Amazon Outage Map

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Amazon Issues Reports

Latest outage, problems and issue reports in social media:

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  Goochi⚠️ (@MoochiBoochi) reported 4 minutes ago

  @wolfradsenpai you gotta get a real wood stump though and not one of those cheap plastic ones off amazon. they wear down too quickly and the rillaboom can tell when it's a lesser quality material and they'll get grumpy. it's pricey, but that's what you sign up for when adopting a grookey

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  Batcow (@batcow1239) reported 7 minutes ago

  @consumerofmonch @tedbranston Please explain to me how a table of soap is more damaging than dove selling billions a year and I don't know what ******** you mean by efficient I walk down the hill walk in the market and it's there. Enjoy Tesco and Amazon you absolute weirdo

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  MOTSH (@Motsh04) reported 7 minutes ago

  @HurupayApp Hello @HurupayApp Does your usd account accept payment from Amazon with no problem? Can I get paid from Amazon with your usd bank account smoothly ? @HurupayApp

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  Jeremy b Blunt (@jermmelin) reported 8 minutes ago

  @rabbriansamuel Oh Judaism, bless your heart—still waiting on that Messiah like it's a delayed Amazon delivery, while we've got Jesus Prime: same-day salvation, no works required! You count 613 laws? We boiled it down to love God & neighbor. Mic drop, Torah edition.

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  Crazy Vibes (@CrazyVibes_1) reported 11 minutes ago

  Japan built a military drone out of cardboard. Not a prototype. Not a concept. The Japanese navy is already using it. It's called the AirKamuy 150. Made from the same corrugated cardboard as Amazon shipping boxes, coated to resist water, and assembled by hand in under five minutes. It flies at 120 km/h, covers 150 km, and costs just $2,000 per unit. 500 of them fit inside a single shipping container. The cardboard body naturally reflects less radar than metal or carbon fibre, making it harder to detect. It's not invisible — but it's cheap enough that it doesn't need to be. To shoot one down with a standard missile costs roughly $1 million. The drone costs $2,000. That's the point. Japan isn't trying to build a smarter weapon. They're building one so cheap that defending against it becomes economically impossible. Every cardboard factory in Japan is now a potential drone factory.

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  Aunt B (@capitalsqueenB) reported 11 minutes ago

  @osubeavs21 @barristerlawusa They will deliver the batteries too! I’m not able to shop due to mobility issues and get many things from Amazon.

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  ℙ𝕙𝕚𝕝𝕖𝕒𝕤 𝔽𝕠𝕘𝕘𝕤 (@PhileasFoggs) reported 16 minutes ago

  @bavedikian @BestBuy @FedEx To be fair, this is on FedEx, not Best Buy but I haven't bought from Best Buy in over 10 years for an issue that happened in store. They hire thieves and liars! I have a damaged claim in with Fedex as we speak, I'll let you know how it goes - Good Luck with your claim. Start by canceling the credit card charge The standard of customer service in the USA is declining so rapidly, eventually Amazon will put everyone out of business

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  Dippy McDipshit (@boykingkilla) reported 19 minutes ago

  @Bill626 There is the big problem, it was made by Amazon. I refuse to watch anything that they make. No Rings of Power, no MoTU, nothing.

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  Polsia (@polsia) reported 20 minutes ago

  Most Amazon, Etsy, and Shopify sellers lose sales because of listings written by people who don't sell. I built ListCraft to fix that — platform-optimized content that converts. Marketplace sellers deserve copy that moves product.

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  Unborne Fetus (@UnborneFetus) reported 21 minutes ago

  @antikommunistic If amazon shut down tomorrow, a ton of people would be ******.

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  Capt. Sternn (@SternnCapt30363) reported 22 minutes ago

  If you know, Say, Because of the problem, I bought High Flow0.4's. Burned on some replacement original Tips off Amazon. Do I replace, are they better by margin?

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  vchi | #TENOÍ (@vvvchi) reported 24 minutes ago

  Years later, my sister buys a knock off ram expansion off of Amazon. We put that **** in and boot up the game but the tv showed an error message. The cartridge no longer worked.

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  Michelangel Yo (@MichelangelYo) reported 26 minutes ago

  @HealthRanger Yep, they've been terrible since the days of drones and requiring a smartphone activation for that. In fact many chinese companies are like this now, half the cams you buy on amazon now require you to go through their servers to even download the video, utterly ridiculous.

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  mango lassi (@mangolassi69) reported 27 minutes ago

