Apple Store status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of Apple Store 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 Apple Store users through our website.

• Sign in (36%)
• Website Down (36%)
• Errors (27%)

Live Outage Map

The most recent Apple Store outage reports came from the following cities:

City	Problem Type	Report Time
Adelaide	Errors	2 days ago
Ahmedabad	Sign in	4 days ago
Ahmedabad	Website Down	4 days ago
Montréal	Errors	2 months ago
Ciudad López Mateos	Sign in	2 months ago
Quito	Website Down	3 months 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.

Apple Store Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Maria Islam (@mariaislam6451) reported 0 seconds ago

  So, going back to the question l asked the technician at the Apple Store: "Are these default settings really protecting the user, or are they silently wearing down the device?" He didn't have an answer. But every iPhone he tested that day had the same 2 switches TURNED ON. Silently burning in the owner's pocket.

• 
  jammington bear (@_Jamesy_T_) reported 23 seconds ago

  Maybe this wouldn’t be such a problem if your Tardis didn’t look like a damn Apple Store

• 
  GeeBeeNZ (@GeeBeeNZ) reported 3 minutes ago

  @Linda401gmail @RadioGenoa Don't do ANY FACIAL recognition ANYWHERE, go without or find a get around like a different browser. Tor Onion. Yes it's slow to load as a VPN. LOAD IT DIRECT FROM TOR, NOT EVER Google Play, Microsoft Store or Apple Store. Use Brave, DuckDuckGo as your default browser to get TOR.

• 
  Vel0x (@vel0xAI) reported 4 minutes ago

  A student in the United States received a $3,000 university grant and spent the entire amount on five Mac Minis, not because he wanted a better study setup, and not because he was trying to impress anyone in his dorm, but because he was tired of waking up every morning and explaining his life to an AI that had forgotten everything by the next session. He did not use the money for textbooks, private tutoring, paid courses, or a new laptop like the university probably expected. He went to an Apple Store, bought five small machines, carried them back to his dorm room, numbered them from 1 to 5 with a black marker, stacked them on a cheap metal shelf beside his desk, connected a power meter to the wall, made instant noodles, and went to sleep while the machines began turning his room into something that looked less like student housing and more like a private AI lab built on scholarship money. His neighbors thought he was mining crypto, which made sense from the outside, because all they saw was a shelf full of computers running through the night, cables hanging behind the desk, a small fan pointed at the stack, and a student who suddenly cared too much about wattage. What they did not understand was that he was not trying to mine coins; he was trying to build a system that remembered his classes, his assignments, his codebase, his mistakes, his goals, and the product he was quietly building while everyone else was still treating AI like a smarter search bar. The problem he wanted to solve was simple but annoying enough to change everything. Every time he opened a new AI chat, he had to explain who he was, what he was studying, what project he was building, what the professor wanted, which parts of the codebase were broken, what he had already tried, what had failed, what he had learned the day before, and why the answer needed to fit his specific situation instead of sounding like generic advice from a model with no memory. He realized that the most valuable thing was not another chatbot, but a system that could keep context long enough to become useful. Each Mac Mini became responsible for a different part of his life. One machine processed his lecture notes and turned them into explanations he could actually understand. Another reviewed his assignments before submission and checked whether his arguments, code, and formatting matched the requirements. A third acted like a private tutor that questioned him until he could explain the material back clearly. A fourth wrote, tested, and refactored code for the product he was building outside class. The fifth coordinated the whole system, kept the rules updated, stored the context, and decided which task needed to run next while he was sleeping. There was no development team behind it, no manager assigning tickets, no daily standup, no productivity consultant, and no university department guiding the experiment. There was only a rules file, five machines on a dorm shelf, and a student who understood that local AI became much more valuable once it stopped being a conversation and started behaving like infrastructure. The university had given him money for education, but he used it to build an education system that did not forget him. That was the part most people missed when they saw the setup. The point was not only that the machines were powerful enough to run useful models locally; the point was that they belonged to him, which meant his lecture notes, unfinished code, business ideas, exam prep, personal mistakes, drafts, and prompts stayed in his room instead of being uploaded into somebody else’s cloud dashboard under somebody else’s terms of service. During the day, he still went to class like everyone else, listened to lectures, submitted assignments, and looked like a normal student trying to get through the semester. At night, the system summarized readings, found gaps in his understanding, generated practice questions, cleaned up code, tested features, wrote documentation, and moved his side project forward without needing him to sit there and manually push every step. When he woke up, he was not starting from zero like everyone else opening a blank chat window. He was starting from wherever the machines had stopped. At first, people in the dorm laughed at the shelf with the numbered Mac Minis because it looked excessive, strange, and slightly ridiculous for a student room. Then they started asking him to summarize lectures they had missed. After that, they asked whether it could help them prepare for exams, review essays, explain technical concepts, debug projects, and remember the context of their classes without forcing them to rewrite the same background information every time they needed help. That was when the private study system became a product. He packaged smaller versions of the setup for other students, not as a replacement university and not as another generic AI wrapper, but as a memory layer for people who were tired of using tools that forgot them every morning. It became private study agents, class note summarizers, exam preparation bots, coding copilots, and project assistants that remembered the user’s material, progress, weaknesses, and deadlines. The grant was $3,000, the machines cost less to run than most monthly subscriptions, and the first paying users came from the same dorm that had originally joked he was mining crypto. What started as a way to survive his own semester turned into a product other students were willing to pay for, because it solved the problem they had all accepted as normal. Now the system makes around $45,000 a month, and the strangest part is that none of it began as a startup pitch. It began as a student using university money to stop repeating himself to a machine. The university thought it was funding his education. What it actually funded was the infrastructure he used to rebuild it.

