Amazon Outage Map

Community Discussion

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Amazon Issues Reports

Latest outage, problems and issue reports in social media:

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  Rochelle (@itsrochellaa) reported 55 seconds ago

  @AmazonHelp But the problem is I also got a new mobile phone during my upgrade. So I don’t have a trusted device because of the new phone and new phone number now. How can I recover my account ? My email and postal address remain the same. And I have my ID. Please can you help

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  MassGuy (@RealMassguy) reported 6 minutes ago

  @DailyPlanetoid @2fort4 What evidence proves he didn't do it? Nothing. What proves he did it? His DNA. His Knife purchase. His knife being missing. Attempting to delete his Amazon purchase history. Driving during the murder window in the same type of car they were looking for. Powering down his phone from just before the murders until just after. **** porn consistent with the crime (sleeping, passed out, etc). Stolen female ID's in a glove in a box in his closet. 23 prior late night trips to the area, and never going back to Moscow after the morning of the murders.

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  Anibal Gutierrez (@AnibalGuti15760) reported 6 minutes ago

  @AmazonHelp Just to give you an idea how much the unwillingness of your tech support to help.I have t send a routers to be fix,the manufacturer required a copy of the invoice which we can’t access to the account any more,the hacker is controlling that account. How do I get that info ?

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  m masquer (@masquer_m14438) reported 6 minutes ago

  @ModernDayCrimes @DangerousThinkg 1,000% correct! Most folks don't understand that digital meters can be used to 'throttle' home use - even if owner didn't agree to it. 'Smart' homes are horrible as well. News stories about elderly deaths in Europe and places like SoCal when power grid was browned out from high temps overload. News story about black Microsoft engineer who completely converted his house to 'smart'. An Amazon delivery driver falsely accused him of some sort of untoward comment and Amazon shut his entire house down with no notice. Including locking him out. Plus, Chinese law requires every microprocessor made there to have a 'backdoor' access built in. Every internet connected 'smart' appliance is a built in window to 'pattern of life'.

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  Humberto (@patife) reported 8 minutes ago

  @ericwdolan Sure I meant more that things get transformed! Postal services were about letters, os they move parcels/ amazon boxes. Email service was about .. email, now they’re about identity/ login.

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  founditcheaper (@founditcheaper1) reported 9 minutes ago

  more dumb stuff on amazon you shouldn't be buying. a 3 pack of forged bbq knives, a camera drone, dark brown hair dye shampoo, a slow feeder dog bowl, non slip stair mats, and a 2 pack of shoe organizers. each one has a promo code. link in bio under september 2 deals can expire at any time

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  Raye (@rayemarkets) reported 10 minutes ago

