AWS Savings Plans: The Complete Guide to All 4 Types (2026)

AWS costs can spiral without commitment-based discounts, but the wrong Savings Plan choice locks you into a commitment you can't escape. With four different types offering discounts ranging from 35% to 72%, choosing wisely has never been more important.

Here's what makes this guide different: I cover all four Savings Plans types with equal depth, including Database Savings Plans (launched December 2024) and the new Purchase Analyzer tool (November 2024). More importantly, I provide a decision framework that actually helps you choose the right type for your workloads, something no AWS documentation or competitor guide offers.

By the end, you'll understand exactly which Savings Plan type fits your workloads, how much to commit without over-committing, and have a clear implementation plan. Let's start with the fundamentals.

What Are AWS Savings Plans?

AWS Savings Plans is a flexible pricing model that offers discounts of up to 72% on AWS compute and database usage. In exchange, you commit to a consistent hourly spend (measured in $/hour) for a 1-year or 3-year term. Unlike Reserved Instances that lock you to specific configurations, Savings Plans commit you to spend, not specific instances.

Four types of Savings Plans are available:

1. Compute Savings Plans: Up to 66% savings with maximum flexibility across EC2, Fargate, and Lambda
2. EC2 Instance Savings Plans: Up to 72% savings for specific instance families in chosen regions
3. SageMaker AI Savings Plans: Up to 64% savings for machine learning workloads
4. Database Savings Plans: Up to 35% savings across 11 AWS database services (launched December 2024)

The key difference from Reserved Instances is the commitment type. With Savings Plans, you're committing to a dollar amount per hour. With Reserved Instances, you're committing to specific instance configurations. This distinction gives Savings Plans significant flexibility advantages for most workloads.

All Savings Plans are managed through AWS Cost Explorer and apply automatically to eligible usage. Reserved Instances apply first if you have them, then EC2 Instance Savings Plans, then Compute Savings Plans. The system prioritizes discounts to maximize your savings.

The Hourly Commitment Model Explained

The hourly commitment model is central to how Savings Plans work. You commit to spending a specific dollar amount per hour (anywhere from $0.001 to $5,000) for your chosen term.

The critical concept: Each hour's commitment is independent. Unused commitment in any hour does NOT carry over to future hours. This is a "use it or lose it" model on an hourly basis.

Here's a practical example with a $10/hour commitment:

• Hour 1: You have $8 of eligible usage. You pay $8 at the Savings Plans rate. The remaining $2 of commitment is unused and lost.
• Hour 2: You have $12 of eligible usage. You pay $10 at the Savings Plans rate. The remaining $2 is charged at On-Demand rates.

This hourly independence means you should size your commitment based on your baseline usage, not your peak. Over-committing means paying for unused hours. Under-committing means some usage stays at On-Demand rates, but that's better than wasting money on unused commitment.

Payment Options: All Upfront vs Partial vs No Upfront

Three payment options are available, each with different tradeoffs between cash flow and total savings:

Important exception: Database Savings Plans only offer No Upfront payment. You cannot pay upfront for additional discount with Database Savings Plans.

Billing mechanics differ from Reserved Instances. Savings Plans charge hourly recurring fees, while Reserved Instances charge monthly recurring fees. This means your Savings Plans charges appear every hour in your Cost and Usage Report, giving you more granular cost visibility.

How Savings Plans Apply to Your Usage

Understanding application order helps you optimize your discount strategy. Here's the sequence AWS uses:

Within each Savings Plans type, plans apply based on highest savings percentage first. If multiple usages have equal savings percentages, Savings Plans apply to the usage with the lowest Savings Plans rate first.

Key rules to remember:

• Savings Plans do NOT apply to Spot Instances
• Savings Plans do NOT apply to usage already covered by Reserved Instances
• In AWS Organizations, owner account usage is covered first, then other accounts
• Each hour's commitment is independent with no rollover

Now that you understand the fundamentals, let's examine each Savings Plans type in detail, starting with the most flexible option.

Compute Savings Plans: Maximum Flexibility

Compute Savings Plans offer the most flexibility of all Savings Plans types. They automatically apply to eligible usage regardless of instance family, size, Availability Zone, Region, operating system, or tenancy. If your architecture is evolving or you use multiple compute services, Compute Savings Plans are likely your best starting point.

