국내 No.1 에너지 IT기업 ‘해줌’의 컨플루언트 클라우드 도입 스토리 | 알아보고 등록하기

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

Tracking the number of orders per second using ksqlDB is very crucial to us, so we can monitor the use and health of the platform in real time.

Lucas Viecelli, | Database Reliability Engineer
iFood

Challenge

Inability to scale real-time operations alongside business growth due to heavy operational overhead and lack of internal AWS MSK expertise; this resulted in failure to flag production issues in a timely and cost-effective manner.

Solution

Confluent Cloud provides a truly cloud-native and complete data streaming platform for event-driven microservices and streaming pipeline to a data lake on AWS to monitor the number of orders and track deliveries on iFood’s platform in real time.

Results

  • Instantly and cost-effectively scale real-time data availability with growing business needs
  • Improved developer velocity and productivity by reallocating engineering resources to more strategic projects
  • Lower TCO to seamlessly run mission-critical use cases at scale securely and reliably
ifood image 2

By leveraging Confluent’s fully managed data streaming platform, iFood built streaming data pipelines, which addressed the challenge of sending and processing real-time data prior to sending it to the data lake.

Facing lots of issues with managing Kafka, iFood’s teams opted for Confluent Cloud, which provided significant ops burden reduction from its serverless offering and complete feature set, including security and Stream Governance.

Today, Confluent tracks and monitors all the phases that a piece of data goes through within iFood’s system, improving the team’s control and diagnostic capacity in relation to real-time data flows.

더 많은 고객 사례

8x8

8x8은 Confluent로 실시간 컨택 센터 분석을 강화합니다.

ifood logo (1)

iFood, 실시간 데이터 흐름을 혁신하고 안전하고 비용 효율적인 방식으로 성장을 지원하기 위해 Confluent 선택

MPL Logo

MPL Enhances Trust and Security of the Platform with Real-Time Data Streaming from Confluent