Amazon Outage Map

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Amazon Issues Reports

Latest outage, problems and issue reports in social media:

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  Filibuster (@caliginousomber) reported 1 minute ago

  @akafaceUS I counter argue that society ruined malls. They became a place where shootings, kidnappings and price gouging ran rampant with little to no consequence. The mentally ill of the world and the government enabling them to keep going into a place filled with people is the problem. Men can wear skirts and walk into women’s bathrooms. People used to be able to drop their kids off at the mall to hang with their friends and kids go missing. Or people walk in with automatic guns and mow people down. And if none of that happens, you’re still looking at having to give your kid $80 so they can buy a sandwich, a smoothie and a bottle of water. All Amazon did was capitalize on that to the fullest. But Amazon, FedEx and UPS were already in full force before the malls went extinct.

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  Atul srivastava (@atul370) reported 2 minutes ago

  @AmazonHelp Poor pathetic service by @amazonIN @AmazonHelp no one contacted me nor no one bothered for customer issues.

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  ˖ . ݁𝜗𝜚. ݁ (@celestiaIjay) reported 4 minutes ago

  thank god i kept my broken amazon knock off since og fate tour

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  Humberto (@patife) reported 4 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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  Onyx Novha (@ItzNovhaTV) reported 6 minutes ago

  Another problem back when i worked for amazon is i noticed amazon drivers shopping and getting food instead of delivering, this is also a reason you’re packages show up late, i can understand if drivers needed to stop and go to bathroom or take a lunch or dinner break that makes sense but call me old fashioned i do not believe amazon drivers should be doing there own personal shopping on shift, that is something they should do while there off shift or have days off.

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  Prescribed Slur ⋆˚✿˖° (@AestheticSlur) reported 8 minutes ago

  @brebvbi On the way via personal remote drone Amazon delivery, it drops me down like a claw machine

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  Piotr Sikora (@VoltanTweets) reported 11 minutes ago

  @NhelvUsername I was asking because one time there was an issue on my ISPs end that resulted in major packet loss to Amazon servers in Tokyo specifically (where Strive is hosted). Games themselves were not affected because they're p2p but there was a decent chance of getting kicked out of park

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  Tesla_Optimus (@Tesla_Optimus_K) reported 12 minutes ago

  Tiger Global didn't dump AI. It moved down the stack. The Aug. 14 13F shows Q2 cuts that look violent: Alphabet 10.63 million shares to 5.81 million, about 45%. Broadcom roughly halved. Netflix gone. Nvidia, Microsoft, Amazon, Meta all trimmed. Then two new lines appear — about 675,000 AMD shares worth ~$392 million, plus a small SpaceX stub. Alphabet is still a top holding near $2.1 billion. This is rebalance, not a white flag. Here's the thing: platforms still fund the capex, chips still bill it. Tiger kept Nvidia huge, doubled Intel, and bought the challenger GPU. Holder counts rose in both Alphabet and AMD. The next tell is cloud margins and who actually wins the rack, not one 13F headline. They sold some of the bill-payer. They bought more of the invoice. Source : Yahoo Finance #TigerGlobal #AMD #Alphabet $GOOGL $AMD

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  leelakurup (@leelakurup) reported 19 minutes ago

  @Tukaram_IndIAS Sir what about companies do not deliver items prepaid and show on line its delivered. Amazon delivery is doing it off late. Then call them convince them item not delivered. Big problem. Any remedy??

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  The Flicktator (@The_Flicktator) reported 19 minutes ago

  @Collider Amazon stop making terrible straight to Prime movies and give us back our ad free tier

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  ChefDankerton (@Dankert315) reported 21 minutes ago

  @ThoughtCrimes80 There's always 1-4 accidents as well. Last time I went down 2 weeks ago, and Amazon truck smashed an exit divider. It was 1 ******* lane for a 1/2 a mile.

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  Madhu Bhavaraju (@madhubhavaraju) reported 26 minutes ago

  Two pieces of news in the ad tech world. Amazon has been sued over ad auctions and Google has been asked to make some changes. The problem we really have is information asymmetry. The tech platforms control the full value chain Audience -> auction -> measurement -> attribution -> optimisation This makes them super efficient beasts but at the cost of transparency. ROAS published should be a guidance and not THE single source of truth. Brands have to build an independent source of measurement such as blended CAC, repeat rate, incremental sales, and new customer rate.

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  Al Hood (@albhood) reported 27 minutes ago

  *You DO have to download Prime Video, sign in with an Amazon ID (free), and purchase the Hurricanes Hockey Network channel *You DO NOT get a discount if you are already a subscriber to Amazon Prime *This will NOT be the only way the HHN will be available

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  Jill🇬🇧🏴󠁧󠁢󠁳󠁣󠁴󠁿💂‍♀️🐶🐾❤️ (@RoyalFan5457) reported 27 minutes ago

  @janiesaysyay Exactly. I went onto Amazon, found the book, scrolled down to “report an issue”. I’ve sent messages to BP & KP calling for the book tobe banned. I’ve posted on several platforms out of sheer exasperation that people think this promotion of extremism & incitement is ok. It isn’t!

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  Raye (@rayemarkets) reported 27 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.