How do you know if a truck needs maintenance before it breaks down? Or if breaks down anywhere in the country, how do you know the exact location to send help to fix them right where they are, or bring them to the closest maintenance shop? And how do you this for your full fleet? As part of the Connected Fleet, Penske collects IoT data including the odometer, location, and engine codes of all the trucks in real time and ingests into their data lake to derive real-time analytics. Penske identifies when a truck is going to break down before it does and performs maintenance to reduce the downtime and keep the uptime SLO. The data ingestion platform leverages Spring Boot, SCDF, Kafka Streams, and fit for purpose Databases like Postgres, MySQL, Gemfire, and Greenplum. Once data is available, machine learning is applied to create models for performing maintenance on trucks in advance. You’ll learn how Penske has leveraged Spring technologies and Data solutions to scale the solution on VMware Tanzu.
Sr. Platfrom Architect, VMware
Sr. Platform Manager, Penske
Track: Architecture