Questions
3 of 4
1When would you use the Batches API instead of regular Messages API calls? — expected answer: async processing of large volumes, 50% cost reduction, non-time-sensitive workloads like bulk evaluation or dataset generation
2What's the max batch size and how do you retrieve results? — expected answer: results come back via a results_url on the batch object; you poll processing_status until it's done
3What statuses can a batch request have? — succeeded, errored, canceled, expired, and in_progress
4Is the Batches API eligible for Zero Data Retention? — No — batch processing requires 29-day retention for async storage, so it's not ZDR-eligible
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03 / 04

What statuses can a batch request have? — succeeded, errored, canceled, expired, and in_progress

Difficulty: 5/10
batch processing, status handling, error handling

Batch requests progress through statuses: in_progress, ended, failed, canceled, or expired. The final status of individual requests within a batch is recorded in the results file.

The batch itself has a high-level processing_status, which can be one of five values. in_progress means the batch is currently being processed. ended indicates that processing is complete and results are available for download. failed means an unrecoverable error occurred with the batch. canceled means the batch was manually cancelled before completion. expired means the batch was not processed within the retention window and its results are no longer available.

For individual requests within a batch, successful results are recorded with a status of succeeded and contain the API response. Failed individual requests will have a status of errored and contain error details instead of a response. Partial failures are possible; a batch can end with a status of ended while some individual requests have errored.

Parsing Individual Request Statuses from Results

Scenario Questions

0-2 years experience

  1. 1If you submit a batch request to the Anthropic API and receive a response indicating the batch is 'in_progress', what would you do next in your client code?
  2. 2How would you map the 'canceled' status to a user‑friendly message in a simple UI?

2-5 years experience

  1. 1You notice that some of your batch requests are ending up with the 'errored' status intermittently. Walk me through how you would investigate and resolve the issue.
  2. 2When implementing a retry mechanism for failed batches, how would you decide which statuses (e.g., errored vs expired) are safe to retry, and why?

5-8 years experience

  1. 1Design a monitoring dashboard for batch processing that tracks the distribution of statuses over time. What metrics would you include and how would you handle high volumes?
  2. 2Explain how you would architect a system to automatically clean up or archive batches that have reached 'succeeded' or 'canceled' status while ensuring no data loss.

8+ years experience

  1. 1At a platform level, how would you evolve the batch status model if you needed to add more granular states (e.g., 'partial_success') without breaking existing clients?
  2. 2Discuss the trade‑offs of pushing status changes via webhooks versus client polling in a large‑scale Anthropic API integration.

Follow-up Questions

  • What retry backoff strategy would you use for 'errored' batches?
  • How would you differentiate between a user‑initiated cancel and an automatic expiration in your logs?
  • Can you describe how you'd expose batch status to a third‑party service that only supports HTTP callbacks?
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