Using the Message Batches API

What actually makes a request batch-shaped

The Batch API isn't a faster or cheaper version of a real-time request in general — it's a different delivery model, built for submitting a large collection of independent requests together and collecting results once they're ready rather than waiting on each one synchronously. The requests inside a batch don't need to be identical, only independent of each other: nothing in one request's outcome should determine what another request in the same batch needs to contain, since they're not guaranteed to complete in any particular order relative to each other.

Building the request set

Each item in a batch carries its own unique identifier alongside its own request parameters, and that identifier is what ties a specific result back to the specific input it came from once results start arriving — results are not guaranteed to come back in submission order, so code that assumes result order matches submission order will silently mismatch inputs and outputs the first time the batch doesn't happen to complete in that order. Treat the identifier, not position, as the only reliable way to reassociate a result with its request.

Polling versus a completion signal

Once submitted, a batch runs asynchronously, and your code needs a way to find out when it's done — either polling the batch's status on an interval or, where supported, reacting to a completion notification instead. Polling too aggressively adds load for no benefit, since a batch that typically completes over a longer horizon doesn't need to be checked every few seconds; polling too infrequently just adds unnecessary latency to when you actually notice completion. Match your polling interval to the batch's realistic completion horizon rather than defaulting to whatever felt reasonable for a synchronous request.

Partial failures inside a batch

A batch can complete with most requests succeeding and a handful failing individually — an individual request's own error doesn't need to take down the whole batch, and your result-handling code needs to expect that mixed outcome rather than assuming a completed batch means every request inside it succeeded. Iterate through results checking each one's own status rather than assuming batch completion implies uniform success, and route failed individual requests back through your normal error-handling path rather than a separate one built only for batch failures.

What to do with results once they're ready

Batch results are retained for a limited window after completion, not indefinitely — build your retrieval and storage step as part of the same pipeline that submitted the batch, rather than as a task to get to eventually, since results genuinely age out if nothing retrieves and stores them in time. This matters more than it sounds: a batch pipeline that reliably submits and completes but has no reliable retrieval step loses results it already paid for.

Testing a batch pipeline before you trust it at volume

Submitting a genuinely large first batch straight into production is a worse way to find problems in your submission and retrieval code than testing with a small one first — a malformed request buried in position four thousand of a large batch is much harder to notice and debug than the same mistake in a batch of five. Validate the full round trip end to end — submission, polling or notification, retrieval, and correctly reassociating every result with its request by id — at small scale before trusting the same pipeline with real volume.

Deciding whether a workload belongs here at all

Not every high-volume workload should move to batch just because volume is high — the requirement is genuine asynchrony, where nothing downstream is blocked waiting on any individual result. See the batch vs realtime calculator for whether your specific volume and deadline actually clear the bar where the discount is worth the added pipeline complexity, and the Message Batches API, in full for the platform availability and limits that apply before you commit to building against it.