GPU Scheduling and Resource Management in Containerized Environments

1. Ecosystem and Tooling
   1. NVIDIA GPU Operator
      1. Operator Architecture
         1. Custom Resource Definitions
         2. Controller Logic
         3. Reconciliation Loops
      2. Component Management
         1. Driver Installation
         2. Container Toolkit Deployment
         3. Device Plugin Management
         4. DCGM Exporter Setup
      3. Lifecycle Operations
         1. Installation Procedures
         2. Upgrade Strategies
         3. Rollback Mechanisms
         4. Configuration Management
      4. Troubleshooting
         1. Common Issues
         2. Diagnostic Tools
         3. Log Analysis
   2. Cloud Provider GPU Services
      1. Amazon Web Services
         1. EC2 GPU Instances
         2. EKS GPU Support
         3. Batch GPU Jobs
         4. SageMaker Integration
      2. Google Cloud Platform
         1. Compute Engine GPUs
         2. GKE GPU Node Pools
         3. AI Platform Integration
         4. TPU Alternatives
      3. Microsoft Azure
         1. GPU Virtual Machines
         2. AKS GPU Support
         3. Machine Learning Services
         4. Batch GPU Computing
      4. Multi-Cloud Considerations
         1. Portability Challenges
         2. Cost Optimization
         3. Vendor Lock-in Avoidance
   3. Machine Learning Platforms
      1. Kubeflow
         1. Pipeline Orchestration
         2. GPU-Aware Scheduling
         3. Model Serving
         4. Experiment Tracking
      2. MLflow
         1. Experiment Management
         2. Model Registry
         3. Deployment Strategies
      3. Ray
         1. Distributed Computing
         2. GPU Resource Management
         3. Hyperparameter Tuning
   4. Batch Processing Systems
      1. Volcano Scheduler
         1. Job Queue Management
         2. Gang Scheduling
         3. Fair-Share Policies
         4. Plugin Architecture
      2. Apache Spark on Kubernetes
         1. GPU-Accelerated Spark
         2. Dynamic Resource Allocation
         3. Shuffle Service
      3. Argo Workflows
         1. GPU Workflow Orchestration
         2. DAG Execution
         3. Artifact Management