In the energy industry, Amazon EKS is utilized to run scalable and secure platforms for operational and analytical applications that support grid operations, asset management, field services, and real-time energy data processing. The main use case for Amazon EKS is to build a unified, cloud-native platform where mission-critical applications can run with high availability, real-time data processing, and secure integration with both cloud and on-premises energy systems.
Energy companies collect massive amounts of data from smart meters, grid sensors, SCADA and OT systems, and renewable energy assets including solar farms and wind turbines. Amazon EKS is ideal for deploying streamlined pipelines such as Kafka and Spark. Amazon EKS is used to containerize and modernize systems to manage on-premises-to-managed Kubernetes environments with improved agility and CI/CD capabilities. A specific application running on Amazon EKS is real-time grid monitoring for anomaly detection. Operations teams need high-frequency telemetry from smart meters, line sensors, transformer health monitors, and substation equipment to quickly detect anomalies such as voltage dips or transformer overheating. The data ingestion layer consists of a Kafka cluster deployed on Amazon EKS that receives streams of grid sensor data at high throughput. Flink or Spark streaming applications run on Amazon EKS for real-time processing to compute rolling averages, identify early signs of asset failures, and perform anomaly scoring. Multiple microservices run for outage detection, asset health scoring, and notifications to field engineers. Additionally, a lightweight API layer runs on Amazon EKS that exposes real-time grid status and dashboards for operations. The front-end application UI layer is also containerized and deployed on Amazon EKS, which encapsulates this use case.
This workflow runs effectively on Amazon EKS.