LoadRunner – Overlay, Correlate & Tile Graphs

LoadRunner - Graph Analysis - Overlay Correlate and Tile

I always consider Test Analysis as most important and technical part in performance testing rather than scripting and execution. Performance test result analysis requires your actual expertise. During the analysis phase, you can determine bottleneck and remediation options at an appropriate level – business, middleware, application, infrastructure, network etc. LoadRunner Analysis tool is really helpful to conduct your analysis on the test result. This tool converts the row test result data into a human-readable format and displays the result through tables, graphs etc. which help to detect the bottleneck. Such graphs enabling you to view and understand the data and analyse system performance after a test run. Analysing the graphs in a single and separate windows makes analysis work hectic and time-consuming.

To overcome this problem the LoadRunner Analysis Tool has an option to merge the graphs. Using this option you can merge different graphs and draw a conclusion of the test. LoadRunner Analysis Tool has 3 types of merging graph options which are:

  1. Overlay
  2. Correlate
  3. Tile

Most of the performance tester always confused with Overlay and Correlate option. After reading this blog you come to know the difference between the overlay and correlate graph option along with tile graph option.

How to merge the graphs in LoadRunner Analysis Tool?

Graph merging gives more meaningful information rather than analysing the graphs separately. Let’s see how graphs are merged. Before you open the graph merging option, ensure you have at least one graph opened already, which you wish to merge. The tool will assume you want to add another graph to the already opened graph. To open the merge graph window:

  • Either select the graph and right-click on it OR Go to ‘View’ in the main menu
  • Click on ‘Merge Graphs…’
LoadRunner - Overlay, Correlate & Tile Graphs - Merge Option

After clicking on ‘Merge Graphs…’ a pop-up will open with a list of graphs to be merged with:

The above figure shows the merging of Running Vuser graph with Hits per Second graph.

Select the type of merging by choosing the appropriate merge option

Analysis tool gives a default name to the newly formed merged graph. You can rename the graph by providing an appropriate name in ‘Title of merged graph’ section. Below figure shows an overlay merged graph of Running Vusers and Hits per Second:

LoadRunner - Overlay

What is an Overlay Graph?

Overlay option merges the contents of two graphs that share a common X-axis. The left Y-axis on the merged graph shows the current graph’s values. The right Y-axis shows the values of the graph that was merged. In the below snapshot:

  • Throughput is a current graph, indicated on the left Y-axis
  • Hits per second is a merged graph, indicated on the right Y’-axis
  • Elapsed Scenario Time is shared by both graphs on the X-axis
LoadRunner - Overlay Graph

There is no limit to the number of graphs that you can overlay. When you overlay two graphs, Y-axis for each graph is displayed separately to the right and left of the graph. When you overlay more than two graphs, Analysis displays a single Y-axis, scaling the different measurements accordingly. Importance of Overlay Graph:

  • It gives a single picture of all merged graph along with shared x-axis.
  • Easy to identify bottleneck time while using elapsed scenario time as X-axis
  • Multiple graphs can be added

Note: In an ideal scenario, if metrics are directly proportional then y-axis graph lines should follow each other. Else the opposite trend should be followed in case metrics are inversely proportional.

Example: During steady-state, Throughput and Hits per second graph follow each other while Errors per second and Average Response Time graph follow the opposite direction.

What is a Correlate Graph?

Correlate option plots the Y-axis of two graphs against each other. The current graph’s Y-axis becomes the X-axis of the merged graph. The Y-axis of the graph that was merged, becomes the merged graph’s Y-axis.In the below snapshot:

  • Throughput is a current graph, indicated on X-axis
  • Hits per second is a merged graph, indicated on Y-axis
LoadRunner - Overlay, Correlate & Tile Graphs

Importance of Correlate Graph:

  • Graphs are plotted against each other helps to identify bottleneck at a particular time.
  • Having different measurement of correlate option

Note: Linear line in forwarding direction indicates good results. Step-up, step-down and spike correlate graphs require investigation.

What is a Tile Graph?

Using Tile option you can view contents of two graphs that share a common x-axis in a tiled layout, one above the other. Y-axis is divided into sections while X-axis is shared by all the graphs. In the below snapshot:

  • Throughput is a current graph, indicated on the lower portion
  • Hits per second is a merged graph, indicated on the upper portion
  • Elapsed Scenario Time is shared by both graphs on X-axis
LoadRunner - Overlay, Correlate & Tile Graphs

Importance of Tile Graph:

  • It gives a single picture of all merged graph along with shared X-axis.
  • Easy to identify bottleneck time while using elapsed scenario time as X-axis

Note: In an ideal scenario, if metrics are directly proportional then graph lines should follow each other. Else the opposite trend should be followed in case metrics are inversely proportional.

Example: During steady state, Throughput and Hits per second graph follow each other while Errors per second and Average Response Time graph follow the opposite direction.


Leave a Reply

Your email address will not be published. Required fields are marked *