This intensive hands-on workshop guides participants through building a complete production-grade streaming pipeline from scratch, using patterns proven at AstraZeneca and refined through teaching 50,000+ engineers at Data Mastery Lab.

THE CHALLENGE:
Organizations struggle to move from batch to real-time processing. Most streaming tutorials demonstrate "hello world" examples that collapse under production load. This workshop addresses the gap with enterprise-tested patterns.

WHAT PARTICIPANTS BUILD:
Using Apache Kafka, Spark Structured Streaming, and Docker, participants construct an end-to-end solution including:

• Multi-source data ingestion (APIs, databases, files)
• Stream processing with exactly-once semantics
• State management and windowed aggregations
• Writing to multiple sinks (Cassandra, Elasticsearch, data lakes)
• Production monitoring and alerting

MEASURABLE OUTCOMES:
Participants leave with:

• Working code repository (ready for production adaptation)
• Reference architecture diagrams
• Checklist for streaming project evaluation
• Before/after performance benchmarks from real implementations

STEP-BY-STEP STRUCTURE:
Morning: Architecture foundations, Kafka setup, producer/consumer patterns
Afternoon: Spark Streaming transformations, state management, deployment with CI/CD

This curriculum has achieved 4.8+ ratings across 50,000 students, with documented success stories of engineers deploying streaming systems within weeks of completing the training.