The tradeoff for this flexibility is a lower maximum discount (66%) compared to EC2 Instance Savings Plans (72%). For many organizations, that 6% difference is worth the peace of mind that comes with not being locked to specific instance families.

Eligible Services (EC2, Fargate, Lambda)

Compute Savings Plans cover three AWS compute services:

Amazon EC2: All instance families, sizes, regions, operating systems, and tenancies (except dedicated instance fees). This includes EC2 instances running in Amazon EMR, EKS, and ECS clusters.

AWS Fargate: Applies to vCPU per hour and memory (GB per hour) dimensions. However, OS license fees are NOT covered. Windows on Fargate has no ARM CPU Architecture option.

AWS Lambda: Duration charges are discounted, but request charges ($0.20 per 1 million requests) receive 0% discount. Only the compute time portion of Lambda billing benefits from Savings Plans. For detailed analysis of which Lambda charges are covered and how to calculate your commitment when Lambda is request-heavy, see our Compute Savings Plans guide.

What's NOT covered:

• Dedicated Instances $2/hour fee (in every region with at least one Dedicated Instance)
• Amazon EKS service charges (only underlying EC2/Fargate compute is covered)
• Lambda request charges
• Fargate OS license fees
• U-type metal instances (only virtual u-type instances)

This breadth of coverage makes Compute Savings Plans ideal for organizations running mixed workloads. You can shift from EC2 to Fargate to Lambda without worrying about your Savings Plans coverage, and understanding ECS pricing and Fargate costs helps you model these transitions accurately.

Discount Rates and Savings Potential

Compute Savings Plans offer up to 66% off On-Demand rates. The actual discount varies based on several factors:

• Term length: 3-year terms provide higher discounts than 1-year
• Payment option: All Upfront offers highest discounts, No Upfront lowest
• Instance family: Memory-optimized instances (X2, X1, X1e) often offer higher savings percentages
• Region: Rates vary by AWS Region

You can view specific discount rates for your configuration in AWS Cost Explorer when purchasing. The rates remain constant throughout your entire plan term.

Best Use Cases for Compute Savings Plans

Choose Compute Savings Plans when:

• Workloads span multiple instance families: You're running a mix of compute-optimized (C5), memory-optimized (R5), and general-purpose (M5) instances
• Multi-service architectures: Your applications use EC2, Fargate, and Lambda together
• Evolving architectures: You're experimenting with instance types or migrating from EC2 to containers or serverless
• Multi-region deployments: Workloads may move between regions
• Development and test environments: Variable requirements where flexibility matters more than maximum discount

If you have stable production workloads committed to a specific instance family, EC2 Instance Savings Plans offer even higher discounts.

EC2 Instance Savings Plans: Maximum Discount

EC2 Instance Savings Plans offer the highest discount of all Savings Plans types: up to 72%. The tradeoff is reduced flexibility. You must commit to a specific instance family in a chosen AWS Region.

For stable production workloads where you know you'll stay on the same instance family, that extra 6% discount over Compute Savings Plans can add up significantly over a 3-year term.

Instance Family and Region Commitment

When purchasing EC2 Instance Savings Plans, you commit to:

• Specific instance family: For example, M5, C5, or R5
• Specific AWS Region: For example, us-east-1 or eu-west-1

You cannot change the family or region during your term without losing the discount. This applies to EC2 instances everywhere, including those running in Amazon EMR, EKS, and ECS clusters.

Example: A C5 commitment in us-east-1 covers all c5 sizes (c5.large, c5.xlarge, c5.2xlarge, etc.) in that region. It does NOT cover C5 instances in other regions or other instance families in us-east-1.

Before committing to EC2 Instance Savings Plans, make sure you understand EC2 pricing models and have analyzed your historical usage patterns.

Flexibility Within Your Commitment

Despite the family and region lock-in, EC2 Instance Savings Plans offer flexibility in other dimensions:

• Instance size: Change from c5.xlarge to c5.2xlarge freely
• Operating system: Switch from Windows to Linux
• Tenancy: Move from Shared to Dedicated
• Availability Zone: Any AZ within your committed region

This flexibility means you can right-size instances, change operating systems for cost optimization, and maintain high availability across AZs without losing your discount.

