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Cost OptimizationsAWS Savings Plans

Basics of AWS Cost Optimizations: Part I

Understanding AWS Savings Plans

AWS is powerful and flexible, but AWS costs can quickly spiral out of control if not managed properly. Whether you're an indiehacker, a startup, or an enterprise, optimizing AWS costs is essential to be efficient and competitive.
This blog post is Part I of a series that breaks down key AWS cost optimization strategies, from Savings Plans, Reserved Instances to AWS Compute Optimizer, Trusted Advisor and Cost Optimization Hub recommendations, helping you make informed decisions to optimize your AWS cloud costs.

AWS Savings Plans

Savings Plans offer significant cost reductions up to 72% compared to On-Demand pricing in exchange for a commitment over a one-year or three-year term. There are three types of Savings Plans:

1. EC2 Instance Savings Plan

  • EC2 Instance Savings Plans are the most restrictive but offer highest discounts up to 72%
  • Commits to specific EC2 instance family (e.g., m5, c5) in a single AWS region
  • Ideal for stable and predictable workloads
  • Applies to both Windows and Linux instances

2. Compute Savings Plan

  • Compute Savings Plans offer more flexibility with slightly lower savings up to 66%
  • Automatically applies across:
    • EC2 instances (any family, size, OS, tenancy)
    • Fargate containers
    • Lambda functions
  • Works across AWS regions and Availability Zones
  • Great for evolving or mixed workloads

3. SageMaker Savings Plan

  • SageMaker Savings Plan is specific to machine learning workloads with savings up to 64%
  • Applies to eligible SageMaker ML instance across
    • Instance family, Instance size, or AWS region
  • Following SageMaker ML instance usages are included:
    • SageMaker Studio Notebook
    • SageMaker On-Demand Notebook
    • SageMaker Processing
    • SageMaker Data Wrangler
    • SageMaker Training
    • SageMaker Real-Time Inference
    • SageMaker Batch Transform
  • Ideal for consistent ML training or inference workloads

Pro Tip: You can stack multiple Savings Plans to cover different usage patterns.

Understanding Savings Plan Recommendations

Savings Plan recommendations are generated based on lookback periods:

  • 7 days: Recent usage patterns
  • 30 days: Monthly trends
  • 60 days: Long-term patterns

AWS provides three payment options for Savings Plans:

  1. No upfront: Higher hourly rates but no initial payment and commitment is charged on a monthly basis
  2. Partial upfront: Balance between cost savings and initial payment, you will be charged atleast 50% of your commitment upfront and the remaining balance will be charged on a monthly basis
  3. All upfront: Maximum savings with entire commitment paid upfront in one payment

AWS Organizations Integration

  • Savings Plans can be purchased in any account within an AWS Organization/Consolidated Billing family
  • The benefit provided by Savings Plans is applicable to usage across all accounts within an AWS Organization/consolidated billing family by default
  • However, you can choose to restrict the benefit of Savings Plans to only the account that purchased them

Getting Savings Plan Recommendations

Via AWS Console

  1. Navigate to AWS Billing and Cost Management Dashboard
  2. Select "Savings Plans" β†’ "Recommendations"
  3. Choose your preferred Savings Plan type, Recommendation level (Payer or Linked account), Savings Plan term (1 year or 3 years), Payment option (No upfront, Partial upfront or All upfront) and lookback period (7 days, 30 days or 60 days)
  4. This will generate the Recommended Savings Plans which can also be downloaded as a CSV file
  5. You can then review the recommendations and purchase the Savings Plans from the dashboard via "Savings Plans" β†’ "Purchase Savings Plans"

Via AWS API

You can also get Savings Plan recommendations via AWS Cost Explorer API.
python
aws-cli
javascript

What's Next?

For more details and FAQs on AWS Savings Plans you can refer to the AWS products page.
In Part II of this series, we will look at AWS Reserved Instances and how to optimize your AWS costs using them.

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