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GPU Performance Monitoring
ARMS 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
GPU monitoring can be implemented in two ways depending on your setup and requirements:
- ARMS SDK — It is useful if you already have an AI application running on GPU that's instrumented with ARMS. 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
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
| Variable | Description | Example |
|---|---|---|
ELSAI_ARMS_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 |