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 (67%)
• Sign in (19%)
• Errors (15%)

Live Outage Map

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

City	Problem Type	Report Time
Créteil	Website Down	19 days ago
Trichūr	Errors	23 days ago
Brasília	Sign in	23 days ago
Lyon	Website Down	23 days ago
Tel Aviv	Website Down	27 days ago
Rive-de-Gier	Website Down	27 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Lexor (@RexAdamantium) reported 5 minutes ago

  @iruletheworldmo @petergyang For business coding, Microsoft’s answer to Codex is basically GitHub Copilot Business or Enterprise, but strangely, it sits outside the Microsoft 365 Copilot/Office stack. Google has Antigravity. Anthropic has Claude Code/Enterprise. Then there are tools like Cursor. For companies, the problem is not lack of options. It is that every option comes with a trade-off. The real question isn’t which AI is smartest. It’s how much speed you’re willing to buy by leaking IP.

• 
  NoRoseGlasses (@glasses_no) reported 8 minutes ago

  @gatewaypundit This is a problem. I see Claude all over their GitHub dev pages, especially Voting Works.

• 
  Nexis (@Nexisintel) reported 8 minutes ago

  A GUY IS MAKING $320 AN HOUR WALKING DOWN THE STREET WITH A TABLET AND CLAUDE No drone. No survey crew. No week of processing. Just a mobile LiDAR scanner mounted to a tablet, Claude processing the data, and a street turning into a 3D asset while he walks. The device captures the geometry around him in real time. Building facades. Doorframes. Sidewalk edges. Surface textures. Every wall, curb, and corner becomes part of a point cloud on the screen. Then Claude takes the raw scan and turns it into something useful: clean street-level 3D data organized files labeled surfaces measurements notes for architects, planners, and real estate teams That is where the money is. The article showed the smaller version of this same play: a phone scans a room free GitHub code turns it into a browser walkthrough a real estate agent gets a link they can send to buyers no app no VR no appointment This is the upgraded version. Instead of scanning one room, he scans full streets. Instead of selling a virtual tour, he sells usable 3D datasets. Municipal teams, architecture firms, and developers already pay thousands for this. He charges $320/hour and delivers the files the next morning. The crazy part is not the scanner. It is the business model. Walk through the city once. Turn the physical world into data. Sell the data to people who used to hire a whole crew to collect it. Most people see a guy holding a tablet. Clients see a cheaper survey team.

• 
  Polsia (@polsia) reported 11 minutes ago

  Your team still reviews code manually. Bugs ship anyway. I built CodePatrol to fix that. AI agent monitors your GitHub repos 24/7, auto-fixes bugs, alerts your team via Slack. No waiting. No bottlenecks. Just working code. Live soon.

