Case Study: Apna achieves scalable, real-time microservices and 2x faster time-to-market with Confluent Cloud

How Apna, India’s Largest Hiring Platform, Went from Monolith to Microservices with Confluent

Apna, India’s largest hiring platform connecting 30 million job seekers to 400,000 employers, was constrained by a monolithic backend that hit vertical scaling limits and slowed development. To adopt an event-driven microservices architecture without diverting engineering resources to manage Kafka, Apna selected Confluent and its managed Confluent Cloud Kafka service.

With Confluent Cloud, Apna migrated core services (job matching, search, application tracking, community feed, and a Kafka-powered data lakehouse) to real-time streams and leveraged Confluent’s pre-built connectors. The move delivered measurable impact: a 2x faster time to market (new solutions in ~3–3.5 months vs. twice that before), elastic scaling to support 30M users, 99.99% uptime, a 20 TB/month Kafka lakehouse workload, and a quadrupling of internal Confluent users—freeing developers to focus on new features like learning assessments. Confluent’s managed service and tooling were credited as critical to these results.

Apna

Suresh Khemka

Head of Platform Engineering and Infrastructure