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CloudPT: Performance Testing for Identifying and Detecting Bottlenecks in IaaS

  • Ameen Alkasem
  • Hongwei Liu
  • Decheng Zuo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11336)

Abstract

This work addresses performance testing for monitoring mass quantities of large-dataset measurements in infrastructure-as-a-Service (IaaS). Physical resources are not virtualized in sharing dynamic clouds; thus, shared resources compete for access to system resources. This competition introduces significant new challenges when assessing the performance of IaaS. A bottleneck may occur if one system resource is critical to IaaS; this may shut down the system and services, which would reduce the workflow performance by a large margin. To protect against bottlenecks, we propose CloudPT, a performance test management framework for IaaS. CloudPT has many advantages: (I) high-efficiency detection; (II) a unified end-to-end feedback loop to collaborate with cloud-ecosystems management; and (III) a troubleshooting performance test. This paper shows that CloudPT efficiently identifies and detects bottlenecks with a minimal false-positive rate (<13%) and it correlates high accuracy using the failure of a host virtual machine (host VM) to start-up with both cloud illustrative batches and transactional workloads such as the Spark, and Kafka framework for a data partitioning and collecting events on an each server. In a framework based on a trace case study, CloudPT diagnosed performance bottlenecks in 20 s with a precision rate of 86%, confirming its real-time efficiency.

Keywords

IaaS Bottlenecks Performance testing VMs Apache Spark 

Notes

Acknowledgments

We are also thankful to anonymous reviewers for their valuable feedback and comments for improving the quality of the manuscript.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina

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