Case Study: J.B. Hunt achieves scalable, data-driven load-matching and new revenue with Microsoft Azure

The fast lane to digital disruption: J.B. Hunt builds load-matching cloud service for shippers and carriers

J.B. Hunt Transport, a 50‑year leader in North American trucking and logistics, faced digital disruption as shippers demanded faster, data‑driven delivery and carriers needed to reduce idle time. To scale its J.B. Hunt 360 platform from an on‑premises, mainframe‑backed architecture to support tens of thousands of third‑party carriers and enable real‑time load matching, the company needed a cloud solution that would handle high volume, elasticity, and advanced analytics.

J.B. Hunt migrated core services to Microsoft Azure—using Virtual Machine Scale Sets, Azure App Service, Azure Kubernetes Service (with Kubernetes), and Azure Machine Learning—integrating Jenkins and Team Foundation Server for deployments. The result is a scalable marketplace that matches loads to the right trucks using historical and real‑time data (fuel, weather, road conditions), creates new revenue and business opportunities, improves vehicle utilization (especially for small carriers), and positions the company as a data‑driven logistics provider.

J.B. Hunt

Jay Davidson

Vice President of Engineering and Technology