Case Study: Derivco achieves near-real-time personalized recommendations at scale with Dapr from Cloud Native Computing Foundation

Performing near-real-time personalized recommendations at scale with Dapr

Derivco, a global tech company in the iGaming industry, faced the challenge of providing near-real-time personalized recommendations to its players. They wanted to move beyond slow batch processing to a system that could leverage AI/ML to instantly identify and act on opportunities to improve an individual player's experience before they were lost due to poor engagement.

To achieve this, Derivco implemented an event-driven system using the Cloud Native Computing Foundation's Dapr application runtime. The solution utilized Dapr's Pub/Sub, State Management, and Virtual Actors to handle over 320 million events daily. This allowed Derivco to deploy a highly scalable production system in under six months, eliminiate environmental issues for developers, and save immeasurable development time by removing the need for boilerplate infrastructure code.

Derivco