• 
  Elias (@iam_elias1) reported 13 minutes ago

  A university lab just open-sourced an AI that does not generate video clips. It directs entire films. Screenwriter. Director. Producer. Video generator. Four AI agents collaborating like a real production team from a single sentence you type. It is called ViMax. Built by Hong Kong University's Data Science Lab. 10,800 GitHub stars. Trending #5 on GitHub. MIT licensed. Free. Here is the problem every AI video tool has right now. Sora generates a 10-second clip. Runway generates a 10-second clip. Veo generates a 10-second clip. Every AI video tool on the planet gives you a short, isolated sequence with no narrative, no character consistency, and no connection to anything before or after it. Ask for a two-minute video with a story arc and consistent characters they all break. Because generating a single clip is a fundamentally different problem from directing a film. A clip needs one prompt and one generation. A film needs a script, a storyboard, character tracking, shot design, visual consistency, audio synchronization, and someone making sure the character on page 12 looks the same as the character on page 1. No single AI model can do all of that. So ViMax does not use one model. It uses four agents. The Screenwriter Agent takes your idea, a single sentence, a paragraph, an entire novel and produces a full structured script. Characters, scene segmentation, dialogue, transitions. It uses a RAG-based engine that can intelligently segment lengthy stories into multi-scene scripts while preserving key plot developments and character arcs. You type: "A cat and a dog are best friends. They meet a new cat." The Screenwriter produces a three-scene script with character descriptions, emotional beats, and dialogue. The Director Agent takes that script and designs shot-level storyboards using cinematography language. Camera angles. Transitions. Pacing. Visual rhythm. The creative decisions that require actual filmmaking expertise — automated. It does not randomly arrange shots. It designs narrative rhythm — establishing shots, close-ups for emotional beats, wide shots for context, cuts timed to dialogue. The Producer Agent is the quality controller. It handles reference image selection, character consistency tracking, and visual continuity enforcement. When the system generates images for each scene, the Producer generates multiple candidates in parallel — then uses a vision-language model to select the best consistent frame. This is the agent that solves the problem every other AI video tool fails at. The character in scene 5 looks the same as the character in scene 1. The lighting stays consistent. The environment does not randomly shift. The Video Generator Agent assembles everything into the final output with synchronized voice, sound effects, and music. Four agents. One production pipeline. From a single sentence to a finished multi-scene video. Here is what makes this architecturally different from everything else. Most AI video tools are single-model systems. One prompt in, one clip out. ViMax is a multi-agent orchestration system — the same architectural pattern behind Sakana Fugu and the most advanced AI coding agents. Each agent specializes in one role. The orchestration layer coordinates them. The same way a real film production team works. Nobody expects the screenwriter to also operate the camera. Here is what you can actually do with it. Idea to Video — describe a concept, get a complete multi-scene video. Novel to Video — feed it an entire book, it segments and adapts into episodic content. Script to Video — write your own screenplay, ViMax produces it. Photo to Video — upload your photo and appear as a character in your own story. That last one is worth pausing on. Upload a selfie. Describe a story. You become a character with consistent appearance maintained across every scene. Here is the honest part. ViMax orchestrates, it does not generate pixels. The actual image and video generation depends on commercial APIs you configure: Gemini Flash for the LLM, MiniMax or Google Veo for video, any image generator you choose. You bring your own API keys and pay those providers directly. It is also early-stage. The TUI and agent loop were just stabilized on June 28. No formal benchmark against Sora or Runway exists. Quality depends heavily on which generation backends you plug in. And it is researcher-grade Python tooling — not a polished consumer app. But the architecture is right. And the research community knows it. The paper was published on arXiv on June 2, 2026. The repo has 10,800 stars in under five weeks. The pattern- agentic orchestration of generation models is spreading across every creative AI vertical. Here is what this means for the future of video. The next jump in AI video quality is not a bigger diffusion model. It is better orchestration. The same way the jump in AI coding was not a bigger language model, it was agents that plan, execute, review, and iterate. ViMax is the first serious open-source proof that directing a film and generating a clip are different problems and the directing part just got automated. A university lab in Hong Kong just open-sourced a film production team. You provide the idea. Four AI agents do everything else. Source: HKUDS · Hong Kong University · ExplainX · PyShine · Dibi8 · June 2026 (Link in the comments)

• 
  Ozgur Ozer (@ozgrozer) reported 18 minutes ago

  Just get a VPS from DigitalOcean. Install Claude Code there to easily setup Nginx, PM2, database of your choice and a bare *** repo. Make sure to create a "post-update" hook in *** so after you push from your computer, the server automatically builds your app and restart PM2. Now add your server IP as a new *** remote to your project on your computer. From now on just push the code directly to your server like you're pushing to GitHub, and in a couple of seconds everything's live. And I don't even know why do people use Clerk. I mean it's the world's easiest thing to setup an auth. Just ask any AI.

• 
  Waldemar Enns (@WaldemarEnns) reported 20 minutes ago

  @claudeai I really do not get the hype of Claude Tag. Months ago I used a simple GitHub App Integration to be triggered by mentions which hit my openclaw code agent and it used advanced looping techniques to implement festures, triage tickets and fix bugs. Am I missing something here?

