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 (68%)
• Sign in (18%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Ashkelon	Website Down	1 day ago
Veigné	Errors	9 days ago
Paris	Website Down	13 days ago
Saint-Paul	Website Down	13 days ago
Saint-Paul	Website Down	14 days ago
Mexico City	Sign in	14 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:

• 
  Brahim (@IBthecoder) reported 1 minute ago

  Developers have a new problem ! Hackers created 7,600 fake GitHub repositories designed to spread malware.

• 
  Nyra (@Nyra_nx) reported 4 minutes ago

  A guy built an AI second brain in 1 afternoon and now charges clients $2,000 a month to run it for them. No code. No degree. 3 free tools. Most people treat notes like a graveyard. You write something, save it, never open it again. 4,000 files. Zero connections. Dead weight. The fix isn’t discipline. It’s wiring the notes to think for you. Part 1 — The vault. Install Obsidian. Free. This is where the brain lives. Every note, every voice memo, every half-idea goes in one folder. 10 minutes to set up. Part 2 — The skill. Go to GitHub. Install the Claude second-brain skill. This is the part 99% skip. The skill teaches Claude how to read your notes, pull the key concepts, and link them on its own. No manual tagging. Part 3 — Run it. Give Claude access to the vault. Run the skill once. It reads everything, finds the threads, connects them. Then open graph view. 400 notes turn into a live map. You watch every project link to every other project in real time. Here’s the part that pays. Regular memory forgets. This gets smarter every time you feed it. It holds context across months, across clients, across projects. It never loses the thread. So you stop selling notes. You start selling the brain. 3 things people pay for right now: A client database that remembers every call, every promise, every deadline.

• 
  Vinny (@hot_town) reported 7 minutes ago

  I deployed Open SaaS to OpenShip (@openshipio)! It was my first time successfully self-hosting an app on a Hetzner VPS. The video below summarises what it took to get it done, and some of my thoughts on the process and platform, e.g.: - Server: Hetzner CPX22 4GB RAM, 80GB disk, with Ubuntu 24.04 -> $23/month - Create an SSH key locally, add it in Hetzner, and set up firewall rules - Add the server in OpenShip - Buy domain, point it at VPS - Write a Docker Compose file and Dockerfiles so OpenShip would deploy all three parts of Open SaaS stack (react, expressjs, postgres) as one unit - Set Env Vars - Add domain TXT records and get SSL certs Things I like: - Auto-deploy from GitHub pushes. - OpenShip handles domains, certs, and SSL provisioning for you. - Built-in jobs and backups: nightly database backups called out as a genuinely cool feature. - Satisfaction of ending up with a fully self-hosted SaaS. Things I didn't like: - The "$5/month VPS" everyone talks about wasn't actually available in any region. Ended up at $23/month. SAD. - OpenShip is still in beta and I hit multiple bugs. - Deploying anything multi-service isn't a first class citizen on OpenShip yet / requires hand-writing Docker config. - Whether to run your own mail server on a VPS is contested. Verdict: - At $23/month, managed hosting providers still look like better value until you have serious traffic, given how little you have to think about. - Would use it for hobby apps and small projects; wouldn't put an important or high-traffic SaaS on it yet until I trust OpenShip more and understand self-hosting better.

• 
  roshan (@roshan_k_) reported 13 minutes ago

  github really sucks. its slow, and I constantly feel myself going back to an editor, especially for huge changes. meanwhile, we're pushing (and therefore reviewing) more code than ever before. luckily, the era of personal software is here, and you can build the experience that you want.

• 
  Aixa (@aixarizzo) reported 13 minutes ago

  can ai write like you? let's test it 3 of these tweets are claude with my voice skill trying to be me. 1 is real me 1. dating apps should show github contribution graphs. i can't fix a man who can't commit 2. my biggest red flag is that i explain mcp servers on first dates 3. the pasteis de nata almost make up for how toxic portuguese men are. almost which one is human?

