Executive Summary: AWS costs can spiral out of control without proper management. This guide shares ten battle-tested strategies that have helped AWS customers achieve 20-75% cost reductions without sacrificing performance or availability. From immediate tactical wins like rightsizing and scheduled scaling to strategic approaches like serverless architecture transformation, each recommendation includes concrete implementation guidance and typical savings potential.
AWS offers a vast array of powerful services, but its complexity can lead to unexpected costs. Many small and mid-sized businesses we've worked with have faced "bill shock" at some point in their cloud journey.
AWS emphasizes cost optimization as a core pillar of its Well-Architected Framework. Understanding this pillar not only delivers immediate savings but also fosters a culture of cost-consciousness, enabling your business to achieve more with less.
However, even with the Framework's guidance, many organizations struggle to implement practical cost-saving strategies. This guide shares actionable best practices that have helped customers reduce their AWS bills by between 20% - 100%.
For personalized insights, join one of our Cloud Cost Clinics, where we'll evaluate these strategies against your current AWS environment and create a roadmap to reduce your monthly spend within 30 days.
Savings Potential: Up to 100% | Implementation Difficulty: Low
The first tip to reduce your bill is to not have one to start with. AWS provides numerous credit programs that can help organizations of all sizes offset initial exploration and adoption costs.
For Startups, programs like AWS Activate can provide a route to your first few $100k of credits. This can be a dramatic boost for companies to get them started on the AWS platform.
As a more established business, your AWS account manager is your best resource. While finding this person isn't always straightforward, you can use the Sales Support form to connect with your account team.
While there's no guarantee you'll be eligible for credits, we've found that discussing future growth plans with your AWS team increases your chances significantly. As AWS Partners, we regularly sit down with customers to navigate available credit programs and help prepare compelling business cases.
Top Tip: Spend credits as if they're your own money
Whether you've been granted $100 or $500k of AWS credits, maintain cost-conscious practices. We've seen too many companies burn through credits with inefficient architectures, only to face painful re-engineering when credits expire. The strategies in this article apply even if you're currently using credits.
Savings Potential: Up to 75% | Implementation Difficulty: Medium
It sounds simple, but consistently, we see clients forgetting to delete or stop resources they're not using. One financial services client we've seen in the past was spending over $1,000 monthly on development environments that were only used during business hours.
Consider a typical business with developers working 9-5, Monday to Friday. That's only 40 of the 168 hours per week (23.8%), meaning up to 76% of compute costs for development environments could be unnecessary.
For development and non-production environments, automated scheduling can deliver immediate savings. Tools like Amazon EventBridge can notify teams to turn environments off or automatically handle this for you. One media customer implemented scheduled shutdowns for their dev environments and saved $1,500 monthly with just two hours of implementation work.
For more sophisticated scheduling, the Instance Scheduler on AWS can stop and start EC2 & RDS instances on specific schedules, accounting for holidays and special events.
Top Tip: Use Infrastructure as Code
When building a new service or experimenting with AWS, make use of infrastructure as code (IaC) tools like AWS CloudFormation, Terraform or AWS CDK. These tools have built-in destroy capabilities that can remove all deployed resources at once – preventing forgotten resources from accruing costs. As an added benefit, IaC improves deployment consistency when you move to production.
Warning - Beware of Production Impact
Scheduling tools can cause serious disruption if improperly configured. We recommend only running solutions like the EC2 instance scheduler in accounts designated as non-production. For IaC tools, use AWS profiles and restrict production access to trusted team members with proper training.
Savings Potential: Up to 35% | Implementation Difficulty: Medium
One of cloud computing's greatest advantages is the ability to scale resources on demand. However, many organizations fail to configure effective scaling strategies due to unclear documentation, lack of application behavior understanding, or simple procrastination.
There are two primary approaches to auto-scaling that deliver quick wins:
If your application has predictable usage patterns, scheduled scaling can be highly effective. For example, if you run a financial application primarily used during trading hours, you can schedule scaling to increase capacity before the market opens and decrease it after closing.