Best Use Cases for EC2 Instance Savings Plans

Choose EC2 Instance Savings Plans when:

• Stable production workloads: You have consistent instance family requirements
• Region-locked workloads: Applications stay in a specific region long-term
• Maximum discount priority: The extra 6% over Compute Savings Plans matters for your budget
• Legacy applications: Systems unlikely to migrate to containers or serverless
• Layering strategy: Combine with Compute Savings Plans for maximum coverage

A common strategy is using EC2 Instance Savings Plans for stable production workloads (72% discount) and Compute Savings Plans for variable dev/test environments (66% discount). This layering maximizes savings while maintaining flexibility where needed.

Use our EC2 pricing calculator to model the cost difference between Compute and EC2 Instance Savings Plans for your specific workloads.

SageMaker AI Savings Plans: ML Workload Optimization

SageMaker AI Savings Plans provide specialized savings for machine learning workloads. With up to 64% off On-Demand rates, they offer significant cost reduction for organizations running consistent ML operations.

Unlike EC2 or Compute Savings Plans, SageMaker AI Savings Plans are designed specifically for the SageMaker service. They apply automatically regardless of instance family, size, Region, or SageMaker component.

Eligible SageMaker Components

SageMaker AI Savings Plans cover seven SageMaker components:

1. SageMaker Studio Notebooks: Interactive development environment
2. SageMaker On-Demand Notebooks: Classic notebook instances
3. SageMaker Processing: Data processing jobs
4. SageMaker Data Wrangler: Data preparation
5. SageMaker Training: Model training jobs
6. SageMaker Real-Time Inference: Endpoint hosting
7. SageMaker Batch Transform: Batch inference

This comprehensive coverage means your entire ML pipeline can benefit from a single Savings Plan commitment.

Discount Rates for ML Workloads

SageMaker AI Savings Plans offer up to 64% off On-Demand rates. The discount applies automatically to all eligible ML instance usage.

Like other Savings Plans types:

• 3-year terms offer higher discounts than 1-year
• All Upfront provides maximum savings
• Rates vary by instance type and region

A key flexibility advantage: you can change from CPU instances (ml.c5.xlarge) to accelerated instances (ml.Inf1) without losing your discount. This is valuable as ML teams often experiment with different hardware for training and inference optimization.

Best Use Cases for SageMaker AI Savings Plans

Choose SageMaker AI Savings Plans when:

• Consistent ML workloads: You run training, inference, or notebooks on a regular basis
• Experimenting with instance types: You want flexibility to try different ML instance configurations
• Multi-component usage: You use multiple SageMaker features (notebooks, training, inference)
• Multi-region ML: Workloads may move between regions for latency or compliance
• Ongoing data science teams: Consistent SageMaker usage across your organization

SageMaker AI Savings Plans are NOT ideal for sporadic ML experiments. If you only run occasional training jobs, On-Demand or Spot may be more cost-effective than locking into a commitment. For detailed guidance on calculating the right commitment for mixed ML workloads and combining Savings Plans with Managed Spot Training, see our complete SageMaker AI Savings Plans guide.

Database Savings Plans: The Newest Option (2024)

Database Savings Plans, launched at AWS re:Invent in December 2024, bring Savings Plans flexibility to AWS database services. With up to 35% off On-Demand rates and coverage across 11 database services, they offer a compelling alternative to RDS Reserved Instances.

However, Database Savings Plans come with important restrictions that make them suitable for specific scenarios.

Eligible Database Services

Database Savings Plans cover 11 AWS database services:

1. Amazon Aurora (PostgreSQL and MySQL)
2. Amazon RDS (PostgreSQL, MySQL, MariaDB, Oracle, SQL Server)
3. Amazon Aurora Serverless v2
4. Amazon Aurora DSQL
5. Amazon DynamoDB
6. Amazon ElastiCache (for Valkey and Redis)
7. Amazon DocumentDB
8. Amazon Neptune
9. Amazon Keyspaces (for Apache Cassandra)
10. Amazon Timestream
11. AWS Database Migration Service (DMS)

This breadth means you can modernize from RDS for Oracle to Aurora PostgreSQL while maintaining your discount, giving you flexibility that RDS Reserved Instances don't offer.

Discount Rates by Deployment Type

Database Savings Plans discounts vary by deployment type:

The higher discounts for serverless deployments make Database Savings Plans particularly attractive if you're using Aurora Serverless v2 or DynamoDB.

