Case Study: ShareChat cuts Kafka costs 60% with WarpStream

Cost-Effective Logging at Scale ShareChat’s Journey to WarpStream

ShareChat, an India-based social media platform serving hundreds of millions of users, struggled with the cost and operational complexity of managing open-source Apache Kafka for their highly elastic machine learning logging workloads. Their challenges included an inability to efficiently auto-scale their stateful clusters and steep inter-availability zone networking fees that dominated their infrastructure costs.

By implementing WarpStream, a drop-in Apache Kafka replacement built on object storage, ShareChat achieved a fully auto-scaling, stateless architecture. WarpStream eliminated manual operations and inter-AZ fees by using zone-aware agents. The solution resulted in a 60% cost reduction compared to their previous multi-AZ Kafka infrastructure, while providing the performance required for their large-scale, batch-oriented data pipelines.

ShareChat

Shubham Dhal

Staff Software Engineer