Choosing the Right Conceptual Engine: Orchestration Models Beyond Process Sequencing
Why This Topic Matters Now Workflow orchestration has become a standard tool for teams managing multi-step processes, from CI/CD pipelines to data engineering workflows. Yet many teams default to the simplest conceptual model: a directed acyclic graph (DAG) where every task runs in a strict sequence, often with branches and joins. That model works fine for batch processing with predictable steps, but it breaks down when processes need to react to external events, handle partial failures gracefully, or involve long-running human approvals. The cost of choosing the wrong conceptual engine is hidden at first—it shows up as brittle error handling, endless retry logic, and workflows that are impossible to debug when something goes wrong mid-step.