Configure Amazon EC2 to meet your security and compliance objectives, and learn how to use other AWS services that help you to secure your Amazon EC2 resources.

Attach a network interface to your instance to specify its private IP addresses, Elastic IP addresses, and security groups.

Your AWS account automatically has a default security group for the default VPC in each Region. If you don't specify a security group when you launch an instance, the instance is automatically associated with the default security group for the VPC. If you don't want your instances to use the default security group, you can create your own custom security groups and specify them when you launch your instances.

Use Amazon EC2 to reboot your instance for necessary maintenance.

Automatically build, train, tune, and deploy models using Autopilot.

Amazon SageMaker provides APIs, SDKs, and a command line interface that you can use to create and manage notebook instances and train and deploy models.

Learn more about how to get inferences from your Amazon SageMaker models and deploy your models for serving inference.

The following diagram shows how you train and deploy a model with Amazon SageMaker. Your training code accesses your training data and outputs model artifacts from an S3 bucket. Then you can make requests to a model endpoint to run inference. You can store both the training and inference container images in an Amazon Elastic Container Registry (ECR).

Learn how the AWS shared responsibility model applies to data protection in Amazon Elastic Compute Cloud.

You can describe the key pairs that you stored in Amazon EC2. You can also retrieve the public key material and identify the public key that was specified at launch.