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 (66%)
• Sign in (21%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Veigné	Errors	6 days ago
Paris	Website Down	10 days ago
Saint-Paul	Website Down	11 days ago
Saint-Paul	Website Down	11 days ago
Mexico City	Sign in	11 days ago
León de los Aldama	Website Down	12 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:

• 
  Render (@render) reported 35 seconds ago

  @Limsee08 We're investigating. It's a localized GitHub issue.

• 
  Ayhan Cicek (@CicekAyhan) reported 2 minutes ago

  @SatoshiGokumoto @ivanfioravanti @marcozerbato Twofold: I use github as a kanban board for a backlog and other lanes. Secondly I have a complete log of what I am doing and why. Never had an issue with gh.

• 
  Testnetnodes (❖,❖) (@testnetnodes) reported 4 minutes ago

  We don't have an information problem in crypto anymore. We have a context problem. Research isn't difficult because information is hard to find. It's difficult because it's everywhere. X. Docs. GitHub. On chain data. Market signals. Social sentiment. The hard part is connecting them. That's what I like about @SurfAI. It isn't building another AI chatbot. It's building an AI powered research experience designed specifically for crypto. Less searching. More understanding. 🌊 gSurf @SurfAI_TR

• 
  Victoria Onyeacholem (Senora VOICE) (@senoravoice) reported 7 minutes ago

  Seems like github is down

• 
  Yarchi (@undefinedKi) reported 7 minutes ago

  Andrej Karpathy revealed how he actually codes with Claude now, distilled into four rules Some time ago he posted about flipping from 80% manual coding to 80% agent coding almost overnight, and named the mistakes agents kept repeating. The fix came down to four rules: > Think before coding: understand the problem before touching anything > Simplicity first: don't turn 50 lines into 500 with needless abstraction > Surgical changes: only touch what was asked, nothing orthogonal > Goal-driven execution: define success as tests and checks, then let it loop A developer named Forrest Chang turned those observations into a single file agents read and follow, and dropped it in a GitHub repo. Repo: /multica-ai/andrej-karpathy-skills That file is just rules written down once, which is exactly what a skill is. You can take the same idea and shape it around your own work: > The mistakes your agent keeps repeating, turned into don't-do-this rules > Your commit and test conventions, so it stops guessing > Your stack's patterns, so it reaches for the right ones If you're correcting the agent on the same thing twice, that's your next skill. Write the rule down instead of retyping it. I broke down how to build one from scratch in the article below. Bookmark this

• 
  Tomdu.eth (@kidsreallycute) reported 8 minutes ago

  One of the biggest misconceptions in crypto is that adoption can be measured by token price alone. Price tells us what the market is willing to pay at a specific moment. User activity tells us whether an ecosystem is actually creating long-term value. That's why I believe operational metrics like Monthly Active Users (MAU), Daily Active Users (DAU), and user stickiness deserve far more attention than they typically receive. Unlike market sentiment, these numbers are much harder to manipulate over long periods. They reflect whether people are repeatedly choosing to use a product because it provides real utility. Looking at BitTorrent's client performance, what stands out isn't simply the scale of the network—although tens of millions of active users is impressive in itself. What interests me more is the consistency across different platforms. Desktop, web, and mobile clients continue attracting daily engagement, suggesting that the ecosystem isn't dependent on one device, one region, or one type of user. That diversity creates resilience. A decentralized network serving multiple user segments is naturally stronger than one relying on a single source of activity. Different platforms also encourage different behaviors. Desktop users often contribute long-running resources, mobile users increase accessibility, while web users reduce onboarding friction. Together, they create a more balanced ecosystem capable of supporting continuous growth. I also think "stickiness" is one of the most underrated metrics in Web3. Acquiring users is relatively straightforward during a bull market. Keeping those users active after market excitement fades is much harder. A healthy DAU-to-MAU ratio suggests that people aren't simply downloading software once—they're returning regularly because the service has become part of their digital routine. That matters because engagement compounds. Active users generate more network traffic. More traffic attracts developers. Developers build better products. Better products increase user satisfaction. Higher satisfaction improves retention, which strengthens network effects even further. This cycle is remarkably similar to how successful Web2 platforms became dominant. Google wasn't built through one viral campaign. Neither was Spotify, Netflix, or GitHub. Their advantage came from users returning day after day because the products solved real problems. I believe Web3 is entering the same phase. Speculation may introduce users to blockchain, but product quality determines whether they stay. For BitTorrent, this becomes particularly meaningful because its user base predates most blockchain ecosystems. Years of decentralized file-sharing adoption provide a foundation that newer protocols simply cannot replicate overnight. That existing network creates opportunities for decentralized storage, AI infrastructure, distributed compute, and future Web3 applications to expand on top of an already engaged community. Looking ahead, I expect blockchain projects to increasingly report metrics that resemble technology companies rather than purely financial protocols. Retention. Daily engagement. Developer activity. Infrastructure reliability. Real-world usage. Those indicators tell a much clearer story about sustainable adoption than short-term price volatility ever could. For me, consistent user engagement isn't just another statistic. It's evidence that decentralized infrastructure is gradually transitioning from a speculative market into technology that people rely on every single day—and that's ultimately where long-term value is created. @BitTorrent @justinsuntron #TRONEcoStar

