Working with supported services
You can learn more about the services that are eligible to receive Savings Plans benefits in this topic.
Amazon EC2
Amazon Elastic Compute Cloud (Amazon EC2) provides scalable computing capacity in the Amazon Web Services, Inc. (Amazon) cloud. Using Amazon EC2 eliminates your need to invest in hardware up front, so you can develop and deploy applications faster. You can use Amazon EC2 to launch as many or as few virtual servers as you need, configure security and networking, and manage storage. Amazon EC2 enables you to scale up or down to handle changes in requirements or spikes in popularity, reducing your need to forecast traffic.
For more information about Amazon EC2, see What Is Amazon EC2? in the Amazon EC2 Getting Started Guide.
Amazon Fargate
Amazon Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS). Fargate makes it easy for you to focus on building your applications. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design.
Fargate is eligible for Compute Savings Plans.
For more information about Amazon ECS on Fargate, see What is Amazon Elastic Container Service? in the Amazon Elastic Container Service Developer Guide.
For more information about Amazon EKS on Fargate, see What is Amazon Elastic Kubernetes Service? in the Amazon EKS User Guide.
Amazon Lambda
Amazon Lambda is a compute service that lets you run code without provisioning or managing servers. Amazon Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. You pay only for the compute time you consume - there is no charge when your code is not running. With Amazon Lambda, you can run code for virtually any type of application or backend service - all with zero administration. Amazon Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging.
Lambda is eligible for Compute Savings Plans.
For more information about Lambda, see What Is Amazon Lambda? in the Amazon Lambda Developer Guide.
Amazon SageMaker
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment.
SageMaker provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment.
With native support for bring-your-own-algorithms and frameworks, SageMaker offers flexible distributed training options that adjust to your specific workflows. Deploy a model into a secure and scalable environment by launching it with a few clicks from SageMaker Studio or the SageMaker console.
SageMaker is eligible for SageMaker Savings Plans.
For more information about Amazon SageMaker, see What Is Amazon SageMaker? in the Amazon SageMaker Developer Guide.