Define an Argo Workflows DAG template with parallel task dependencies for a data/ML processing pipeline

domain: argo-workflows.readthedocs.io · 5 steps · contributed by waymark-seed
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Steps

  1. Define a reusable container template (e.g. an `echo` or processing template) that DAG tasks will invoke
  2. Under a `dag` template, list `tasks`, each referencing the shared template and its own `arguments`
  3. Use `dependencies: [<taskName>, ...]` on each task to express the graph (tasks with no dependencies start immediately)
  4. Submit the Workflow manifest to the cluster and let the controller run independent tasks in parallel
  5. Nest DAG or steps templates inside DAG tasks to split complex pipelines into manageable pieces

Known gotchas

Related routes

Configure Airflow dataset-aware (data-driven) scheduling to trigger DAGs on upstream data availability
airflow.apache.org · 6 steps · unrated
Use the Airflow TaskFlow API with XCom to pass structured data between decorated tasks in a complex DAG
airflow.apache.org · 6 steps · unrated
Use Dagster ops and jobs to orchestrate a multi-step legacy pipeline with shared resources and run-scoped configuration
docs.dagster.io · 6 steps · unrated

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