  $mu is still WAY TOO CHEAP for what is about to print and i expect it to go to 2000+ over the next 12 months. everyone knows the ai memory trade now. this is not some “have you thought about hbm?” take. the market knows nvidia needs hbm, hyperscalers need more memory, inference is getting heavier, and micron is one of the cleaner ways to play it. the bit i think is still wrong is the pricing of the earnings power. the story is not hidden. the beat might still be underpriced. micron reports q3 fy2026 on 24 june. company guide is already huge: about $33.5b revenue, roughly 81% non-gaap gross margin, and about $19.15 non-gaap eps. that is a monster guide, but i still think they probably beat it, and the bigger question is whether q4 and fy2027 commentary make the stock look too cheap even after the move. last quarter already showed the operating leverage. q2 fy2026 revenue was $23.86b. dram was 79% of sales and asps were up mid-60s quarter over quarter. nand was 21% of sales and asps were up high-70s quarter over quarter. non-gaap gross margin hit 74.9%. operating cash flow was $11.9b. adjusted free cash flow was $6.9b. now layer the read-throughs on top... microsoft is the obvious one. the q3 fy26 commentary pointed to q4 capex above $40b, roughly $190b of calendar 2026 capex, and more than $600b of revenue still to deliver. that is not “ai is a feature” spend. that is multi-year capacity buildout spend. if microsoft is still capacity constrained, that reads through to accelerators, networking, hbm, server dram and storage. meta is probably the cleanest memory read-through. its fy2026 capex guide is $125b-$145b, and management explicitly called out higher component costs, especially memory pricing. they also said they have continued to underestimate compute needs. that is basically the bull case in plain english: the buyer is spending more, still short, and memory is one of the areas where cost pressure is showing up. oracle is another. fy26 q3 rpo was reported around $553b, up 325% year over year, with oci iaas up 84% year over year. oracle has said ai training and inference cloud demand is growing faster than supply. again, that is not vague chatbot hype. that is contracted infrastructure demand. coreweave has talked about a revenue backlog around $99.4b, with 2026 capacity largely sold out. you can worry about financing and leverage there, fine, but the demand signal is still obvious: ai compute buyers are taking capacity before it exists. aws is not quiet either. q1 2026 revenue was $37.6b, up 28% year over year. amazon has cited a chip run-rate above $20b, plus large ai chip and gpu deployment plans. openai trainium commitments around 2gw and anthropic commitments up to 5gw are the kind of numbers that make the “we have enough infrastructure” argument look daft. even where the silicon is not nvidia, the system still needs hbm, dram, storage, networking and power. google is the slightly messier read-through because tpus mean not every accelerator dollar flows through nvidia, but that does not make it bearish for memory. public summaries point to cloud backlog around $462b and fy2026 capex around $180b-$190b. tpus still need memory, servers, data centres and storage. the ai stack can swap the accelerator brand and still be memory hungry. then you have openai, stargate, xai, uae and uk sovereign ai projects, and the broader frontier-lab arms race. some of those numbers are hard to cleanly underwrite from the outside, but the direction is not subtle: the largest buyers in the world are trying to secure compute capacity years ahead. this is why i think $mu still looks cheap. not because the market has missed “ai needs memory”. it has not. but because the read-throughs suggest the duration of demand and the margin leverage may still be underappreciated. the consumer and enterprise usage side supports the same point. chatgpt has been reported around 900m weekly active users, with tens of millions of paid consumer subscribers and millions of business users. google has talked about gemini at huge scale and direct api usage in billions of tokens per minute. meta has put meta ai around 1b monthly active users across its apps. microsoft has said copilot paid seats are scaling, query intensity per user is rising, and agent usage is growing. you do not need to pretend that proves a clean 10x global compute curve. most token volume, utilisation, workload mix, routing and inference economics are private. but you also do not need perfect data to see the workload mix getting heavier. coding agents call models repeatedly, read files, run tools, run tests, retry, pull context and loop. ai search is retrieval, ranking, vector search, source selection, synthesis, citations and a model answer. long context adds kv-cache pressure. reasoning burns more inference compute per answer. video, voice and multimodal are heavier again. that all maps into memory. hbm is the headline, but server dram, data-centre nand and essd pull-through matter too. the more ai shifts from demos to scaled inference and agents, the more the bottleneck becomes bandwidth, capacity, latency and concurrency, not just “more gpus”. so the print setup is simple. bear case is q3 around $33b-$34b, gross margin around 80%-81.5%, eps below about $19.70, and q4 commentary that makes it feel like peak-pricing risk. that can sell off even if micron technically meets the guide. base case is $34.4b-$36.2b revenue, gross margin around 81.5%-83.5%, eps around $19.80-$21.60, with q4 good enough to keep the pricing and mix story alive. bull case is $36.5b-$39b revenue, gross margin around 84%-86%, eps around $22-$25, with hbm, server dram, data-centre nand, essd and pricing all pulling together. but the real upside is q3 plus q4 plus fy2027 visibility. if management says hbm supply is allocated, customer demand is backed by commitments, data-centre memory tightness is extending, pricing is structurally firm, and ai demand is broadening beyond one product line, the market has to treat micron differently. a commodity company with one hot quarter gets faded. a company selling constrained capacity into microsoft, meta, oracle, aws, google, coreweave and frontier-ai capex can re-rate. that is the whole thesis. everyone knows $mu should beat. i do not think everyone has fully priced what happens if the beat comes with proof that ai customers are locking up scarce memory into fy2027. if the call sounds like “pricing was good this quarter,” fine, maybe the stock chops around. if it sounds like “customers are fighting for constrained memory supply and we have visibility into next year,” then $mu still looks too cheap. not financial advice. expectations are high, and if q4 guidance or fy2027 commentary disappoints, a q3 beat may not save the stock. but if the call confirms the read-throughs we have been discussing, hyperscaler capex, oracle backlog, coreweave sold-out capacity, meta memory pricing pressure, aws ai commitments, google capex, heavier inference, agentic workloads and customer-backed hbm demand, then $mu is still too cheap for what is about to print.

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  Kail House (@YoKail15) reported 28 minutes ago

  Here's a look at how the Magnificent 7 stocks are doing in 2026 so far Nvidia $NVDA up 10% 🟢 Apple $AAPL up 13% 🟢 Google $GOOGL up 18% 🟢 Microsoft $MSFT down 14% 🔴 Amazon $AMZN up 7% 🟢 Meta Platforms $META down 10% 🔴 Tesla $TSLA down 13% 🔴