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only to find that the resource they’re requesting isn’t in that PoP ’s cache. Routing: If you are using a CDN—and you should be!—a a customer in Leeds might get routed to the MAN datacentre. Accordingly, they’ll get routed all the way back to your origin server to retrieve it from there.
From the business logic point of view, this was a pretty typical eCommerce service for hierarchical and faceted navigation, although not without peculiarities, but high performance requirements led us to the quite advanced architecture and technical design. So, the only way was to cache all necessary data to minimize interaction with RDBMS.
The Amazon.com ecommerce platform consists of hundreds of decoupled services developed and managed in a decentralized fashion. In response, we began to develop a collection of storage and database technologies to address the demanding scalability and reliability requirements of the Amazon.com ecommerce platform.
Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.
Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.
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