Optimizing AWS Savings Plans for Maximum Cost Efficiency
Maximize AWS cost savings with our comprehensive guide to Savings Plans optimization. Learn effective strategies for purchase planning and utilization management.
Venkatakrishna Pullela
Amazon Employee
Published May 20, 2025
AWS Savings Plans provide powerful ways to reduce infrastructure costs—but unlocking their full value requires more than just purchasing commitments. A strategic approach—starting with foundational clean-up and progressing through continuous, data-driven optimization—is essential for realizing sustainable cost savings.
1. Establish a Realistic Baseline with Foundational Optimizations
Before purchasing or modifying any Savings Plans, it's critical to ensure your environment is already optimized. This forms the foundation of all future commitment decisions.
Key steps include:
- Right-size compute instances: Use AWS Compute Optimizer and Cost Explorer to identify and adjust over- or under-provisioned instances. Right-sizing ensures the recommendations you receive for commitments reflect actual needs.
- Delete unused resources: Remove idle EBS volumes, unattached load balancers, legacy AMIs, and other unused infrastructure.
- Upgrade to modern instance types: When possible, transition to newer generation instance families (e.g., M7g, C7gn) that offer better price-performance.
- Evaluate architectural changes: Consider moving to managed services, containers, or serverless to reduce EC2 dependency and shift to more flexible compute options like Fargate or Lambda (which are covered by Compute Savings Plans).
Only after this cleanup will your cost and usage data accurately reflect true demand—establishing a solid baseline for making informed commitment decisions.
2. Use the Savings Plans Purchase Analyzer for Smarter Decision-Making
The Savings Plans Purchase Analyzer is a new AWS-native tool that helps you make more informed and customized Savings Plan purchases by analyzing historical usage patterns.
Key features include:
- Customize hourly commitments: Simulate various commitment amounts to determine the optimal balance between spend and flexibility.
- Select the right look-back period: Choose from 7, 30, or 60 days (or a custom range) to reflect the period with the most stable compute usage. This avoids basing purchases on temporary spikes or lulls.
- Exclude expiring plans: Remove expiring Savings Plans from projections to visualize future uncovered usage and plan accordingly.
This tool is ideal after baseline optimization, helping you simulate real-world scenarios and refine your purchase strategy.
3. Adopt Incremental Commitment Strategies
You don’t need to commit to your entire estimated hourly usage all at once—especially if you're managing dynamic or growing environments.
- Purchase in cycles: Start with a smaller Savings Plan than recommended, monitor coverage and utilization, and incrementally purchase additional commitments as usage stabilizes.
- Repeat and refine: Use each incremental purchase as an opportunity to assess actual savings and avoid over-committing.
This staged approach enables flexibility and improves your ability to match commitment to evolving workloads—particularly useful in fast-growing or transforming environments.
4. Continuously Reevaluate and Recalibrate Commitments
Even well-planned commitments can become misaligned over time due to changing business needs or modernization efforts. It’s important to periodically reassess.
- Sell unused Standard RIs on the RI Marketplace: If you purchased Reserved Instances (RIs) in the past and the usage drops or shifts regions, list underutilized RIs in the marketplace to recover some sunk costs, and look into purchasing a Savings Plan instead for added flexibility.
- Monitor coverage and utilization: Use AWS Cost Explorer and Savings Plans utilization reports to ensure your commitments still align with real usage.
Making continuous adjustments allows you to stay agile while keeping costs in check.
5. Leverage Spot Instances for Flexible or Spiky Workloads
Savings Plans are best suited for steady-state workloads. For variable, spiky, or non-critical tasks, Spot Instances offer dramatic savings—up to 90% compared to On-Demand.
- Use Spot for fault-tolerant workloads: Offload CI/CD jobs, analytics, web crawling, and other interruptible processes.
- Adopt blended capacity groups: Use Auto Scaling groups with a mix of Spot, On-Demand, and Reserved capacity to optimize cost and performance.
By pushing burst workloads to Spot, you reduce your On-Demand baseline, thereby increasing the efficiency of your Savings Plan coverage.
6. Optimize Batch Job Scheduling for Better Savings Plan Coverage
Savings Plans apply at the hourly level. If batch jobs are concentrated during a few peak hours, Savings Plans may go underutilized during off-peak times.
- Spread workloads across 24 hours: Distribute scheduled jobs more evenly throughout the day to flatten usage spikes and improve hourly coverage.
- Use orchestration services: Employ Amazon EventBridge, Step Functions, or workflow engines like Amazon MWAA to control job timing without manual intervention.
Aligning usage with hourly coverage patterns enhances the return on your commitment investment.
7. Choose the Right Plan Type, Term, and Payment Option
Different Savings Plan options support different business priorities:
- Compute Savings Plans: Maximize flexibility across instance families, regions, and compute options (EC2, Lambda, Fargate).
- EC2 Instance Savings Plans: Offer deeper discounts but are limited to specific instance families in a region.
- Payment structures:
- All Upfront: Highest discount, ideal for stable budgets.
- Partial/No Upfront: Less upfront investment, more flexibility in cash flow.
Carefully balancing term length (1-year vs. 3-year) and payment preference ensures optimal value and fiscal alignment.
8. Subscribe to Savings Plans Alerts and Monitor Continuously
Proactive monitoring and notifications are key to avoiding surprises and missed opportunities.
- Enable Savings Plans alerts: Set up notifications to inform you when a plan is approaching expiration, giving you time to evaluate and re-purchase with no coverage gaps.
- Use AWS Budgets and Trusted Advisor: Get alerts for commitment underutilization, anomalies, and optimization suggestions.
- Integrate with the Cost and Usage Report (CUR): Automate deeper analysis or integrate with third-party FinOps platforms for multi-account or enterprise-wide governance.
Conclusion
The path to cost optimization with AWS Savings Plans starts with operational hygiene—rightsizing, deleting unused resources, and understanding workload patterns. From there, tools like the Savings Plans Purchase Analyzer and strategies like incremental purchasing and spot adoption enable customers to fine-tune coverage, maintain flexibility, and maximize savings over time.
Cost optimization isn’t a one-time project. It’s a continual, data-driven process that evolves with your workloads and business priorities.
For more resources and tooling, visit the AWS Cost Optimization Hub
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.