Case Study: Vandebron achieves rapid real-time renewable energy forecasting with D2iQ Mesosphere DC/OS Platform

Vandebron Leverages Big Data to Build Their Renewable Energy Forecasting Pipeline

Vandebron, a renewable energy marketplace in the Netherlands, needed to build a secure, real-time machine learning pipeline to forecast wind energy production 24 hours ahead. To support this data-intensive challenge, Vandebron worked with D2iQ and its Mesosphere DC/OS Platform to create a high-performance distributed architecture for ingesting and processing gigabytes of data every six hours.

D2iQ helped Vandebron implement a production-ready SMACK-based stack with tools like Apache NiFi, Jupyter, Kafka, Spark, and Cassandra across separate test, acceptance, production, and monitoring clusters. The result was rapid deployment in just three months, data processing in 3–4 minutes, and much faster service rollouts—shrinking some deployments from weeks to hours and backend releases from about an hour to 10 minutes.

Vandebron

Giuseppe Procaccianti

Head of Big Data