AWS Cost Optimization Checklist: 20 Proven Ideas to Consider

Managing AWS costs can be tricky, especially when your cloud usage keeps growing, and you don’t always see where the money is going. Idle EC2 instances, oversized databases, unused storage, and constant data transfers can quietly push your bill up month after month.

This blog gives you 20 practical and simple ways to optimize AWS costs. You’ll learn how to rightsize instances, move the right workloads to serverless, use affordable storage tiers, cut network charges, and set up budgets, alerts, and cleanups so costs stay under control.

Whether you’re a developer aiming to sharpen your AWS cost management skills or a business leader exploring DevOps strategies to optimize spend, this checklist is for you. It highlights where to look, what to change, and how to plug common cost leaks. Start using it today and turn your AWS bill into a competitive advantage.

The Business Case for Optimizing AWS Costs

Optimizing your AWS spend isn’t just about cutting expenses – it’s about making the cloud work smarter for your business. As applications scale, services expand, and workloads shift, costs can quickly outpace growth if not managed carefully. Effective cost optimization ensures that every dollar spent on AWS contributes directly to performance, scalability, and long‑term value.

Key benefits include:

• For business owners: predictable monthly bills, healthier profit margins, fewer financial surprises, and easier budgeting
• For developers: cleaner architectures, fewer oversized or idle resources, and systems that are easier to maintain and scale
• For overall AWS usage: pay‑as‑you‑go efficiency, reduced costs through smart choices like shutting down idle resources or selecting the right storage tier, and a culture of ongoing optimization that keeps your cloud lean, stable, and ready to grow

20 Proven Ways to Optimize AWS Costs

These 20 tips cover compute, storage, databases, networking, and billing, and will help you manage AWS costs without slowing down your applications.

1. Rightsize Underutilized EC2 Instances

Many organizations run EC2 instances that are far larger than they need – simply because they want to “play safe” or because the instance was provisioned during a busy period and never adjusted later. CloudWatch metrics and AWS Compute Optimizer can help you quickly identify instances where CPU, memory, or network usage is low.

Rightsizing involves:

• Moving to smaller instance types
• Switching to burstable T-series instances
• Breaking monolithic servers into multiple smaller instances if needed

With careful evaluation, you can reduce compute spending without affecting performance.

2. Move Suitable Workloads to Serverless

If your applications don’t need to run 24/7, moving suitable workloads to serverless is one of the most effective AWS cost optimization tactics. Services like AWS Lambda and AWS Fargate bill only when your code runs, making them ideal for spiky APIs, background jobs, and scheduled tasks. For low-utilization workloads, shifting from always-on EC2 to serverless can cut compute costs by up to 70–80%, because you replace idle capacity with pay-per-invocation pricing and turn architecture choices directly into ongoing AWS savings with no loss in performance.

3. Switch to Newer-generation Instance Types

Newer instance families, especially AWS Graviton-based types, such as M7g, C7g, and T4g, offer better performance at a lower price point. They are designed to do more work per dollar. If you move from older instances (such as M4/M5 or C4/C5) to Graviton-based ones, many workloads can run 20 to 40% cheaper while keeping performance the same or even better. It can lead to quick AWS cost savings with a few changes.

4. Use Auto Scaling to Prevent Paying for Idle Capacity

Instead of keeping large instances running all the time “just in case,” set up Auto Scaling to adjust capacity based on real traffic. When demand is high, Auto Scaling adds instances; when demand drops, it removes them. This helps you avoid paying for unused compute at night, on weekends, or during off-peak hours and is a key part of AWS cost management tactics. If you work with AWS DevOps services, they can help you design and fine-tune scaling policies so your applications stay responsive while your costs stay predictable.

5. Move Old or Rarely Used Data to Cheaper S3 Tiers

Not all data needs to sit in S3 Standard. For logs, backups, archives, reports, and old data, S3 Infrequent Access or Glacier tiers offer much lower pricing. By defining lifecycle rules, AWS can automatically move older data to cheaper tiers.

This approach gives you:

• Lower storage costs
• Automated data transitions
• No manual intervention once configured

It’s simple to set up and highly effective.

6. Delete Unattached EBS Volumes

When EC2 instances are terminated, their EBS volumes often remain. These “orphaned” volumes continue to generate charges even though they’re no longer used. Over time, as workloads scale, these unused volumes can accumulate.

Performing a periodic review of unattached EBS volumes ensures that you pay only for the disks your systems actively require.

