How to calculate server processing time between two UITs

1) Find a specific process instance in the report on the processes tab of /designer and click the link to view the legacy process dashboard
2) Click "Process Details" in the top left corner.
3) Open the Process Nodes tab.

This shows the start / end times for each node that is executed in a process instance.

Another option would be to save the value of now() into process variables after the first user input task is completed and then again before the 2nd is activated and then compare the values.

I know that options, it is manual and process by process.. Is there any automated way calculate to measure average server processing time between two UI node.

If you use the 2nd option, you can create a portal report that calculates the duration for each process instance, then use aggregation to display the average.

Well.. we tried that option as well.. but it does not provide accurate numbers because process have several UI tasks.. portal report and metrics was not sufficient for us to measure server processing time. Any other suggestions?

If you just need to see the processing time, you can navigate to the dashboard of the process in question, and go to Process Details > Process Nodes to see the time each node took to complete.

Its manual activity and we need to know all nodes in-between and manually add up Process Nodes times of all node times to arrive at complete server time. I am looking for the same to do automatically rather than manual for all instances of process. model.. If required to perform aggregation and identify slow executing node as well..

If you have exhausted the options available in portal, you could consider creating a CDT that has a field for each node, update that specific field when the node completes, and write the cdt to a database at the end of the process or before the last UI task.
If the process is likely to change drastically or has a very large number of nodes this becomes less efficient. but would provide the metrics you are looking for and make aggregation very simple.