Building highly reliable data pipelines at Datadog | Datadog

This post details Datadog's best practices for building highly reliable data pipelines, focusing on architectural design, fault tolerance, and monitoring. Key strategies include using isolated, short-lived clusters for Spark jobs, leveraging spot instances to enforce fault tolerance, and breaking down long jobs vertically and horizontally. The post also emphasizes the importance of comprehensive monitoring through tagged clusters and the Datadog Agent to detect failures early and ensure timely data delivery.