This study conducts a comparative analysis of virtual machine (VM) performance and security testing across three leading cloud service providers Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. The study evaluates computational efficiency, network performance, and security resilience under controlled conditions using Joomla as a test workload. Benchmarking tools such as Geekbench, Sysbench, Apache JMeter, and OWASP ZAP were employed to assess performance metrics, including CPU processing power, memory throughput, disk I/O, and vulnerability detection. Statistical analyses using t-tests provided insights into the significant differences in throughput, error rates, and data processing efficiency across platforms. Findings indicate that GCP outperforms in data processing and network efficiency, while AWS and Azure demonstrate comparable performance in standardized workloads. The study recommends for optimizing cloud resource allocation, enhancing security protocols, and selecting the most suitable cloud platform based on workload demands. The results provide insights for organizations, developers, and researchers seeking to enhance cloud infrastructure performance and security.

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Comparative Analysis of Virtual Machine Performance and Security Test Across Leading Cloud Providers

  • Ifeoluwa Elegbe,
  • Hayden Wimmer

摘要

This study conducts a comparative analysis of virtual machine (VM) performance and security testing across three leading cloud service providers Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. The study evaluates computational efficiency, network performance, and security resilience under controlled conditions using Joomla as a test workload. Benchmarking tools such as Geekbench, Sysbench, Apache JMeter, and OWASP ZAP were employed to assess performance metrics, including CPU processing power, memory throughput, disk I/O, and vulnerability detection. Statistical analyses using t-tests provided insights into the significant differences in throughput, error rates, and data processing efficiency across platforms. Findings indicate that GCP outperforms in data processing and network efficiency, while AWS and Azure demonstrate comparable performance in standardized workloads. The study recommends for optimizing cloud resource allocation, enhancing security protocols, and selecting the most suitable cloud platform based on workload demands. The results provide insights for organizations, developers, and researchers seeking to enhance cloud infrastructure performance and security.