• 
  yessi (@yessicaster) reported 6 minutes ago

  I’m the kind of friend to surprise you at the apple store and wait out a bad day w you while they fix your phone.. or the friend who negotiates with the tow truck driver while your car is broken down in the middle of street

• 
  FINMAN (@erikfinman) reported 9 minutes ago

  @jstamby @jstamby Massive domes solve survival. Taste solves the Apple Store problem.

• 
  Jacob Hewes (@SportsSciJacob) reported 10 minutes ago

  Walked to the Apple Store today thinking my $3000 MacBook that I thought was broken for the last two years I was gonna have to pay 600 bucks to get fixed sure enough it works then I go to the T-Mobile store and find out I can get a brand new Apple Watch for free. Must’ve been my lucky day.

• 
  Lucas (@Lucas62949380) reported 12 minutes ago

  Download your session application on apple store or play store so we have more secret and secure chat there on any account hack you’re down for bro My Session Id 05fe0ad0eaef801c18da5485f2148265d7530ab81b176ffa87fb1995dcd3c24074

• 
  100and1 Gadgets Orchid (@mollfixdiapers) reported 13 minutes ago

  @69LifeCode @EmzyGadgets People that bought from Apple Store in USA face the same issue , The tweet said might and some.

• 
  masYNYa (@KijAkubovs86334) reported 14 minutes ago

  A developer walked out of an Apple Store carrying 7 Mac mini boxes. Security watched him. Other customers watched him. He sat down in the lounge, opened his laptop, and got to work before he even got home. Pause at [0:09]. Look at the meter plugged in on the left. 180 watts. That is the entire operation at full load. Your gaming PC idles higher than that. Five M4 Mac minis. Clustered into one machine with EXO. No cloud. No API subscription. No data leaving the room. Ever. A Llama 70B running local on MLX. It ingests a 90,000 word manuscript. Cleans the formatting. Splits the chapters. Marks every line of dialogue with the emotion it should be read in. Then a local voice model narrates the entire book in one locked voice that never gets tired and never raises its day rate. 40 hours of clean audiobook narration. Every month. While he sleeps. He sells the finished files to indie authors and faceless YouTube channels who cannot afford a studio and will not wait three weeks for one. $23 a month in electricity. $11,840 a month out. The 7 boxes on the floor are not a flex. They are the infrastructure. His girlfriend asked why he didn't just buy more. He already ordered them.

