Free Resource - How to Process 1 Billion Events Per Day
A technical case study from 10+ years building enterprise-scale data platforms. Learn the architecture patterns and technology choices that enable billion-event processing.
What You'll Learn
This case study reveals the architecture patterns, technology choices, and optimization strategies used to build data platforms processing over 1 billion events per day.
Inside the Case Study
- Architecture Patterns
- Event streaming design, data lake architecture, real-time processing patterns, and horizontal scaling strategies.
- Technology Stack
- Kafka, BigQuery, Kubernetes, DBT, and Terraform. Learn why each technology was chosen and how they work together.
- Performance Optimization
- Latency reduction techniques, cost optimization strategies, and monitoring approaches for billion-event scale.
- Lessons Learned
- Real-world challenges, failure patterns to avoid, and architectural decisions that enabled scaling from millions to billions of events.
About the Author
Abdelkader Bekhti has 10+ years of experience building enterprise-scale data platforms for luxury brands and financial institutions. He's architected systems processing over 1 billion events per day and currently works with select growth companies globally.