Apache Flink for Engineers: 5 Real-World Use Cases
Identify which production workloads are a good fit for Apache Flink, understand how Flink handles stateful stream processing, and confidently decide when to replace a batch job with a streaming pipeline
4 sections ยท 8 lessons
Course outline
What Makes Flink Different
- Stream processing vs. batch processing
- Flink's stateful processing model
Use Case 1 & 2: Fraud Detection and Real-Time ETL
- Real-time fraud detection
- Real-time ETL with CDC
Use Case 3 & 4: Analytics and Event-Driven Apps
- Real-time aggregation and alerting
- Event-driven application orchestration
Use Case 5: ML Feature Engineering
- Real-time feature computation for ML
- When to use Flink vs. keep the batch job