본문으로 건너뛰기
cccskills
무료GitHub에 공개

aws-cost-cleanup

Identify unused AWS resources, estimate potential savings, and prepare cleanup scripts with preview steps. Covers storage retention policies and scheduled cleanup so teams can review dependencies before removing resources and track the resulting savings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Automated cleanup of unused AWS resources to reduce costs

연동 도구AWS
설치 방법 보기

이럴 때 유용합니다

  • Inventory unused resources and estimate savings
  • Prepare cleanup scripts for EBS volumes and Elastic IPs
  • Review S3 versions and storage retention rules
  • Automate recurring resource cleanup with Lambda

포함된 파일(1)

  • SKILL.md8.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AWS Cost Cleanup

Automate the identification and removal of unused AWS resources to eliminate waste.

When to Use This Skill

Use this skill when you need to automatically clean up unused AWS resources to reduce costs and eliminate waste.

Automated Cleanup Targets

Storage

  • Unattached EBS volumes
  • Old EBS snapshots (>90 days)
  • Incomplete multipart S3 uploads
  • Old S3 versions in versioned buckets

Compute

  • Stopped EC2 instances (>30 days)
  • Unused AMIs and associated snapshots
  • Unused Elastic IPs

Networking

  • Unused Elastic Load Balancers
  • Unused NAT Gateways
  • Orphaned ENIs

Cleanup Scripts

Safe Cleanup (Dry-Run First)

#!/bin/bash
# cleanup-unused-ebs.sh

echo "Finding unattached EBS volumes..."
VOLUMES=$(aws ec2 describe-volumes \
  --filters Name=status,Values=available \
  --query 'Volumes[*].VolumeId' \
  --output text)

for vol in $VOLUMES; do
  echo "Would delete: $vol"
  # Uncomment to actually delete:
  # aws ec2 delete-volume --volume-id $vol
done
#!/bin/bash
# cleanup-old-snapshots.sh

CUTOFF_DATE=$(date -d '90 days ago' --iso-8601)

aws ec2 describe-snapshots --owner-ids self \
  --query "Snapshots[?StartTime<='$CUTOFF_DATE'].[SnapshotId,StartTime,VolumeSize]" \
  --output text | while read snap_id start_time size; do
  
  echo "Snapshot: $snap_id (Created: $start_time, Size: ${size}GB)"
  # Uncomment to delete:
  # aws ec2 delete-snapshot --snapshot-id $snap_id
done
#!/bin/bash
# release-unused-eips.sh

aws ec2 describe-addresses \
  --query 'Addresses[?AssociationId==null].[AllocationId,PublicIp]' \
  --output text | while read alloc_id public_ip; do
  
  echo "Would release: $public_ip ($alloc_id)"
  # Uncomment to release:
  # aws ec2 release-address --allocation-id $alloc_id
done

S3 Lifecycle Automation

# Apply lifecycle policy to transition old objects to cheaper storage
cat > lifecycle-policy.json <<EOF
{
  "Rules": [
    {
      "Id": "Archive old objects",
      "Status": "Enabled",
      "Transitions": [
        {
          "Days": 90,
          "StorageClass": "STANDARD_IA"
        },
        {
          "Days": 180,
          "StorageClass": "GLACIER"
        }
      ],
      "NoncurrentVersionExpiration": {
        "NoncurrentDays": 30
      },
      "AbortIncompleteMultipartUpload": {
        "DaysAfterInitiation": 7
      }
    }
  ]
}
EOF

aws s3api put-bucket-lifecycle-configuration \
  --bucket my-bucket \
  --lifecycle-configuration file://lifecycle-policy.json

Cost Impact Calculator

#!/usr/bin/env python3
# calculate-savings.py

import boto3
from datetime import datetime, timedelta

ec2 = boto3.client('ec2')

# Calculate EBS volume savings
volumes = ec2.describe_volumes(
    Filters=[{'Name': 'status', 'Values': ['available']}]
)

total_size = sum(v['Size'] for v in volumes['Volumes'])
monthly_cost = total_size * 0.10  # $0.10/GB-month for gp3

print(f"Unattached EBS Volumes: {len(volumes['Volumes'])}")
print(f"Total Size: {total_size} GB")
print(f"Monthly Savings: ${monthly_cost:.2f}")

# Calculate Elastic IP savings
addresses = ec2.describe_addresses()
unused = [a for a in addresses['Addresses'] if 'AssociationId' not in a]

eip_cost = len(unused) * 3.65  # $0.005/hour * 730 hours
print(f"\nUnused Elastic IPs: {len(unused)}")
print(f"Monthly Savings: ${eip_cost:.2f}")

print(f"\nTotal Monthly Savings: ${monthly_cost + eip_cost:.2f}")
print(f"Annual Savings: ${(monthly_cost + eip_cost) * 12:.2f}")

Automated Cleanup Lambda

import boto3
from datetime import datetime, timedelta

def lambda_handler(event, context):
    ec2 = boto3.client('ec2')
    
    # Delete unattached volumes older than 7 days
    volumes = ec2.describe_volumes(
        Filters=[{'Name': 'status', 'Values': ['available']}]
    )
    
    cutoff = datetime.now() - timedelta(days=7)
    deleted = 0
    
    for vol in volumes['Volumes']:
        create_time = vol['CreateTime'].replace(tzinfo=None)
        if create_time < cutoff:
            try:
                ec2.delete_volume(VolumeId=vol['VolumeId'])
                deleted += 1
                print(f"Deleted volume: {vol['VolumeId']}")
            except Exception as e:
                print(f"Error deleting {vol['VolumeId']}: {e}")
    
    return {
        'statusCode': 200,
        'body': f'Deleted {deleted} volumes'
    }

