GPU Performance Monitoring
Shield360 uses OpenTelemetry to help you monitor NVIDIA and AMD GPUs for AI applications. Track GPU metrics like utilization, temperature, memory usage, and power consumption during AI training and inference workloads.
Choose your method
Section titled “Choose your method”GPU monitoring can be implemented in two ways depending on your setup and requirements:
Shield360 SDK
It is useful if you already have an AI application running on GPU that’s instrumented with Shield360.
It extends your existing observability to include GPU metrics alongside your LLM traces.
OpenTelemetry GPU Collector
It is useful for remote GPUs with only LLM models hosted, containerized deployments.
This approach allows you to get GPU metrics without modifying application code.
Supported Parameters
Section titled “Supported Parameters”SDK Configuration Options
Section titled “SDK Configuration Options”| Parameter | Type | Default | Description |
|---|---|---|---|
collect_system_metrics | boolean | False | Enable GPU and system metrics collection |
otlp_endpoint | string | None | OpenTelemetry OTLP endpoint URL |
otlp_headers | string | None | Authentication headers for OTLP endpoint |
service_name | string | "unknown_service" | Name of your AI application |
environment | string | None | Deployment environment (dev, staging, prod) |
Environment Variables
Section titled “Environment Variables”| Variable | Description | Example |
|---|---|---|
SHIELD360_COLLECT_SYSTEM_METRICS | Enable GPU monitoring | true |
OTEL_EXPORTER_OTLP_ENDPOINT | OTLP endpoint URL | http://127.0.0.1:4318 |
OTEL_SERVICE_NAME | Service name for telemetry | my-gpu-app |
OTEL_DEPLOYMENT_ENVIRONMENT | Deployment environment | production |