Case Study·

Enabling the world’s largest home ownership network to be more digitally agile

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Engineering Amazon Web Services (AWS) products to help Move Inc. continuously innovate and add value to it real estate flagship products.

About the Client

Move, Inc. is a real estate listing company based in Santa Clara, California. The company operates the Move Network of real estate websites, the largest of which is Move has a longstanding partnership with the National Association of Realtors, the real estate industry’s largest trade association, for operating

Business Challenge

The client has many front facing applications to connect home buyers and sellers. One of the key applications is ‘Find a Realtor’. Find a Realtor helps the home buyer search and identify a real estate agent within their desired area. During the development and integration phase, the developers wanted to get early feedback on an application and quick quality deployments on test and further-up environments. Another problem was with automated deployments of the containerized application—they needed to be deployed in a more robust manner so that real application does not face downtime. Failure analysis and the maintainability of the application is critical.


Brillio’s solution established a microservices based system utilizing cloud services and tools that enable DevOps support for the front-end application, while also seamlessly integrating various web services and data aggregation. This requires setting-up a Jenkins pipeline for analyzing, verifying and building code using SonarQube, es-lint, containerization of application with integration testing so that the end product is fully verified before deploying to further-up environments. Our solution helps reduce the application’s dependency on multiple web services, minimizing downtime and ease of maintenance as well as helping the team to provide improved quality of application development as it minimizes infrastructure issues.

Key considerations:

  • Setting up a Jenkins job to trigger the code analysis using SonarQube and es-lint on every code push
  • Automating the process of build deployment in the test environment after every update in the codebase
  • Approval based process for build deployment in production environment
  • Use of cloudformation scripts to deploy the application on ECS cluster service using blue-green deployment strategy to avoid any impact on real time availability
  • Use of Application Load Balancers on the top of ECS cluster service to manage auto-scaling of applications
  • Application logging and monitoring to identify the performance and potential issues
  • Setting up a pager duty with Splunk alerts to notify about any production issues

AWS Services Used

  • AWS Cloud Formation Templates
  • AWS Lambda
  • AWS Cloud Watch
  • AWS EC2
  • SQS
  • SNS
  • ECS Cluster

Third party Solutions Used

  • Jenkins
  • Splunk
  • Github
  • NewRelic
  • Es-lint
  • Gradle

Benefits and Business Impact

Significant reduction of application downtime and improved stability was achieved. The solution ensured uniformity of data across various sections of the application. There were significant cost and time savings as a result of avoiding production bugs and issues that previously consumed the team’s time. Finally, the solution will also reduce time spent by developers trying to identify the root cause of issues.This architecture enables the easy expansion of the system if any new services are to be added in the future.

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