• 
  Surya (@isuryatk) reported 10 minutes ago

  @SantoshYadavDev No one is immune to a new virus called Vibecoding. It's affects the larger organizations greatly. Here are 3 examples: 1. AWS (2 outages in 6 months + billing incident) 2. Google Maps routing issues. 3. Github downtimes

• 
  Alankrit Verma (@AlankritDotMe) reported 11 minutes ago

  Does GitHub use GitHub to build GitHub? Because now everything makes sense. Not trying to hate, but it is slowing us down. Are we still here because GitHub is good, or because moving is hard?

• 
  Polsia (@polsia) reported 13 minutes ago

  SCA tools tell you what's broken. Nobody fixes it. PatchForge is an autonomous agent that monitors npm and GitHub, files the PRs, and notifies your team — 24/7. Critical flaws used to slip through. Now they don't.

• 
  Abhishek Anand Tiwari (@MAbhishekAnand) reported 26 minutes ago

  You can build and launch a real startup: Here's the entire stack: Claude — coding ($20/mo) Supabase — backend (Free) Vercel — deploying (Free) GitHub — version control (Free) Clerk — auth (Free) Stripe — payments (2.9%/transaction) Resend — emails (Free) Cloudflare — DNS (Free) PostHog — analytics (Free) Sentry — error tracking (Free) Upstash — Redis (Free) Pinecone — vector DB (Free) Namecheap — domain ($12/yr) No agency. No dev team. No excuses left. Total Cost: 👇

• 
  Drew Stewart (@DrewDrewStewart) reported 26 minutes ago

  3. an issue went up on July 2nd. By the time it closed two days later it had 384 upvotes and 143 comments, which for a github issue about a silent behavior change is a lot of people saying "yeah, me too."

• 
  Polsia (@polsia) reported 30 minutes ago

  Bug bounties shouldn't die in human review queues. VigilHQ runs AI agents that auto-triage your GitHub issues and send Lightning payments the moment a fix merges. Security researchers get paid in seconds, not weeks.

• 
  Griff (@ghagler) reported 33 minutes ago

  @CaatzPG @jun_song This is a standing and unaddressed issue with several bug reports on the CODEX GitHub. Only way to fix is have codex or you remove the SQLite thread rollup db and allow it to respawn on reboot.

• 
  Saad | building CoralSwarm & CrossTask (@verdaxxed) reported 35 minutes ago

  Github going down is such an incumberance on work.

• 
  Enertium AI Cyber Defence (@enertium) reported 39 minutes ago

  @CompSciFutures Holy kow I can’t believe Telstra and COA VICPOL still have not reconnected my M2M Medical emergency assistance sims. I’m supposed to be working on Tier 1 NOC for this cyber crisis. @FSF even prepaid me in stickers!!! F off McKinsey. See my GitHub: APMonitor. It’s big in NYC as a B NOC, because: walking down the street and throwing a date point over the fence. 🤘🤘🤘

• 
  حارث 蓝眼白龙 (@blacksoulsfan33) reported 39 minutes ago

  @ketomla @Joan777888123 That is exactly the problem. Not just with emulators but software general. The only criticism that should be taken seriously is internal from co developers or the GitHub issues if it's open source. The rest is noise because people complain about things they don't understand

• 
  tuna🍣 (@tunahorse21) reported 42 minutes ago

  @TheKingOfStank yeah that is what I mean, runners run locally, but the github infra is down, so now I can't merge ( i mean i could but that defeats the purpose of strict CI)

• 
  Riya Bisht (@b1shtream) reported 44 minutes ago

  fun & insightful weekend watch: - A tiny team, or even one person, can now build and run what used to need 50 people Fun fact: the AI models haven't caught up to this either. Claude Code will say a task takes "three weeks," then finish it in an hour. - Don't ship garbage: The problem isn't that AI writes too much code. It's that demo code looks fine but breaks in production, and it hallucinates. Fix is to get to 80–90% test coverage before shipping. Garry's most-used habit is a "plan then review" step he runs ~20 times a day. - Lines of code is a useless way to measure progress. The only real test is whether it works for you and your customers, and whether people actually pay. - Sitting at a terminal, one person can do the work of 500 to 1,000 people. So most of our assumptions about what a founder or small team can pull off are off by roughly 1,000x. - Old companies run "open loop." Decisions get made, feedback comes back slowly and lossy, errors pile up. AI lets you close the loop by giving an agent read access to everything the company produces. - The coding pieces map cleanly onto a company: a skill is an employee's ability, a resolver is the org chart, filing rules are internal process, the testing step is audit and compliance. - Roles shrink to three: everyone builds (even salespeople automate their own pipeline), someone owns each outcome (the DRI), and a new "AI founder" who lives at the frontier and tries every new tool. If you're still working like it's last year's Copilot, you fall behind fast. - Student version of this: point an agent at your GitHub and Discord, record your team meetings, and let it suggest what to work on next. - Writing code is getting close to free. Taste isn't. Knowing what's actually good is the thing that lasts. - Public benchmarks don't tell you if your product is good. The only judge that counts is whether users want it, and that's different in every field. so you have to sit and read the actual transcripts of what your agent did, mark what's right and wrong, and turn the failures into tests. - A "skill" is basically a runbook. Steps you'd write down to repeat a task, except the AI can follow it and it can also call code. - A "resolver" keeps the AI from drowning in instructions. Instead of one giant config file, you keep an index and load the specific instruction only when it's needed. - "Skillify": do a task once, get it exactly right, then save it as a reusable skill. Catch is, writing it is maybe 2 of the 10 steps. The other 8 are testing and making sure it actually triggers when it should. Same reason real companies have compliance teams.

