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Data Engineering

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Performance Testing Tool for Cognira PromoAI Application

Project Overview: In the retail industry, the data that comprises client data can take many forms, including product data, sales data, inventory data, … etc. For that specific reason, the Cognira PromoAI solution performance should meet this constant rising load & meet our client needs & expectations. As we are moving towards enhancing our system’s performance, the Cognira team would definitely ensure that adequate load & stress testing are performed on it solution before delivery. Therefore, the objective of this project is to help with the automation of performance testing: including Load & Stress testing the application.

Project Objectives:

1- Develop a user-friendly performance automated -testing application that covers the following:

  • Load Testing: test how the product performs under normal use
  • Stress Testing: test how the product performs under abnormal or extreme user
  • Define the upper limit of tha Cognira PromoAI App limit & detect load balancing defects (Page Load Issues, System lag, Timeouts, DataBase Failures .. etc)
  1. Analyze & Report KPIs as a Result of the performance testing response

  2. Create a Dashboard sharing those KPIs & generate representative graphs of the actual system’s performance

  3. Monitor the system’s performance in times of Delivery & help detect errors

  4. Help the QA Team detect eventual denials of service, slowdowns, security issues, and data corruption at an early stage – maximize profitability

During the project implementation period, the candidate will be asked to:

  • Participate to the daily tasks of the QA Team
  • Follow an Agile approach for testing
  • Communicate wisely with the API / DevSecOps / Data Engineering Team
  • Build the automated Performance Testing tool
  • Cooperate with the DE Team to prepare the load testing data
  • Cooperate with the API / DevOps Team to deploy the Performance Testing Environment & load data into it
  • Run the script & observe the system’s performance -Intercept the system’s errors & prepare KPIs as a response to the system’s behavior & translate those into representative graphs
  • Detect the system peak limit & share those with the QA Manager
  • Monitor the system & prevent any possible performance defects for future deliveries


Selenium, Python, BDD Framework (Behave/Cucumber) ,API Testing Framework , BlazeMeter / JMeter Git / Bitbucket ,Docker ,Jenkins

Potential Tools to Benchmark & Use:

The Grinder Gatling Tsung JMeter Locust

Date d’expiration: 04 décembre, 2023

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