Performance testing : An Overview

The document discusses performance testing. It defines performance testing as determining how fast and stable a system is. It outlines why performance testing is important to identify problems early, prevent revenue and credibility loss from poor performance, and ensure systems meet expectations. It also discusses various performance testing terms, metrics, processes, limitations of manual testing, and benefits of automation using tools like LoadRunner and JMeter.

Performance testing validates an application's responsiveness, stability, and other quality attributes under various workloads. It involves load testing, stress testing, endurance testing, spike testing, volume testing, availability testing, and scalability testing. The key parameters analyzed are response time, throughput, and memory utilization. Performance testing helps determine an application's speed, scalability, stability, and ability to handle changes in load and traffic over time.

Load testing is done to determine system limits, verify response times under high load, check stability, and predict future needs. Open source tools like JMeter, Yandex Tank, and Taurus can be used. With JMeter, a test plan is created with thread groups, HTTP requests, and listeners to start load testing. Issues like slow responses or server crashes are identified. Short term fixes include restarting servers or tuning configurations, while long term solutions involve moving to the cloud, using caching, or splitting applications into microservices. Other commercial load testing tools are also available from companies like SOASTA and BlazeMeter.

Why performance testing is important? Introduction to performance testing. Load profiles, metrics Performance testing tools Implementation process Performance testing engineer skills JMeter intro LINKS: About performance testing: http://docplayer.net/29696161-Performance-matters-key-consumer-insights.html http://www.softwaretestingclass.com/what-is-performance-testing/ https://www.blazemeter.com/blog http://revolutionit.com.au/performance-testing-digital-projects-dont-leave-it-to-the-developers/ https://www.youtube.com/embed/61Kkgnx-zF8?list=PLSjEh0z5QH9lKpMO4Nf3buFiP7tt0gTRN Concurrent users calculation: https://blog.xceptance.com/2013/07/26/concurrent-users-the-art-of-calculation/ https://techbeacon.com/how-many-virtual-users-do-i-need-load-testing https://www.webperformance.com/library/tutorials/CalculateNumberOfLoadtestUsers/ Browser performance: https://www.slideshare.net/nicjansma/measuring-real-user-performance-in-the-browser Books for start: “Web Load Testing For Dummies”, Scott Barber with Colin Mason “JMeter Cookbook”, Bayo Erinle

Load Testing Best Practices: Application complexity is increasing, yet the stringent requirements for web performance is increasing exponentially. Learn more about the three major types of load testing, determine which you need and how to conduct them.

BugRaptors Perform performance testing using different types of tools helps determining how fast some aspect of a system performs under a particular workload. It can help different purposes like it demonstrates that the system meets performance criteria in any condition.

This document discusses performance testing tools and techniques. It defines performance from the perspectives of developers, infrastructure, and end users. Key aspects covered include defining realistic user scenarios, available tools like JMeter, ApacheBench, Gatling and Locust, and the importance of continuous performance testing. The document recommends using the Apdex score as part of your definition of done, specifying good test scenarios, running tests simultaneously, choosing the right tool for your needs, and considering tools like Taurus that enable continuous performance testing.

- JMeter is an open source load testing tool that can test web applications and other services. It uses virtual users to simulate real user load on a system. - JMeter tests are prepared by recording HTTP requests using a proxy server. Tests are organized into thread groups and loops to simulate different user behaviors and loads. - Tests can be made generic by using variables and default values so the same tests can be run against different environments. Assertions are added to validate responses. - Tests are run in non-GUI mode for load testing and can be distributed across multiple machines for high user loads. Test results are analyzed using aggregated graphs and result trees.

The document discusses gathering requirements for performance testing an application. It lists questions to ask about the application type and architecture, test environment, workload model, and performance goals. Key information needs include the application technology, database and server used, network details, protocols, user sessions and load over time, and goals for response times and system utilization under load. The requirements gathered will help determine the appropriate performance tests and pass/fail criteria.

This document outlines a performance test plan for Sakai 2.5.0. It describes the objectives, approach, test types, metrics, goals, tools, and data preparation. The objectives are to validate Sakai meets minimum performance standards and test any new or changed tools. Tests include capacity, consistent load, and single function stress tests. Metrics like response time, CPU utilization, and errors will be measured. Goals include average response time under 2.5s and max under 30s, CPU under 75%, and 500 concurrent users supported. Silk Performer will be used to run tests against a Sakai/Tomcat/Oracle environment. Over 92,000 students and 1,557 instructors of data will be preloaded

The document discusses performance testing using Apache JMeter. It covers topics like an overview of performance testing, the purpose of performance testing, key types of performance testing like load testing and stress testing. It also discusses pre-requisites of performance testing, the performance testing life cycle, challenges of performance testing and how to record and playback tests using JMeter.

Testing software is conducted to ensure the system meets user needs and requirements. The primary objectives of testing are to verify that the right system was built according to specifications and that it was built correctly. Testing helps instill user confidence, ensures functionality and performance, and identifies any issues where the system does not meet specifications. Different types of testing include unit, integration, system, and user acceptance testing, which are done at various stages of the software development life cycle.

This document provides an agenda and overview for a performance testing training with JMeter. It begins with an introduction to performance testing, including the purpose and types of performance testing. It then covers getting started with JMeter, including installation, setup, and running JMeter. The remainder of the document outlines the content to be covered, including building test plans with JMeter, load and performance testing of websites, parameterization, adding assertions, and best practices. The goal is to teach participants how to use JMeter to perform various types of performance testing of applications and websites.

In software engineering, performance testing is in general testing performed to determine how a system performs in terms of responsiveness and stability under a particular workload. It can also serve to investigate, measure, validate or verify other quality attributes of the system, such as scalability, reliability and resource usage.

The Heuristic Test Strategy Model provides a framework for designing effective test strategies. It involves considering four key areas: 1) the project environment including resources, constraints, and other factors; 2) the product elements to be tested; 3) quality criteria such as functionality, usability, and security; and 4) appropriate test techniques to apply. Some common test techniques include functional testing, domain testing, stress testing, flow testing, and scenario testing.