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Handling Digital Data Process

Enhanced existing digital marketing platform through cloud services


  • Handle and consolidate data coming from a variety of sources 
  • Implement microservices for various business functions. 
  • Automate the entire deployment process thereby reducing the time to market. 
  • Given that there were multiple services involved (microservices architecture), time to market was usually high due to the testing effort involved in multiple environments. 
  • Optimize the operational cost of the setup through better utilization of resources on AWS.


  • Implemented Lambda functions to handle data coming from multiple sources. 
  • Implemented microservices and deployed to ECS (Docker Containers) 
  • Modified the design to use Spot Instances instead of the on-demand EC2 instances for running one of their daily jobs. 
  • Improved the build and deployment pipeline through the use of Jenkins. 
  • Automated verification using Jasmine, Mocha, Karma.

Tools & Technologies

AWS, Jenkins, Github, Python, React, Node JS, Docker

Key benefits

  • Streamlined the data transformation process using a serverless architecture. 
  • Since the build and deployment process was automated, changes could be rolled out faster and without errors. 
  • Test automation ensured better coverage of test cases. 
  • Operational costs came down significantly through the use of Spot Instances. 
  • ECS also ensured that resource utilization was better.