Tools: That 500GB EBS Volume is 90% Empty: Right-Size It and Stop Wasting Money 💾

Most EBS volumes are wildly over-provisioned. Here's how to find the bloated ones, safely shrink them, and automate right-sizing with Terraform. ## 💸 Where the Money Hides ## 🔍 Step 1: Find the Bloated Volumes (Terraform + CloudWatch) ## 🏗️ Step 2: Apply the Right-Sizing (Terraform) ## Downgrade io2 → gp3 (Biggest savings) ## Reduce over-provisioned IOPS ## Right-Size with Environment-Aware Defaults ## ⚡ Quick Audit: Run This Right Now ## 💡 Pro Tips ## ⚠️ Important Gotcha ## 📊 TL;DR Here's a question nobody asks often enough: How much of your EBS storage are you actually using? In most AWS accounts, the answer is terrifyingly low. Teams provision 500GB "just in case" and use 40GB. They request io2 when gp3 would be fine. They set 10,000 IOPS when the volume barely hits 200. You're paying for every unused gigabyte, every idle IOP, every megabyte of throughput — every second of every day. Let's find the waste and kill it. 🔪 EBS pricing has three dimensions, and most teams overspend on all of them: A real example from a production account: Three volumes. Nearly $8K/year wasted. And most accounts have dozens. Deploy this monitoring module to identify over-provisioned volumes: You'll get a weekly email like this: Actionable, specific, dollar amounts. No guessing. 📬 If you see any io1 or io2 volumes — that's where the money is. 🎯 You can change volume type, IOPS, and throughput online — but you CANNOT shrink volume size. EBS only allows increasing size. If a volume is 500GB but you only use 50GB, you'd need to create a new 100GB volume, copy data, and swap. The monitoring Lambda focuses on IOPS/type optimization since those are zero-downtime changes. Bottom line: EBS is the silent budget killer. You can't see unused IOPS or throughput in the console — they just quietly drain your wallet. Deploy the analyzer, check the report, and stop paying for air. 💨 Run the audit CLI command above. I bet you'll find at least one io2 volume that should be gp3. Go on, I'll wait. 😏 Found this helpful? Follow for more AWS cost optimization with Terraform! 💬 Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse CODE_BLOCK: EBS Cost = Storage (GB) + IOPS + Throughput gp3 pricing: Storage: $0.08/GB/month IOPS: Free up to 3,000, then $0.005/IOPS Throughput: Free up to 125 MB/s, then $0.04/MB/s io2 pricing: Storage: $0.125/GB/month IOPS: $0.065/IOPS/month ← This gets expensive FAST Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: EBS Cost = Storage (GB) + IOPS + Throughput gp3 pricing: Storage: $0.08/GB/month IOPS: Free up to 3,000, then $0.005/IOPS Throughput: Free up to 125 MB/s, then $0.04/MB/s io2 pricing: Storage: $0.125/GB/month IOPS: $0.065/IOPS/month ← This gets expensive FAST CODE_BLOCK: EBS Cost = Storage (GB) + IOPS + Throughput gp3 pricing: Storage: $0.08/GB/month IOPS: Free up to 3,000, then $0.005/IOPS Throughput: Free up to 125 MB/s, then $0.04/MB/s io2 pricing: Storage: $0.125/GB/month IOPS: $0.065/IOPS/month ← This gets expensive FAST COMMAND_BLOCK: # modules/ebs-monitor/main.tf resource "aws_lambda_function" "ebs_analyzer" { filename = data.archive_file.analyzer.output_path function_name = "ebs-rightsizing-analyzer" role = aws_iam_role.analyzer.arn handler = "index.handler" runtime = "python3.12" timeout = 300 source_code_hash = data.archive_file.analyzer.output_base64sha256 environment { variables = { SNS_TOPIC_ARN = aws_sns_topic.ebs_alerts.arn LOOKBACK_DAYS = "14" USAGE_THRESHOLD = "50" # Flag if <50% utilized } } } data "archive_file" "analyzer" { type = "zip" output_path = "${path.module}/analyzer.zip" source { content = <<-PYTHON import boto3 import os from datetime import datetime, timedelta ec2 = boto3.client('ec2') cw = boto3.client('cloudwatch') sns = boto3.client('sns') def get_metric_max(volume_id, metric_name, days): """Get max value of a CloudWatch metric