Why Orchestration Can't Validate Business Rules

Orchestration Limitations

Orchestration tools are good at running Task B after Task A. None of them can answer whether Task B should run at all, given what today's data and today's rules actually look like.

What Orchestration Does

Orchestrators excel at "run Task B after Task A completes." They manage dependencies, retries, scheduling. But they can't answer "should we run Task B given the current state of the data?" This is the key distinction between orchestration and decision logic.

# Orchestration defines the sequence
@dag
def customer_pipeline():
    raw = extract_customers()
    clean = clean_data(raw)
    enrich = add_segments(clean)
    load = write_to_warehouse(enrich)

This runs every time on schedule. It doesn't check: Is this data still valid? Has the segmentation logic changed? Should test customers be excluded today?

What's Missing

Decision logic that validates whether a task should execute, not just when. Questions like:

Has the upstream data schema changed in a breaking way?

Is this task operating on deprecated data?

Do current business rules allow this transformation?

Example Failure

Your pipeline classifies data quality for incoming records. The business changes the quality scoring rules to require additional validation checks. The orchestrator keeps running the old classification logic because it doesn't know the rule changed. The pipeline completes successfully but produces incorrect quality scores. The underlying issue is that business logic is embedded in SQL rather than being queryable context.

What's Needed

A layer between orchestration and execution that validates current context before running tasks. The orchestrator schedules. The dynamic logic layer decides.