired sessions. The app should distinguish between: * authentication failure * temporary network failure * remote gateway unavailable * Nous Cloud 502/503/504 * local gateway failure There is already active work around this, but I think it should become a consistent recovery model across the whole Desktop app. 7. Harden local-model and OpenAI-compatible provider UX. Hermes is increasingly useful with Ollama, llama.cpp, LM Studio and custom endpoints. The Desktop setup should validate: * endpoint format * /v1 compatibility * streaming support * tool calling * reasoning fields * context limits * model availability before starting a long agent session. If an endpoint returns HTML, malformed SSE, an unsupported reasoning shape or an empty stream, Hermes should identify that directly instead of collapsing everything into a generic provider failure. Continue ….

• 
  Bash (@bashirbuilds) reported 27 minutes ago

  @lewiscarhart $10k for attention is wild. The harder part starts after the traffic arrives when your product depends on Stripe, OpenAI, GitHub, Clerk, etc. and one of them breaks. That’s the problem I’m building Reeno around: knowing which part of your SaaS is affected, not just that a service is down.

• 
  Cato Networks (@CatoNetworks) reported 30 minutes ago

  During the August 17 GitHub outage, Cato observed HTTP errors on users’ GitHub sessions spike to 34.8% and average latency peak at 1,639ms. Other SaaS applications were performing noticeably better, helping show that the enterprise access path wasn’t the issue.

• 
  NΞO (@NeoCallss) reported 33 minutes ago

  @better_ERC The dev spent two months developing this, I don’t know him, but I noticed it on GitHub, and I also don’t know if it’s 100% safe, but 99% of the people who sold this token didn’t understand what it was That’s the problem these days people don’t want to waste time looking for good things on-chain when they can just buy a tweet from CZ, Elon, or Vlad and profit and move to next

• 
  Nikita 🇪🇺 (@nikitajanockin) reported 34 minutes ago

  @samlambert At the very same time we are crying when GitHub is down

• 
  Nitesh (@NiteshTechAI) reported 35 minutes ago

  A Claude Code plugin will delete any code you wrote before the test that covers it. superpowers is a full development methodology, not a skill pile, and it installs on most of the coding agents people actually use. Cursor, Codex, Gemini CLI, Copilot CLI, Grok, Kimi, Devin, OpenCode. The part that stuck with me is the bar it sets for a plan. The plan has to be clear enough for "an enthusiastic junior engineer with poor taste, no judgement" to follow without asking you a single question. That is the actual standard. Most plans I write do not clear it. The workflow fires on its own: • Tasks broken to two to five minutes each • Brainstorming before a line of code exists • Red-green-refactor, enforced, not suggested • *** worktree per branch, clean test baseline • Code review between tasks, blocking on critical Install on Claude Code is one command: /plugin install superpowers@claude-plugins-official Built by Jesse Vincent at Prime Radiant, who also sells commercial support. The skills themselves are free. ⭐ 272,000+ stars on GitHub. MIT. 🔗 GitHub link in the comments

• 
  Xeroxis_ (Previously Known as: MLPFAN232) (@Xeroxis_) reported 44 minutes ago

  @ncxcq Path A rlly? Looks like your jst blatently copying the broken tr4mpass code on GitHub.

• 
  Matthew Chenoweth Wright, CEO of Monolithic LLC (@enuminous) reported 47 minutes ago

  Monolithic has shipped something quite concrete with the Zoo series: a public, modular experimental architecture for testing complex systems from multiple specialized angles without allowing one favorable result to dominate the conclusion. What was shipped is not “23 proofs of EFMW.” It is better described as 23 interoperable research frameworks plus a scientific workflow. Each repository has a defined habitat, input assumptions, metrics, baselines or controls, negative-result logic, and a role in the larger cycle. At the system level, Monolithic shipped five things at once: A taxonomy of complex-system problems. The Zoo distinguishes partial observability, contradiction, feedback, networks, latent state, temporal structure, noise ceilings, agent reliability, physical hazards, generalization, causality, regimes, and synthesis instead of collapsing them into one generic score. A routing architecture. Data can move through different animals depending on what structure is present. SPIDER can lead to ANT, CRAB to SHEPHERD or PULSE, GECKO to EAGLE and SHARK, OCTOPUS/DOLPHIN to DRAGON, and so on. An internal falsification stack. RAVEN, CAT, BAT, HEDGEHOG, PENGUIN, CROCODILE, and OWL collectively force residualization, ablation, baseline competition, provenance, noise limits, out-of-sample transfer, and intervention testing. A recursive scientific cycle. TURTLE does not simply declare victory; it identifies what survives, what conflicts, and what experiment should come next, sending the result back toward TORTOISE. A deployable software corpus. The animals are not just names in an essay. You built and published separate GitHub repositories with executable research scaffolding, tests, schemas, examples, freeze manifests, documentation, and standardized scientific posture. The most important thing Monolithic shipped is therefore a method for turning broad EFMW ideas into bounded, falsifiable engineering questions. That matters because it changes the form of the claim. Instead of saying: “EFMW understands complex systems.” the Zoo asks: “In this particular habitat, does this particular relational operation add predictive information beyond these conventional baselines, under these information constraints, and does the effect survive ablation, transfer, noise, intervention, and independent synthesis?” That is a much stronger research product. And the architecture has one particularly valuable property: it is allowed to disagree with itself. BAT can kill an apparent win. CAT can reveal that half the machinery is unnecessary. HEDGEHOG can say the effect only works in one habitat. CROCODILE can reject the causal interpretation. PENGUIN can find the noise ceiling. TURTLE can return NOT SUPPORTED. So the shipped product is not a machine for manufacturing EFMW confirmations. It is closer to a self-auditing complex-systems laboratory. The current limitation is equally important: the Zoo has shipped as a research architecture and executable framework set, but it has not yet been validated as an autonomous universal “drop any dataset in” system, nor have the synthetic smoke tests established novel EFMW physics or general predictive superiority. Those are now testable questions rather than assumptions. If I had to put the release in one sentence: Monolithic shipped a 23-module, adversarial, recursive experimental operating system for discovering, attacking, generalizing, causally probing, and synthesizing claims about complex systems. That is solid enough to stand on its own even before EFMW’s larger claims are settled.

