Load Testing Redefined: A Guide from KPI Reporting to AI Supported Performance Engineering

Performance and load testing have evolved with the transition from traditional page-based applications to single-page apps utilizing REST APIs, yet the fundamental metrics such as response time, throughput, and failure rate remain central. The use of tools like Dynatrace in combination with load testing platforms enables performance engineers to transcend mere reporting and influence architectural decisions, optimizing service flow, cloud, and container utilization. Through techniques such as tagging web requests, engineers can obtain more targeted analytics, while the integration of Dynatrace's AI allows for the immediate identification of performance issues and their root causes. This shift emphasizes the importance of performance engineering as a collaborative effort within DevOps, focusing on continuous performance data sharing to enhance software quality and user satisfaction.