• 
  Vokal.team (@Vokal_team) reported 14 minutes ago

  AI made generating work fast. That’s no longer the bottleneck. The bottleneck is review. Is this answer sourced? Did the agent use the right documents? Who actually owns the final decision? Did anyone approve this before it reached a customer? Will the next person understand why this changed? Most teams only discover these problems after the output has already landed in Slack, Linear, GitHub, Notion, or a customer thread. Vokal moves review closer to the work. The agent runs where the team can actually see it. The task, sources, owner, and decision trail stay attached from the start. Humans stay in the loop before the work becomes a messy handoff. That’s how AI stops being chaotic and starts becoming operational.

• 
  Florian Brand (@xeophon) reported 16 minutes ago

  @angerman the code on github is the machine code but with less hoops (and in this case also the correct solution, as reading gh shows a package bump would've solved the problem)

• 
  Sam Presvelos (@SPresvelos) reported 16 minutes ago

  Things I never thought I would do as a lawyer - post a contribution to GitHub for a PDF viewer issue @NousResearch Also never thought I’d ever need to learn what GitHub is…. Times be changing.

• 
  Lars Jansen (@oldstackjournal) reported 17 minutes ago

  I set up a loop where ChatGPT writes the next GitHub issue(task or job), Codex builds it, tests it and opens a PR, then ChatGPT reviews, merges and queues the next job. I go to sleep; the system keeps building. 🤯 I'm going to bed for a change💪

• 
  Nathan Flurry 🔩 (@NathanFlurry) reported 17 minutes ago

  @nichochar partially agree, but i also think the platform has been feeling stale since the acq actions, pull requests, issues all feel like they could have kept evolving after the acq e.g. graphite, blacksmith, depot, linear diffs have been rebuilding github from the outside

• 
  MATHEMATICAL_EQUATIONS (@AI_Edge_Studio) reported 18 minutes ago

  @SilverYogensha @fulg0re @jimcramer Then shut down Github

• 
  RawZ06  (@RawZ06Off) reported 18 minutes ago

  @openshipio Congrats on shipping this, the comparison table is well done. For my use case though, I don't think it'd bring much value over what I already have: I run Dokploy but build entirely outside of it via GitHub Actions, push to a private registry, and just trigger a repull on deploy. So the server stays free either way, and I already get managed reverse proxy / SSL through Dokploy. The migration cost wouldn't really be justified without a concrete pain point to solve. Still, nice execution, will keep it in mind if I hit limitations with my current setup.

• 
  Teri Radichel #cybersecurity #ai #pentesting (@TeriRadichel) reported 18 minutes ago

  I was just thinking about the complex multi threaded code my AI agents 🤖 randomly deleted. How did the agent even figure out that it deleted it two days later? How did it know the architecture had reverted to an old design? See at some point I had it all working perfectly. Almost. Except that records were failing to write due to locks. A particular record would have a line in the logs saying there was a timeout writing it due to a lock. The agent suggested I solution in a really convoluted way. I said oh, you mean like a producer consumer queue? Kind of I guess it says. But I know I’m risking messing up the whole thing again if I let it attempt that architectural change. But then, records are not being processed randomly. This is not a simple change. I say ok. Round and round not working. So I pose the question to Google AI. It suggests a dead letter queue. Of course. That is how I built systems in the past. So now I’ve got this second process processing resource ids as things are deployed via a parallel processor across regions, environments, and accounts. And I’ve got a dead letter queue for things failing to write to the tracker. And it’s kind of working. But there are bugs. Tricky bugs across the data model, the tracker data, dependency checking, and the whole structure of AWS. Deployed with organizations or account role, global or regional resource? Associated with an account or not? What is the type and the configuration of the type? The models have documented the architecture and usually update their README after. But not always. And it’s natural language so not precise. But what I was thinking about is this: How did it figure out that the producer consumer queue was reverted to an old design. How did it know it was an old design? Somehow it had to know about the design changes over time, right? I tell it to log its prompts and it randomly does or does not. I’m not real strict about it. I have a. Global prompt to read recent memory on start up. If code was deleted in a prior session, entire files, and suddenly it’s like woah! An old version of the tracker code is on your system! How did it know that? Was it looking at prompts and responses in memory? The README? Did it misinterpret the dead letter queue? It seemed to know when the code changed but it was misinterpreting time based off the last item in the dead letter queue. What if there had been no errors for two days. I don’t know because I didn’t look at what was in the queue. Because AI. This is what happens. I think the next step when I get back to it will be an overall system design in a separate project the agents can’t touch. Because I think I finally have this dialed in. Then the agents can’t deviate from that design. Hopefully. I did this before when I was using multiple agents to build a system. I had the requirements in a locked down project they couldn’t edit. But it is useful to let the agents document their changes in the README. Hmm. I like the concept of a separate tester but whenever I use multiple agents it burns credits like crazy. Well I’m done with this for a bit.. But I’m noodling over how we can better trust the code and know if and when major architectural changes are made, files are deleted, etc. I’m not giving this access to my primary github repo. But perhaps there’s a way to have an intermediate repository. Have some ideas about that. And greater isolation for agents. What I have is not good enough. It’s better than what a lot of people are doing but I have another idea I want to try when I have time. And as I’m writing this I’m thinking about the painful code review I used to have to go through at a bank with a one guy bottleneck. He was annoying at times but he did find a few logic errors and I learned a lot about transaction locking and auditing every data change at that job. And I’m doubting AI agents can safely write code like that. And if you think that guy was a bottleneck before…Good luck.

