Case Study: Utopus Insights reduces data processing time from weeks to hours with Amazon Web Services

Utopus Reduced Data Processing Time from Weeks to Hours by Going Serverless on AWS

Utopus Insights, a renewable energy analytics company, was struggling to keep up with rapidly growing data volumes and on-premises processing limits. To scale its forecasting and ML workloads, it worked with Amazon Web Services and adopted serverless and cloud services, including AWS Lambda, Amazon Kinesis Data Streams, Amazon S3, AWS Fargate, Amazon EKS, Amazon EC2, and Amazon EC2 Auto Scaling.

With Amazon Web Services, Utopus Insights moved its data processing and scoring pipelines to the cloud, enabling it to stream about 7 TB of data daily and process more than 200 billion signals each day. The result was dramatic: data that once took 2 weeks to process on premises can now be processed in under 2 hours, while its data lake grew to 266 TB and its systems can scale to support over 50,000 processing unit cores.

Utopus Insights

Ziad Rida

Technical Director of Architecture