Case Study: iFood scales real‑time data and boosts developer velocity with Confluent

iFood Taps Confluent to Revolutionize Its Real-Time Data Flows and Support Their Growth in a Secure and Cost-Efficient Manner

iFood, a Brazilian meal-delivery company handling more than 60 million orders per month across 1,200+ cities, faced scaling limits because tightly coupled services and batch pipelines made troubleshooting slow and fragile. After struggling to self-manage Kafka on AWS MSK—incurring heavy operational overhead, security/authentication issues, and manual updates—iFood engaged Confluent and adopted Confluent Cloud (with ksqlDB and Schema Registry) to modernize its real-time data platform.

Confluent implemented a fully managed, cloud-native streaming platform that built pipelines between 2,000 microservices and to an AWS data lake, enabling event-driven processing and real-time order-per-second monitoring via ksqlDB. The Confluent solution delivered instant, cost-effective elastic scaling for 60M orders/month, reduced operational burden so engineers could focus on strategic work, lowered TCO, improved security and governance, and now powers about 700 applications across iFood.

iFood

Lucas Viecelli

Database Reliability Engineer