Performance analysis of SAP MII with LoadRunner (SAP ME/OEE/Custom PODs)
SAP MII (Manufacturing Integration and Intelligence) application are combination of Transactions (Business Logic Services) and query templates connected to multiple sources with user interface (commonly known as POD) for given production plant. Over period of time, the performance issues creep in, resulting in a transaction getting executed over multiple seconds due to peak load or poorly designed transactions.
The performance evaluation for SAP MII is an important goal in systems to predict the peak behavior of system, as at given point all the shop floor activities are being managed by SAP MII and any failure will lead to down-time or work-stoppage at production floor.
This article describes the steps to perform the performance analysis of SAP MII centric landscape using HPE LoadRunner ( Generator, Controller, Analysis)
The process for performing the load testing of SAP MII applications (especially Production Operator Dashboard) which are centric for human machine interface in Plant environment. It has following 5 steps:
- Plan: Planning the scenarios is based on certain parameters and it is based on number of Operators, lines, workstation in given production environment.
- Number of concurrent users: based on POD users in given line
- Create Vuser scripts: The MII transactions (BLS) are integrated to Load Generator on this steps. The individual calls are integrated on this step. This creates automated scripts. Both BLS/Xqcute query can be inserted into Vuser scripts. The URL must contain the username & password for SAP MII.
- Defining the scenarios: The transaction (BLS) are combined together to form the scenarios which are executed in group. In the Load Runner, prepare the scenarios with number of parallel connections to simulate the plant environment.
- Run the scenarios: The real performance execution is performed at this step.
- Analyze: Analyzing the response time for each transactions (MII) to look into response times and have clarity on predictable behavior in production environment.