Data Analytics on AWS

Case Study Energy

A solar and renewable energy company uses Apex's Cloud solution to upgrade their platform to support IoT, faster response times, and query trends, resulting in reduced expenses and time to resolve issues.

SITUATION

Our client, a leading international energy products provider, was using a legacy technology platform which analyzed data from solar panels. The legacy platform was causing issues with missed SLA's, had low availability and high data center costs. Our client needed a platform that offered support for IoT, faster response times, and the ability to query trends over a larger historical data repository. Our client lacked the expertise in the legacy applications as a result of personnel turnover, which resulted in a frozen legacy code base that needed modernization.

SOLUTION

The client’s legacy application was Ruby-based on Linux Ubuntu. Our team proposed .NET with a new intuitive dashboard leveraging Amazon Redshift and Amazon ElastiCachefor Redis. The modernization included data ingress, queue readers and storage. After data processing, the analysis layer recorded and analyzed the data. Our team’s final deliverable utilized Elastic Load Balancer (ELB), Elastic Compute Cloud (EC2), Elastic Block Store (EBS), Relational Database Service (RDS) for PostgreSQL, Redshift, S3, ElastiCacheand Route 53.

90% Reduction in Time to Resolve

RESULT

The benefits of our solution included a new fleet dashboard powered by data with a real-time view of solar collectors globally. This solution reduced operating expenses and resulted a reduction average time to resolve solar panel issues from four hours to four minutes. It also allowed creation of an unlimited data store to enable historical trend analysis, framework for configuration, and systematic change management. The customer’s data can now be turned into actionable insights to support their business mission.