What was the first step that ran in the pipeline, and what ran after it?

In most orchestrated data pipelines, tasks are defined as nodes in a directed acyclic graph (DAG). The first step that runs is the one with no upstream dependencies—often a data ingestion or source extraction task. Once that task completes, the orchestrator evaluates downstream nodes whose upstream dependencies are satisfied. For example, in Airflow, the scheduler looks at the DAG definition and triggers the first operator. After that, the next operators that depend on the first one will be queued. The exact order can also be influenced by task priorities, concurrency limits, and resource availability. Understanding this flow is critical because it determines data freshness, error propagation, and resource utilization. If you see a step running before its declared dependencies, it usually indicates a mis‑configured DAG or a manual trigger that bypassed the normal scheduling logic.