• 
  Drunk Dividends 🥂 Small Biz & Finance (@DrunkDividends) reported 15 minutes ago

  @unusual_whales If the Apple Store alone was broken into it's own company it would be bigger than SpaceX

• 
  bytez (@6uappi) reported 17 minutes ago

  someone stacked 5 Mac Minis on their desk and built a private AI cluster that runs models no single machine could handle no cloud, API key, no monthly bill and no data leaving the room. the tool is called exo(open source) it connects multiple machines over your local network and splits the model across all of them like one giant GPU. what this setup actually does: 5 Mac Minis networked together = combined RAM that can run 70B+ parameter models locally exo handles the distribution automatically you just point it at your machines and it figures out the rest the node graph on screen shows each machine as a node passing inference layers to the next one latency is fast enough for real use. not a toy or demo. a working private inference cluster total hardware cost: less than one month of serious cloud GPU rental the thing nobody talks about: when you run inference locally across your own machines, you own the entire stack. no rate limits. no context window restrictions from a provider. no terms of service. no outage at 2am killing your pipeline. most people think running serious AI locally requires a $30,000 server rack this guy built it from hardware you can buy at any Apple Store

• 
  Hemanth Nelavai (@HemanthNelavai) reported 22 minutes ago

  @gharkekalesh If you are ready to buy iPhone for ₹1,00,000 then better buy from official Apple store or their official website. Customer service will definitely be hundred times better if any problem arises

• 
  Jack (@jackcoder0) reported 22 minutes ago

  Her Apple Watch battery dropped to 78% after just one year. She wore it daily. She charged it overnight. She used it like every other Apple Watch owner she knew. Yet her battery had degraded faster in 12 months than her iPhone had in 3 years. She took it to the Genius Bar, expecting them to confirm it was defective. The technician ran every diagnostic. "Your watch isn't broken. It's just been running 24 hours a day doing things it doesn't need to do. There are 4 default settings on every Apple Watch that hammer the battery overnight. Apple knows. They've known since the first Series 1 launched. They don't change the defaults." She asked why. He gave the same answer Apple Store employees have learned to give silence. Then he opened the Watch app on her iPhone and walked her through everything. Here's what he showed her. 🧵

• 
  James Yeung (@jamesyeung18) reported 23 minutes ago

  @aat_ai40683 Thanks bro. I actually took my mouse to the Apple Store and have them fix it for me! It now works fine!

• 
  L (@benghazi_ebooks) reported 24 minutes ago

  Can’t find it because the search function is broken but I am thinking about the email exchange in the Epstein files involving Barak and Koren discussing headphones being returned at a specific Apple store location in NYC. Which was obviously coded talk about moving something

• 
  Ján Bakoš (@jani0077) reported 26 minutes ago

  @vlmxs @SnazzyLabs Speeds are really down in a clumsy environment. Tried it in our local Apple Store and it came out weird that some pages took loading more than 10 seconds. Then ran Speedtest and the speeds capped at about 30 Mb/s, while the store had 1 Gb/s wireless (I was the only customer).

• 
  NMW (@NoisyMountainw1) reported 31 minutes ago

  It’s been over a week since my MacBook Pro laptop kicked the bucket. I took it to the Apple Store last Saturday to see what the issue was. When the technician dissembled the MacBook to see what the problem was, he saw dust inside.

• 
  Jacky Fan (@FrankMaoSean) reported 31 minutes ago

  Has the review speed of the Apple Store slowed down again? The submitted update has been pending for three days and still hasn't started the review.

