Deploying Large-Scale Real-Time Predictions with Apache Kafka: A Playtika Case Study

cnvrg.io delivered a simple, and quick solution to Playtika’s unique ML production challenges. It reduced technical debt in Playtika’s workflow, and connected data scientists from engineering teams. cnvrg.io MLOps solutions, enabled Playtika’s engineering team to easily deploy, update and monitor ML in production to ensure peak performance, and reduced complex triggering and scheduling as data came in. Their data scientists are able to visualize results and business impact in real-time in a unified platform. With multiple deployment options, cnvrg.io offered a one click deployment solution which resulted in frictionless deployment solutions for every model in production. cnvrg.io enabled Playtika to instantly deploy with Kafka and easily integrated into their existing system. Playtika’s ML services perform better than ever, with native integration with Kubernetes and Apache Kafka allowing them to successfully handle any spike in incoming demand and predict and handle workloads and scale consistently and linearly by adding more pods.

Increased performance by 40%

Gained up to 50% increase in successful throughput

Reduced latency and error rates to zero