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Machine Learning Engineering on AWS

You're reading from   Machine Learning Engineering on AWS Build, scale, and secure machine learning systems and MLOps pipelines in production

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781803247595
Length 530 pages
Edition 1st Edition
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Author (1):
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Joshua Arvin Lat Joshua Arvin Lat
Author Profile Icon Joshua Arvin Lat
Joshua Arvin Lat
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Table of Contents (19) Chapters Close

Preface 1. Part 1: Getting Started with Machine Learning Engineering on AWS
2. Chapter 1: Introduction to ML Engineering on AWS FREE CHAPTER 3. Chapter 2: Deep Learning AMIs 4. Chapter 3: Deep Learning Containers 5. Part 2:Solving Data Engineering and Analysis Requirements
6. Chapter 4: Serverless Data Management on AWS 7. Chapter 5: Pragmatic Data Processing and Analysis 8. Part 3: Diving Deeper with Relevant Model Training and Deployment Solutions
9. Chapter 6: SageMaker Training and Debugging Solutions 10. Chapter 7: SageMaker Deployment Solutions 11. Part 4:Securing, Monitoring, and Managing Machine Learning Systems and Environments
12. Chapter 8: Model Monitoring and Management Solutions 13. Chapter 9: Security, Governance, and Compliance Strategies 14. Part 5:Designing and Building End-to-end MLOps Pipelines
15. Chapter 10: Machine Learning Pipelines with Kubeflow on Amazon EKS 16. Chapter 11: Machine Learning Pipelines with SageMaker Pipelines 17. Index 18. Other Books You May Enjoy

Cleaning up

Now that we have completed an end-to-end ML experiment, it’s about time we perform the cleanup steps to help us manage costs:

  1. Close the browser tab that contains the EC2 Instance Connect terminal session.
  2. Navigate to the EC2 instance page of the instance we launched using the Deep Learning AMI. Click Instance state to open the list of dropdown options and then click Terminate instance:

Figure 2.37 – Terminating the instance

As we can see, there are other options available, such as Stop instance and Reboot instance. If you do not want to delete the instance yet, you may want to stop the instance instead and start it at a later date and time. Note that a stopped instance will incur costs since the attached EBS volume is not deleted when an EC2 instance is stopped. That said, it is preferable to terminate the instance and delete any attached EBS volume if there are no critical files stored in the EBS volume.

  1. In...
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