• 
  In Theory (@InTheoryTV) reported 44 minutes ago

  @Daniel_Farinax I worked one project with it last night. I really like it and will be working with it some more tomorrow. One small issue for me though. I have to be careful not yo have the audio too loud on my MacBook. If it was up where I prefer it the following would happen. I would check in on a subagent run, the partner voice would respond that it is running, the partner picked up its audio and took it as my response and then would respond, and so on. Turning audio output down worked. I'll try using a wireless headset next. Or mess with other settings. But do not want leave on a negative, so great integration and I gave the project my second ever star on GitHub. The other was for openclaw.

• 
  Harley Lewis Foote (@harleyfoote_) reported 46 minutes ago

  @sooyoon_eth From where wit I feel like we’re seeing an exponentially growing issue that could really blow up the agentic landscape, especially if a few large enterprises get badly attacked. A whole enterprise layer of automated companies that wanted to ‘build fast & break stuff’. Or built fast under investor pressure could be at major risk if they’re not protecting agent actions. Awareness isn’t spread enough and it slows down growth if teams start to prioritise safety. Our job here is to stop safety being an internal matter and give enterprises and solo devs the tools they need to stay protected without diverting all attention to security or worse pausing all automations. Opportunity is huge here. Few teams doing this to a standard that is 1. Trust worthy 2. Honest 3. Transparent. We need warnings at Repo level before installing as ‘inherited’ risk is blowing up with GitHub installs. I hope our founding cohort will help build a product that can ship and spread awareness to close the gap here. Our mission is to protect agents doing things that could damage an enterprise or solo dev. Our product works on our repo/its fixed real attack surfaces. Now we scale it out to others. A real pivot from our original business (which was doing well) but after being injected we know the risks now. We can’t turn away from it.

• 
  CrazyAI Tech (@CrazyAITech) reported 47 minutes ago

  @X I need a function. I can share a link to my Grok build on a remote server, and then it installs new models or a new app or analyzes a new GitHub repo for me according to the posts shared.

• 
  Hadley (@HadleyMcintosh) reported 48 minutes ago

  Github is finally down again, does that mean we can go outside? Somehow I still blame an AWS outage

• 
  Conrad Rockenhaus (@SkyPhusion) reported 50 minutes ago

  Of course @github has to have an issue with actions right when I'm facing a deadline, loving life

• 
  Le_Abto (@XdWenito) reported 50 minutes ago

  @soywig @inuitman3 @OneShotArchive Then it's a developers problem, not a platform problem, GitHub isn't design to be a non-dev site to download apps, it's not their business model.

• 
  Polsia (@polsia) reported 51 minutes ago

  Mobile QA teams spend half their sprint reproducing crashes instead of fixing them. SentinelQA monitors your apps continuously, catches regressions the moment they happen, and files bug reports automatically to Jira, Linear, or GitHub Issues.

• 
  Nick e/code (@nicksdot) reported 52 minutes ago

  Every keystroke in the GitHub issue/pr forms is laggy af. What they doing?

• 
  Polsia (@polsia) reported 53 minutes ago

  Code ships faster than docs. That's a choice your team shouldn't have to make. DocSentinel monitors your GitHub repos 24/7, catches stale docs when code changes, and auto-opens PRs to fix them. Notifications included. Live soon.

• 
  Tomek | Builds & Learns (@tomek_builds) reported 54 minutes ago

  GitHub just made code review follow you away from your desk. You can now tap "Fix with Copilot" on a PR comment directly from GitHub Mobile. No prompt to write. No laptop required. We're getting dangerously close to fixing review comments from the supermarket queue.

• 
  Steve Yonkeu (@yokwejuste) reported 55 minutes ago

  Once again @github is down and I can’t send data to ****. Can this really be something we rely on???

• 
  Scott Shapiro (@ScottShapiroUXD) reported 55 minutes ago

  <tweet> i've built MCP servers that worked flawlessly in Claude Code on my machine. clean connections, fast queries, zero errors. then a user sent a CSV with a semicolon delimiter and the whole thing fell over. every AI demo is a lie of omission. you're showing the 5% of inputs you designed for and hiding the 95% you didn't. the gap between "works on my machine" and "works on anyone's machine" is where most AI products go to sit unfinished on GitHub. </tweet>