For applications with less predictable traffic, metrics-driven scaling is essential. Target Tracking policies aim to maintain a specific metric (like 70% CPU utilization) by automatically adding or removing capacity. Step Scaling offers more control for applications with unique scaling characteristics.
Top Tip: Leverage Load Tests to Understand Application Performance
Effective auto-scaling requires understanding your application's behavior under various conditions. We recommend conducting gradual load tests to observe how your application responds to increasing traffic.
A rule of thumb we use with clients: your application should handle 10x normal traffic without auto-scaling, and 100x normal traffic with auto-scaling. Beyond that, architectural redesign may be necessary. This approach prevents over-engineering while ensuring adequate capacity for growth.
Savings Potential: Up to 20% | Implementation Difficulty: Medium
Over-provisioning resources is one of the most common and easily fixable cost inefficiencies we encounter. Many organizations migrate from on-premises to AWS and simply replicate their existing resource allocation - despite the cloud's flexibility to scale on demand.
Getting familiar with EC2 instance families can unlock significant savings. For compute-intensive applications, instance classes like c6i or c7g may provide better price-performance than general-purpose options. For memory-intensive workloads, r-series instances often deliver better value.
We recommend that once you're familiar with how your application behaves on EC2 that you perform right-sizing to better match your application to the resources that it needs to operate effectively.
EC2 automatically provides CPU metrics, while memory utilization requires the Amazon CloudWatch Agent. After collecting these metrics for 2-3 weeks, you'll have a clearer picture of actual resource requirements versus what you've provisioned.
Top Tip: Use Canary Deployments for Risk-Free Experimentation
If you've implemented automated deployments, you're well-positioned to test different instance types. In production environments, canary deployments let you route a small percentage of traffic to instances with different configurations, allowing you to compare performance before committing to changes.
Savings Potential: Up to 90% | Implementation Difficulty: Medium-High
Amazon EC2 Spot Instances provide access to unused EC2 capacity at discounts up to 90% compared to On-Demand prices. While not suitable for all workloads, Spot Instances can dramatically reduce costs for fault-tolerant applications.
Batch processing jobs are perfect candidates for Spot because occasional interruptions simply mean jobs will restart, not fail completely.
Unlike earlier implementations, modern Spot Instances provide clearer visibility via interruption notices, giving applications time to save state and gracefully handle transitions. AWS has also expanded Spot availability to services like AWS Fargate and Amazon SageMaker Training, broadening potential use cases.
Top Tip: Use Spot for Non-Production Workloads
Even if your production applications require the reliability of On-Demand instances, consider Spot for development and testing environments. This approach not only reduces costs but also helps teams design more resilient applications by exposing them to occasional instance failures-similar to chaos engineering principles.
Savings Potential: Up to 20% | Implementation Difficulty: Medium
AWS Graviton processors are custom ARM-based chips that deliver better price-performance than x86 alternatives. Graviton instances (identified by "g" in their names, like t4g, c7g) typically cost 20% less while offering comparable or better performance for many workloads.
For applications built with modern languages and frameworks, the transition is often straightforward.
The primary challenge lies in compatibility with applications or dependencies that require x86-specific binaries. Companies with mixed development environments (Macs with M-series chips and Windows/Linux x86 machines) may already be familiar with cross-architecture builds.
See our solution for a simple multi-arch build pipeline on GitHub.
AWS has extended Graviton support to EC2, AWS Fargate, AWS Lambda, and other services, creating multiple opportunities for cost optimization.
Top Tip: Start with ARM-based Databases
Database workloads often benefit significantly from Graviton processors. If you use managed database services like Amazon RDS for PostgreSQL or MySQL, switching to Graviton-based instances is typically seamless and delivers immediate savings.