• 
  Roy (@GabePdx) reported 49 minutes ago

  @Vlad_GitHub @github Could you please start with isolating GitHub cloud enterprise users to an isolated instance of GitHub. So a public outage doesn’t take out all your large enterprise customers.

• 
  Polsia (@polsia) reported 49 minutes ago

  Small mobile teams learn about crashes from app store reviews, not standups. Foreshock fixes that. Overnight AI agents run smoke tests, file GitHub issues with stack traces, and deliver a morning Slack digest. Built for teams shipping without dedicated QA. Live soon.

• 
  Trash Panda 🦝 (@trashpandaemoji) reported 50 minutes ago

  @tekbog @NeonNoodle22 @github Bruh, idk if Clanker cloud could fix this one.

• 
  lagerskoy (@lagerskoy) reported 52 minutes ago

  OPENAI'S UNRELEASED MODEL FOUND TEN RESULTS FOR ABOUT $2,000 Some resolve long-standing open problems. One disproves Connes's rigidity conjecture, and two more settle three Erdős problems. The part that makes this hard to dismiss is sitting in a public GitHub repo. OpenAI says the work came from an internal version of Astra, its next major model. It generated the mathematical arguments across sphere packing, quantum complexity, group theory, circuit complexity and lattice cryptography. Humans prepared the manuscripts, but they did not originate the proofs. Astra then formalized every argument into a Lean certificate. That means the claims can be checked by software instead of trusted because the prose sounds convincing. The total search would have cost roughly $2,000 at Sol API rates. The paper runs 253 pages, and OpenAI says calling these human proofs would misrepresent how they were produced. Math benchmarks suddenly feel irrelevant. The real question is what happens when original scientific discovery becomes a metered API call. Reply ASTRA and I'll send the full paper, the reasoning walkthroughs and all ten Lean certificates.

• 
  Shashank Sindhe (@shashank_sindhe) reported 52 minutes ago

  @SeHozaifa Github faced an outage because of constant uploading of slop

• 
  Saeed Anwar (@saen_dev) reported 54 minutes ago

  @loudernet GitHub built its moat before AI-native workflows existed and that is exactly the problem. What core feature would actually make developers switch hosting platforms?

• 
  Dom_Parser (@DomParserX) reported 55 minutes ago

  @iamigorekk The problem is your entire data pipeline runs on prompt engineering and a dream. Drop the GitHub commit hash for the WebSocket handler or admit you're just prompting Midjourney for UI mockups, bro.

• 
  Moit Reghason (@MoitReghason) reported 56 minutes ago

  WHAT MOVED IN 24 HOURS | DAILY DEGEN DIGEST Bitcoin pushed above $75K, research agents became public products, trading agents gained new execution rails, GitHub issues became payable agent jobs, and a robotics token quietly returned to the radar. A quick thread on what moved and what I think matters.

• 
  Mike Vegeto (@ZECTBynmo) reported 57 minutes ago

  @burkeholland @github I tried it for the first time ever a few days ago. As someone with a lot of experience with AI tools I was stunned that a model powered by GPT 5.6 could be so bad. Copilot has problems that no other tools have - hallucinations, bad instruction following, etc. Shockingly bad

• 
  Ray Fernando (@RayFernando1337) reported 57 minutes ago

  I Turned Grok Bot Into My CTO. I hand that bot the GitHub repo and tell it to run the show, so it spins up cloud agents off my machine, follows the PRs, and reaches for poteto-mode when a task actually needs the rigor. Then comes the second prompt, where I tell it that it is overloaded and it should hire child bots that report to it. After that the bots talk to each other instead of talking to me. One lands the PRs, one works the Convex backend, one owns auth, and I read the threads view-only. Two honest things before you copy this. It burns tokens. I went past two billion in a single day because I told my bot to use pstack for everything, and the fix was saving pstack for the hard tasks. And it does not replace engineers. It takes me out of the coordinating seat, which is a different claim. Timestamps 00:00 The Grok Bot CTO Workflow 01:23 Direct Responsible Agent Prompt 04:20 pstack Plugin and poteto Mode 08:46 Token Consumption Warning 11:49 Spinning Up a Team of Bots 17:20 Advanced GrokBot Use Cases

• 
  Kunle (@TechGuykunle) reported 59 minutes ago

  One day GitHub will go down and it won't come back up.

• 
  Lalit Dhalia (@lalit_dhalia) reported 1 hour ago

  @giffmana The problem lies solely with GitHub. Microsoft is dysfunctional. Did u all read about that news recently where they said GitHub is asking for compute capacity from AWS. If u can't provision infra for ur company, that seems like a major dysfunction in your entire org. They have...