In order to provide testers with representative synthetic performance scenario elements as fast as possible, a solution needs to synthesize/mimic as closely as possible the behaviors of real users on production systems. Due to the fact that it is a highly manual and time-consuming endeavor, the majority of performance tests do not accurately reflect real-world conditions. It continues to follow the legacy process established by the market's pioneers. While modern solutions do leverage automation to accelerate many aspects of performance and load testing, the approach to answering the fundamental question “What is a representative test that reflects real-world behavior and traffic?” has not changed in the past 25 years. And, of course, analyzing results and working with software engineering teams to resolve identified issues.Running tests, either manually or programmatically.Actually building robust and maintainable test scripts.Coordinating with business experts and gathering data to build the strategy that tests the right things, under the right load.Performance engineering (of which performance testing is integral) has traditionally been a practice that requires numerous manual steps and long-to-acquire knowledge involving a steep learning curve: Nevertheless, far too frequently, validating performance via realistic testing has become a bottleneck. Application performance has become a critical differentiator in the competitive landscape. And performance has become critical: users and customers expect a seamless digital experience on any device, at any time, and from any location. Application environments are more complex than ever, with SaaS, microservices, legacy monolithic applications, and packaged enterprise applications such as SAP all highly connected and coexisting. Cycle times for software development and delivery are becoming increasingly shorter and more frequent.
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