Amazon Technologies, Inc.

Lucia Castellanos

Jordan Barry Brest

Varvara Nasonova

Sai Vishnu Kiran Bhyravajosyula

Methods, systems, and computer-readable media for optimizing application configurations in a provider network are disclosed. An application description is determined that comprises one or more resource utilization characteristics of an application. Automated analysis is performed of a plurality of potential configurations for the application based at least in part on the application description. The automated analysis comprises scoring at least a portion of the potential configurations based at least in part on a scoring function. A recommended configuration for the application is determined based at least in part on the automated analysis. The recommended configuration comprises a type and number of computing resources in a multi-tenant provider network.

Optimizing application configurations in a provider network

A network resource ('NR') delivery acceleration system predicts web browsing behavior of users based on their frequent navigation habits, the navigation habits of the majority and/or content based prediction. Based on these predictions, the system accelerates the delivery of selected network resources, such as resources on web pages, to user devices in one or more ways, such as by selectively prefetching, caching, preemptively delivering, and/or pre-rendering content items. To determine access probabilities for candidate pages (such as those frequently visited by the user), the NR delivery acceleration system adapts or trains one or more models, such as logistic regression and/or frequency-based models, using individual/personalized browsing histories of users, their content (topic) preferences, and/or aggregated patterns of navigation.

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Palo Alto, CA, United States of America

Lucia Castellanos