GPU Scheduling and Resource Management in Containerized Environments

1. Monitoring and Observability
   1. GPU Metrics Collection
      1. Hardware-Level Metrics
         1. GPU Utilization
         2. Memory Utilization
         3. Power Consumption
         4. Temperature Monitoring
         5. Clock Frequencies
         6. PCIe Throughput
      2. Software-Level Metrics
         1. Process GPU Usage
         2. Memory Allocation
         3. Kernel Execution Time
         4. API Call Latency
      3. Collection Methods
         1. NVIDIA Management Library
         2. AMD ROCm SMI
         3. Intel GPU Tools
         4. Kernel Perf Events
   2. Monitoring Infrastructure
      1. DCGM Integration
         1. Health Monitoring
         2. Telemetry Collection
         3. Policy Management
         4. Diagnostic Capabilities
      2. Prometheus Integration
         1. GPU Exporters
         2. Metric Scraping
         3. Time Series Storage
         4. Alert Rules
      3. Grafana Dashboards
         1. Visualization Design
         2. Dashboard Templates
         3. Real-Time Monitoring
         4. Historical Analysis
   3. Application Performance Monitoring
      1. GPU Application Profiling
         1. NVIDIA Nsight Systems
         2. AMD ROCProfiler
         3. Intel VTune Profiler
      2. Container-Level Monitoring
         1. Resource Usage Tracking
         2. Performance Bottlenecks
         3. Memory Leak Detection
      3. Distributed Training Monitoring
         1. Multi-GPU Coordination
         2. Communication Overhead
         3. Load Balancing
   4. Logging and Tracing
      1. GPU Driver Logs
         1. Kernel Messages
         2. Driver Debug Information
         3. Error Reporting
      2. Application Logging
         1. CUDA Runtime Logs
         2. Application-Specific Logs
         3. Performance Traces
      3. Distributed Tracing
         1. Request Tracing
         2. GPU Operation Correlation
         3. End-to-End Visibility