Even simple changes or enhancements impacted many downstream applications and use cases, requiring huge amounts of communication. Metcalfe’s law sort of applied as each additional service or developer was added, complexity grew at an n^2 rate. The Emergence of AWSĪs Amazon ballooned in size with its retail business, it began to run into limitations of its monolithic 90s-era software practices. We will also explain how Microsoft Azure, Google Cloud, Nvidia Cloud, Oracle Cloud, IBM Cloud, Equinix Fabric, Coreweave, Cloudflare, and Lambda are each fighting Amazon’s dominance across multiple vectors and to various degrees.īefore we dive into our thesis, we need a bit of a history lesson first. We will also cover what Amazon is intentionally doing that harms its position in AI and enterprise automation and will ultimately cause them to lose market share in computing.
This overview will tackle the technology and total cost of ownership perspectives of Amazon’s in-house semiconductor ambitions. We will present an overview of Amazon’s various in-house semiconductor designs, including Nitro, Graviton, SSDs, Inferentia, and Trainium. This report will cover these 3 phases of cloud computing and how Amazon’s continued dominance in the first two phases doesn’t necessarily give them a head start in the battle for the future of computing. Technological prowess, culture, and/or business decisions will hamper them from capturing the next wave of cloud computing like they have the last two. This engine has driven Amazon to become the preeminent computing company in the world, but that is changing.Īmazon is an amazing technical company, but they lack in some ways. AWS has dominated the market by catering to startups and businesses alike, offering scalable, reliable, low-cost compute, and storage solutions.
Amazon Web Services (AWS) has long been synonymous with cloud computing.
Amazon owns more servers than any other company in the world despite its internal needs being much smaller than Google, Microsoft, Meta, and Tencent.
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