Krisztina M. Kovacs
Project Description:
This project aimed to evaluate and optimize the performance of a set of new Software as a Service (SaaS) components deployed in a cloud environment for an R&D project. Leveraged industry-standard tools and cloud infrastructure to conduct comprehensive performance testing, ensuring the SaaS components can handle varying loads efficiently and maintain high availability during standard use.
Key Objectives:
Performance Benchmarking: Establish performance benchmarks for the SaaS components under different load conditions to identify potential bottlenecks.
Scalability Testing: Evaluate the scalability of the SaaS component by simulating varying user loads and measuring its response time, throughput, and resource utilization.
Resource Utilization Analysis: Analyze the resource usage (CPU, memory, I/O) of the SaaS component to ensure optimal allocation and cost-efficiency.
Reliability Assessment: Test the reliability and resilience of the SaaS component under stress conditions to ensure it can withstand peak loads without failure.
Tools & Technologies:
JMeter (measure various performance metrics)
AWS EC2 and S3 (deployment and storage)
Grafana (visualization)