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AWS Cost Optimization

CloudYali's AWS Cost Optimization features help you identify and implement savings opportunities across your Amazon Web Services infrastructure. Our platform continually analyzes your AWS resources and provides actionable recommendations to reduce unnecessary spending.

Supported AWS Resources​

CloudYali's cost optimization engine can generate recommendations for the following AWS resources:

Compute Resources​

  • Amazon Elastic Compute Cloud (Amazon EC2) instances
  • Amazon EC2 Auto Scaling groups
  • AWS Lambda functions
  • Amazon Elastic Container Service (Amazon ECS) tasks on AWS Fargate

Storage Resources​

  • Amazon Elastic Block Store (Amazon EBS) volumes
  • Amazon RDS DB instance storage

Database Services​

  • Amazon RDS DB instances
  • Amazon DynamoDB (reserved capacity)
  • Amazon ElastiCache (reserved nodes)
  • Amazon MemoryDB (reserved instances)
  • Amazon Redshift (reserved nodes)
  • Amazon OpenSearch Service (reserved instances)

Commitment Plans​

  • Compute Savings Plans
  • EC2 Instance Savings Plans
  • SageMaker Savings Plans
  • EC2 Reserved Instances
  • Amazon RDS Reserved Instances

Types of Cost Optimization Recommendations​

CloudYali provides six primary types of cost optimization recommendations for AWS resources:

1. Stop Unused Resources​

Potential Savings: Up to 100% of the resource cost

Identifies idle or unused resources that can be safely stopped or terminated, including:

  • Idle EC2 instances with minimal CPU utilization
  • Unattached EBS volumes
  • Unused Elastic IPs
  • Idle RDS instances

Example Recommendations:

  • "Stop EC2 instance i-0abc123def456 which has been idle for 14 days"
  • "Delete unattached EBS volume vol-0xyz789abc123 to save $8.50 per month"

2. Rightsize Resources​

Potential Savings: 20-75% of the resource cost

Identifies resources that are overprovisioned for their current workload and recommends moving to a smaller or more appropriate instance type:

  • EC2 instance downsizing
  • EBS volume resizing
  • AWS Lambda memory reduction
  • AWS Fargate task size optimization

Example Recommendations:

  • "Downsize EC2 instance i-0abc123def456 from m5.xlarge to m5.large to save $73.20 per month"
  • "Reduce Lambda function memory allocation from 1024MB to 512MB to save $12.40 per month"

3. Upgrade to Modern Resources​

Potential Savings: 10-40% of the resource cost

Identifies opportunities to upgrade to newer generation services or resources that offer better performance at a lower cost:

  • Migrate from older EC2 instance families to newer ones
  • Upgrade from older EBS volume types to newer, more efficient options

Example Recommendations:

  • "Upgrade from EBS io1 volume to io2 for improved performance and 25% cost reduction"
  • "Migrate from m4.large instances to m5.large for better performance and 10% cost reduction"

4. Graviton Migration​

Potential Savings: 15-40% of the compute cost

Identifies opportunities to migrate from x86-based EC2 instances to ARM-based AWS Graviton processors:

  • EC2 instance types that can be migrated to Graviton equivalents
  • Compatible workloads where Graviton processors can deliver cost savings

Example Recommendations:

  • "Migrate EC2 instance from m5.xlarge to m6g.xlarge to save 20% on compute costs"
  • "Convert your Auto Scaling group from r5 to r6g instance types for 25% savings"

5. Purchase Savings Plans​

Potential Savings: 20-72% compared to On-Demand pricing

Recommends commitment-based discount plans based on your consistent usage patterns:

  • Compute Savings Plans
  • EC2 Instance Savings Plans
  • SageMaker Savings Plans

Example Recommendations:

  • "Purchase a 1-year Compute Savings Plan with $1,000 hourly commitment to save $8,760 annually"
  • "Purchase a 3-year EC2 Instance Savings Plan for your steady-state workloads to save 60% compared to On-Demand rates"

6. Purchase Reserved Instances​

Potential Savings: 20-75% compared to On-Demand pricing

Recommends Reserved Instance purchases for consistent, predictable workloads:

  • EC2 Reserved Instances
  • RDS Reserved Instances
  • OpenSearch Reserved Instances
  • ElastiCache Reserved Nodes
  • Redshift Reserved Nodes
  • DynamoDB Reserved Capacity

Example Recommendations:

  • "Purchase 10 RDS Reserved Instances for your production database cluster to save $12,000 annually"
  • "Convert 15 consistently running EC2 instances to Reserved Instances for 40% savings"

How to Access AWS Cost Recommendations​

  1. Log in to your CloudYali Dashboard

  2. Navigate to the Cost Optimization section

    • Click on "Cost Optimization" in the main navigation menu

  3. Filter for AWS Recommendations

    • Use the provider filter to show only AWS recommendations
    • Further filter by recommendation type, resource type, or potential savings amount

  4. Review and Implement Recommendations

    • Each recommendation includes detailed information about the potential savings and implementation steps
    • Click on a recommendation to see more details and specific actions to take

Best Practices for AWS Cost Optimization​

  • Regularly Review Recommendations: Check for new cost optimization opportunities at least monthly
  • Implement High-Impact Recommendations First: Focus on recommendations with the largest potential savings
  • Test Before Implementing: For rightsizing recommendations, test workloads after making changes to ensure performance isn't affected
  • Combine Strategies: Use a combination of all six recommendation types for maximum savings
  • Automate Where Possible: Consider automating the implementation of non-disruptive recommendations

Need Assistance with AWS Cost Optimization?​

If you need help implementing AWS cost optimization recommendations or have questions about specific recommendations:

  • Email Support: Contact us at support@cloudyali.io
  • Schedule a Consultation: Book a session with our cloud cost optimization experts