  Every time Damodaran uploads a video, I always watch it because he usually takes a concept that sounds simple on the surface and then breaks down the incentives and economics underneath it, and this discussion on scaling versus profitability is a good example. The common startup narrative is that companies should grow as quickly as possible, capture market share, and worry about profits later, but Damodaran's argument is that this approach only works when the structure of the business actually supports it. A large addressable market and fast revenue growth can tell us how big a company might become, but they tell us very little about how valuable that company will eventually be unless growth can translate into better unit economics, operating leverage, pricing power, and returns on invested capital. A company can therefore become much larger without becoming economically stronger, and in some cases scaling simply multiplies the weaknesses that were already embedded in the original business model. This is why the distinction between scalability and business quality is so important. Software businesses can often add customers at very low marginal cost, meaning revenue can grow much faster than the underlying cost base, while businesses involving manufacturing, logistics, physical infrastructure, or expensive customer acquisition may require significant incremental spending for every additional dollar of revenue. Even within technology, being asset-light does not automatically solve the problem because customer acquisition costs, incentives, cloud infrastructure, research spending, and competition can effectively become variable costs that rise alongside growth. Scale only creates meaningful operating leverage when the incremental economics improve as the company gets larger, and if costs continue rising roughly in line with revenue, the company may eventually discover that what looked like a temporary profitability problem was actually structural. Amazon is therefore an important example, but also a dangerous template for other startups to copy. Amazon could tolerate years of weak accounting profitability because its scale was gradually building infrastructure, distribution density, customer relationships, marketplace liquidity, and purchasing power that improved the economics of the business over time, so the losses were connected to assets and competitive advantages that eventually supported much greater profitability. The mistake is assuming that every company reporting losses while growing quickly is following the same path, because some businesses are simply using investor capital to subsidize prices, acquire customers, or enter markets without creating corresponding economic advantages. Both companies can initially show the same headline numbers of rapid revenue growth and negative earnings, but one may be accumulating future operating leverage while the other is accumulating obligations that require continuous external capital. Damodaran's "Field of Dreams" can become a "Field of Nightmares" precisely when investors assume profitability will automatically appear once sufficient scale has been reached. The venture capital structure makes this problem more interesting because the incentives of the investor and the economics of the underlying company are not necessarily aligned. Venture portfolios depend heavily on a relatively small number of very large winners, which means a venture capitalist may rationally prefer a founder to pursue a much larger and riskier outcome rather than build a smaller company producing steady profits. A company that could become a profitable business worth a few hundred million dollars may be economically attractive to its founder, employees, and customers, but it might barely move the returns of a multibillion-dollar venture fund, while turning that same company into a speculative attempt at a ten-billion-dollar outcome provides much more upside to the fund. Scaling therefore becomes partly a consequence of portfolio mathematics rather than purely a consequence of what is optimal for the company itself, which helps explain why startups are frequently encouraged to expand geographically, add products, increase hiring, and raise increasingly large funding rounds even before the economics of the original business have been fully proven. Damodaran's point about pricing versus valuation extends this incentive further. Private markets frequently anchor financing rounds around comparable transactions, revenue multiples, user growth, subscribers, or projected future revenue rather than the present value of sustainable future cash flows, so scale itself becomes an input into the next financing round. Once that happens, raising capital can create a self-reinforcing cycle where capital funds growth, growth supports a higher private-market price, the higher price enables another larger funding round, and that new capital funds even more growth. During favorable capital-market conditions this cycle can continue for years, making it difficult to distinguish between a genuinely improving business and a company whose growth is partly being manufactured by increasingly abundant financing. The real test only arrives when the marginal investor becomes less willing to finance losses and the company has to demonstrate that customers, margins, and cash generation can support the business without constant capital injections. The expansion of private capital has allowed this process to continue much further than it could several decades ago. Companies historically reached public markets relatively early because public equity was one of the few ways to obtain the capital required for large-scale expansion, whereas mutual funds, sovereign wealth funds, private equity firms, crossover investors, and very large venture funds can now provide billions of dollars while companies remain private. Damodaran describes this as the creation of a gray market between traditional venture capital and public equity, and one consequence is that startups can reach enormous revenue bases and valuations before facing the level of disclosure, governance scrutiny, and profitability expectations traditionally associated with public companies. His data also show how much this has changed the profile of companies reaching the public market, with companies generally arriving larger in revenue terms but substantially less likely to be profitable than companies going public several decades ago. There is also a governance dimension that becomes increasingly important as companies scale privately. A founder managing a small startup and a founder controlling an organization worth tens or hundreds of billions of dollars are effectively running very different institutions, yet rapid private-market scaling can allow the governance structure of the first company to survive into the second. Founder control, dual-class shares, fragmented investor bases, and competition among venture investors can weaken the normal mechanisms that challenge management decisions, while large valuations can reinforce the belief that the founder's strategy has already been validated. The danger is that valuation growth can substitute for operational accountability during the scaling phase, and by the time profitability, capital allocation, organizational complexity, or governance problems become visible, the company may already employ thousands of people and control significant amounts of capital. Another part of Damodaran's argument that I find important is that staying small should not automatically be interpreted as failure. Some businesses naturally have better economics when they remain concentrated around a specific customer base, product category, geography, or brand position, because expanding beyond that niche can weaken pricing power or require disproportionately higher capital and marketing spending. Ferrari is an obvious example of a company whose economics partly depend on scarcity, but the principle applies much more widely: maximizing revenue is not necessarily the same thing as maximizing enterprise value. A business generating high returns on capital within a limited market can be economically superior to a much larger competitor producing weak returns after enormous capital investment, which means the correct objective should ultimately be value creation rather than size itself. Personally, this is where I agree strongly with Damodaran, because I do not see profitability and growth as opposite objectives in the first place. A company should absolutely sacrifice near-term profits when it has opportunities to reinvest capital at attractive returns, especially when that spending strengthens distribution, technology, network effects, customer retention, infrastructure, or another durable competitive advantage, but there needs to be a credible economic mechanism connecting today's spending with tomorrow's cash generation. I care much less about whether a rapidly growing company currently reports a profit than about what happens to the economics of the next dollar of revenue, because improving contribution margins, lower acquisition costs, stronger retention, greater pricing power, and falling capital requirements provide evidence that scale is actually making the business better. This also makes the discussion extremely relevant to the current artificial intelligence cycle. Artificial intelligence companies are being pushed to scale models, computing infrastructure, data centers, users, enterprise distribution, and revenue extraordinarily quickly, while the capital required to support that expansion is also becoming enormous. Some of that spending could eventually create exceptional businesses if inference economics improve, utilization rises, customers become deeply embedded in the products, and artificial intelligence generates enough willingness to pay to produce strong margins, but scale alone cannot prove that outcome. If computing costs and capital requirements continue rising alongside usage, then very fast revenue growth could coexist with mediocre returns on capital, particularly when companies must continuously finance new generations of chips and infrastructure simply to remain technologically competitive. For me, the most important question in artificial intelligence therefore is gradually shifting from how fast these companies can grow to how much economic value remains after paying for the infrastructure required to generate that growth, because eventually the market has to separate companies that are using capital to build durable operating leverage from companies that simply need ever larger amounts of capital to keep the scaling story alive.

