Background :Cloud computing has transformed the landscape of application deploy-ment, offering on-demand access to compute resources, databases, and services viathe internet. This thesis explores the development of an innovative online book-storeweb application, harnessing the power of cloud infrastructure across AWS,Azure, andGCP. The front end utilises HTML, CSS, and JavaScript to create responsive webpages with an intuitive user interface. The back-end is constructed using Node.jsand Express for high-performance server-side logic and routing, while MongoDB, adistributed NoSQL database, stores the data. This cloud-native architecture facili-tates easy scaling and ensures high availability.

Objectives: The main objectives of this thesis are to develop an intuitive onlinebookstore enabling users to add, exchange, and purchase books, deploy it acrossAWS, Azure, and GCP for scalability, implement load balancers for enhanced per-formance, and conduct load testing and benchmarking to compare the efficiency ofthese load balancers. The study aims to determine the best-performing cloud plat-form and load-balancing strategy to ensure an exceptional user experience for ouronline bookstore. Comparing load balancer data across these platforms to determinetheir performance ensures the best user experience for our online bookstore by takingthe metrics.

Methods: The website deployment is done on three cloud platforms by creatinginstances separately on each platform, and then the load balance is created for eachof the services. By using the monitoring tools of every platform, we get the resultinggraphs for the metrics. From this, we increase and decrease the load in the ApacheBenchmark tool by taking the specific tasks from the website and comparing thevisualisation of the results done in an aggregate graph and summary reports. It isthen used to test the website’s overall performance by using metrics like throughput,CPU utilisation, error percentage, and cost efficiency.

Results: The results are based on the Apache Benchmark Load Testing Tool of aselected website between the cloud platforms. The results of AWS, Azure, and GCPcan be shown in the aggregate graph. The graph results are based on the testingtool to determine which service is best for users because it shows less load on theserver and requests data in the shortest amount of time. We have considered 10 and50 requests, and based on the results, we have compared the metrics of throughput,CPU utilisation, error percentage, and cost efficiency. The 10 and 50 requests’ resultsare compared to determine which cloud platform performs better.

Conclusions: According to the results from the 10 and 50 requests, it can be con-cluded that GCP has a higher throughput and CPU utilisation than AWS and Azure.They are less flexible and efficient for users. Thus, it can be said that GCP outper-forms in terms of load balancing.