Bottleneck analysis is the most critical phase in Performance Testing Life Cycle. Those who are new to performance testing, they will be very eager to understand how to analyze the results and pinpoint the issues. Apparently, bottleneck analysis and isolate the issues comes by experience and by great analytical skills. In this blog post, we will see how to identify the bottleneck issues by comparing Average Transaction Response Time and Transaction Performance Summary.
Consider we have following three transactions
- Book Ticket
Below is the Transaction Performance Summary graph for the above transactions. In this example, the average response time for Book Ticket transaction is 11 seconds.
Below is the Average Transaction Response Time graph which shows Book Ticket transaction’s response time is very high (15 seconds) at 1st and 7th minute of the scenario.
Our aim is to identify the pinpoint of the issue and to analyze the root cause of high response time for the Book Ticket transaction. To achieve above said objective, we need diagnostics tool, by default HP provides following diagnostics modules: J2EE/.NET, Siebel, Oracle, SAP R/3.
Now, we will see how to isolate the bottleneck issue through diagnostics. Prerequisite is Web Page Diagnostic feature should be enabled before executing the scenario.
Breaking down a transactions helps us to identify the bottleneck issues. Open the Average Transaction Response Time in Analysis, right-click on it and select Web Page Diagnostics for Book Ticket.
Web Page Diagnostics displays breakdown of each page component’s download time of Book Ticket transaction. If the download time is too long, analyze the which measurements is responsible for the lengthy download such as FTP Authentication, DNS Resolution Time, Time to Buffer, Handshaking time etc. If you suspect, there should be any server related problem, check the First Buffer Breakdown option.
It is ideal to check the Network Monitor graphs; it helps to determine what network problem caused the bottlenecks. Also we can identify the bottleneck by using auto-correlating feature. Right-click on Average Transaction Response Time and select Auto Correlate. Mention the time frame for analysis, and the correlate options (which data that you want to correlate) such as SQL Server, Windows Resources, and WebLogic (JMX) etc.
WebLogic (JMX) or JVM Heap Size or Private Bytes might be the cause of slow performance of Book Ticket transaction.
In this way we can pinpoint the issues by analyzing Average Transaction Response Time graph. There are other ways too to determine the cause. In next blog post, we will see about Network and Server Problems.