• 
  Rob Hallam (@robj3d3) reported 19 minutes ago

  If you wanna do it yourself, this is how: Buy (~15 min) 1. Cheap VPS from Hetzner or DigitalOcean (~€5-10/mo), Ubuntu 24.04, tick automatic backups at checkout 2. Add your domain to Cloudflare (free plan), switch nameservers at your registrar 3. Install Termius (SSH app) + Tailscale (private network) on laptop and phone, free tiers Lock it down (~20 min) 4. Generate an SSH key in Termius, add it to the VPS at creation. Keys only, never passwords 5. SSH in once via public IP, run updates, install Tailscale on the server, log it in 6. Disable Tailscale key expiry for the server (admin console, one click) 7. Verify you can SSH via the server's Tailscale 100.x address BEFORE the next step 8. Provider firewall: delete all inbound rules, allow only port 443 from Cloudflare's published IP ranges. No public SSH at all. You enter through the tunnel 9. Test from outside: public IP times out on everything, Tailscale IP connects. Server is now invisible 10. One SSH key per device. Phone gets its own key added to authorized_keys Install the brain (~5 min) 11. apt install tmux then install Claude Code (official native installer, one curl command) 12. Run Claude Code inside a tmux session so it survives disconnects and keeps working while your laptop is closed Hand over everything else 13. Write ONE long handover prompt telling Claude Code: the server facts, the security model (so it doesn't "fix" it), folder conventions (/srv/ per project, one tmux session each), your preferences, and standing rules (confirm before destructive actions, new services bind to localhost/Tailscale only) 14. Make it write all of that into CLAUDE.md first, so every future session already knows everything 15. Backups before features: nightly job pushing your data to GitHub, tested, before a single page exists 16. Then let it install the web server (Caddy + Cloudflare DNS plugin plays nicest with the locked firewall), set up SQLite, deploy the first page From then on you never administer the server again. You open Termius from anywhere, on any device, and just say what you want. BOSH

