Question

A media analytics company runs a nightly job that summarizes approximately 500,000 news articles collected during the day. The results are consumed by an internal dashboard the next morning, so there is no real-time requirement — the only constraint is that all summaries must be ready before 7:00 AM. The team currently sends each article through on-demand InvokeModel calls in a tightly parallelized loop, but they are hitting frequent ThrottlingExceptions and their monthly Bedrock bill has become the largest line item in their AWS spend. Which approach best reduces cost while eliminating throttling for this workload?

Accepted Answer

Submit the 500,000 articles as a Bedrock batch inference job that writes outputs to Amazon S3, scheduled to complete overnight.

Answer

Purchase Provisioned Throughput with a 6-month commitment to guarantee dedicated capacity for the nightly run.

Answer

Keep on-demand InvokeModel but add exponential backoff with jitter and request a service quota increase for tokens per minute.

Answer

Switch to the Converse API with streaming responses to lower per-request latency during the parallel loop.