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

This article announces detailed observability metrics and the SageMaker Insights dashboard for monitoring generative AI inference endpoints at scale.

• SageMaker now emits 100+ detailed metrics covering GPU health, token latency, KV cache pressure, and traffic distribution
• Built-in SageMaker Insights dashboard in CloudWatch replaces need for custom Grafana and Prometheus configuration
• Performance tab monitors fleet health, token latency (TTFT/ITL), and engine pressure with latency breakdown
• Capacity tab tracks GPU/CPU/memory utilization trends to plan deployments and identify resource constraints
• Reliability tab shows AZ distribution, cold start anatomy, and insufficient capacity error diagnostics
• Detailed metrics enabled by default on new endpoints; existing endpoints require opt-in via MetricsConfig flag
• Connect to Grafana or other PromQL-compatible tools using CloudWatch PromQL endpoint with pre-built dashboard template
• Pricing: $0.50 per GB ingested for OpenTelemetry metrics; no separate charge for detailed observability

SageMaker Insights provides production ML teams with comprehensive observability to monitor, debug, and optimize generative AI inference workloads across multiple models and GPU instances.