Performance Analysis of Google Cloud Platform for Web-Based Applications

Amiruddin. A Amiruddin; Rahmawati Rahmawati; Nurhaedar Nurhaedar; Musa Musa

doi:10.57152/malcom.v6i1.2351

Authors

Amiruddin. A Amiruddin Politeknik Lembaga Pendidikan dan Pengembangan Profesi Indonesia
Rahmawati Rahmawati Universitas Almarisah Madani
Nurhaedar Nurhaedar Politeknik Lembaga Pendidikan dan Pengembangan Profesi Indonesia
Musa Musa Politeknik Lembaga Pendidikan dan Pengembangan Profesi Indonesia

DOI:

https://doi.org/10.57152/malcom.v6i1.2351

Keywords:

Cloud Computing, Google Cloud Platform, Performance, Scalability, Web Application

Abstract

Selecting an appropriate cloud computing service remains a major challenge in web-based application development, as it directly affects performance, scalability, security, and operational costs. Google Cloud Platform (GCP) offers multiple computing services, yet empirical comparisons among its core services are still limited. This study aims to evaluate and compare the performance of Compute Engine, App Engine, and Kubernetes Engine in hosting web-based applications. A quantitative experimental approach was employed using a Node.js and PostgreSQL-based e-commerce application, tested under various workload scenarios using Apache JMeter. Performance metrics, including response time, throughput, latency, scalability, reliability, security, and cost, were analyzed. The results indicate that Compute Engine provides stable performance for predictable workloads, App Engine delivers low latency with higher operational costs, and Kubernetes Engine offers the best scalability and resource efficiency. Performance optimization techniques such as caching and CDN integration further improved API responsiveness. This study concludes that Kubernetes Engine is the most suitable choice for large-scale and dynamic web applications. Optimal GCP service selection should align with workload characteristics and organizational requirements.

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References

R. Johnson and M. Lee, “A comparative study of AWS, Azure, and GCP,” International Journal of Cloud Services, vol. 12, no. 3, pp. 123–130, 2022.

J. Smith, “Cloud storage efficiency in Google Cloud,” Journal of Cloud Computing, vol. 15, pp. 45–56, 2023.

D. Harris, “Security features of Google Cloud Platform,” Cloud Security Journal, vol. 5, no. 1, pp. 89–95, 2022.

K. Brown, “Container orchestration with Kubernetes Engine,” Cloud Innovation Journal, vol. 8, no. 2, pp. 34–40, 2023.

P. White, “Cost evaluation of GCP in enterprise environments,” Cloud Cost Journal, vol. 11, pp. 60–70, 2023.

H. Li and P. Chandra, “Performance analysis of Kubernetes autoscaling under heavy load,” Journal of Cloud Computing Systems, vol. 9, no. 2, pp. 55–67, 2023.

A. Kumar, “Machine learning implementation on GCP,” AI Cloud Journal, vol. 7, no. 1, pp. 15–20, 2022.

R. Gupta, T. Sharma, and J. Lee, “Comparative evaluation of public cloud performance: AWS, Azure, and GCP,” Journal of Cloud Infrastructure, vol. 10, no. 4, pp. 112–125, 2023.

P. Singh, D. Tan, and E. Wong, “Optimizing cloud resource allocation using container-based approaches,” International Journal of System Engineering, vol. 15, no. 2, pp. 65–80, 2024.

F. Nasution and H. Park, “AI-driven resource optimization in GCP environments,” Journal of Applied Cloud Engineering, vol. 6, no. 1, pp. 41–58, 2024.

M. Rahman and K. Lee, “Cost-performance tradeoff in multi-cloud strategies,” Journal of Information Systems, vol. 13, no. 2, pp. 98–112, 2024.

C. O’Neill, “Compliance and governance in modern cloud infrastructures,” Cloud Compliance Review, vol. 4, no. 3, pp. 77–88, 2023.

L. Zhao et al., “Container performance under large-scale web workloads,” Journal of Web Systems, vol. 18, no. 1, pp. 22–37, 2024.

S. Lee and M. Wong, “Evaluating fault tolerance in hybrid and multi-cloud environments,” Journal of Advanced Cloud Studies, vol. 19, no. 3, pp. 101–118, 2025.

P. White, “Cost evaluation of GCP in enterprise environments,” Cloud Cost Journal, vol. 11, pp. 60–70, 2023.

L. Zhao et al., “Container performance under large-scale web workloads,” Journal of Web Systems, vol. 18, no. 1, pp. 22–37, 2024.

M. Rahman and K. Lee, “Cost-performance tradeoff in multi-cloud strategies,” Journal of Information Systems, vol. 13, no. 2, pp. 98–112, 2024.

P. Singh, D. Tan, and E. Wong, “Optimizing cloud resource allocation using container-based approaches,” International Journal of System Engineering, vol. 15, no. 2, pp. 65–80, 2024.

C. O’Neill, “Compliance and governance in modern cloud infrastructures,” Cloud Compliance Review, vol. 4, no. 3, pp. 77–88, 2023.

Y. Zhou and D. Tan, “HTTP optimization techniques for cloud-based APIs,” Journal of Networked Systems, vol. 16, no. 1, pp. 45–59, 2024.