If you experience problems or receive error messages during image preparations, review the following logs. Log location varies depending on whether you are running EC2Config, EC2Launch v1, or EC2Launch v2 with Sysprep.

Because your instance metadata is available from your running instance, you do not need to use the Amazon EC2 console or the AWS CLI. This can be helpful when you're writing scripts to run from your instance. For example, you can access the local IP address of your instance from instance metadata to manage a connection to an external application.

Search for an AMI that meets your requirements.

Add rules to your security group for specific kinds of access.

SageMaker Distribution is a collection of Docker images, which includes popular libraries and packages for machine learning, data science, and data analytics visualization. The Docker images include deep learning frameworks such as the following:

Amazon SageMaker Studio Classic is an integrated machine learning environment where you can build, train, deploy, and analyze your models all in the same application.

Describes how you can track the lineage of machine learning workflows.

Fine-tune foundation models on your data to get responses that are customized to your use case.

Learn how to use the @step decorator to convert local code to pipeline steps.

Using SageMaker for large model inference.