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  🇺🇲king John🇲🇽 (@J0HNM45T3RCH13F) reported 11 minutes ago

  @8BitDo Getting it tomorrow Amazon do to a payment info issue but updated the info getting it tomorrow can't wait

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  Captiin (@CaptnUson) reported 18 minutes ago

  @KennyEmm8101 There is also no record that Preston was offered Amazon and refused it. Bezos stepped down as CEO in 2021 and handed the job to Andy Jassy,

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  two (@one2gloss) reported 22 minutes ago

  @_2skinny its not a recall its just an amazon issue

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  Derek Johnson (@rattletrap1776) reported 23 minutes ago

  Protesting Data Centers because you do not like AI… Is like Protesting to shut down Amazon Publishing and Printing because you read one bad book… 😝 Stop being ig—nernt 🤡📌

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  STR8BGN (@StraightBugging) reported 24 minutes ago

  @Variety Energetic my ***. Horrible acting and terrible plot. It's like speed, but she's running. Amazon Studios strikes out again.

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  Conor (@leprechaunsrfun) reported 29 minutes ago

  @AmazonHelp No you're good this is a staff issue with the delivery hand off

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  STL Sports Fan (@BStock72) reported 30 minutes ago

  @TheRy_InSTL Regardless, it's a terrible look that for Dallas and Anaheim it's part of the standard Amazon offering but for us it's an add-on service.

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  Ghyan (@GhyanOnX) reported 31 minutes ago

  Outstanding customer service, @amazonIN @AmazonHelp: 1. Botch my order 2. Fail to pick it up for 10 straight days 3. Have your highest escalation team act like arrogant trash and hang up on me :) You screwed up, you refuse to fix it, and your support is a toxic joke!