Case Study: IMVU achieves scalable cloud-native analytics and 50% growth with Provectus

IMVU uses their new re-architected data platform for data streaming and analytics to generate faster critical insights on customer lifetime behavior at scale on AWS

IMVU, the world’s largest avatar-based social network, needed to modernize an aging on-premise data platform that was difficult to scale and maintain. With growing data volumes, a monolithic Hadoop setup, and limited support for real-time and advanced analytics, the team wanted better ways to analyze customer behavior and support machine learning use cases. Provectus partnered with IMVU to address these challenges, using AWS-based data platform modernization services.

Provectus re-architected IMVU’s data infrastructure for AWS by migrating Hadoop workloads to Amazon EMR, optimizing Hive/Spark jobs, mirroring Kafka streams to the cloud, and introducing tools such as Airflow, Presto, EKS, Terraform, and Ranger. The new cloud-native platform enabled faster analytics, near real-time insights, improved retention modeling, and better operational efficiency. The modernization also contributed to a 2x TCO optimization, processing 1 PB of data daily, and supported IMVU’s 50% growth during the Covid-19 pandemic.

IMVU