Apple Store Outage Map

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Apple Store Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Jacky Fan (@FrankMaoSean) reported 1 minute 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.

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  I need more sunshine (@chicagoaudra) reported 2 minutes ago

  Anyone else having issues with newer @apple phones? I have an @apple iPhone 17pro that I’ve had problems with since I bought it through @ATT around Christmas. It has not worked consistently, with any of my Bluetooth devices, and is getting worse over time. Even my watch (series 11) is almost never connected and runs out of batteries really quickly now because it is constantly trying to connect and reconnect to the phone. Spent hours at the Apple Store a while back where they made me reset my phone and I couldn’t restore from the backup at all. I did that and the problem did not resolve. It mostly finds the devices but won’t connect or won’t stay connected or even paired. All of my devices work on my husband’s phone just fine (same phone). I have not been able to use any of my devices at all in over a week now, yet my phone somehow “passes” their diagnostics, despite not working at all in practical reality. It failed one test in the Apple Store but then passed when they redid it, so of course, they went with the pass. 🙄 Because of the “passing” the diagnostics, they refuse to replace the phone and won’t do anything about it. They just tell me it has to be a software issue and “the engineering team is working on it.” For months now. None of this happened with my iPhone 15pro and it doesn’t work with other phones either. How is this acceptable? They just took my money and I am SOL when it doesn’t work? No offer of a different device, a refund etc, no attempt to solve my issue. Just sucks to be me? Anyone have ideas of what I can try next? I have spent way too much time on this, but I would like a phone of my own that works. Also, if you are thinking of the Apple iPhone 17 pro, skip it. I feel like I’ve been ripped off and I don’t feel like they should be able to just take my money and leave me with this lemon of a product. Is there a lemon law for phones? Tired of this. I’m so sorry I got rid of my 15.

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  Chris M. Walker (@cmwalker) reported 3 minutes ago

  This meme is supposed to be motivational… it’s actually bullshit. First of all it implies that 50% of people keep working at what they want to achieve. 1% is more like it. The other problem is that bro on the bottom gives up right before he succeeds. Thats optimistic too. Most people swing the axe one time and see it didn’t even break an inch off the wall and give up. People just do not want to do the volume that’s needed to succeed at anything. They think they want the result. They think they are willing to do the work. What they really want is the Instagram post. They want to appear to succeed. They want everything but doing what it takes. The reason I’m thinking about this today is that I just went through 236 revisions for the script of 1 video on a YouTube channel that hasn’t even launched yet. That’s after one channel took me 10 years to get to 100k subscribers. And despite all that boring tedious work swapping a single word for another… …I still don’t feel like it’s good enough and just had a thought on how I can make it better and am going to start over from zero. Most people give up when their first 30 second reel doesn’t make them Mr. Beast. Kobe Bryant used to take 800 to 1,000 made jumpshots a day in the offseason. Not taken. Made. He’d be in the gym at 4am doing the same boring movement thousands of times while the rest of the league slept. The 81 point games were built on ten thousand swings nobody saw. Steve Jobs scrapped the entire design of the first Apple Store when it was nearly finished, months of work, because he decided it was organized around products instead of around what people wanted to do. He started over. The redo became the most profitable retail on earth per square foot. Neither of them was a few inches from the diamonds getting lucky. They swung the axe an absurd number of times, hated a lot of the swings, and kept going anyway. So if you actually want to succeed at something, get ready to be bored. For a long time. Doing the same unglamorous reps long after it stopped being exciting and long before it started paying. Or, if you just want to look successful, take a photo of yourself, drop it into ChatGPT, and tell it to put you in front of a private jet. It’s gotten pretty good at that. Think Big

• 
  BeeDee (@T_B_T) reported 5 minutes ago

  @Kahamsha Probably take my flying car down to the Apple Store to buy a new iPhone 64 to have it installed in my left temple and rewatch it again?

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  MasterBismuth (@MasterBismuth) reported 7 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.

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  Dack (@DackHasker) reported 9 minutes ago

  like sure I'm a nutjob or whatever, but "sir for $75 you can be taking it into the apple store, and we can be pleased to address your issue" just die lol. I don't care. waste my time, waste my life sure, but really? $75 just for me to bring it to you? How about $75,000 and you can go die.

• 
  Zavian Kairo (@ZavianKairo_AI) reported 13 minutes ago

  The uncomfortable truth: Apple’s business model rewards storage anxiety. The more often customers see “Storage Almost Full,” the more likely they are to: 1. Pay for iCloud subscriptions 2. Upgrade to higher-storage models 3. Buy a new iPhone entirely Every default setting on a new iPhone trends in the direction of consuming more storage, not less. The 7 fixes above take about 10 minutes total. They cost nothing. They will recover an average of 40–60 GB on most iPhones over 12 months old. The Apple Store employee said one more thing before he left: “We see this every day. Most people don’t even check Settings → General → iPhone Storage before they walk in. They just assume the phone is too small for them. It almost never is.” RT this so more iPhone users stop spending $1,000 on a storage problem that could be solved with 7 toggles.

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  Yada Yada Yada Farm (@bcglass2012) reported 14 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.

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  woofthevote (@woofthevote) reported 14 minutes ago

  @Lordmiles Therefore the supply chain means its not about just walking to buy the Iphone and Airpods from the Apple store down the street. Theres a whole supply chain of driving armored trucks down non existent roads for no reason at all because Zambu money is worthless.

• 
  Prime AI (@primemans) reported 16 minutes ago

  A man noticed his phone storage kept showing “full” after 18 months — even though he barely had any photos. He deleted apps. Cleared messages. Removed downloads. Still, every couple of weeks, the same warning returned: “Storage Almost Full.” He was ready to upgrade and buy a new iPhone. At the Apple Store, an employee stopped him for a second: “Before you spend $1,000 on a new phone, check this first.” She opened Settings → General → iPhone Storage and immediately spotted the problem. “There are 7 things quietly eating your storage. Most iPhones have them enabled by default — and almost nobody knows about them.” Then she walked him through everything in less than 10 minutes. 🧵

• 
  Vel0x (@vel0xAI) reported 23 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.

• 
  DARK DECEPTION (@DarkDeceptionDD) reported 24 minutes ago

  Super Dark Deception CH2's release has been delayed on Switch, PS4, and PS5 due to patch approval issues. PS4 & PS5 are still expected to launch this weekend. Switch is dependent on Nintendo's response time. Here are the platforms where CH2 is currently available: Steam, Xbox One, Xbox Series X|S, Google Play, Apple Store. Epic Games Store is under review and set to launch early next week.

• 
  Asher Crowe 🪺 (@ashercrw) reported 28 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.

• 
  Lucas (@Lucas62949380) reported 30 minutes ago

  Download session app from your Apple Store or play store let’s chat secretly over here concerning hack deals, let’s access her account and login then you can go through everything which you need to know in there 05fe0ad0eaef801c18da5485f2148265d7530ab81b176ffa87fb1995dcd3c24074

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  Hemanth Nelavai (@HemanthNelavai) reported 32 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