E-commerce Analytics Dashboard
Real-time Event Streaming
Real-time pipeline aggregating millions of events to provide instant insights into conversion metrics and operational bottlenecks.
The Problem
Traditional analytics dashboards were 24 hours behind. The business needed real-time insights into cart abandonment and inventory velocity during flash sales.
Architecture
Designed a high-throughput ingest pipeline using Go microservices publishing to Apache Kafka. ClickHouse consumes from Kafka using Materialized Views for real-time aggregation.
Decision Log
"Chose ClickHouse over PostgreSQL/Elasticsearch for its unparalleled OLAP performance on time-series event data. Go was selected for the ingest layer due to its efficient concurrency model."
Performance
Optimization
Implemented a WebSocket layer in Node.js to push live dashboard updates to the Next.js frontend, avoiding expensive long-polling.
Scaling Logic
Kafka partitions allow linear scaling of the Go ingest consumers. ClickHouse cluster scales horizontally for read queries.
Challenges
Exactly-once processing semantics. Solved by implementing deduplication logic in the ClickHouse Materialized Views using ReplacingMergeTree engines.
Final Impact
Provided the operations team with a live dashboard during Black Friday, allowing them to dynamically adjust pricing and inventory in real-time, boosting revenue by 15%.