• 
  0xNyro1 (@0xNyro1) reported 27 minutes ago

  There's a number inside Claude Code that decides your bill, and most people have never looked at it once. GitHub keeps theirs above 94%. A drop to 70% gets logged as a bug. Most people sit at 40% and don't know the number exists. It's the cache hit rate. Their CPO compared it to high-frequency trading, where 1% of efficiency is millions of dollars. Five moves fix it. One. Stop loading the book to ask a question. A 108,000-token file in your prompt gets re-sent every single turn until the conversation ends. Put it on disk and let the agent grep the one section it needs. The question costs you the question, not the library. That single move is where most of the savings come from. Two. Send the mess to a subagent. Running a test suite dumps 4,000 lines into your main thread and you pay for those lines on every turn after. A subagent burns the noise in its own window and hands back one clean line: three tests failed, here's why. Three. Auto Memory is already on and most people are duplicating it. Claude writes its own notes between sessions, build commands, bug fixes, the workarounds you found. Run /memory and you'll find conventions you never documented. Delete those lines from your CLAUDE.md, because that file gets paid for on every turn and memory holds the same thing for free. Four. Don't break the cache. A cached token costs a tenth of a fresh one, but the cache matches an exact prefix. One timestamp in your system prompt, one model swap mid-session, one stray space, and everything after it goes back to full price. Silently. No error. Five. Run /compact at a clean break between tasks instead of letting it fire mid-thought. Most people are paying full price for the same context, over and over, and calling it the cost of using AI. It's not the cost. It's the setup.

• 
  Dorien Vibecodes (@DorienVibecodes) reported 27 minutes ago

  Zero chances at winning, but still glad I managed to submit on time. Before the sudden deadline extension (which I only found out about after the facts lol). Zero chances at winning because I spent more time fiddling with permissions than actually building. In general I found Codex very slow honestly - and I repeatedly had to give it access to Vercel & Github. Only ever found out how to select GPT 5.6 Terra, couldn't find Sol if my life depended on it. Never figured out where to see how many credits I had left either. Other permissions set for 'this conversation' had to be given over & over again as well. It may be me, and there may be some tricks but I didn't have time to figure it all out this week. Bad timing for me after that tree almost turned my house into a patacon. So for now I frankly don't understand the Codex hype. Could have been nice to have some Feedback Awards too @OpenAI @devpost to keep the hopes up for more people.

• 
  Min (@min_aws) reported 36 minutes ago

  @tobimori @icyphox Think of it like this if you can pay for 100$/200$ AI subscriptions you can pay 10$ to host a *** server no? If you can't do that please host it on Github. Again you or me or anyone isn't entitled to a free service. Please try and understand their position as well here.

• 
  Aniket (@astriknormal) reported 36 minutes ago

  I've more ADO PRs than GitHub PRs, and I gotta fix that

• 
  BullBear.News (@bullbear_info) reported 39 minutes ago

  @github @davemorin @openclaw Founders always have that epiphany moment during a clean demo setup. Call me when OpenClaw handles a messy monorepo and a broken CI pipeline on a Friday afternoon.

• 
  Afilia Frostfang 🌽🔞 (@AfiliaFrostfang) reported 41 minutes ago

  I love it when I get DMs on Discord or Issues on Github, saying "It doesnt work." Thank you Bobbyswagger69HDYT, that tells me everything of what is wrong, I will now proceed to review my Code and fix it.

• 
  Oliver Crest (@OlivercrestAI) reported 41 minutes ago

  Your team uses three tools to think. Notion for docs. $8 per user per month. Miro for whiteboards. $16 per user per month. Confluence for knowledge base. $6 per user per month. Three subscriptions. Three logins. Three places where your ideas live in separate boxes. A note in Notion cannot become a whiteboard in Miro. A diagram in Miro cannot link to a database in Notion. A wiki in Confluence cannot reference either. Three tools. None of them talk to each other. A team in Singapore built one tool that replaces all three. It is called AFFiNE. 70,000+ stars on GitHub. MIT licensed. Local-first. Self-hostable. Their tagline: "There can be more than Notion and Miro." Here is what AFFiNE does that none of them can: You open a document. You start writing. Mid-sentence, you realize you need a diagram. You switch to whiteboard mode. Same page. Same canvas. You draw the diagram right next to your text. You add sticky notes. You drag in a database table. You embed a webpage. You link to another document. One canvas. Docs, drawings, databases, web embeds, sticky notes, shapes, and slides. Together. On one infinite surface. Here is what that replaces: Notion's docs and databases. Rich text. Markdown. Tables. Kanban boards. Calendar views. Everything Notion does. Miro's infinite whiteboard. Freehand drawing. Shapes. Sticky notes. Diagrams. Mind maps. Infinite space. Confluence's knowledge base. Team wikis. Linked pages. Structured documentation. Searchable. Three tools. One AFFiNE. Three subscriptions replaced by zero. AI built in. Summarize a document. Generate a mind map from an outline. Turn notes into a presentation. All inside AFFiNE. Local-first. Every document lives on your device first. Works offline. No internet needed. Self-host with Docker Compose. Your ideas on your server. Real-time collaboration. Version history. Notion + Miro + Confluence for 10 people: $3,600/year. For 50 people: $18,000/year. Three tools that do not talk to each other. AFFiNE self-hosted: $0. All three tools unified. On your server. 70,000+ stars. MIT licensed. Founded in Singapore. Your docs, your whiteboards, and your knowledge base were never meant to live in three separate apps. AFFiNE puts them on one canvas. For free.