Important Limitations and Restrictions

Database Savings Plans have significant restrictions you must understand:

Term and payment limitations:

• 1-year term ONLY: No 3-year option available
• No Upfront payment ONLY: You cannot pay upfront for additional discount

Combination restrictions:

• Cannot combine with RDS Reserved Instances for the same workload
• Cannot combine with DynamoDB reserved capacity for the same workload
• You CAN use Reserved Instances/reserved capacity for one workload and Database Savings Plans for different workloads

Regional availability:

• Available in all AWS Regions except China Regions

What's NOT covered:

• Storage charges
• Backup charges
• I/O charges
• Data transfer charges

These restrictions mean Database Savings Plans offer less discount potential than 3-year All Upfront RDS Reserved Instances. The value proposition is flexibility, not maximum discount.

Best Use Cases for Database Savings Plans

Choose Database Savings Plans when:

• Database modernization: You're planning to migrate between database engines (e.g., Oracle to Aurora)
• Multi-database architectures: You use RDS, DynamoDB, and ElastiCache together
• Instance type flexibility: You want to change database instance types without RI exchanges
• New workloads: You're starting fresh and 1-year commitment is acceptable
• Serverless databases: You heavily use Aurora Serverless v2 or DynamoDB (higher discount rates)

NOT ideal if:

• You need maximum discount (RDS RIs offer more)
• You prefer upfront payment for additional savings
• You want 3-year terms
• You have existing RDS RIs covering your workloads

For complete Database Savings Plans coverage including the RIs vs Database SP decision framework, discount structure by deployment type, and sizing methodology, see the complete Database Savings Plans guide.

Savings Plans vs Reserved Instances: When to Use Each

The Savings Plans vs Reserved Instances decision comes down to flexibility versus capacity reservation. Both offer up to 72% discounts, but they work differently.

Understanding when each makes sense helps you build an optimal commitment strategy.

Side-by-Side Comparison Table

The fundamental difference: Savings Plans commit to spend, Reserved Instances commit to configuration. This makes Savings Plans more adaptable to changing architectures.

When Reserved Instances Still Make Sense

Despite AWS recommending Savings Plans for most workloads, Reserved Instances have specific advantages:

Capacity Reservations: Standard RIs provide AZ-specific capacity reservations. If you need guaranteed capacity during peak demand (think Black Friday for retail), Standard RIs ensure AWS reserves that capacity for you. Savings Plans don't offer this.

Existing RI portfolio: If you have RIs with good utilization, there's no reason to change. RIs and Savings Plans work together, with RIs applying first.

SLES instances: Savings Plans prices for SUSE Linux Enterprise Server instances differ from corresponding RI prices. Depending on your configuration, RIs might offer better value.

Hybrid strategy: Use RIs for capacity-critical workloads where you need guaranteed availability, and Savings Plans for everything else.

Migrating from RIs to Savings Plans

If you have existing Reserved Instances and want to transition to Savings Plans:

1. Let RIs expire naturally: No penalty for letting RIs run their term
2. Replace with Savings Plans as RIs expire: Start purchasing Savings Plans to cover the gap
3. Use Purchase Analyzer to model the transition: See how your coverage changes as RIs expire
4. Consider Convertible RIs: These can be exchanged for other configurations, giving you time to evaluate

You can run both simultaneously without issues. Reserved Instances apply first, then Savings Plans cover remaining eligible usage. This makes migration a gradual process rather than a risky switch.

How to Choose the Right Savings Plan Type

Choosing between the four Savings Plans types isn't about which has the highest discount. It's about matching your workload characteristics to the right commitment model.

Here's a decision framework that no AWS documentation provides.

Decision Framework by Workload Type

Quick decision guide:

Layering Multiple Savings Plans Types

You can combine multiple Savings Plans types for maximum coverage and savings. Here's how layering works:

Example strategy:

• EC2 Instance Savings Plans for production R5 instances (72% discount)
• Compute Savings Plans for dev/test environments (66% discount)
• Database Savings Plans for RDS and DynamoDB (35% discount)
• SageMaker AI Savings Plans for ML workloads (64% discount)

Application order when layering:

1. EC2 Instance Savings Plans apply first (more specific)
2. Compute Savings Plans apply to remaining compute usage
3. Database and SageMaker Savings Plans apply independently to their respective services

This layering strategy uses more specific plans (higher discount) for stable workloads and flexible plans (lower discount) for variable workloads. You can also use AWS cost estimation tools to model layered scenarios. Note that AI inference costs like Amazon Bedrock pricing are per-token and sit outside Savings Plans entirely.

