Cross-Layer Cloud Resource Configuration Selection in the Big Data Era

Abstract

Cloud computing has transformed people's perception of how Internet-based applications can be deployed in datacenters and offered to users in a pay-as-you-go model. Despite the growing adoption of cloud datacenters, challenges related to big data application management still exist. One important research challenge is selecting configurations of resources as infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) layers such that big data application-specific service-level agreement goals (such as minimizing event-detection and decision-making delays, maximizing application and data availability, and maximizing the number of alerts sent per second) are constantly achieved for big data applications. This article discusses the issue of selecting resource configurations across multiple layers of a cloud computing stack by considering deployment of a real-time stock recommendation big data application over an Amazon Web Services public datacenter.