7. Switch from gp2 to gp3 Volumes

gp3 volumes offer the same durability as gp2 but at a lower base price and with more flexible performance options. You can often get the same or better IOPS (Input/Output Operations Per Second) and throughput for less money. Upgrading your existing gp2 volumes to gp3 is simple and can ensure instant AWS cost savings, especially in environments with many instances and large disks.

8. Use Lifecycle Rules for Cleanup and Archiving

S3 buckets often accumulate logs, temporary files, and archives that never get cleaned up. Lifecycle rules allow you to:

• Delete old objects
• Transition files to cheaper tiers
• Manage data retention automatically

With lifecycle rules in place, bucket growth remains controlled and predictable.

9. Track Database Spend with AWS Budgets and Cost Explorer

Before you tune anything, you need clear visibility into what you’re paying for. Use AWS Budgets and Cost Explorer to break down database and data warehouse costs by service, tag, or environment, and spot trends or sudden spikes. Pair this with the AWS Cost and Usage Report (CUR) to drill into detailed usage patterns and identify quick-win areas to reduce AWS costs.

10. Use Aurora Serverless v2 for Variable Workloads

If your database traffic is highly variable, seasonal, or unpredictable, Aurora Serverless v2 can be more cost-effective than fixed-size instances. This is because it scales capacity up and down automatically, so you only pay for what you use. For standard RDS instances in non-production environments (like dev, QA, or staging), one of the simplest cost wins is to stop them outside business hours and start them again when needed. Combining Aurora Serverless for spiky workloads with stop/start schedules for non-prod RDS can deliver big savings without hurting performance or developer productivity.

11. Use DynamoDB Auto-scaling or On-demand Mode

With DynamoDB, it’s easy to over-provision read/write capacity “just to be safe,” but that often means paying for capacity you rarely use. Switching to auto-scaling or on-demand mode lets DynamoDB adjust capacity in line with real traffic, keeping your application responsive while cutting waste. This is a practical example of how AWS cost optimization built into the platform can quietly save you money every month.

12. Optimize Redshift with RA3 Nodes

In traditional Redshift setups, compute and storage scale together, so needing more storage can force you to pay for more compute than you actually need. RA3 nodes separate storage from compute, allowing you to scale each independently based on workload. This flexibility helps you fine-tune performance for heavy analytics jobs while still focusing on AWS cost optimization and long-term AWS cost management.

13. Reduce Inter-region and Cross-AZ Data Transfers

AWS charges extra when data moves between regions and between Availability Zones. If your services constantly talk across regions or AZs, you’re paying more than necessary. By placing tightly coupled services in the same region and minimizing cross-AZ traffic, you reduce transfer costs and improve performance at the same time.

14. Use CloudFront for Caching and Content Delivery

Amazon CloudFront caches your static and dynamic content closer to users around the world. This reduces the number of requests that hit your origin servers (like S3 or EC2). As a result, you pay less for data transfer from the origin and use less compute, both of which are critical parts of AWS cost optimization.

15. Use AWS Direct Connect for High-volume Workloads

If you regularly send large volumes of data between your on-premises data center and AWS, standard internet traffic can be costly and unpredictable. AWS Direct Connect provides a dedicated network link that can lower data transfer rates and give more consistent performance, leading to long-term savings for data-heavy workloads.

16. Use Reserved Instances or Savings Plans

If you know certain workloads will run for 1 to 3 years, reserved instances or savings plans can be much affordable than on-demand pricing. They work best for steady and predictable workloads, such as production databases or core application servers. A small amount of planning here can lead to big, long-term AWS cost savings.

17. Use Spot Instances for Flexible Workloads

Spot instances let you use spare AWS capacity at a large discount, often 70 to 90% lower than on-demand. The downside is that AWS can stop them on short notice. They’re ideal for flexible, fault-tolerant jobs, such as CI/CD pipelines, batch processing, machine learning training, or rendering, where interruptions are acceptable, and you want to reduce AWS costs. Many teams rely on AWS DevOps services to decide which workloads are safe to move to Spot, set up fallback strategies, and automate deployments so savings don’t come at the cost of reliability.

18. Tag All Resources for Accountability and Cost Tracking

Tags (such as project, team, environment, and owner) help you see exactly where your money is going and who owns which resources. Combine this with AWS Organizations and a multi-account setup – separate accounts for Dev, QA, Prod, and major workloads – so cost, security, and cleanup are easier to manage. With clear account boundaries and consistent tagging, it becomes much simpler to analyze spend in AWS Budgets, Cost Explorer, or AWS Cost and Usage Report (CUR), clean up unused resources, and charge costs back to the right teams.