Commitment Sizing: How Much to Commit

This is where most organizations make costly mistakes. The key principle: commit to baseline usage, not peak.

Sizing guidelines:

• Target 70-80% of BASELINE usage: Not peak, not average including spikes
• Start conservative: You can always add more Savings Plans later
• Use 30-day lookback for typical workloads, 60-day for seasonal
• Exclude one-time spikes from your analysis

Why conservative sizing wins:

• Better to under-commit and pay some On-Demand than over-commit and waste money
• You can add more Savings Plans at any time
• Unused commitment is lost every hour with no rollover

Breakeven calculation: If you're comparing All Upfront vs No Upfront, calculate your breakeven point:

Breakeven hours = Upfront cost / Hourly savings rate

Ensure your workload will run long enough to exceed breakeven before committing.

Before committing to any Savings Plan, estimate your AWS costs to understand your baseline usage patterns.

How to Purchase Savings Plans

The purchase process is straightforward, but using the right tools before purchasing can prevent costly mistakes.

AWS provides several tools to help you make informed decisions: Recommendations, Purchase Analyzer, and the shopping cart. Let's walk through each.

Understanding AWS Recommendations

AWS generates personalized Savings Plans recommendations based on your historical usage patterns. You'll find these in AWS Cost Explorer under Savings Plans > Recommendations.

How recommendations work:

• Based on past usage (7, 30, or 60 day lookback period)
• Analyzes On-Demand usage patterns
• Optimized to maximize savings at the payer account level
• Includes estimated monthly savings, coverage, and utilization

Limitations to be aware of:

• Recommendations don't account for planned changes or migrations
• They don't consider seasonal variations unless you use appropriate lookback
• Payer account recommendations optimize for organization-wide savings, not individual accounts

My recommendation: Use AWS recommendations as a starting point, not a final decision. Validate with your knowledge of upcoming workload changes before purchasing.

Using the Savings Plans Purchase Analyzer

The Savings Plans Purchase Analyzer (launched November 2024) is an interactive tool that lets you model purchase scenarios before committing. This is the tool I recommend using before every purchase.

Key capabilities:

• Estimate cost, coverage, and utilization impact
• Use custom lookback periods (select specific days within last 60 days)
• Exclude expiring Savings Plans from analysis
• Compare multiple commitment amounts
• View hourly impact across your historical period

Three output charts:

1. Cost Chart: On-Demand cost vs estimated cost with Savings Plan
2. Coverage Chart: Percentage of eligible usage covered over time
3. Utilization Chart: How much of your commitment is being used

How to access: AWS Billing and Cost Management Console > Savings Plans > Purchase Analyzer

Pro tip: Use the "exclude expiring Savings Plans" option when planning renewals. This shows you what coverage looks like after current plans expire.

Step-by-Step Purchase Process

1. Navigate to Savings Plans: AWS Billing and Cost Management Console > Savings Plans
2. Review Recommendations: Check the Recommendations page for AWS-generated suggestions
3. Run Purchase Analyzer (recommended): Model your commitment before purchasing
4. Configure your purchase:
   • Select Savings Plans type (Compute, EC2 Instance, SageMaker, Database)
   • For EC2 Instance SP: Select region and instance family
   • Choose term (1-year or 3-year)
   • Choose payment option (All Upfront, Partial Upfront, No Upfront)
   • Enter hourly commitment amount ($/hour)
5. Add to Cart: Review your selections
6. Submit Purchase: Finalize and submit

The purchase activates immediately unless you're queueing for a future date.

Queuing Purchases for Future Dates

You can queue Savings Plans purchases up to 3 years in advance. This is useful for:

• Replacing expiring Savings Plans seamlessly
• Planning for known future workload launches
• Budget planning for upcoming quarters

How it works:

• Set a specific start date for activation
• Charges only apply when the queued purchase activates
• You can delete queued purchases before the start date
• Queued purchases appear with "Queued" status in your inventory

The 7-Day Return Policy

AWS introduced a 7-day return window for Savings Plans in March 2024, providing a safety net for purchase mistakes.

