How do you design clustering systems with multi-stage pipeline orchestration?

Multi-stage clustering pipelines separate ingestion, feature engineering, clustering, and evaluation into orchestrated stages.

Large-scale clustering systems are built as DAGs (Directed Acyclic Graphs). Each stage is independently scalable: ingestion collects raw data, feature engineering transforms it, clustering computes groups, and evaluation validates results. Orchestrators like Airflow or Kubeflow manage dependencies and retries. This modular design improves maintainability and fault isolation.