Cultivating Software Performance in Cloud Computing

TL;DR

This paper discusses the challenges and methods for jointly optimizing software performance in cloud computing environments, focusing on data collection, processing, and analysis to improve overall system efficiency.

Contribution

It identifies key challenges in cloud performance data management and provides insights into optimizing software performance through comprehensive data analysis.

Findings

Unified performance data enhances optimization accuracy

Data quality verification improves reliability of performance analysis

Addressing environment and data challenges is crucial for cloud optimization

Abstract

There exist multitudes of cloud performance metrics, including workload performance, application placement, software/hardware optimization, scalability, capacity, reliability, agility and so on. In this paper, we consider jointly optimizing the performance of the software applications in the cloud. The challenges lie in bringing a diversity of raw data into tidy data format, unifying performance data from multiple systems based on timestamps, and assessing the quality of the processed performance data. Even after verifying the quality of cloud performance data, additional challenges block optimizing cloud computing. In this paper, we identify the challenges of cloud computing from the perspectives of computing environment, data collection, performance analytics and production environment.