over N days.""" response = cw.get_metric_statistics( Namespace='AWS/EBS', MetricName=metric_name, Dimensions=[{'Name': 'VolumeId', 'Value': volume_id}], StartTime=datetime.utcnow() - timedelta(days=days), EndTime=datetime.utcnow(), Period=3600, Statistics=['Maximum'] ) points = response.get('Datapoints', []) return max((p['Maximum'] for p in points), default=0) def handler(event, context): days = int(os.environ['LOOKBACK_DAYS']) threshold = int(os.environ['USAGE_THRESHOLD']) volumes = ec2.describe_volumes( Filters=[{'Name': 'status', 'Values': ['in-use']}] )['Volumes'] recommendations = [] for vol in volumes: vol_id = vol['VolumeId'] vol_type = vol['VolumeType'] size_gb = vol['Size'] provisioned_iops = vol.get('Iops', 0) provisioned_tp = vol.get('Throughput', 0) # Get peak usage over lookback period peak_read_ops = get_metric_max(vol_id, 'VolumeReadOps', days) peak_write_ops = get_metric_max(vol_id, 'VolumeWriteOps', days) peak_iops = (peak_read_ops + peak_write_ops) / 3600 # Convert to per-second peak_read_bytes = get_metric_max(vol_id, 'VolumeReadBytes', days) peak_write_bytes = get_metric_max(vol_id, 'VolumeWriteBytes', days) peak_throughput = (peak_read_bytes + peak_write_bytes) / 3600 / 1024 / 1024 # MB/s savings = [] # Check IOPS utilization if provisioned_iops > 3000 and peak_iops < provisioned_iops * (threshold / 100): recommended_iops = max(3000, int(peak_iops * 1.3)) # 30% headroom iops_savings = (provisioned_iops - recommended_iops) * 0.005 if vol_type == 'io2': iops_savings = (provisioned_iops - recommended_iops) * 0.065 savings.append(f" IOPS: {provisioned_iops} → {recommended_iops} (save ${iops_savings:.2f}/mo)") # Check if io2 can downgrade to gp3 if vol_type in ('io1', 'io2') and peak_iops < 16000 and peak_throughput < 1000: current_cost = size_gb * 0.125 + provisioned_iops * 0.065 gp3_iops = max(3000, int(peak_iops * 1.3)) gp3_cost = size_gb * 0.08 + max(0, gp3_iops - 3000) * 0.005 type_savings = current_cost - gp3_cost if type_savings > 5: savings.append(f" Type: {vol_type} → gp3 (save ${type_savings:.2f}/mo)") # Check throughput utilization (gp3 only) if vol_type == 'gp3' and provisioned_tp > 125: if peak_throughput < provisioned_tp * (threshold / 100): recommended_tp = max(125, int(peak_throughput * 1.3)) tp_savings = (provisioned_tp - recommended_tp) * 0.04 savings.append(f" Throughput: {provisioned_tp} → {recommended_tp} MB/s (save ${tp_savings:.2f}/mo)") if savings: # Get instance name attachments = vol.get('Attachments', []) instance_id = attachments[0]['InstanceId'] if attachments else 'detached' tags = {t['Key']: t['Value'] for t in vol.get('Tags', [])} name = tags.get('Name', vol_id) recommendations.append( f"{name} ({vol_id}) - attached to {instance_id}\n" f" Current: {size_gb}GB {vol_type}, {provisioned_iops} IOPS\n" f" Peak IOPS: {peak_iops:.0f}, Peak Throughput: {peak_throughput:.1f} MB/s\n" + "\n".join(savings) ) if recommendations: total_recs = len(recommendations) message = ( f"EBS Right-Sizing Report ({total_recs} volumes need attention)\n" f"Lookback period: {days} days\n\n" + "\n\n".join(recommendations) ) sns.publish( TopicArn=os.environ['SNS_TOPIC_ARN'], Subject=f'EBS Right-Sizing: {total_recs} volumes over-provisioned', Message=message ) return {'volumes_analyzed': len(volumes), 'recommendations': len(recommendations)} PYTHON filename = "index.py" } } # Run weekly resource "aws_cloudwatch_event_rule" "weekly_ebs_check" { name = "ebs-rightsizing-check" schedule_expression = "rate(7 days)" } resource "aws_cloudwatch_event_target" "ebs_analyzer" { rule = aws_cloudwatch_event_rule.weekly_ebs_check.name arn = aws_lambda_function.ebs_analyzer.arn } resource "aws_lambda_permission" "allow_eventbridge" { action = "lambda:InvokeFunction" function_name = aws_lambda_function.ebs_analyzer.function_name principal = "events.amazonaws.com" source_arn = aws_cloudwatch_event_rule.weekly_ebs_check.arn } resource "aws_sns_topic" "ebs_alerts" { name = "ebs-rightsizing-alerts" } resource "aws_iam_role" "analyzer" { name = "ebs-rightsizing-analyzer-role" assume_role_policy = jsonencode({ Version = "2012-10-17" Statement = [{ Action = "sts:AssumeRole" Effect = "Allow" Principal = { Service = "lambda.amazonaws.com" } }] }) } resource "aws_iam_role_policy" "analyzer" { name = "ebs-rightsizing-analyzer-policy" role = aws_iam_role.analyzer.id policy = jsonencode({ Version = "2012-10-17" Statement = [ { Effect = "Allow" Action = ["ec2:DescribeVolumes"] Resource = "*" }, { Effect = "Allow" Action = [ "cloudwatch:GetMetricStatistics" ] Resource = "*" }, { Effect = "Allow" Action = ["sns:Publish"] Resource = aws_sns_topic.ebs_alerts.arn }, { Effect = "Allow" Action = [ "logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents" ] Resource = "arn:aws:logs:*:*:*" } ] }) } Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # modules/ebs-monitor/main.tf resource "aws_lambda_function" "ebs_analyzer" { filename = data.archive_file.analyzer.output_path function_name = "ebs-rightsizing-analyzer" role = aws_iam_role.analyzer.arn handler = "index.handler" runtime = "python3.12" timeout = 300 source_code_hash = data.archive_file.analyzer.output_base64sha256 environment { variables = { SNS_TOPIC_ARN = aws_sns_topic.ebs_alerts.arn LOOKBACK_DAYS = "14" USAGE_THRESHOLD = "50" # Flag if <50% utilized } } } data "archive_file" "analyzer" { type = "zip" output_path = "${path.module}/analyzer.zip" source { content = <<-PYTHON import boto3 import os from datetime import datetime, timedelta ec2 = boto3.client('ec2') cw = boto3.client('cloudwatch') sns = boto3.client('sns') def get_metric_max(volume_id, metric_name, days): """Get max value of a CloudWatch metric over N days.""" response = cw.get_metric_statistics( Namespace='AWS/EBS', MetricName=metric_name, Dimensions=[{'Name': 'VolumeId', 'Value': volume_id}], StartTime=datetime.utcnow() - timedelta(days=days), EndTime=datetime.utcnow(), Period=3600, Statistics=['Maximum'] ) points = response.get('Datapoints', []) return max((p['Maximum'] for p in points), default=0) def handler(event, context): days = int(os.environ['LOOKBACK_DAYS']) threshold = int(os.environ['USAGE_THRESHOLD']) volumes = ec2.describe_volumes( Filters=[{'Name': 'status', 'Values': ['in-use']}] )['Volumes'] recommendations = [] for vol in volumes: vol_id = vol['VolumeId'] vol_type = vol['VolumeType'] size_gb = vol['Size'] provisioned_iops = vol.get('Iops', 0) provisioned_tp = vol.get('Throughput', 0) # Get peak usage over lookback period peak_read_ops = get_metric_max(vol_id, 'VolumeReadOps', days) peak_write_ops = get_metric_max(vol_id, 'VolumeWriteOps', days) peak_iops = (peak_read_ops + peak_write_ops) / 3600 # Convert to per-second peak_read_bytes = get_metric_max(vol_id, 'VolumeReadBytes', days) peak_write_bytes = get_metric_max(vol_id, 'VolumeWriteBytes', days) peak_throughput = (peak_read_bytes + peak_write_bytes) / 3600 / 1024 / 1024 # MB/s savings = [] # Check IOPS utilization if provisioned_iops > 3000 and peak_iops < provisioned_iops * (threshold / 100): recommended_iops = max(3000, int(peak_iops * 1.3)) # 30% headroom iops_savings = (provisioned_iops - recommended_iops) * 0.005 if vol_type == 'io2': iops_savings = (provisioned_iops - recommended_iops) * 0.065 savings.append(f" IOPS: {provisioned_iops} → {recommended_iops} (save ${iops_savings:.2f}/mo)") # Check if io2 can downgrade to gp3 if vol_type in ('io1', 'io2') and peak_iops < 16000 and peak_throughput < 1000: current_cost = size_gb * 0.125 + provisioned_iops * 0.065 gp3_iops = max(3000, int(peak_iops * 1.3)) gp3_cost = size_gb * 0.08 + max(0, gp3_iops - 3000) * 0.005 type_savings = current_cost - gp3_cost if type_savings > 5: savings.append(f" Type: {vol_type} → gp3 (save ${type_savings:.2f}/mo)") # Check throughput utilization (gp3 only) if vol_type == 'gp3' and provisioned_tp > 125: if peak_throughput < provisioned_tp * (threshold / 100): recommended_tp = max(125, int(peak_throughput * 1.3)) tp_savings = (provisioned_tp - recommended_tp) * 0.04 savings.append(f" Throughput: {provisioned_tp} → {recommended_tp} MB/s (save ${tp_savings:.2f}/mo)") if savings: # Get instance name attachments = vol.get('Attachments', []) instance_id = attachments[0]['InstanceId'] if attachments else 'detached' tags = {t['Key']: t['Value'] for t in vol.get('Tags', [])} name = tags.get('Name', vol_id) recommendations.append( f"{name} ({vol_id}) - attached to {instance_id}\n" f" Current: {size_gb}GB {vol_type}, {provisioned_iops} IOPS\n" f" Peak IOPS: {peak_iops:.0f}, Peak Throughput: {peak_throughput:.1f} MB/s\n" + "\n".join(savings) ) if recommendations: total_recs = len(recommendations) message = ( f"EBS Right-Sizing Report ({total_recs} volumes need attention)\n" f"Lookback period: {days} days\n\n" + "\n\n".join(recommendations) ) sns.publish( TopicArn=os.environ['SNS_TOPIC_ARN'], Subject=f'EBS Right-Sizing: {total_recs} volumes over-provisioned', Message=message ) return {'volumes_analyzed': len(volumes), 'recommendations': len(recommendations)} PYTHON filename = "index.py" } } # Run weekly resource "aws_cloudwatch_event_rule" "weekly_ebs_check" { name = "ebs-rightsizing-check" schedule_expression = "rate(7 days)" } resource "aws_cloudwatch_event_target" "ebs_analyzer" { rule = aws_cloudwatch_event_rule.weekly_ebs_check.name arn = aws_lambda_function.ebs_analyzer.arn } resource "aws_lambda_permission" "allow_eventbridge" { action = "lambda:InvokeFunction" function_name = aws_lambda_function.ebs_analyzer.function_name principal = "events.amazonaws.com" source_arn = aws_cloudwatch_event_rule.weekly_ebs_check.arn } resource "aws_sns_topic" "ebs_alerts" { name = "ebs-rightsizing-alerts" } resource "aws_iam_role" "analyzer" { name = "ebs-rightsizing-analyzer-role" assume_role_policy = jsonencode({ Version = "2012-10-17" Statement = [{ Action = "sts:AssumeRole" Effect = "Allow" Principal = { Service = "lambda.amazonaws.com" } }] }) } resource "aws_iam_role_policy" "analyzer" { name = "ebs-rightsizing-analyzer-policy" role = aws_iam_role.analyzer.id policy = jsonencode({ Version = "2012-10-17" Statement = [ { Effect = "Allow" Action = ["ec2:DescribeVolumes"] Resource = "*" }, { Effect = "Allow" Action = [ "cloudwatch:GetMetricStatistics" ] Resource = "*" }, { Effect = "Allow" Action = ["sns:Publish"] Resource = aws_sns_topic.ebs_alerts.arn }, { Effect = "Allow" Action = [ "logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents" ] Resource = "arn:aws:logs:*:*:*" } ] }) } COMMAND_BLOCK: # modules/ebs-monitor/main.tf resource "aws_lambda_function" "ebs_analyzer" { filename = data.archive_file.analyzer.output_path function_name = "ebs-rightsizing-analyzer" role = aws_iam_role.analyzer.arn handler = "index.handler" runtime = "python3.12" timeout = 300 source_code_hash = data.archive_file.analyzer.output_base64sha256 environment { variables = { SNS_TOPIC_ARN = aws_sns_topic.ebs_alerts.arn LOOKBACK_DAYS = "14" USAGE_THRESHOLD = "50" # Flag if <50% utilized } } } data "archive_file" "analyzer" { type = "zip" output_path = "${path.module}/analyzer.zip" source { content = <<-PYTHON import boto3 import os from datetime import datetime, timedelta ec2 = boto3.client('ec2') cw = boto3.client('cloudwatch') sns = boto3.client('sns') def get_metric_max(volume_id, metric_name, days): """Get max value of a CloudWatch metric over N days.""" response = cw.get_metric_statistics( Namespace='AWS/EBS', MetricName=metric_name, Dimensions=[{'Name': 'VolumeId', 'Value': volume_id}], StartTime=datetime.utcnow() - timedelta(days=days), EndTime=datetime.utcnow(), Period=3600, Statistics=['Maximum'] ) points = response.get('Datapoints', []) return max((p['Maximum'] for p in points), default=0) def handler(event, context): days = int(os.environ['LOOKBACK_DAYS']) threshold = int(os.environ['USAGE_THRESHOLD']) volumes = ec2.describe_volumes( Filters=[{'Name': 'status', 'Values': ['in-use']}] )['Volumes'] recommendations = [] for vol in volumes: vol_id = vol['VolumeId'] vol_type = vol['VolumeType'] size_gb = vol['Size'] provisioned_iops = vol.get('Iops', 0) provisioned_tp = vol.get('Throughput', 0) # Get peak usage over lookback period peak_read_ops = get_metric_max(vol_id, 'VolumeReadOps', days) peak_write_ops = get_metric_max(vol_id, 'VolumeWriteOps', days) peak_iops = (peak_read_ops + peak_write_ops) / 3600 # Convert to per-second peak_read_bytes = get_metric_max(vol_id, 'VolumeReadBytes', days) peak_write_bytes = get_metric_max(vol_id, 'VolumeWriteBytes', days) peak_throughput = (peak_read_bytes + peak_write_bytes) / 3600 / 1024 / 1024 # MB/s savings = [] # Check IOPS utilization if provisioned_iops > 3000 and peak_iops < provisioned_iops * (threshold / 100): recommended_iops = max(3000, int(peak_iops * 1.3)) # 30% headroom iops_savings = (provisioned_iops - recommended_iops) * 0.005 if vol_type == 'io2': iops_savings = (provisioned_iops - recommended_iops) * 0.065 savings.append(f" IOPS: {provisioned_iops} → {recommended_iops} (save ${iops_savings:.2f}/mo)") # Check if io2 can downgrade to gp3 if vol_type in ('io1', 'io2') and peak_iops < 16000 and peak_throughput < 1000: current_cost = size_gb * 0.125 + provisioned_iops * 0.065 gp3_iops = max(3000, int(peak_iops * 1.3)) gp3_cost = size_gb * 0.08 + max(0, gp3_iops - 3000) * 0.005 type_savings = current_cost - gp3_cost if type_savings > 5: savings.append(f" Type: {vol_type} → gp3 (save ${type_savings:.2f}/mo)") # Check throughput utilization (gp3 only) if vol_type == 'gp3' and provisioned_tp > 125: if peak_throughput < provisioned_tp * (threshold / 100): recommended_tp = max(125, int(peak_throughput * 1.3)) tp_savings = (provisioned_tp - recommended_tp) * 0.04 savings.append(f" Throughput: {provisioned_tp} → {recommended_tp} MB/s (save ${tp_savings:.2f}/mo)") if savings: # Get instance name attachments = vol.get('Attachments', []) instance_id = attachments[0]['InstanceId'] if attachments else 'detached' tags = {t['Key']: t['Value'] for t in vol.get('Tags', [])} name = tags.get('Name', vol_id) recommendations.append( f"{name} ({vol_id}) - attached to {instance_id}\n" f" Current: {size_gb}GB {vol_type}, {provisioned_iops} IOPS\n" f" Peak IOPS: {peak_iops:.0f}, Peak Throughput: {peak_throughput:.1f} MB/s\n" + "\n".join(savings) ) if recommendations: total_recs = len(recommendations) message = ( f"EBS Right-Sizing Report ({total_recs} volumes need attention)\n" f"Lookback period: {days} days\n\n" + "\n\n".join(recommendations) ) sns.publish( TopicArn=os.environ['SNS_TOPIC_ARN'], Subject=f'EBS Right-Sizing: {total_recs} volumes over-provisioned', Message=message ) return {'volumes_analyzed': len(volumes), 'recommendations': len(recommendations)} PYTHON filename = "index.py" } } # Run weekly resource "aws_cloudwatch_event_rule" "weekly_ebs_check" { name = "ebs-rightsizing-check" schedule_expression = "rate(7 days)" } resource "aws_cloudwatch_event_target" "ebs_analyzer" { rule = aws_cloudwatch_event_rule.weekly_ebs_check.name arn = aws_lambda_function.ebs_analyzer.arn } resource "aws_lambda_permission" "allow_eventbridge" { action = "lambda:InvokeFunction" function_name = aws_lambda_function.ebs_analyzer.function_name principal = "events.amazonaws.com" source_arn = aws_cloudwatch_event_rule.weekly_ebs_check.arn } resource "aws_sns_topic" "ebs_alerts" { name = "ebs-rightsizing-alerts" } resource "aws_iam_role" "analyzer" { name = "ebs-rightsizing-analyzer-role" assume_role_policy = jsonencode({ Version = "2012-10-17" Statement = [{ Action = "sts:AssumeRole" Effect = "Allow" Principal = { Service = "lambda.amazonaws.com" } }] }) } resource "aws_iam_role_policy" "analyzer" { name = "ebs-rightsizing-analyzer-policy" role = aws_iam_role.analyzer.id policy = jsonencode({ Version = "2012-10-17" Statement = [ { Effect = "Allow" Action = ["ec2:DescribeVolumes"] Resource = "*" }, { Effect = "Allow" Action = [ "cloudwatch:GetMetricStatistics" ] Resource = "*" }, { Effect = "Allow" Action = ["sns:Publish"] Resource = aws_sns_topic.ebs_alerts.arn }, { Effect = "Allow" Action = [ "logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents" ] Resource = "arn:aws:logs:*:*:*" } ] }) } CODE_BLOCK: EBS Right-Sizing Report (3 volumes need attention) Lookback period: 14 days app-server-data (vol-0abc123) - attached to i-0def456 Current: 500GB gp3, 5000 IOPS Peak IOPS: 180, Peak Throughput: 12.3 MB/s IOPS: 5000 → 3000 (save $10.00/mo) database-logs (vol-0xyz789) - attached to i-0ghi012 Current: 200GB io2, 10000 IOPS Peak IOPS: 1420, Peak Throughput: 45.2 MB/s Type: io2 → gp3 (save $537.00/mo) IOPS: 10000 → 3000 (save $0.00/mo) Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: EBS Right-Sizing Report (3 volumes need attention) Lookback period: 14 days app-server-data (vol-0abc123) - attached to i-0def456 Current: 500GB gp3, 5000 IOPS Peak IOPS: 180, Peak Throughput: 12.3 MB/s IOPS: 5000 → 3000 (save $10.00/mo) database-logs (vol-0xyz789) - attached to i-0ghi012 Current: 200GB io2, 10000 IOPS Peak IOPS: 1420, Peak Throughput: 45.2 MB/s Type: io2 → gp3 (save $537.00/mo) IOPS: 10000 → 3000 (save $0.00/mo) CODE_BLOCK: EBS Right-Sizing Report (3 volumes need attention) Lookback period: 14 days app-server-data (vol-0abc123) - attached to i-0def456 Current: 500GB gp3, 5000 IOPS Peak IOPS: 180, Peak Throughput: 12.3 MB/s IOPS: 5000 → 3000 (save $10.00/mo) database-logs (vol-0xyz789) - attached to i-0ghi012 Current: 200GB io2, 10000 IOPS Peak IOPS: 1420, Peak Throughput: 45.2 MB/s Type: io2 → gp3 (save $537.00/mo) IOPS: 10000 → 3000 (save $0.00/mo) COMMAND_BLOCK: # Before: io2 with expensive provisioned IOPS 💸 resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "io2" iops = 10000 # Paying $650/mo for IOPS alone tags = { Name = "database-logs" } } # After: gp3 with free baseline IOPS ✅ resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "gp3" iops = 3000 # Free baseline throughput = 125 # Free baseline tags = { Name = "database-logs" } } # Savings: $659/mo → $16/mo = $643/mo saved 🤯 Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # Before: io2 with expensive provisioned IOPS 💸 resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "io2" iops = 10000 # Paying $650/mo for IOPS alone tags = { Name = "database-logs" } } # After: gp3 with free baseline IOPS ✅ resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "gp3" iops = 3000 # Free baseline throughput = 125 # Free baseline tags = { Name = "database-logs" } } # Savings: $659/mo → $16/mo = $643/mo saved 🤯 COMMAND_BLOCK: # Before: io2 with expensive provisioned IOPS 💸 resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "io2" iops = 10000 # Paying $650/mo for IOPS alone tags = { Name = "database-logs" } } # After: gp3 with free baseline IOPS ✅ resource "aws_ebs_volume" "database_logs" { availability_zone = "us-east-1a" size = 200 type = "gp3" iops = 3000 # Free baseline throughput = 125 # Free baseline tags = { Name = "database-logs" } } # Savings: $659/mo → $16/mo = $643/mo saved 🤯 COMMAND_BLOCK: # Before: 5000 IOPS but peaks at 180 resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 5000 # $10/mo for IOPS you don't use throughput = 250 # $5/mo for throughput you don't use tags = { Name = "app-data" } } # After: Use free baselines ✅ resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 3000 # Free! Covers 180 peak with 16x headroom throughput = 125 # Free! Covers 12 MB/s peak easily tags = { Name = "app-data" } } # Savings: $15/mo → $0 extra = $15/mo saved Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # Before: 5000 IOPS but peaks at 180 resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 5000 # $10/mo for IOPS you don't use throughput = 250 # $5/mo for throughput you