Machine learning optimizes efficiency of cloud databases -- GCN

Research intended to help scientists maximize data throughput to process microbiome or metagenomics data ended up improving the cloud efficiency of long-running dynamic workloads, saving both cloud providers and users money. The software, called OPTIMUSCLOUD, boosts efficiency for cloud-hosted databases by rightsizing resources. It works by using machine learning to develop algorithms that help optimize the cost and performance of both the virtual machine selection and the database management system options. "Our system takes a look at the hundreds of options available and determines the best one normalized by the dollar cost," said Somali Chaterji, a Purdue University assistant professor of agricultural and biological engineering and OPTIMUSCLOUD team leader. "When it comes to cloud databases and computations, you don't want to buy the whole car when you only need a tire."