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AWS Savings Plans offer a discount from On-Demand for a specific usage commitment. On the other hand, AWS Spot instances offer steeper discounts, but aren’t guaranteed to be available.
If you’re looking to consistently optimize your AWS costs, taking advantage of both Savings Plans and Spot is key — but balancing them can be complex. Not enough Spot means workload spikes result in expensive On-Demand rates. And over-committing to Savings Plans can leave you paying for compute you don’t need. To make matters more complicated, some workloads are better suited for Spot and some are best for Savings Plans.
To maximize savings, it’s key to understand how AWS Savings Plans are applied, what they apply to, and how much to use. AWS prioritizes covering usage to achieve the highest discount rate(s) first — yet it’s actually possible to achieve even more savings than this by driving certain resources onto Spot such that Savings Plans cover other, non-discounted resources.
We’ll take you through how it all works and how you can hack the system with “Freeable Savings Plans” for next-level AWS discounts. First, let’s quickly go over the basics.
What is AWS Spot?
AWS Spot Instances are spare AWS compute capacity that users can purchase at a heavy discount. It allows AWS to monetize idle time in their data center by offering it on the Spot market. AWS gives you a discount on the instance, but not a guarantee that you’ll be able to use it to the end of your compute need.
Contrary to common belief, Spot instances are actually quite reliable. And, many workloads in the cloud are already being dynamically scaled with frameworks like Kubernetes able to handle interruption just fine.
What are Compute Savings Plans?
Savings Plans are a flexible pricing model that offer low prices on Amazon EC2, AWS Lambda, and AWS Fargate usage, in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a 1 or 3 year term. When you purchase Savings Plans, you will be charged the discounted Savings Plans price for your usage up to your commitment.
Compute Savings Plans provide the most flexibility and help to reduce your costs by up to 66%. Compute Savings Plans apply automatically to EC2 instance usage regardless of instance family, instance size, Availability Zone, AWS Region, Operating System or tenancy, and also apply to Fargate or Lambda usage.
For example, with Compute Savings Plans, you can change from C4 to M5 instances, shift a workload from EU (Ireland) to EU (London), or move a workload from EC2 to Fargate or Lambda at any time and automatically continue to pay the Savings Plans price.
AWS Savings Plans are often used for predictable usage. They apply to EC2 instance usage regardless of instance family, size, AZ, Region, OS or tenancy (source: AWS.com)
For a full comparison of the various types of Savings Plans and Reserved Instances (think EC2 Instance Savings Plans, Sagemaker Savings Plans, Standard Reserved Instances, Convertible Reserved Instances, and more) you can consult the full guide to AWS Commitments.
Now, let’s get into some use cases when it comes to deciding between Spot and Savings Plans.
Problem statement:
Let’s assume an AWS Account has a Compute Savings Plans commitment and wants to maximize its usage for the best overall savings.
Problem 1: How do you know how much Spot to use?
In some cases, moving EC2 instances to Spot won’t save you money.
If you don’t have enough EC2 instances to fully consume the Compute Savings Plans commitment and then you move some of your On-Demand instances to Spot, unnecessary additional charges for the Spot will actually cost you more.
Because Savings Plans apply hourly, it’s complicated and difficult to continually track your usage and the optimal amount of Spot to use.
Problem 2: Resources not covered by AWS Savings Plans are charged On-Demand prices
If you fully utilize your Compute Savings Plans and there are instances not covered by Compute Savings Plans, some On-Demand instances can’t be moved onto Spot (like RDS, for example). Or, you may not want to move certain workloads that are unable to handle interruption to Spot — meaning that these workloads don’t get a discount.
Solution: Get discounts on all of your compute with the “Freeable Savings Plan” and nOps Copilot
AWS automatically applies Savings Plans to usage that has already occurred, prioritizing the highest discount rate. However, there are times in which you would actually prefer to move some of these workloads onto Spot (rather than Savings Plans), so that the Savings Plan can be used for other resources that can’t be put onto Spot.
By proactively and strategically moving certain usage onto Spot, nOps Copilot ensures that each workload is on the right type of discount to continually maximize your total savings. Copilot allows you to get discounts on:
- Harder-to-cover resources (for example, resources that can’t be put on Spot), so that you get discounts on ALL of your compute.
- Resources outside of your connected clusters. Because Savings Plans apply across your organization, Copilot can drive certain usage to Spot to allow resources even outside of your target workload to be covered by freed Savings Plans.
While it’s very complicated to manually calculate how much of your Savings Plans to use to get a discount on all of your eligible compute usage, Copilot does it for you effortlessly.
How it works:
Compute Copilot ASG Lambda analyzes your AWS Savings Plans across your organization and your dynamic usage. Predictive ML is used to forecast your On-Demand usage and Savings Plans usage for the next hour to predict the amount of “Freeable” Compute Savings Plans.
If you have an unfulfilled Compute Savings Plans available and your ASG scales out with On-Demand instances, Compute Copilot Lambda will not move you onto Spot.
If Copilot predicts there is some amount of Freeable Compute Savings for the next hour, it will automatically replace On-Demand with Spot when the On-Demand price is lower or equal to the predicted Freeable Compute Savings amount. As a result, it will free Savings Plans to cover some other previously uncovered On-Demand instance.
You can consult the documentation for more details on how nOps automatically and continually moves your workloads onto the most reliable and best priced Spot instances, balancing commitments and Spot for optimal price and stability.
About nOps
At nOps, our mission is to make it easy for engineers to optimize costs, so they can focus on building and innovating. With our platform, there’s no longer a reason to manually manage workloads and pick instance families; Copilot does it for you more effectively and at a lower cost.
And there’s no vendor lock-in — Copilot updates configurations in your AWS-native tools, meaning no major architecture update is needed to onboard or offboard. Plug it in or walk away at any time.
Join our customers using nOps to cut cloud costs and leverage automation with complete confidence by booking a demo today!
