Learn about creating and managing Amazon EMR clusters from Amazon SageMaker Studio Classic to process large-scale data for machine learning workloads.

Compile deep learning (DL) models to achieve an improved training efficiency by using Amazon SageMaker Training Compiler.

Use Amazon Elastic Inference (EI) to speed up the throughput and decrease latency for inference in Amazon SageMaker

Use these instances for baseline performance and the ability to burst to higher performance as required by your workload.

Monitor scheduled events for your instances.

The rules of a security group control the inbound traffic that's allowed to reach the instances that are associated with the security group. The rules also control the outbound traffic that's allowed to leave them.

Add an instance store volume to an Amazon EC2 instance at launch and then prepare it for use.

Terminate your instance when you no longer need it and stop incurring charges for that instance.

You can bring part or all of your publicly routable IPv4 or IPv6 address range from your on-premises network to your AWS account. You continue to control the address range and you can advertise the address range on the internet through AWS. After you bring the address range to AWS, it appears in your AWS account as an address pool.

Copy an AMI to another Region, or to create a version backed by encrypted Amazon EBS snapshots.