Improving Datacenter Utilization Through Containerized Service-Based Architecture

Abstract

The modern datacenter's computing capabilities have far outstripped the applications running within and have become a hidden cost of doing business due to how software is architected and deployed. Resources are over-allocated to monolithic applications that sit idle for large parts of the day. If applications were architected and deployed differently, shared services could be used for multiple applications as needed. When combined with powerful orchestration software, containerized microservices can both deploy and dynamically scale applications from very small to very large within moments—scaling the application not only across a single datacenter but across all datacenters where the application(s) are deployed. In this paper, we analyze data from an application(s) deployed both as a single monolithic codebase and as a containerized application using microservice-based architecture to calculate the performance and computing resource waste are both architected and deployed. A modern approach is offered as a solution as a path from how to go from a monolithic codebase to a more efficient, reliable, scalable, and less costly deployment model.

The Impact of Academic Publications over the Last Decade on Historical Bitcoin Prices Using Generative Models

“…The influence on Bitcoin prices from popular social networks makes prices extremely volatile and speculative. However, the influences of users are not equal and a hypertextinduced topic selection algorithm was used to split the dataset into two groups based on the users' influence [47]. Topic modelling was employed to extract topics from the discourses of the two groups.…”