Performance Testing Overview.

Performance testing is the practice of evaluating how a system performs in terms of responsiveness and stability under a particular workload. Performance tests are typically executed to examine speed, robustness, reliability, and application size. The process incorporates "performance" indicators such as:

• Browser, page, and network response times
• Server request processing times
• Acceptable concurrent user volumes
• Processor memory consumption; number and type of errors that might be encountered with app

Performance testing gathers all the tests that verify an application’s speed, robustness, reliability, and correct sizing. It examines several indicators such as a browser, page and network response times, server query processing time, number of acceptable concurrent users architected, CPU memory consumption, and number/type of errors which may be encountered when using an application.

In short, to ensure that it will meet the service levels expected in production, as well as deliver a positive user experience. Application performance is a key determinant of adoption, success, and productivity.

As it can be cost prohibitive to have to solve a production performance problem, continuous performance testing strategy optimization is the key to the success of an effective digital strategy.

Why is system performance testing important?

The performance tests you run will help ensure your software meets the expected levels of service and provide a positive user experience. They will highlight improvements you should make to your applications relative to speed, stability, and scalability before they go into production. Applications released to the public in absence of testing might suffer from different types of problems that lead to a damaged brand reputation, in some cases, irrevocably.

The adoption, success, and productivity of applications depends directly on the proper implementation of performance testing.

While resolving production performance problems can be extremely expensive, the use of a continuous optimization performance testing strategy is key to the success of an effective overarching digital strategy.

There are many different types of performance tests.

Load Tests

Load testing simulates the number of virtual users that might use an application. In reproducing realistic usage and load conditions, based on response times, this test can help identify potential bottlenecks. It also enables you to understand whether it’s necessary to adjust the size of an application’s architecture.

Unit Tests

Unit testing simulates the transactional activity of a functional test campaign; the goal is to isolate transactions that could disrupt the system.

Stress Tests

Stress testing evaluates the behavior of systems facing peak activity. These tests significantly and continuously increase the number of users during the testing period.

Spike Tests

Spike testing seeks to understand implications to the operation of systems when activity levels are above average. Unlike stress testing, spike testing takes into account the number of users and the complexity of actions performed (hence the increase in several business processes generated).

Soak Tests

Soak testing increases the number of concurrent users and monitors the behavior of the system over a more extended period. The objective is to observe if intense and sustained activity over time shows a potential drop in performance levels, making excessive demands on the resources of the system.

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