---
title: "Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch"
slug: "aws-macht-sagemaker-inferenz-mit-100-neuen-cloudwatch-metriken-glaesern"
date: 2026-06-18
category: tech-pub
tags: [amazon]
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/aws-macht-sagemaker-inferenz-mit-100-neuen-cloudwatch-metriken-glaesern
---

# Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch

**Published**: 2026-06-18 | **Category**: tech-pub | **Sources**: 1

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## TL;DR

- AWS is adding more than 100 detailed inference metrics for SageMaker AI in CloudWatch, covering GPU use, GPU memory, KV cache pressure, token latency, traffic distribution across Availability Zones, cold starts, and inference component placement.

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## Summary

- AWS is adding more than 100 detailed inference metrics for SageMaker AI in CloudWatch, covering GPU use, GPU memory, KV cache pressure, token latency, traffic distribution across Availability Zones, cold starts, and inference component placement.
- New SageMaker endpoint configurations enable detailed observability by default. Existing endpoints need a new endpoint config and update; AWS says metrics should begin flowing roughly two minutes after the endpoint reaches InService.
- The SageMaker Insights dashboard groups views into Performance, Capacity, and Reliability. It surfaces TTFT, inter-token latency, overhead latency, token throughput, AZ distribution, scaling events, and insufficient capacity errors.
- For vLLM and SGLang, teams get token-level signals such as TTFT and ITL. Existing Grafana workflows can query the same metrics through a PromQL-compatible CloudWatch endpoint.

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## Why it matters

New SageMaker endpoint configurations enable detailed observability by default.

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## Key Points

- New SageMaker endpoint configurations enable detailed observability by default.
- Existing endpoints need a new endpoint config and update; AWS says metrics should begin flowing roughly two minutes after the endpoint reaches InService.
- The SageMaker Insights dashboard groups views into Performance, Capacity, and Reliability.
- It surfaces TTFT, inter-token latency, overhead latency, token throughput, AZ distribution, scaling events, and insufficient capacity errors.
- For vLLM and SGLang, teams get token-level signals such as TTFT and ITL.

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## Nauti's Take

AWS is removing a painful tax on GenAI teams: you no longer just see that an endpoint is slow, you can pin it on GPU memory, KV cache pressure, cold starts, or AZ skew. If you run LLMs in production, this means less guesswork and stronger arguments against lazy overprovisioning.

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## FAQ

**Q:** What is Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch about?

**A:** - AWS is adding more than 100 detailed inference metrics for SageMaker AI in CloudWatch, covering GPU use, GPU memory, KV cache pressure, token latency, traffic distribution across Availability Zones, cold starts, and inference component placement.

**Q:** Why does it matter?

**A:** New SageMaker endpoint configurations enable detailed observability by default.

**Q:** What are the key takeaways?

**A:** New SageMaker endpoint configurations enable detailed observability by default.. Existing endpoints need a new endpoint config and update; AWS says metrics should begin flowing roughly two minutes after the endpoint reaches InService.. The SageMaker Insights dashboard groups views into Performance, Capacity, and Reliability.

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## Related Topics

- [amazon](https://news.ainauten.com/en/tag/amazon)

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## Sources

- [Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch](https://aws.amazon.com/blogs/machine-learning/monitor-and-debug-generative-ai-inference-with-sagemaker-detailed-metrics-and-insights-dashboard-on-cloudwatch/) - AWS Machine Learning Blog

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## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

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*Last Updated: 2026-06-22*