Performance Graphs & Analysis
QA Mentor’s Performance Graph and Analysis Report is a specialized document that captures, describes, and illustrates our findings from an in-depth Performance Test.
End User Response Times
One of the most commonly requested, important, and utilized metric, this graph helps measure current or hypothetical user satisfaction. It can easily convey if performance goals are being met for each page or transaction and can capture the increase or decrease in response times in relation to other load activities.
This metric can be either detailed or generalized. If the data points to an issue, the metric is given in a more detailed manner by associating utilization and response times with number of users or transactions. In this way, the requirement threshold can be seen visually and understood as it relates to the current usage or potential growth of the system. Resources reported on include processor, memory, disk I/O, and network I/O.
Component Response Times
Very useful to the technical team, the component response times helps determine what parts are responsible for the end-user response times. If applicable, the metric ties the component response times to end-user actions to help understand the relationship.
Extremely useful for systems with frequent builds, this chart show performance improvements or degradations over time and can pinpoint exact code or application changes that cause performance issues, or improved performance.
Volumes, Capacities, and Rates
Metrics related to these include hits per second, transactions per second, bandwidth usage, and database storage. When put in context with other metrics, these can help point to areas with current or impending performance issues.
These metrics provide information as it relates to the efficiency of your network. Routers, gateways, and switches evaluations are included.
Server or application-hosting software analysis are included in these metrics, such as Microsoft .NET CLR and those related to ASP.NET.
Application health is portrayed in these metrics to help identify performance issues related to concurrent threads, deadlocks, or web service request queues.
Throughput and latency for the entire application are measured and conveyed in these metrics.
These metrics are commonly used to analyze and set the parameters of a performance test since they capture the real-time business usage of the application, such as number and type of transactions within a period of time.