Case Study: DNV GL achieves scalable machine learning deployment with Microsoft Corporation’s Azure Kubernetes Service

DNV GL scales up machine learning using Azure Kubernetes Service

DNV GL, the world’s largest classification society, needed a faster and more scalable way to deploy machine learning applications used to improve safety for ships and offshore structures. After its early ML success created deployment and management bottlenecks, the company turned to Microsoft Corporation and Azure services, including Azure Kubernetes Service, to support its growing internal analytics platform, ML Factory.

Microsoft Corporation implemented ML Factory on Azure Kubernetes Service with containerized microservices, Azure DevOps, Azure Monitor, and related Azure tools to automate deployment, scaling, security, and monitoring. The result was a dramatic improvement in efficiency: deployment time dropped from one to two weeks to just minutes, resource usage became more elastic and cost-effective, and DNV GL gained a sustainable platform for scaling its machine learning portfolio without downtime.

DNV GL

Wlodzimierz Borkowski

Site Reliability Engineer