How to Optimize Cloud Costs with CUR and Resource Inventory

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Using the AWS Cost and Usage Report (CUR) alone is insufficient for effective cloud cost management. Netflix developed Cloud Efficiency Analytics, a platform integrating inventory, usage, and cost data—an approach worth replicating.

While CUR provides cost and usage metrics, it may obscure inefficiencies. For example:
– 1000 EC2 instances covered by Savings Plans, but 100 are underutilized (10% capacity).
– Who owns these resources? What are their Amazon Resource Names (ARNs)?

Key Steps for Cloud Cost Optimization:

1. Maintain a Cloud Inventory

2. Monitor Usage Metrics

  • Use Amazon CloudWatch or third-party tools.

3. Analyze Cost vs. Utilization

You Should Know:

AWS CLI Commands for Cost & Resource Tracking

1. List EC2 Instances with Low CPU Utilization

aws cloudwatch get-metric-statistics --namespace AWS/EC2 --metric-name CPUUtilization --dimensions Name=InstanceId,Value=i-1234567890abcdef0 --statistics Average --start-time 2023-10-01T00:00:00Z --end-time 2023-10-31T23:59:59Z --period 86400 

2. Extract CUR Data via Athena

SELECT line_item_usage_account_id, product_instance_type, SUM(line_item_unblended_cost) AS cost 
FROM cur_db.cur_table 
WHERE line_item_product_code = 'AmazonEC2' 
GROUP BY line_item_usage_account_id, product_instance_type 
ORDER BY cost DESC; 

3. Tag Untagged Resources

aws resourcegroupstaggingapi tag-resources --resource-arn-list arn:aws:ec2:us-east-1:123456789012:instance/i-1234567890abcdef0 --tags Owner=DevTeam 

4. Find Unattached EBS Volumes

aws ec2 describe-volumes --filters Name=status,Values=available --query "Volumes[].VolumeId" 

5. Check Savings Plan Coverage

aws ce get-savings-plans-coverage --time-period Start=2023-10-01,End=2023-10-31 --granularity MONTHLY 

What Undercode Say:

Cloud cost optimization requires more than just CUR. A structured approach combining inventory tracking (CMDB-style), usage analytics, and automated tagging ensures efficiency. Netflix’s method proves that integrating cost, usage, and ownership data is critical for long-term savings.

Prediction:

As cloud environments grow, AI-driven cost anomaly detection will become standard, reducing manual oversight. Expect AWS to enhance Resource Explorer with automated optimization recommendations.

Expected Output:

  • Reduced cloud waste via automated resource tracking.
  • Improved accountability through tagging and ownership logs.
  • Actionable insights from CUR + usage analytics integration.

Relevant URLs:

References:

Reported By: Ivopinto01 Aws – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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