How to Optimize AWS cost by 20%

Introduction

Cloud computing has revolutionized how businesses operate, with Amazon Web Services (AWS) leading the charge as the dominant cloud service provider. While AWS offers incredible scalability and functionality, many organizations find themselves facing unexpectedly high monthly bills. If you've ever experienced sticker shock when opening your AWS invoice, you're not alone. The good news? There are numerous ways to optimize AWS costs without compromising performance or requiring major architectural overhauls.

In this guide, I'll walk you through practical, actionable strategies to cut AWS costs while maintaining—or even improving—your cloud infrastructure's performance. Whether you're a startup watching every dollar or an enterprise looking to optimize cloud spending, these approaches can help you achieve significant savings without adding engineering overhead.

Understanding Your AWS Spending

Before you can effectively optimize AWS costs, you need clear visibility into where your money is going. This starts with proper cost analysis and monitoring tools.

Leveraging AWS Cost Explorer

AWS Cost Explorer is your first line of defense against unnecessary spending. This powerful tool allows you to visualize, understand, and manage your AWS costs and usage over time. I've found that regular use of Cost Explorer helps identify spending patterns you might otherwise miss.

When I first started using Cost Explorer for a client project, we discovered nearly 20% of their spending was on unused or underutilized resources. The intuitive interface makes it easy to:

• View cost data for the past 13 months
• Forecast potential spending for the next three months
• Filter and group data by various dimensions (services, linked accounts, tags)
• Save reports for regular review

Don't overlook the power of Cost Explorer's resource utilization reports. These reports specifically help identify EC2 instances and RDS instances that are either idle or significantly underutilized—prime candidates for downsizing or termination.

Setting Up Budgets and Alerts

Once you understand your spending patterns, set up AWS Budgets to create custom budgets and receive alerts when costs exceed (or are forecasted to exceed) your specified thresholds. I recommend:

• Creating separate budgets for different departments or projects
• Setting alerts at 50%, 80%, and 100% of budget thresholds
• Reviewing and adjusting budgets quarterly

One client implemented this strategy and caught a development environment that had been accidentally left running over a weekend—saving them hundreds of dollars by receiving an alert when spending suddenly spiked.

Right-Sizing Your Resources

One of the most effective ways to optimize AWS costs is ensuring you're using appropriately sized resources for your workloads. Many organizations significantly overprovision resources "just to be safe," but this approach directly impacts your bottom line.

Instance Right-Sizing

According to AWS's own data, right-sizing is typically the most impactful cost-optimization lever, potentially reducing costs by up to 36%. Here's my approach to effective instance right-sizing:

1. Analyze resource utilization. Monitor CPU, memory, storage, and network usage over 2-4 weeks to establish baseline requirements.
2. Identify underutilized instances. Look for instances consistently using less than 40% of provisioned resources.
3. Select appropriate instance types. Match workload requirements to the most cost-effective instance families and sizes.
4. Test before committing. Validate performance on the new instance type before finalizing changes.

For example, shifting from general-purpose m5.4xlarge instances to compute-optimized c5.2xlarge instances saved one of our clients nearly 30% on their EC2 costs while actually improving performance for their CPU-intensive workload.

Storage Optimization

Storage costs can quickly add up, particularly with EBS volumes and S3 buckets. Consider these strategies:

• Delete unattached EBS volumes. Run regular audits to identify and remove orphaned volumes.
• Implement S3 lifecycle policies. Automatically transition infrequently accessed data to cheaper storage classes like S3 One Zone-IA or Glacier.
• Use gp3 volumes instead of gp2. The newer gp3 volumes offer better price-performance ratio for most workloads.

I recently helped a client implement S3 lifecycle policies that automatically moved logs older than 30 days to S3 Glacier, reducing their storage costs by 70% without any impact on operations.

Leveraging Purchasing Options

AWS offers several purchasing options that can dramatically reduce costs compared to on-demand pricing. Understanding and strategically implementing these options can yield significant savings.

Reserved Instances and Savings Plans

For predictable workloads, Reserved Instances (RIs) and Savings Plans offer substantial discounts in exchange for commitments:

• Reserved Instances. Provide up to 72% discount compared to on-demand pricing for 1-3 year commitments.
• Savings Plans. Offer up to 72% savings with more flexibility than RIs, applying to EC2, Fargate, and Lambda usage.