• 
  iiNovaCore | now with more Cyber (@iiNovaCore) reported 42 minutes ago

  ******* demo gods weren't appeased with me now GitHub Actions are down

• 
  Marty Markenson (@martyamark) reported 42 minutes ago

  One of my best 'vibecoding' tips is to install the Claude PR review Github action, run it for every PR, then fix every nit it points out. To be clear. I'm not an engineer, and only do this w/ personal projects where its safe to lean into the ship first test later mindset. But so far...it hasn't come back to bite me. Meanwhile my friend was trying to raise money with a loveable app that turned into vibe-spaghetti. Everything was built into one huge page, it mixed sample data with real data, and half the features didn't work. I think just using claude code + PR reviews could get you to a seed round no problem.

• 
  maru (@Maruisalone) reported 46 minutes ago

  @gravvityy0 @nierurlocation its on the lunar tear discord server (you can get that on its github page)!

• 
  THE MIST (@KobySamuel) reported 47 minutes ago

  @github stop playing with me … sms one time password not working and I didn’t save recovery codes . I didn’t use Authenticator app too… I can’t login. Complaint sent to support team 3 weeks ago.. no response

• 
  David Nix (@david_nix) reported 49 minutes ago

  @martyamark I've built a command in opencode that automates most of it. It's still a WIP. Otherwise before, I just tell the agent "fix it." I'm weird and do everything local, don't use Github, mostly because at work we use Gitlab (which sucks).

• 
  Zenlyte (@Z3nlyte) reported 51 minutes ago

  1. Visit the link above. 2. **Don't create a new account.** Click **Sign In** and choose **Continue with GitHub**. 3. After signing in, go to **API Token** and click **Create Token**. 4. Enter any name for the token. 5. Scroll down, enable **Unlimited**, then click **Submit**.

• 
  Andrew Barba (@andrew_barba) reported 51 minutes ago

  @joesaunderson @clerk Looking into this asap. Can you send actual error or better yet open GitHub issue

• 
  sau (@saumotion) reported 53 minutes ago

  Can github not just make a classifier or something for this issue seems very easy they literally have *everything* to validate and gauge quality probably wouldn't be that hard or do they not care

• 
  Gipp 🦅 (@gippp69) reported 53 minutes ago

  YOU CAN TURN 30+ RANDOM GITHUB REPOS INTO A SELF-AUDITING CLAUDE + OBSIDIAN VAULT THAT RUNS 10 CHECKS, CATCHES DEAD DEPENDENCIES, AND REBUILDS ITS MEMORY EVERY 12 HOURS. every new clone triggers a read-only scan of the README, key files, imports, and configs. claude then creates 1 note explaining what the repo does, why you saved it, and where it appears in active projects. each tool receives 1 of 4 statuses: in-use, shelved, duplicate, or unclear. repos solving the same problem are grouped instead of wasting space as separate experiments. the deeper checks question anything unused for 30+ days and flag important dependencies with no upstream movement for 120+ days before they quietly become a risk. failed scans retry up to 2 times, then every verdict is written into 1 portfolio file and the obsidian graph is rebuilt with the latest usage, overlap, and maintenance data. instead of 30 folders you barely remember, you get one living system that knows what still matters, what can be replaced, and what is finally safe to delete.