Eligibility requirements:

• Purchased within last 7 days
• Purchased in the same calendar month
• Hourly commitment is $100 or less
• Haven't reached return limit

Return limit: Maximum of 10 returns per management account per calendar year

What happens when you return:

• Full refund for any upfront charges
• Usage during the return period is charged at On-Demand rates

This return policy provides peace of mind for smaller purchases, but doesn't cover large commitments. Always use Purchase Analyzer before committing to amounts over $100/hour.

Savings Plans in AWS Organizations

For organizations with multiple AWS accounts, understanding how Savings Plans sharing works is essential for maximizing utilization and managing costs across business units.

AWS Organizations provides flexible options for sharing Savings Plans benefits across accounts.

Organization-Wide Discount Sharing

By default, Savings Plans benefits are shared across all accounts in your AWS Organization:

1. Owner account usage is covered first: The account that purchased the Savings Plan gets priority
2. Remaining benefits shared: After the owner account's usage is covered, remaining commitment benefits other organization accounts
3. Maximizes utilization: Cross-account sharing prevents unused commitment from going to waste

Both the purchasing account and benefit-receiving accounts must have sharing enabled. Management account controls these settings.

For detailed guidance on structuring your accounts, see the AWS multi-account strategy guide and AWS Organizations setup.

Group Sharing: Prioritized and Restricted Modes

Launched in November 2024, Group Sharing provides more granular control over how Savings Plans benefits are distributed:

Prioritized Group Sharing:

1. Owner account usage covered first
2. Benefits shared with accounts in defined groups
3. Remaining benefits shared with other organization accounts

Restricted Group Sharing:

1. Benefits exclusively shared within defined account groups
2. No sharing outside designated groups
3. Complete isolation between groups

Configuration:

• Groups are defined using AWS Cost Categories
• Each account can belong to only one sharing group
• Payer account is not part of sharing groups
• Available in all regions except GovCloud and China

Use cases:

• Business unit chargeback: Keep department Savings Plans benefits within that department
• Regulatory isolation: Prevent sharing between compliance-sensitive accounts
• Cost allocation: Simplify cost attribution by limiting benefit sharing

Centralized vs Decentralized Purchasing Strategy

Three approaches for multi-account organizations:

Centralized (Recommended for most):

• Management account purchases based on organization-wide recommendations
• Maximizes overall savings through cross-account sharing
• Simplifies management and tracking
• Better utilization through automatic benefit distribution

Decentralized:

• Each business unit purchases for their accounts
• Maintains budget accountability per team
• More complex to manage overall
• May result in lower utilization if accounts have variable usage

Hybrid:

• Central purchases for shared/common workloads
• Teams purchase for team-specific, predictable workloads
• Balances centralization benefits with team accountability

For most organizations, centralized purchasing with organization-wide sharing delivers the best overall savings.

Monitoring and Optimizing Your Savings Plans

Purchasing Savings Plans is just the beginning. Ongoing monitoring ensures you're getting the expected value and helps you plan for renewals.

Two key metrics matter: Coverage and Utilization. Understanding the difference is crucial.

Coverage vs Utilization: What's the Difference?

These metrics answer different questions:

Utilization: "Am I wasting any of my commitment?"

Utilization = (SP commitment used) / (Total SP commitment) x 100%

• Target: 100% (using everything you committed to)
• Low utilization means you over-committed

Coverage: "How much of my usage is discounted?"

Coverage = (Usage covered by SP) / (Total eligible usage) x 100%

• Target: 70-90% (leave room for peaks at On-Demand)
• Low coverage means opportunity for more Savings Plans

Example scenario:

• You have $10/hour commitment
• You have $8/hour of usage

Utilization: $8 / $10 = 80% (you're wasting 20% of commitment) Coverage: 100% (all your usage is covered)

This example shows why both metrics matter. High coverage but low utilization means you over-committed. Low coverage but high utilization means you have room for additional Savings Plans.

