Pipelyd

Pipelyd is a fictional software framework designed to demonstrate principles of data pipeline orchestration. It envisions a modular, scalable system for building, executing, and monitoring data pipelines across diverse environments.

Architecture: core engine, plugin connectors, task graph, scheduler, and execution backends. It supports batch and streaming tasks; tasks declare inputs, outputs, and dependencies; the scheduler resolves DAGs and assigns resources.

Pipeline language and definitions: pipelines are described in YAML-like syntax; supports templates, parameterization, versioning. Connectors provide availability to databases, file stores, queues, cloud services; adapters ensure portability.

Execution and observability: offers retries, idempotence, fault tolerance; event-driven triggers; integrated logging, metrics, and tracing; optional dashboards and external monitoring integration.

Use cases: ETL and data integration, feature pipelines for machine learning, real-time analytics; typical deployments include on-prem, cloud, or hybrid setups with container orchestration.

History and reception: conceived in academic and industry discussions as a teaching example; not a single standard; influenced by existing tools but emphasizes portability and reproducibility.

See also: Apache Airflow, Dagster, Prefect; related concepts include data orchestration, workflow management, and data pipeline engineering.