don't use tags = { Name = "app-data" } } # After: Use free baselines ✅ resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 3000 # Free! Covers 180 peak with 16x headroom throughput = 125 # Free! Covers 12 MB/s peak easily tags = { Name = "app-data" } } # Savings: $15/mo → $0 extra = $15/mo saved COMMAND_BLOCK: # Before: 5000 IOPS but peaks at 180 resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 5000 # $10/mo for IOPS you don't use throughput = 250 # $5/mo for throughput you don't use tags = { Name = "app-data" } } # After: Use free baselines ✅ resource "aws_ebs_volume" "app_data" { size = 500 type = "gp3" iops = 3000 # Free! Covers 180 peak with 16x headroom throughput = 125 # Free! Covers 12 MB/s peak easily tags = { Name = "app-data" } } # Savings: $15/mo → $0 extra = $15/mo saved COMMAND_BLOCK: # modules/ebs-rightsized/main.tf variable "environment" { type = string } variable "size_gb" { type = number } variable "workload_type" { type = string default = "general" # general, database, logging validation { condition = contains(["general", "database", "logging"], var.workload_type) error_message = "Must be: general, database, or logging." } } locals { # Smart defaults based on workload + environment volume_configs = { general = { type = "gp3" iops = 3000 # Free baseline is enough for most workloads throughput = 125 } database = { type = var.environment == "prod" ? "gp3" : "gp3" iops = var.environment == "prod" ? 6000 : 3000 throughput = var.environment == "prod" ? 250 : 125 } logging = { type = "gp3" iops = 3000 # Logs are sequential writes, don't need high IOPS throughput = var.environment == "prod" ? 250 : 125 } } config = local.volume_configs[var.workload_type] } resource "aws_ebs_volume" "this" { availability_zone = var.availability_zone size = var.size_gb type = local.config.type iops = local.config.iops throughput = local.config.throughput tags = { Name = var.name Environment = var.environment Workload = var.workload_type ManagedBy = "terraform" } } Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # modules/ebs-rightsized/main.tf variable "environment" { type = string } variable "size_gb" { type = number } variable "workload_type" { type = string default = "general" # general, database, logging validation { condition = contains(["general", "database", "logging"], var.workload_type) error_message = "Must be: general, database, or logging." } } locals { # Smart defaults based on workload + environment volume_configs = { general = { type = "gp3" iops = 3000 # Free baseline is enough for most workloads throughput = 125 } database = { type = var.environment == "prod" ? "gp3" : "gp3" iops = var.environment == "prod" ? 6000 : 3000 throughput = var.environment == "prod" ? 250 : 125 } logging = { type = "gp3" iops = 3000 # Logs are sequential writes, don't need high IOPS throughput = var.environment == "prod" ? 250 : 125 } } config = local.volume_configs[var.workload_type] } resource "aws_ebs_volume" "this" { availability_zone = var.availability_zone size = var.size_gb type = local.config.type iops = local.config.iops throughput = local.config.throughput tags = { Name = var.name Environment = var.environment Workload = var.workload_type ManagedBy = "terraform" } } COMMAND_BLOCK: # modules/ebs-rightsized/main.tf variable "environment" { type = string } variable "size_gb" { type = number } variable "workload_type" { type = string default = "general" # general, database, logging validation { condition = contains(["general", "database", "logging"], var.workload_type) error_message = "Must be: general, database, or logging." } } locals { # Smart defaults based on workload + environment volume_configs = { general = { type = "gp3" iops = 3000 # Free baseline is enough for most workloads throughput = 125 } database = { type = var.environment == "prod" ? "gp3" : "gp3" iops = var.environment == "prod" ? 6000 : 3000 throughput = var.environment == "prod" ? 