AWS Cost Optimization: Detailed Steps

By Bishal Dhimal | Dec 2025

📌 Table of Contents 1. Review AWS Billing & Cost Management Dashboard 2. Identify High-Cost Services 3. Analyze Unused or Underused Resources 4. Review Reserved Instances vs On-Demand 5. Evaluate Auto Scaling Configuration 6. Move to Spot Instances 7. Review EC2 Instance Types & Sizes 8. Utilize S3 Storage Classes Efficiently 9. Optimize Data Transfer Costs 10. Consolidate AWS Accounts 11. Review RDS Instance & Storage Costs RDS Detailed Optimization

1. Review the AWS Billing & Cost Management Dashboard

Detailed Actions:

Go to the Cost Explorer and filter costs by service, region, and time.
Use Cost Allocation Tags to categorize and allocate costs to departments or projects.
Set up AWS Budgets with thresholds for notifications.

Best Practices:

Set monthly budgets and daily alerts to prevent surprise billing.

2. Identify High-Cost Services

Detailed Actions:

Check Cost Explorer for EC2, RDS, Lambda, and S3 to identify high-cost services.
Drill down by regions and accounts for detailed spending analysis.

Best Practices:

Use Cost Anomaly Detection for early warnings of unexpected cost spikes.

3. Analyze Unused or Underused Resources

Detailed Actions:

Use AWS Trusted Advisor to detect idle EC2 instances, unattached EBS volumes, or unused Elastic IPs.
Rightsize EC2 instances based on utilization recommendations.

Best Practices:

Implement auto-scaling to dynamically adjust resources based on demand.

4. Review Reserved Instances vs On-Demand

Detailed Actions:

Check RI Utilization and Coverage reports to ensure value from Reserved Instances.
Switch steady workloads to Reserved Instances or Savings Plans for up to 75% savings.
Evaluate which workloads should remain on On-Demand for flexibility.

Best Practices:

Use Convertible RIs for flexibility to change instance type, family, or OS.

5. Evaluate Auto Scaling Configuration

Review Auto Scaling Groups and policies based on CPU, memory, etc.
Schedule scaling for off-peak hours.

Combine Auto Scaling with Spot Instances for non-critical workloads.

6. Move to Spot Instances

Use Spot Instances for non-production workloads for up to 90% savings.
Distribute workloads using EC2 Spot Fleet or Auto Scaling with Spot.

Ensure fault tolerance and checkpointing as Spot Instances can be terminated unexpectedly.

7. Review EC2 Instance Types & Sizes

Use Compute Optimizer to identify over-provisioned instances.
Consider Graviton-based instances for better price/performance.

Monitor instances via CloudWatch to ensure proper sizing.

8. Utilize S3 Storage Classes Efficiently

Move infrequently accessed data to S3 IA or Glacier.
Implement Lifecycle Policies to transition data automatically.

Enable S3 Intelligent-Tiering for unknown access patterns.

9. Optimize Data Transfer Costs

Review cross-region/availability zone transfers; consolidate resources.
Use CloudFront to reduce origin data transfer costs.

Use VPC Peering or AWS Transit Gateway to reduce cross-region costs.

10. Consolidate AWS Accounts

Use AWS Organizations to consolidate billing and achieve volume discounts.
Organize accounts by department, project, or business unit.

Use Service Control Policies (SCPs) to manage permissions and compliance.

11. Review RDS Instance & Storage Costs

Analyze RDS instances for right-sizing.
Use Amazon Aurora for cost-effective scalability.
Review storage and backups; enable auto-scaling and delete unnecessary snapshots.

RDS Detailed Optimization

1. Evaluate RDS Instance Types and Sizes

Use Compute Optimizer and Trusted Advisor to identify underutilized instances.
Consider switching to better instance families or Graviton-based instances.

Monitor CPU, memory, disk I/O using CloudWatch.
Enable RDS Auto Scaling to adjust instance size automatically.

2. Consider Amazon Aurora

Migrate MySQL/PostgreSQL workloads to Amazon Aurora for price/performance benefits.
Use Aurora Serverless for variable workloads to pay only for what you use.

Evaluate performance using AWS Pricing Calculator for potential savings.

3. Optimize RDS Storage Costs

Switch to General Purpose SSD if Provisioned IOPS is not required.
Delete old snapshots and backup files.
Enable Storage Auto Scaling to avoid over-provisioning.

Set retention periods for backups and snapshots.
Use Performance Insights to monitor and optimize storage usage.

4. Use Reserved DB Instances (RIs)

Switch predictable workloads to Reserved DB Instances.
Use Convertible RIs for flexibility during the term.

Track RI utilization to ensure reservations match actual usage.

5. Optimize Backup & Snapshot Retention

Review backup retention policies and reduce unnecessary retention.
Delete old manual snapshots and optimize cross-region backup strategy.

Set up lifecycle policies to delete outdated backups automatically.
Schedule backups during off-peak hours.

6. Use Multi-AZ Only When Needed

Evaluate high availability needs before enabling Multi-AZ.
For non-production environments, use Single-AZ to save costs.

7. Utilize Read Replicas

Implement Read Replicas to scale read-heavy workloads.
Optimize replica location to reduce latency and data transfer costs.

Monitor replica lag and use Auto Scaling for replicas if needed.

8. Analyze Performance with Performance Insights

Enable Performance Insights to identify bottlenecks and high-latency queries.
Optimize database queries to avoid over-provisioning.

Regularly review query performance and wait times to optimize costs.

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