Pipeline catch-up and recovery

In the world of data engineering, failure is not a question of if but when. Data pipeline failures are inevitable, regardless of whether they are caused by server outages, network problems, or code bugs. The ability to recover from these failures is what differentiates a well-designed pipeline from a fragile one. Understanding the types of failures that can occur and their potential impact on your pipeline is the first step in designing a resilient system.

Through a combination of redundancy, fault tolerance, and quick recovery mechanisms, data pipelines achieve resilience. Redundancy is the presence of backup systems in the event of a system failure. Fault tolerance is the process of designing a pipeline to continue operating, albeit at a reduced capacity, even if some components fail. Quick recovery mechanisms, on the other hand, ensure that the system can resume full operation as quickly as possible following a failure.

When a data pipeline fails...