design-batch-architecture

To process multiple items in parallel with deterministic state tracking, you define a concrete batch state schema and isolate workers per item. This ensures resumable execution and a clean merge workflow to consolidate outputs into a canonical report.

You need a batch processing architecture when handling 10 or more items per operation. It dispatches parallel headless workers to produce isolated outputs and uses a deterministic merge process to consolidate those results into a canonical report.

Design a merge pipeline for parallel batch processing by defining explicit merge semantics and enforcing idempotent merges. This consolidates parallel worker outputs into a canonical report while using lock mechanisms to prevent conflicts.

The best way to handle worker failures during parallel batch processing is to enforce explicit safety controls and clear failure handling within the batch state schema. This maintains per-item isolation and supports resumable state tracking.

Yes, you can validate batch inputs and worker prompts before executing a parallel processing run by configuring a dry-run. This verifies the state schema, merge logic, and safety controls prior to dispatching the actual workers.

A batch merge workflow produces inconsistent state across parallel workers when it lacks deterministic state tracking and explicit lock mechanisms. Defining a concrete state schema and enforcing idempotent merges resolves these conflicts.