Automated Orchestration with Checkpoints

Overview

Coordinate end-to-end analytical pipelines with checkpoint/resume capabilities and activity-based depth adjustment. The core principle: every stage that can fail must be resumable, and every pipeline must adapt its depth to the data it encounters.

When to Use

• Pipeline processes multiple stages sequentially and failures lose hours of work
• Large data corpus requires chunked processing with rate-limit awareness
• Analysis depth should scale with data volume (shallow scan vs. deep dive)
• Long-running jobs need graceful interruption and restart
• Multiple data sources must be combined across stages with partial-failure tolerance

When NOT to use:

• Single-shot scripts under 5 minutes with no intermediate state
• Pipelines where full re-execution is cheap and acceptable
• Real-time streaming (use event-driven patterns instead)