Deploy SageMaker AI inference endpoints with set GPU capacity using training plans
📰 AWS Machine Learning
Deploy SageMaker AI inference endpoints with reserved GPU capacity using training plans
Action Steps
- Search for available p-family GPU capacity
- Create a training plan reservation for inference
- Deploy a SageMaker AI inference endpoint on the reserved capacity
- Manage the endpoint throughout the reservation lifecycle
Who Needs to Know This
Data scientists and machine learning engineers benefit from this approach as it allows them to reserve GPU capacity for model evaluation and manage inference endpoints efficiently
Key Insight
💡 Reserving GPU capacity using training plans ensures efficient model evaluation and inference endpoint management
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🚀 Deploy SageMaker AI inference endpoints with reserved GPU capacity
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