OpenAI Batch API with Go: Offline Batching, Failure Replay, and Cost Boundaries
Short answer: if your workload is delay-tolerant, batchable, and replay-safe, move it from online calls to Batch API. The savings are real, but only if you design splitting, failure routing, and replay first. Many teams treat Batch API as a cheaper sync endpoint. That usually creates a replay mess instead of stable savings. A conservative rollout starts with cost boundaries and SLOs, then implements offline batching and controlled replay. ...