In my experience working with clients across various industries, I've found that a balanced approach works best:

1. Cover your baseline capacity (60-70% of total usage) with 3-year Savings Plans or RIs for maximum discount
2. Use 1-year commitments for another 10-15% of your predictable but less certain workloads
3. Keep the remaining capacity on-demand for flexibility

One enterprise client implemented this strategy and reduced their overall AWS compute costs by 43% in the first year.

Spot Instances for Non-Critical Workloads

Spot Instances offer discounts of up to 90% compared to on-demand pricing, making them incredibly cost-effective for fault-tolerant workloads like:

• Batch processing jobs
• CI/CD pipelines
• Testing environments
• Stateless web services with load balancing

When implementing Spot Instances, it's crucial to:

• Design applications to handle instance termination gracefully
• Use Spot Fleet to maintain target capacity across multiple instance types
• Implement checkpointing for long-running processes

A media processing client of ours shifted their background processing jobs to Spot Instances and reduced those specific workload costs by 87% while still maintaining throughput requirements.

Implementing Automation for Cost Control

Manual optimization can only take you so far. Implementing automation ensures continued cost efficiency without constant human intervention.

Automated Instance Scheduling

Not all workloads need to run 24/7. Development, testing, and staging environments are prime candidates for scheduled shutdowns:

• Use AWS Instance Scheduler to automatically start and stop EC2 and RDS instances based on schedules
• Implement Lambda functions with CloudWatch Events for custom scheduling logic
• Consider third-party solutions for more complex scheduling needs

I've seen non-production environment costs reduced by 65% simply by shutting down resources outside of business hours (nights and weekends).

Auto-Scaling Based on Demand

Proper auto-scaling ensures you're only paying for capacity when you actually need it:

• Implement target tracking scaling policies based on actual metrics like CPU utilization or request count
• Use predictive scaling for workloads with regular patterns
• Don't forget to scale down databases and other supporting services alongside application tiers

One e-commerce client implemented proper auto-scaling before Black Friday, and despite handling 3x their normal traffic, their costs only increased by 60% compared to baseline—a much better outcome than provisioning for peak load year-round.

Clean-Up and Governance

Even with the best intentions, AWS environments tend to accumulate wasted resources over time. Regular clean-up efforts and proper governance are essential for ongoing cost optimization.

Resource Tagging and Cost Allocation

Implementing a comprehensive tagging strategy enables accurate cost allocation and identifies opportunities for optimization:

• Tag all resources with owner, project, environment, and cost center
• Use tag-based access control to enforce tagging policies
• Regularly review untagged resources and assign ownership

When implemented correctly, this approach not only helps with cost allocation but also creates accountability that naturally reduces waste. Our team at Perfsol has extensive experience implementing tagging strategies that have helped clients reduce "unknown" spending by over 90%.

Regular Clean-Up Procedures

Schedule regular clean-up tasks to maintain an efficient environment:

• Delete unused AMIs, snapshots, and backups
• Terminate zombie instances that aren't part of production workloads
• Remove unused Elastic IPs, load balancers, and NAT gateways
• Clear out unneeded CloudWatch logs and old versions in S3 buckets

These "spring cleaning" activities typically reduce overall AWS spending by 5-15% with no impact on performance or reliability.

Conclusion

Optimizing AWS costs doesn't have to involve massive architectural changes or significant engineering overhead. By implementing the strategies outlined in this guide—understanding your spending through AWS Cost Explorer, right-sizing resources, leveraging favorable purchasing options, implementing automation, and maintaining good governance—you can significantly reduce your cloud spending while maintaining or even improving performance.

At Perfsol, our team of AWS cost optimization experts has helped businesses of all sizes cut their AWS costs by an average of 35% without compromising on performance or reliability. With our extensive experience in AWS architecture and cost optimization, we understand the nuances of building efficient cloud environments that balance performance and cost.

Ready to stop overpaying for your AWS infrastructure? Whether you need help implementing these strategies or want a comprehensive review of your current AWS environment, the Perfsol team is here to help. Contact us today to discover how our expertise can transform your cloud spending and optimize your AWS costs.

Resources

For more information on AWS cost optimization strategies, check out these valuable resources:

• Optimize AWS Costs Without Architectural Changes or Engineering Overhead
• AWS Cost Explorer Documentation
• AWS Savings Plans Overview