Case Study

Modernizing a Monster Monolith Application One Feature at a Time

Our client, a large multinational consulting organization, was looking to modernize their client staffing management and estimation application without any downtime or changes in user experience. They were running into scalability issues as the firm grew and needed to use the power of the cloud to help them scale.

The process of adding new features was slow, complex, and detrimental to the growth of their business. They needed to modernize the way they operated but didn’t want to change the user functionality of the client or take a big bang approach to migration.

From Monolith to Microservices Without Any Downtime

Our senior consulting team provided due diligence on our client’s scaling challenges and recommended migrating the monolith application to a new cloud-based AWS microservices and serverless solution.

Due to the agile methodology in which we implemented the changes, their migration to the cloud was gradual and completely invisible to the end-users with zero downtime. New changes were implemented and tested incrementally, which allowed them to migrate to the cloud safely and successfully.

Accelerating Development of New Financial Models

By migrating the monolith application to the cloud, we enabled our client to introduce new complex financial models that previously weren’t possible with their legacy applications.

Now, users of the application can create new data and process-intensive financial models in seconds,  regardless of the complexity and amount of data that needs to be processed. This enabled our client to respond to competition quickly and flexibly without any IT involvement.

Agile and Up to Date

The 100% cloud-based solution enabled our client to access additional features to power their software, as well as give them a pathway for easier development.  We utilized serverless compute functionality of Lambda, and Amazon’s relational database Aurora to power the application.

With our help, they are now able to make feature updates on a consistent bi-weekly schedule, enabling them to roll-out smaller features and fixes, resulting in a stable environment and growing feature set.