• 
  Asher Crowe 🪺 (@ashercrw) reported 32 minutes ago

  A 31-YEAR-OLD IN BELGRADE IS PULLING $8,400 A MONTH OFF FIVE MAC MINIS RUNNING IN A TOWER ON HIS DESK. The whole stack costs $19 a month in electricity to operate. The hardware paid for itself in week one. The setup is so quiet his girlfriend didn't notice when he turned it on. His name is Stefan. This is the cleanest example of the new solo operator economy I've seen all year and the numbers deserve a full breakdown. The hardware is five M4 Mac Minis stacked in a tower on his desk. Each one has a number written on it in marker, 1 through 5, so he knows which node dropped when one goes silent. A pink dumbbell sits on the shelf above them. A can of compressed air on the windowsill. The whole thing hums quieter than the mini fridge in the corner. The five machines are clustered with EXO into one virtual machine. EXO is the open-source framework that lets you string together consumer hardware into a distributed inference rig without needing a degree in systems engineering. The setup runs Llama 70B locally on MLX, Apple's machine learning framework optimized for unified memory. Nothing he runs ever touches a cloud server. No API costs. No rate limits. No latency tax. The model runs on his desk and answers in milliseconds. Here's the workflow he built around it. A client uploads a raw manuscript. Anywhere from 60,000 to 120,000 words. Indie author novels, self-help books, faceless YouTube channel scripts, the kind of long-form content that needs narration but doesn't have a studio budget. The Llama 70B model does the reading work first. It ingests the raw text, cleans the formatting, splits the chapters automatically, and tags every line of dialogue with the emotional tone it should be read in. Excited. Whispered. Angry. Resigned. Then it writes the chapter descriptions that faceless YouTube channels paste directly under their uploads. All of it done locally. All of it done in one pass. Then an open voice model on the same stack takes over and narrates the entire book in a single locked voice. The voice never gets tired, never asks for a re-record, never raises its day rate, never catches a cold the day before a session. The same voice across every chapter, every book, every client. Consistency that human narrators physically cannot match. A local audio mastering model handles the final polish. Compression, leveling, breath cleanup, room tone matching. The output is studio-quality audio ready for upload. The stack renders 28 hours of clean narration per month while he sleeps. He wakes up, exports the files, sends them to clients, invoices them, and goes back to whatever he wants to do with his day. Now the part that breaks people. The power draw across all five machines running at full load is 180 watts. He has a KUMAN meter plugged into the wall to track it. A single gaming PC idles higher than that. The entire AI studio he built consumes less electricity than a hair dryer on low. At Serbian residential rates that works out to roughly $19 a month in operating cost. Eight thousand four hundred dollars in, nineteen dollars out. A 442x margin on power alone before you account for the fact that the hardware paid for itself the first week he turned it on. His girlfriend asked why the power bill didn't move after he built it. He told her it can't, the machines barely draw anything. She asked what the whole thing cost to set up. He told her. She asked why he didn't build ten. That's the right question. A traditional audiobook studio has a narrator on a day rate, a booth, an engineer, and a monthly power bill that buries solo operators. The cheapest professional narrator in the US charges around $200 per finished hour. The cheapest decent one runs closer to $400. A 10-hour audiobook costs an indie author at least $2,000 in narration alone, plus mastering, plus mixing, plus the three week turnaround time while the narrator fits the project into their schedule. Stefan delivers the same product for a fraction of the cost, in 48 hours, with consistent quality across every chapter, and his only constraint is how fast he can find clients. The economics are completely deranged compared to traditional service businesses. He doesn't pay rent on a studio. He doesn't pay a narrator. He doesn't pay for cloud compute. His marginal cost per audiobook is approximately the electricity it takes to run the cluster for the duration of the render, which is measured in pennies. A few realizations worth sitting with. The frontier of AI economics is no longer in San Francisco. It's in apartments in Belgrade, Lagos, Manila, and Tbilisi, where operators with low overhead and high technical curiosity are quietly running businesses that look impossible from the outside. The geographic distribution of who actually makes money from AI is going to look nothing like the geographic distribution of who funded the labs. Local inference is the quiet revolution nobody on this app is talking about loudly enough. Every workflow that currently runs on OpenAI or Anthropic APIs has a cousin that runs on a Mac cluster for the price of an electrical outlet. The companies paying $30k a month in cloud bills are going to wake up in 18 months and find their margins eaten by operators paying $19. The audiobook market is just the beginning. Every service business with high human labor costs and predictable output requirements is about to get the same treatment. Voiceover work, transcription, translation, copywriting, image editing, video editing, customer support, technical writing. Each one of these has a local-inference version waiting to be built by someone with a stack of Mac Minis and an EXO config file. Stefan didn't invent anything. He just connected the right pieces. The pieces have been sitting on GitHub for over a year. The Mac Minis have been on shelves at every Apple Store. EXO is free. The voice models are open. The orchestration is a weekend project. The only barrier was knowing it was possible. Now you know.

