Performance Testing helps a Private Bank to identify the Bottlenecks on their platform




Mobile Testing

Client Overview

A private bank based in Myanmar, is focused on enhancing its core banking and eChannel solutions as a key component of its banking transformation initiative.

Problem Statement

  • The client wanted to analyze the load-bearing capacity and performance of their application under concurrent user load.
  • The engagement's scope involved measuring the end-to-end response time of the web application while also focusing on performance optimization on the server side.

Tech Stack

Solution Approach

  • The testing methodology used for efficient project execution included planning, design, execution and analysis, test purpose, and reporting.
  • Our team planned, understood the test requirements, and reviewed the system architecture for a clear insight into the application.
  • Based on the analysis, our team finalized performance testing and monitoring tools to be used.
  • Tested both their web and mobile banking platforms using distributed load testing.
  • The execution stage consisted of three cycles :
    • Cycle-1 consisted of baseline, load, and volume tests to verify system connectivity and availability.
    • Cycle-2 involved the application of KPI, SLA, and final testing. Before initiating cycle-2, it was ensured that the baseline defects were fixed.
    • Cycle-3 included repeating the steps of the cycle 2, after resolving the bugs that were encountered.


Thorough evaluations and strategic advice played a crucial role in improving the overall efficiency and growth capacity of the system.

Discovering the underlying causes of the problems would lead to significantly improving the user experience.

Capacity of website would be benchmarked to determine the bottleneck.

Assessing the application's capability to efficiently handle a growing number of users without compromising performance.

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Identified issues related to application availability and long-term performance, such as memory leakage and garbage collection.
Added think time and delay of 5 to 10 seconds after each iteration.
Assessed the response time for various time sensitive transactions and business processes.

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