Setting Up Alerts and Budgets

AWS provides several alerting mechanisms:

Expiration Alerts:

• Alert 1, 7, 30, or 60 days before Savings Plans expire
• Up to 10 email recipients per alert
• Essential for planning renewals

Queued Alerts:

• Alert before queued purchases activate
• Same timing options as expiration alerts

Utilization Budgets:

• Set threshold (e.g., alert if utilization drops below 80%)
• Receive email or SNS notifications
• Helps catch over-commitment early

Coverage Budgets:

• Set threshold (e.g., alert if coverage drops below 70%)
• Identifies opportunities for additional purchases

EventBridge Integration: For advanced automation, Savings Plans emit events to EventBridge when state changes occur:

• payment-pending to active
• active to retired
• queued to active

You can use these events to trigger Lambda functions for automated workflows.

Quarterly Review and Renewal Process

Establish a regular review cadence:

Monthly quick check:

• Is utilization above 95%?
• Is coverage appropriate for your workloads?

Quarterly deep review:

• Analyze utilization trends
• Evaluate additional purchase opportunities
• Check for expiring Savings Plans in next 90 days

Renewal planning (start 30-60 days before expiration):

1. Run Purchase Analyzer with "exclude expiring SP" option
2. Evaluate if commitment level should change
3. Queue renewal purchases for seamless coverage
4. Consider workload changes since last purchase

Common Savings Plans Mistakes and How to Avoid Them

Even with the best intentions, teams make predictable mistakes with Savings Plans. Here's how to avoid the most costly ones.

Over-Committing Based on Peak Usage

The mistake: Using peak or maximum usage to size your commitment.

The result: Low utilization, wasted money every hour.

Prevention:

• Commit to baseline (steady-state) usage only
• Target 70-80% of average baseline, not 100% of peak
• Use On-Demand or Spot for peak/burst capacity
• Remember: unused commitment every hour is lost forever

Ignoring Workload Changes Before Purchase

The mistake: Purchasing right before a migration, modernization, or decommission.

Example: Buying EC2 Instance Savings Plans right before migrating to Fargate.

Prevention:

• Consider upcoming changes in the next 1-3 years
• If uncertain, choose Compute Savings Plans (more flexible)
• Use shorter 1-year terms if changes are likely
• Wait to purchase if major architecture changes are imminent

The "Set and Forget" Trap

The mistake: Purchasing Savings Plans and never reviewing utilization.

The result: Utilization drops as workloads change, money wasted.

Prevention:

• Set up utilization budget alerts (alert at less than 80% utilization)
• Quarterly reviews to assess trends
• Adjust future purchases based on utilization data
• Plan renewals proactively, not reactively

Recovery Strategies If You've Over-Committed

If you've already over-committed, your options are limited:

No secondary marketplace: Unlike Reserved Instances, you cannot sell unused Savings Plans commitment.

Cannot cancel or modify: Once purchased, the commitment stands for the full term.

Recovery options:

1. Shift workloads: If possible, move more workloads to utilize commitment
2. Increase eligible usage: Add workloads in other areas covered by your Savings Plans
3. Accept the loss: Size correctly next time

If purchased recently:

• Use the 7-day return policy (if commitment is $100/hour or less)
• Return limit is 10 per management account per year

Prevention for next time:

• Always use Purchase Analyzer before purchasing
• Start conservative, add more later
• Target 70-80% of baseline, not 100%

Summary and Next Steps

Savings Plans offer significant cost savings, but choosing the right type matters more than chasing the highest discount percentage. Here's what to remember:

Four types, four use cases:

• Compute Savings Plans (66%): Maximum flexibility for evolving architectures
• EC2 Instance Savings Plans (72%): Maximum discount for stable instance families
• SageMaker AI Savings Plans (64%): ML workload optimization
• Database Savings Plans (35%): Flexibility across database services

Key principles:

• Commit to baseline usage (70-80%), not peak
• Use Purchase Analyzer before every purchase
• Monitor utilization monthly, review quarterly
• Start conservative, you can always add more

Your next step: Review your AWS Cost Explorer recommendations and run a Purchase Analyzer simulation for your highest-spend compute or database workloads. Understand your baseline before committing.

For a comprehensive approach to AWS cost management beyond Savings Plans, check out AWS cost optimization best practices and the cost optimization checklist.

What's your biggest challenge with AWS Savings Plans? Drop a comment below and I'll help you work through it.

Frequently Asked Questions