Last updated Aug 17, 2023 Edit Source

Savings Plans offer you similar discounts as Reserved Instances (RI) but simplifies the purchasing process

You can choose two different terms

• 1 Year
• 3 Year

You choose the following Payment Options:

• All Upfront
• Partial Upfront
• No Upfront

AWS Savings Plan has 3 different savings types:

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Allows users to rent virtual computers on which to run their own computer applications.

• Compute Savings Plans provide the most flexibility and help to reduce your costs by up to 66%.
• These plans automatically apply to EC2 instance usage, AWS Fargate, and AWS Lambda service usage regardless of instance family, size, AZ, region, OS, or tenancy.

Elastic Compute Cloud (EC2) allows you to launch Virtual Machines (VM)

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A Virtual Machine (VM) is an emulation of a physical computer using software.
Server Virtualization allows you to easily create, copy, resize or migrate your server.
Multiple VMs can run on the same physical server so you can share the cost with other customers.
Imagine if your server or computer was an executable file on your computer

When we launch a virtual machine we call it an “instance”

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EC2 is highly configurable where you can choose an amazon machine image (AMI) that affects options such as:

• the amount of CPUs
• the amount of memory
• the amount of network bandwith
• the operation system (OS) eg. Windows 10, Ubuntu, Amazon Linux 2
• Attach multiple virtual hard-drives for storage eg. Elastic Block Store (EBS)

EC2 is also considered the backbone of AWS because the majority of AWS services use EC2 as the underlying server
eg. S2, RDS, DynamoDB, Lambdas

• provide the lowest prices, offering savings up to 72% in exchange for commitment to usage of individual instance families in a region.
• automatically reduces your cost on the selected instance family in that region regardless of AZ, size, OS or tenancy.
• give you the flexibility to change your usage between instances within a family in that region.

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Amazon SageMaker is a fully managed service to build, train, and deploy machine learning models at scale

• Apache MXNet on AWS, open-source deep learning framework

• TensorFlow on AWS open-source machine intelligence library

• PyTorch on AWS open-source machine learning framework

• Helps you reduce SageMaker costs by up to 64%.

• automatically apply to SageMaker usage regardless of instance family, size, component, or AWS region.