enterprise services or assets that share a common infrastructure or platform require coordinated performance testing, with all consumers creating production-like transaction volumes and load on shared infrastructures or platforms. Because this activity is so complex and costly in money and time, some organizations now use tools to monitor and simulate production-like conditions (also referred as "noise") in their performance testing environments (PTE) to understand capacity and resource requirements and verify / validate quality attributes. Timing It is critical to the cost performance of a new system that performance test efforts begin at the inception of the development project and extend through to deployment. The later a performance defect is detected, the higher the cost of remediation. This is true in the case of functional testing, but even more so with performance testing, due to the end-to-end nature of its scope. It is crucial for a performance test team to be involved as early as possible, because it is time-consuming to acquire and prepare the testing environment and other key performance requisites. Tools Performance testing is mainly divided into two main categories: Performance scripting This part of performance testing mainly deals with creating/scripting the work flows of key identified business processes. This can be done using a wide variety of tools. Each of the tools mentioned in the above list (which is not exhaustive nor complete) either employs a scripting language (C, Java, JS) or some form of visual representation (drag and drop) to create and simulate end user work flows. Most of the tools allow for something called "Record & Replay", where in the performance tester will launch the testing tool, hook it on a browser or thick client and capture all the network transactions which happen between the client and server. In doing so a script is developed which can be enhanced/modified to emulate various business scenarios. Performance monitoring This forms the other face of performance testing. With performance monitoring, the behavior and response characteristics of the application under test are observed. The below parameters are usually monitored during the a performance test execution Server hardware Parameters CPU Utilization Memory Utilization Disk utilization Network utilization As a first step, the patterns generated by these 4 parameters provide a good indication on where the bottleneck lies. To determine the exact root cause of the issue, software engineers use tools such as profilers to measure what parts of a device or