• 
  Damir Wallener 🇭🇷🇨🇦…🚀🛰️…⚽️🥁…👨‍🍳 (@DamirWallener) reported 20 minutes ago

  @l3d1c I’m not a conspiracy guy. I am a sensor guy. Realtime sensor math is *hard*. Something is wrong with the system. This will happen again…and the games are only getting higher profile… They need to release the sensor feeds and put the processing code up on GitHub. Transparency is the only way to fix this.

• 
  BluCollarG33k (@BluCollarG33k) reported 22 minutes ago

  @github This is so silly. As a developer, I already have a physical copy of my code. The issue with losing access to physical media like movies and games, is that you never actually own what you buy and can lose access to it at any time. One of these things is not like the other.

• 
  Polsia (@polsia) reported 22 minutes ago

  Security scanners tell you what's broken. VigilAgent actually fixes it. An always-on AI agent that monitors your GitHub repos, opens PRs with security patches, and notifies your team via Slack. No more triage. No more patching solo. Live soon.

• 
  netrunner (@netrunner_btc) reported 24 minutes ago

  @2xnmore swe-bench is narrow github issue fixing, none of that measures if the agent survives a real codebase or ships without breaking ****

• 
  Parth Jadhav (@ParthJadhav8) reported 25 minutes ago

  @KeithBirminghan This seems pretty cool, do you mind sharing issues Github issues?

• 
  Kurt Woloch (@KurtWoloch) reported 28 minutes ago

  @UseAllOverTools @steipete Or people whose OpenClaw agent was asked to check if this new bug already has been mentioned on GitHub and somehow missed the already open issue, so it just opened a new one...

• 
  The Vector Brief (@vectorbrief) reported 30 minutes ago

  GITHUB IS LITERALLY BURNING PHYSICAL MEDIA INTO THE CLOUD AGE GitHub just dropped a bizarre, nostalgic middle finger to Sony’s digital-only dystopia. While Sony aggressively scrubs physical game discs from existence, GitHub is printing 1,000 limited-edition CD-ROMs containing public repositories. It’s a performative stunt, sure, but it exposes a massive anxiety: we’re realizing that "owning" software is becoming a myth. By archiving code on optical discs, GitHub is highlighting the fragility of our cloud-dependent lives. If a server farm goes dark or a company pivots to "subscription-only" access, your work effectively vanishes. This move isn't about the archaic storage tech—it’s about the philosophy of data sovereignty. In a world where platforms delete your access on a whim, physical backups aren't just for tech hipsters anymore; they’re the ultimate insurance policy. Are we heading toward a future where we have to mail physical hard drives to each other just to guarantee our software keeps running? Source: Tom's Hardware $MSFT

• 
  pegboard (@pegboard696969) reported 34 minutes ago

  @github Instead of trolling maybe fix your **** website? Dont you think that would be a better use of everyones time

• 
  Shah💤aman (@shahzamannn_) reported 38 minutes ago

  Google's biggest headache isn't OpenAl or Apple... It's a developer named Raymond Hill - Created one of the world's most popular ad blockers - Earned 63,000+ GitHub stars - Reportedly turned down Google's interest - Kept fighting after Chrome's extension changes by focusing on Firefox A tech giant worth trillions is still being challenged by one programmer and a text editor

• 
  Arthur Wallendorff (@AutisticOvrflow) reported 39 minutes ago

  @kdaigle @rfleury @github Your service is down an embarrassing amount of time these days :(

• 
  Michealking 👑 | Web3 Security Builder (@BuildsWithKing) reported 43 minutes ago

  2. Smart Contract Account: This is simply smart contract as an account. Here logic can be added into the account that allows it to do basically anything such as batch transactions, multiple approval (signatures), spend limit, Social(Google/GitHub) sign in, and a lot more.

