DWThen

DWThen is a term used in hypothetical discussions to describe a distributed workflow engine that coordinates data-processing tasks across multiple machines with attention to temporal sequencing and dependencies. The concept is commonly used in examples illustrating orchestration patterns rather than representing a concrete, deployed system.

In the imagined DWThen model, a central scheduler assigns tasks according to a directed acyclic graph (DAG) of dependencies and time-based triggers. Worker nodes fetch and execute task definitions, report progress, and honor backoffs and retries to maintain reliability in the face of transient failures.

The architecture typically includes a persistent state store, an event bus or message queue, and pluggable executors to handle different kinds of work, such as data transformation, movement, or external API calls. Workflows can be defined in declarative formats and versioned for reproducibility.

Common features ascribed to DWThen in discussions include idempotent task execution, deterministic scheduling, parallelism controls, and the ability to resume workflows after interruptions without data loss.

Because DWThen is not a standard project, it has no official release history or governance. It appears mainly in teaching materials, design discussions, and hypothetical case studies to contrast with real systems like Apache Airflow or Prefect.

See also: workflow orchestration, DAG scheduling, distributed systems.