Cloud Migration Case Study
At a large government agency SJ Technologies introduced Amazon Web Services (AWS) GovCloud as the platform for development. The ease with which the architecture, design, and software could be changed within the AWS cloud environment to meet the evolving requirements from the business users proved to be a demonstrable benefit of the team’s approach.
Developing software in the cloud as an alternative to creating a new government data center environment demonstrated immediate results. In the past, new projects began with the specification for and creation of a new data center hosting environment. Since these requirements were generally complex and costly, the added time could extend the development schedule by months. One of the major benefits of developing software in the cloud is: with the infrastructure automatically provided, work could begin immediately. In addition, early decisions made about infrastructure can prove to be constraining for the development team in terms of estimating ultimate needs about size and capacity. Since scalability is offered as an affordable option, the team did not have to concern themselves with worrying about size limits and performance loads.
An added benefit was that once the infrastructure requirements for the application were demonstrated in the AWS cloud, these tested requirements then became the basis for establishing the government data center hosting requirements for production. This benefit was important because it allowed the team, including the data center staff, to more precisely estimate current and future needs. This was the case since they could see what was actually used as opposed to merely fore-casting. This data allowed them to properly allocate funds without under or over estimating the amount required.
There were many benefits that resulted from developing this project in the cloud and many that are still being realized but here are some of the most important:
- Hardware costs for the development environment were avoided.
- Production environment could be largely replicated from working cloud environment.
- No need to forecast for capacity and performance since scaling and load balancing are dynamic.
- Development schedule was significantly improved.