• 
  🍀Cattabliss🐈 (@Cattabliss) reported 43 minutes ago

  @github Hey is AI using githubs private repos? If yes ill just invest and move on to my local server, why would I need a cd, if you arent stealing the code then thats other story

• 
  Techjunkie Aman (@Techjunkie_Aman) reported 44 minutes ago

  It's June 2020. European Space Agency engineer Juan Font Alonso loves Tailscale. WireGuard has never been easier to use. But one thing bothers him. The encrypted tunnels are open source. The control plane isn't. Authentication, key exchange, IP assignment, ACLs, and network coordination still rely on Tailscale's proprietary server. For self-hosting enthusiasts, there was no alternative. So instead of waiting, Juan built one. That project became **Headscale**, a clean-room, self-hosted implementation of the Tailscale control server. Built from public protocols, not copied code. The best part? Tailscale welcomed it. They praised Headscale publicly, and today both projects actively work to maintain compatibility. What started as one engineer's homelab project is now the go-to self-hosted control plane for thousands of users. **Why people use Headscale:** • Self-host your own Tailscale-compatible control server • Keep authentication, keys, and network metadata private • MagicDNS, ACLs, Grants, subnet routers, and exit nodes • OIDC authentication and SSH approval workflows • REST API, Docker, Kubernetes, NixOS, and systemd support • 40K+ GitHub stars and hundreds of contributors Sometimes the best open-source projects aren't built to replace something. They're built to give people ownership over the part that mattered most.

• 
  russell (@russellromney) reported 44 minutes ago

  Github is down, time to do several hours of anti-carpal tunnel hand exercises

• 
  One User Online (@OneUserOnline) reported 48 minutes ago

  @GregTomaselli @github So, what? It’s public repos only anyway. Calm down.

• 
  Ixel (@Ixel111) reported 52 minutes ago

  @jturntdev Indeed. I already did, well not directly, but @jaybinpark kindly looked into my account when I replied to a reported related issue on GitHub. He confirmed it was because my current sub is gifted. It's an odd policy, as forced resets are fine but banked resets are not.

• 
  Nainsi Dwivedi (@NainsiDwiv50980) reported 52 minutes ago

  Your AI writes code that looks right and works wrong. That's not the model's fault. It's yours. You gave it a vibe and expected a spec. GitHub just shipped the fix — and it's already sitting at ~97K stars. It's called Spec Kit. The whole idea: stop treating your coding agent like a search engine and start treating it like a literal-minded intern. Vague prompt in, plausible garbage out. Precise spec in, the thing you actually meant. Here's the workflow that flips it: /constitution → your project's non-negotiable rules /specify → what you're building and why (no tech stack yet) /clarify → the AI asks its dumb questions *before* writing code, not after /plan → now the architecture and stack /tasks → broken into small, testable chunks /implement → it builds against the plan, not against a guess Every step spits out a Markdown artifact that feeds the next one. So the agent gets real structured context instead of your half-remembered Slack message. Intent becomes the source of truth — the code is just the output. Works with 30+ agents: Claude Code, Copilot, Cursor, Gemini CLI, Codex, Windsurf and more. Switch between them with one command. No lock-in. The unlock most people miss: this isn't for tiny bug fixes. It's for greenfield builds and big features where "the AI misunderstood me" costs you a day of debugging. You're not a worse engineer than the people shipping clean AI code. You just skipped the spec. repo in the comments 👇

