Summary
Designing a robust data pipeline is a forward-looking task. While we cannot predict all possible failures, we can certainly prepare for them by implementing sound architectural principles such as redundancy and fault tolerance. A robust ETL pipeline is not just about moving data from point A to point B efficiently; it’s also about ensuring that the pipeline can recover from failures and ensure data integrity. Effective checkpointing and logging practices play a crucial role in this regard.
Logging serves as the eyes and ears of a data engineer. It provides real-time visibility into the operations of a pipeline, allowing for performance tracking and speedy troubleshooting of issues. The key to effective logging is to provide enough information to understand the what, when, and why of any event or error.
Modularity simplifies code maintenance, enhances readability, and allows for scalable design. It also facilitates code reuse—a module designed for a specific...
