Amazon EC2 Capacity Blocks for ML

2m 35s

This course is focused on explaining Amazon EC2 Capacity Blocks for machine learning (ML) and how they can be utilized to reserve GPU instance capacity in advance for ML workloads.

Learning Objectives

  • Learn the purpose and benefits of EC2 capacity blocks for machine learning

  • Understand the pricing considerations for EC2 capacity blocks

  • Understand the lifecycle of EC2 capacity blocks and how they are utilized

Intended Audience

  • Machine learning engineers

  • Infrastructure engineers with an interest in machine learning

  • Anyone managing the underlying compute capacity for training and deploying machine learning models


To get the most out of this lesson, you should have:

  • A strong understanding of Amazon EC2, including EC2 instance types

  • The different pricing models for EC2 instances

  • Familiarity with Amazon EventBridge, AWS CloudTrail, and Amazon EC2 UltraClusters

About the Author
Alana Layton, opens in a new tab
Sr. AWS Content Creator
Learning paths

Alana Layton is an experienced technical trainer, technical content developer, and cloud engineer living out of Seattle, Washington. Her career has included teaching about AWS all over the world, creating AWS content that is fun, and working in consulting. She currently holds six AWS certifications. Outside of Cloud Academy, you can find her testing her knowledge in bar trivia, reading, or training for a marathon.

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