• 
  Sammy Bags (@SammyBagsmfnobs) reported 36 minutes ago

  @109Cuntrees @TifahCrump777 Anybody that’s says there Gods favorite is ******* insane, I know I’m not gods favorite! I just spent 3 hours in an Apple Store just to be given back a broken phone by fat ***** #selfaware

• 
  Roxie (@Roxi3Roxie) reported 38 minutes ago

  @BunheadHQ They just closed the BAB that looks like this in my mall and replaced it with a shoe store, moved the build a bear down the lot into an ugly apple store esque building. So ugly.

• 
  Kyeyune Richard (@krk24richards) reported 39 minutes ago

  @DrBellahh You and your people you buy used iPhones, me I buy new and from Apple Store. So handle your problems

• 
  Sean (@sean_plus_one) reported 45 minutes ago

  @yonann Lost me at "Perception of Customer Support" Have a problem, go to Apple store and they handle it. W/ Apple Care no issues. PC, who do I go to? Best buy, where they upsell/run-around try to sell x. Time is your most valuable asset! *Cough

• 
  0xSuhar (@suhar_ceo) reported 45 minutes ago

  ok so I just saw the most unhinged tech setup and I need to talk about it someone stacked like 50+ Mac Minis on a shelf. yellow shelf. looks like a construction site met an Apple Store. and honestly?? this is lowkey genius and I'm mad nobody told me sooner because here's the ***** secret the M-series Mac Mini might be the best value compute unit on the market right now. per watt, per dollar, per cubic inch of space. it destroys traditional server hardware in efficiency. it just doesn't LOOK like serious infrastructure so people dismiss it but some guy in a random office somewhere said you know what, I don't need a $400k rack from Dell. I need 60 of these bad boys, some ethernet, and a dream. and now he has a build/test pipeline that probably runs faster than your company's entire cloud setup no loud fans. no special power requirements. no "enterprise support contract" where someone charges you $800 to restart a service. just apples. wall to wall apples. the chair sitting lonely in the corner of the shot is sending me. someone WORKS there. they just sit next to the apple army every day and think nothing of it we are not the same #ai #macmini #macmini4

• 
  Sumeet Gupta (@guptasumeet) reported 46 minutes ago

  @AppleSupport my imac has been lying with your genius bar for 20 days with no solution. Its latest model with all the top specs. Within warranty period and your team isnt able to fix it for so long ! Its been lying with your apple store in noida. Poorest customer service!

• 
  Watthewat (@Haptraz) reported 49 minutes ago

  @Somniss Quality Indie games are the future. It's just super easy to make a prototype. Steam has to find a solution to this problem. Their market will turn into google play apple store at some point.

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  Yada Yada Yada Farm (@bcglass2012) reported 53 minutes ago

  @deesnider Goto your local apple store and they ll fix it, a lot these responses are just people wanting to talk. Good luck.

• 
  imran (@instaguyonx) reported 59 minutes ago

  @Rushu_Tushu Yeah, I got the same, but when I got a problem, I went to Apple Store to get it fixed, but they said this is a first copy which looks like original, but inside the earbuds, a copy

• 
  MasterBismuth (@MasterBismuth) reported 60 minutes ago

  I have at least one theory concerning that, and it all boils down to passing the buck. The companies insuring these lootboxes for Nvidia will likely insist upon installing some sort of odious security measures in the hardware. Much like the store model iPhones at the Apple store.