基本信息
- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/improve-operational-visibility-for-inference-workloads-on-amazon-bedrock-with-new-cloudwatch-metrics-for-ttft-and-estimated-quota-consumption
来源摘要/节选
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As organizations scale their generative AI workloads on Amazon Bedrock , operational visibility into inference performance and resource consumption becomes critical. Teams running latency-sensitive applications must understand how quickly models begin generating responses. Teams managing high-throughput workloads must understand how their requests consume quota so they can avoid unexpected throttling. Until now, gaining this visibility required custom client-side instrumentation or reactive troubleshooting after issues occurred.
Today, we’re announcing two new Amazon CloudWatch metrics for Amazon Bedrock, TimeToFirstToken and EstimatedTPMQuotaUsage . These metrics give you server-side visibility into streaming latency and quota consumption.…
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