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  • AutoPilot Workshop
    • How Amazon SageMaker Autopilot works
    • Getting Started
    • Load Autopilot Example
    • Run Autopilot Example
    • Workshop Clean-up
  • SageMaker Operators for Kubernetes Workshop
    • Getting Started
      • Overview
      • Prerequisites
      • Install Eksctl
      • Create Cluster
      • Install Kubeflow
      • Install SageMaker Operators
    • Dashboard
      • Dashboard
    • Notebook
      • Create a notebook
      • Data Preparation
    • Training and Inference
      • Training
      • Inference
      • Batch Inference
      • Hyper Parameter Optimization
    • Improving the TensorFlow Model
      • Network Improvements
      • Data Preparation
      • Training Script
      • Training and Inference
    • Next Steps
      • Next Steps
      • Cleanup
  • SageMaker Components for Kubeflow Pipelines Workshop
    • Getting Started
      • Overview
      • Prerequisites
    • Creating the Pipeline
      • S3 Bucket
      • SageMaker Job Role
      • Compile the Pipeline Definition
      • Register the Pipeline
    • Running the Pipeline
      • Run the Pipeline
      • Check Pipeline Status
      • Batch Transform Output
      • Real Time Inference
    • Deep Learning Pipeline
      • Create a Jupyter Notebook
      • Create and Run Pipeline
    • Next Steps
  • Resources
    • Use Existing Code
      • Use Existing Tensorflow Code
      • Use Existing Pytorch Code
      • Use Existing MxNet Code
      • Use Existing Scikit Learn Code
      • Use Existing R Code
      • Using SageMaker Spark
    • Advanced Topics
      • Reinforcement Learning
      • Graph Neural Networks
      • Automatically Stopping Training jobs
      • Generative AI
      • Iterative Model Pruning
      • Model specific real-time analysis
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    • Sample SageMaker Use Cases
      • Structured data
      • Time Series
      • Computer Vision
      • Natural Language Processing
      • SageMaker Marketplace Examples on SageMaker
    • Specific SageMaker Features
      • Prepare Datasets
      • Build, Train and Deploy models
      • Use Advanced Training capabilities
      • Use Advanced Deployment capabilities
      • Optimize Costs

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Amazon SageMaker Workshop > Resources > Specific SageMaker Features > Use Advanced Deployment capabilities

Use Advanced Deployment capabilities

  1. Deploy Multi-model Endpoints
  2. Deploy Inference Pipelines
  3. Monitor models with SageMaker Model Monitor
  4. Compile models with SageMaker Neo