IMVU's Transformation: Leveraging AWS for Advanced Analytics and Machine Learning

IMVU, the world’s largest avatar-based social network, was facing challenges with its aging on-premise data platform. The company wanted to enhance and re-architect their platform to support advanced analytics and Machine Learning use cases. However, with an exponentially growing data volume and a monolithic Hadoop architecture, the IMVU team was struggling to efficiently utilize user-generated data. The existing infrastructure limited innovation and capacity for advanced analytics. IMVU’s analysts lacked the tools to rapidly generate business-critical reports on customer in-game behavior at scale. They were working with historical data in batches, which resulted in late reports, inaccurate assumptions about customer in-game purchases, slower sales, and loss of profit. The analytics team also lacked a test environment to efficiently check analytics assumptions. The platform was powered by a 90-node on-premise Hadoop cluster, which was not cost-efficient and resulted in high costs and low efficiency.

IMVU is the world’s largest avatar-based social network with over 7 million monthly users. The platform allows users to customize their avatars, chat with friends, shop, hang out at cool parties, and earn real money by creating virtual products. IMVU was one of the pioneers and early adopters of Apache Hadoop, taking advantage of Big Data technologies before they became mainstream. Despite maintaining deep internal expertise, the company was facing challenges in supporting and upgrading their 90-node Hadoop cluster and in-house built tooling. The company sought to modernize their platform’s data architecture by introducing CI/CD, Infrastructure as Code (IaC), and other best practices.