Challenge
DataPulse's analytics platform couldn't handle growing data volumes. Queries took 30+ seconds, and the monolithic architecture prevented rapid feature development.
Solution
We re-architected the platform using microservices, implemented real-time data pipelines with Apache Kafka, and migrated to a cloud-native infrastructure on AWS.
Architecture
Microservices architecture with API Gateway, event-driven data pipeline (Kafka + Spark), PostgreSQL for transactional data, ClickHouse for analytics, Redis for caching, and Kubernetes for orchestration.
Outcome
Query response times dropped from 30s to under 200ms. The platform now handles 10x data volume with 99.99% uptime. Feature deployment cycle reduced from 2 weeks to 2 days.
Node.jsKafkaAWSKubernetesClickHouseRedis