Cleanup Workflow

  1. Discovery Phase (Read-only)

    • Run all describe commands
    • Generate cost impact report
    • Review with team
  2. Validation Phase

    • Verify resources are truly unused
    • Check for dependencies
    • Notify resource owners
  3. Execution Phase (Dry-run first)

    • Run cleanup scripts with dry-run
    • Review proposed changes
    • Execute actual cleanup
  4. Verification Phase

    • Confirm deletions
    • Monitor for issues
    • Document savings

Safety Checklist

  • Run in dry-run mode first
  • Verify resources have no dependencies
  • Check resource tags for ownership
  • Notify stakeholders before deletion
  • Create snapshots of critical data
  • Test in non-production first
  • Have rollback plan ready
  • Document all deletions

Example Prompts

Discovery

  • "Find all unused resources and calculate potential savings"
  • "Generate a cleanup report for my AWS account"
  • "What resources can I safely delete?"

Execution

  • "Create a script to cleanup unattached EBS volumes"
  • "Delete all snapshots older than 90 days"
  • "Release unused Elastic IPs"

Automation

  • "Set up automated cleanup for old snapshots"
  • "Create a Lambda function for weekly cleanup"
  • "Schedule monthly resource cleanup"

Integration with AWS Organizations

# Run cleanup across multiple accounts
for account in $(aws organizations list-accounts \
  --query 'Accounts[*].Id' --output text); do
  
  echo "Checking account: $account"
  aws ec2 describe-volumes \
    --filters Name=status,Values=available \
    --profile account-$account
done

Monitoring and Alerts

# Create CloudWatch alarm for cost anomalies
aws cloudwatch put-metric-alarm \
  --alarm-name high-cost-alert \
  --alarm-description "Alert when daily cost exceeds threshold" \
  --metric-name EstimatedCharges \
  --namespace AWS/Billing \
  --statistic Maximum \
  --period 86400 \
  --evaluation-periods 1 \
  --threshold 100 \
  --comparison-operator GreaterThanThreshold

Best Practices

  • Schedule cleanup during maintenance windows
  • Always create final snapshots before deletion
  • Use resource tags to identify cleanup candidates
  • Implement approval workflow for production
  • Log all cleanup actions for audit
  • Set up cost anomaly detection
  • Review cleanup results weekly

Risk Mitigation

Medium Risk Actions:

  • Deleting unattached volumes (ensure no planned reattachment)
  • Removing old snapshots (verify no compliance requirements)
  • Releasing Elastic IPs (check DNS records)

Always:

  • Maintain 30-day backup retention
  • Use AWS Backup for critical resources
  • Test restore procedures
  • Document cleanup decisions

Kiro CLI Integration

# Analyze and cleanup in one command
kiro-cli chat "Use aws-cost-cleanup to find and remove unused resources"

# Generate cleanup script
kiro-cli chat "Create a safe cleanup script for my AWS account"

# Schedule automated cleanup
kiro-cli chat "Set up weekly automated cleanup using aws-cost-cleanup"

Additional Resources

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Assess a new or existing AI project by examining its code, goals, and constraints. Recommend skills confirmed to exist in the available registry, then outline tasks and implementation phases with dependencies, completion criteria, and checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Planning the first steps of a new AI project
  • Assessing technical issues in an existing project
  • Selecting relevant skills from an available registry
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

007

무료

Review code and infrastructure for security risks, map potential threats, and plan stronger defenses. The skill covers OWASP checks, attack and defense exercises, and incident response, with validation required for each environment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reviewing code and infrastructure security
  • Mapping threats with STRIDE or PASTA
  • Planning stronger security settings
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

Turn a repeatable task into an Andru.ia skill with clear inputs, outputs, examples, and limits. Draft SKILL.md, check the folder structure and required validations, and prepare a pull request describing the changes for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Creating a skill for a repeatable task
  • Improving an existing skill’s examples and limits
  • Validating skill files and preparing a pull request
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

Prepare an industry briefing once a project's sector is defined. It covers sector context, potentially applicable regulations, familiar interface patterns, technology choices, and risks, while separating verified evidence from hypotheses and questions requiring further review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Researching industry requirements before product design
  • Checking regulations for a project's jurisdiction
  • Choosing interface patterns familiar to target users
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

Create presentation drafts from text, outlines, or documents through the 2slides API. Match a reference image's style, choose themes, add AI voice narration, and export slide images or audio for review and use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Create a presentation from text or an outline
  • Summarize a document into slides
  • Match slide styling to a reference image
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

Plan a 360-degree or peer feedback process and create empty response templates from confirmed requirements. Produces consistent CSV, SQL, JSON Schema, or Notion property mappings while keeping visibility choices and scoring configuration separate.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Plan an anonymous peer feedback process
  • Create a CSV template for feedback responses
  • Align feedback fields across SQL and JSON Schema
sickn33/agentic-awesome-skills4.8만2026년 10월 21일 업데이트

sickn33의 스킬 모두 보기

이 스킬의 문제 신고