In the last couple of years we have experienced unprecedented advancements in the area of artificial intelligence and machine learning. Real-time agents assisting customers, business critical decisions powered by the input of ML models, etc..

While MLOps helps describe the processes and principles for productionizing machine learning models, it is paramount for these models and the surrounding infrastructures to remain operational. In recent years, feature stores have established themselves as a keystone infrastructure for the operational layers in those modern ML systems, participating in the prevention of downtime or loss of data that can result in significant financial and reputational losses for organizations.

In this webinar we will explore the High Availability capabilities of Hopsworks. We will demonstrate how the resiliency of individual components and a multi-region architecture catered for applications with the highest availability and redundancy requirements creates a fundamentally safer infrastructure for machine learning at large scale, preventing operational risks.