19. Set AWS Budgets, Cost Alerts, and Anomaly Detection

With AWS Budgets and Cost Explorer, you can set monthly or project-based spending limits and get alerts when your actual or forecasted spend crosses those limits. Cost anomaly detection can also highlight sudden spikes, such as a misconfigured service, so you can fix issues before they turn into a large bill.

20. Perform Monthly Cleanup Reviews and NAT Optimization

Over time, your account can fill up with unused snapshots, old AMIs, idle Elastic IPs, leftover NAT gateways, and unused load balancers. Each one adds small but steady costs. NAT Gateways, in particular, can become a major hidden expense because you pay per GB processed. Use Cost Explorer to find high-traffic NATs, then add Gateway VPC Endpoints for S3 and DynamoDB, and Interface Endpoints for frequently used services so traffic bypasses the NAT. Combine this with a monthly cleanup of unused resources to keep both obvious and hidden AWS costs under control.

Tools to Automate AWS Cost Optimization

AWS provides several built-in tools that make it easier to automate monitoring, rightsizing, and cleanup. Here are a few of them:

• AWS Trusted Advisor

  Trusted Advisor scans your account and points out idle or underused resources, along with other best practices. It’s a quick way to find easy cost-saving opportunities.

• AWS Compute Optimizer

  Compute Optimizer looks at how your EC2, EBS, Lambda, and container workloads are used and suggests better sizes or instance types. This helps you rightsize resources without guesswork.

• AWS Cost and Usage Report (CUR)

  The Cost and Usage Report gives a detailed view of where your money is going across services, accounts, and tags. It is useful for spotting trends and tracking the impact of your cost optimization efforts.

• Third-party FinOps Tools

  Tools like CloudHealth, Spot.io, and Harness add extra automation and reporting on top of AWS. They can help larger teams manage budgets, get alerts, and apply AWS cost optimization policies at scale.

Sample Cost-saving Scenarios

Here are a few simple examples that show how small changes can deliver meaningful AWS cost savings:

• Switching EC2 Workloads to Spot Instances

  Many flexible or fault-tolerant workloads can run on Spot Instances, often saving 70 to 90% compared to on-demand pricing.

• Upgrading EBS Volumes from gp2 to gp3

  Moving to gp3 provides the same performance at a lower price and can reduce EBS costs by 20 to 60% depending on IOPS needs.

• Archiving Cold Data to S3 Glacier

  If you store large amounts of historical or rarely accessed data, shifting it to S3 Glacier can cut huge storage costs.

You May Also Read: The Ultimate Guide to Cloud Cost Optimization for Businesses

Bottom Line

Managing AWS costs doesn’t have to be complex. By taking a few simple steps regularly, you can keep your cloud fast, efficient, and within budget.

Rightsizing EC2, using newer instance types, moving old data to cheaper storage, tuning databases, reducing extra data transfer, and cleaning up unused resources – all of these actions help lower AWS costs effectively. On top of that, tools like Trusted Advisor, Compute Optimizer, and the Cost and Usage Report make it easier to see where your money is going and what to fix.

To make getting started simple, don’t try to do everything at once. In one week, pick three quick wins—rightsize one EC2 instance, switch a gp2 volume to gp3, or move a bucket to a cheaper S3 tier, and set up a single AWS Budget with an alert. Then come back to this checklist and add a few more; over time, those small, steady changes compound into meaningful AWS savings.

Frequently Asked Questions

1. Will AWS cost optimization slow down my applications?

Not if you do it the right way. The goal is to cut waste, not power. Most changes, like rightsizing instances, using smarter storage tiers, and removing unused resources, keep your apps just as fast, and in many cases, make them run smoother and more efficiently.

2. How often should I review my AWS costs?

A light review every month and a deeper review every quarter works well. This keeps surprises away and turns cost optimization into a regular habit, not a one-time project.

3. Is AWS cost optimization only for large enterprises?

Not at all. Even small startups can waste money on idle instances, oversized databases, or unused storage, and small savings matter a lot when budgets are tight.

4. Can cost optimization help with security and governance, too?

Yes. Cleaning up unused accounts, resources, and old snapshots reduces your attack surface and makes it easier to track who owns what.

5. How soon can I see savings after starting AWS cost optimization?

NIn many cases, you can see savings within days or weeks once you rightsize instances, clean up unused resources, or switch storage tiers. Bigger, architectural changes may take longer, but they usually deliver deeper, long-term savings.