250 : 125 } logging = { type = "gp3" iops = 3000 # Logs are sequential writes, don't need high IOPS throughput = var.environment == "prod" ? 250 : 125 } } config = local.volume_configs[var.workload_type] } resource "aws_ebs_volume" "this" { availability_zone = var.availability_zone size = var.size_gb type = local.config.type iops = local.config.iops throughput = local.config.throughput tags = { Name = var.name Environment = var.environment Workload = var.workload_type ManagedBy = "terraform" } } COMMAND_BLOCK: module "app_volume" { source = "./modules/ebs-rightsized" name = "app-data" environment = "dev" size_gb = 100 workload_type = "general" # → gp3, 3000 IOPS (free), 125 MB/s (free) ✅ } module "db_volume" { source = "./modules/ebs-rightsized" name = "postgres-data" environment = "prod" size_gb = 500 workload_type = "database" # → gp3, 6000 IOPS, 250 MB/s (only pays for extra) ✅ } Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: module "app_volume" { source = "./modules/ebs-rightsized" name = "app-data" environment = "dev" size_gb = 100 workload_type = "general" # → gp3, 3000 IOPS (free), 125 MB/s (free) ✅ } module "db_volume" { source = "./modules/ebs-rightsized" name = "postgres-data" environment = "prod" size_gb = 500 workload_type = "database" # → gp3, 6000 IOPS, 250 MB/s (only pays for extra) ✅ } COMMAND_BLOCK: module "app_volume" { source = "./modules/ebs-rightsized" name = "app-data" environment = "dev" size_gb = 100 workload_type = "general" # → gp3, 3000 IOPS (free), 125 MB/s (free) ✅ } module "db_volume" { source = "./modules/ebs-rightsized" name = "postgres-data" environment = "prod" size_gb = 500 workload_type = "database" # → gp3, 6000 IOPS, 250 MB/s (only pays for extra) ✅ } COMMAND_BLOCK: # Find your most expensive EBS volumes aws ec2 describe-volumes \ --query 'Volumes[?State==`in-use`].{ ID:VolumeId, Type:VolumeType, Size:Size, IOPS:Iops, Throughput:Throughput, Instance:Attachments[0].InstanceId }' \ --output table # Find io1/io2 volumes (biggest savings targets) aws ec2 describe-volumes \ --filters "Name=volume-type,Values=io1,io2" \ --query 'Volumes[].{ID:VolumeId,Size:Size,IOPS:Iops,Cost:to_string(Size)}' \ --output table Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: # Find your most expensive EBS volumes aws ec2 describe-volumes \ --query 'Volumes[?State==`in-use`].{ ID:VolumeId, Type:VolumeType, Size:Size, IOPS:Iops, Throughput:Throughput, Instance:Attachments[0].InstanceId }' \ --output table # Find io1/io2 volumes (biggest savings targets) aws ec2 describe-volumes \ --filters "Name=volume-type,Values=io1,io2" \ --query 'Volumes[].{ID:VolumeId,Size:Size,IOPS:Iops,Cost:to_string(Size)}' \ --output table COMMAND_BLOCK: # Find your most expensive EBS volumes aws ec2 describe-volumes \ --query 'Volumes[?State==`in-use`].{ ID:VolumeId, Type:VolumeType, Size:Size, IOPS:Iops, Throughput:Throughput, Instance:Attachments[0].InstanceId }' \ --output table # Find io1/io2 volumes (biggest savings targets) aws ec2 describe-volumes \ --filters "Name=volume-type,Values=io1,io2" \ --query 'Volumes[].{ID:VolumeId,Size:Size,IOPS:Iops,Cost:to_string(Size)}' \ --output table - Never right-size blind — Always check 14+ days of CloudWatch metrics before changing anything - Add 30% headroom — If peak IOPS is 1,500, set to 2,000 not 1,500. Traffic spikes happen - io2 → gp3 is the biggest win — io2 IOPS cost 13x more than gp3 ($0.065 vs $0.005) - gp3 baseline is generous — 3,000 IOPS and 125 MB/s are free. Most workloads never exceed this - You can modify live volumes — AWS supports online volume modification. No downtime needed for type/IOPS/throughput changes ✅ - Size can only go up — You can't shrink an EBS volume. For oversized storage, you need to create a new smaller volume and migrate data - Combine with gp2 → gp3 migration — If you haven't migrated from gp2 yet, do that first for an automatic 20% storage savings