Saving Potential: Up to 68% | Implementation Difficulty: Low
Organizations with large data storage needs can achieve substantial savings through smarter storage management. S3 intelligent tiering automatically moves objects between access tiers based on usage patterns, optimizing costs without sacrificing performance for frequently accessed files.
S3 offers multiple storage classes with different price points and retrieval characteristics:
With minimal configuration, you can implement lifecycle policies that automatically transition objects to appropriate tiers based on age or access patterns.
Saving Potential: Up to 100% | Implementation Difficulty: High
Serverless architectures represent the ultimate form of consumption-based pricing-you pay only when your code runs. For organizations with variable workloads or applications still building their user base, serverless can eliminate idle resource costs entirely.
The serverless ecosystem has matured significantly, with services like AWS Lambda, API Gateway, EventBridge, SQS, and DynamoDB forming a robust foundation for modern applications. Even traditionally resource-intensive services like EMR, Redshift, and OpenSearch now offer serverless options.
Top Tip: Start with Asynchronous Workloads
You don't need to rebuild your entire application to benefit from serverless. Begin by identifying asynchronous processing tasks-like report generation, data processing, or scheduled jobs-that can be extracted from your main application.
Savings Potential: Up to 75% | Implementation Difficulty: Low
For stable workloads you expect to run for at least a year, Reserved Instances (RIs) and Savings Plans offer substantial discounts in exchange for time commitments.
For example: A healthcare client with predictable workloads could implemented a mix of 1-year and 3-year Savings Plans, reducing their monthly compute bill by up to 42% with no architectural changes. The key is to carefully analyze your usage patterns to determine the appropriate commitment level.
RIs require commitments to specific instance families and regions for 1 or 3 years. The discount increases with upfront payment-All Upfront offering the highest discount, followed by Partial Upfront and No Upfront options.
AWS provides an RI recommendations feature in the cost-management console that acts as the perfect starting point.
Savings Plans provide similar discounts but with greater flexibility. Rather than committing to specific instances, you commit to a consistent hourly spend. This spending can apply to EC2, Fargate, and Lambda usage, providing flexibility as your architecture evolves.
Top Tip: Start with Partial Commitments
If you're uncertain about future requirements, start by committing to 60-70% of your current stable usage. For example, if you spend $10,000 monthly on compute and expect at least $7,000 to remain consistent, a Savings Plan at that level provides immediate savings while maintaining flexibility for future optimizations or workload changes.
Savings Potential: Up to 30% | Implementation Difficulty: Medium-High
Network costs often go unnoticed until applications scale, at which point they can become a significant portion of your AWS bill. Two areas frequently offer optimization opportunities:
NAT Gateways allow resources in private subnets to access the internet. While they provide high availability, they incur charges based on both hourly uptime and data processing.
For applications with high traffic to AWS services like S3 or DynamoDB, VPC Endpoints provide direct connectivity without routing through NAT Gateways.
For non-production environments where high availability is less critical, NAT Instances (EC2 instances configured as NAT gateways) can provide similar functionality at a lower cost, though with increased management overhead.
While deploying across multiple Availability Zones (AZs) is essential for production reliability, it introduces cross-AZ data transfer charges when resources communicate between zones.
For development and testing environments, consolidating resources in a single AZ can eliminate these charges entirely.
For production, optimizing application communication patterns to minimize cross-AZ traffic can yield significant savings. Techniques like zone-aware routing and caching can reduce unnecessary data transfers while maintaining high availability.
Especially for customers making use of EKS, managing inter-AZ traffic is essential.
Getting your head around these cost levers takes time and expertise. Our AWS Cloud Cost Clinic provides a structured approach to reducing your AWS spend:
We're a relatively new practice but have got extensive experience in the AWS platform. We're eager to help companies lower their bill so that they can have a more successful AWS cloud journey.
At all points we like to communicate with our clients and keep you informed about next steps tha the process.
Ready to get control of your AWS costs? Schedule your free 30-minute discovery call today to learn how our proven approach can help your organization optimize cloud spending while improving performance and reliability.
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