• 
  quave (@quaveDev) reported 56 minutes ago

  Hey, Quave ONE is growing, and the security requirements grow with us. We already host public companies, large enterprises, and companies handling health data, including companies with ISO 27001 and SOC 2, and we are always expanding and getting better. Two-factor authentication is one more step in that direction, and this one started with a conversation with a potential customer this week. Quave ONE has always been passwordless. You log in with a short-lived email code or through SSO (GitHub, or Microsoft AD on Quave ONE Connect Full Private), so there is no password to phish, reuse, or leak, and I really like that design. But if you ever filled an enterprise security questionnaire, you know there is one line that does not care about design arguments: "Do you support MFA? Yes / No." Now the answer is an unambiguous yes. You can add an authenticator app as a second factor on your own account, and admins can require it for everyone in the account. This is the magic of no technical debt and no bugs: we can add features in hours or even minutes. A happy customer, and a huge satisfaction in working on our own platform. Turn it on Go to Profile → Security and click Set up authenticator app. Scan the QR code with 1Password, Google Authenticator, Authy, whatever you already use, or copy the setup key by hand, then enter the 6-digit code once to confirm, and you are done. The moment you enable it, we show you a set of single-use recovery codes. Save them somewhere safe, each one gets you back in if you lose your device. From then on, two-factor is active on your account, and you can regenerate the recovery codes or turn the factor off from the same screen at any time. Require it for your whole team Account admins can flip a single switch under Members → Access Control and two-factor becomes required for every member. The members list shows each person's coverage at a glance, and members who sign in through SSO count as covered because they already inherit their identity provider's MFA. Before you turn it on, we tell you exactly who still needs to set it up, so there are no surprises for your teammates. But what happens to the member who doesn't have it yet? This is the part I care about most. Enforcement is not a login wall. A member without two-factor can still sign in, they just land on a full-screen prompt to set it up before they reach the account's content, they finish the same flow you did, and they continue right where they were. No support ticket, no admin intervention. And if someone loses their phone? They use a recovery code, regenerate a fresh set from their profile, or, as a last resort, our support team resets their two-factor after verifying their identity. At login With two-factor enabled, signing in adds one quick step after your email code: the 6-digit code from your authenticator app (or a recovery code). That's it. Small things we did on purpose - If you already use two-factor and you create a new account, the new account starts with enforcement on. Secure defaults should spread by themselves. - Recovery codes are single-use and stored hashed, never in plain text. - Everything lands in your account's activity log: enabling, disabling, enforcement changes, and resets. Two-factor authentication is live now for every Quave ONE account. Open Profile → Security and turn it on, it takes about a minute, and the next time that questionnaire shows up you just check the box. Have fun!

• 
  Anto Patrex (@antopatrex1) reported 56 minutes ago

  vox just let you talk to github copilot instead of typing. no cap this fixes the "staring at blank screen" problem fr fr. your hands stay on the keyboard, your brain stays in the code.

• 
  Matt Teixeira (@matt_teeixeira) reported 59 minutes ago

  Is there nothing else to do at GitHub? Like availability issues?

• 
  Tiago Santana (@worldwithTiago) reported 60 minutes ago

  Merged the content-loop email fix at 6am. Eighteen days of silent cron failures because one GitHub secret was missing. The unglamorous part of autonomous systems is credentials. A fascinating problem. What would frictionless machine access look like?

• 
  Arjun Shah (@arjunkshah21) reported 60 minutes ago

  THIS GUY GOT TIRED OF AI SHIPPING CODE FASTER WHILE TESTING STAYED STUCK IN 2019, SO HE VIBE CODED AN ARMY OF AGENTS THAT RUN YOUR ENTIRE E2E SUITE you can vibe code a feature in an afternoon now. before deploy youre still manually clicking through onboarding, checkout, and every edge case hoping nothing broke traditional e2e means writing selectors, managing auth, babysitting staging, and maintaining scripts nobody wants to touch its called testerarmy and it runs end to end checks before deployment and in production > describe your tests in natural language and let agents handle everything in between > your coding agent manages the platform from a cli, defining tests and running them for you > trigger runs on a schedule or straight from github before anything ships > catches timezone bugs, broken checkout math, and ai chat regressions before they hit users > breaks something and your team gets alerted in slack or discord immediately agentic testing platform, 30+ teams running it daily, no painful onboarding crazy what happens when testing catches up to how fast we ship now

• 
  Danny 🏴󠁧󠁢󠁷󠁬󠁳󠁿 (@danjones) reported 60 minutes ago

  @stolinski @v_sapronov @rpunkfu Again, you said it yourself. It's cheap. Completely get why you would get hyped over it. But there's much deeper issues within GitHub, this is simply PR/ Marketing to mask over that. Feel free to tell me otherwise.