cost-optimization

通过资源规模调整、标签策略、预留实例和支出分析优化云成本。适用于降低云支出、分析基础设施成本或实施成本治理政策时使用。

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name:cost-optimizationdescription:Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

Cloud Cost Optimization

Strategies and patterns for optimizing cloud costs across AWS, Azure, and GCP.

Do not use this skill when

  • The task is unrelated to cloud cost optimization

  • You need a different domain or tool outside this scope
  • Instructions

  • Clarify goals, constraints, and required inputs.

  • Apply relevant best practices and validate outcomes.

  • Provide actionable steps and verification.

  • If detailed examples are required, open resources/implementation-playbook.md.
  • Purpose

    Implement systematic cost optimization strategies to reduce cloud spending while maintaining performance and reliability.

    Use this skill when

  • Reduce cloud spending

  • Right-size resources

  • Implement cost governance

  • Optimize multi-cloud costs

  • Meet budget constraints
  • Cost Optimization Framework

    1. Visibility


  • Implement cost allocation tags

  • Use cloud cost management tools

  • Set up budget alerts

  • Create cost dashboards
  • 2. Right-Sizing


  • Analyze resource utilization

  • Downsize over-provisioned resources

  • Use auto-scaling

  • Remove idle resources
  • 3. Pricing Models


  • Use reserved capacity

  • Leverage spot/preemptible instances

  • Implement savings plans

  • Use committed use discounts
  • 4. Architecture Optimization


  • Use managed services

  • Implement caching

  • Optimize data transfer

  • Use lifecycle policies
  • AWS Cost Optimization

    Reserved Instances


    Savings: 30-72% vs On-Demand
    Term: 1 or 3 years
    Payment: All/Partial/No upfront
    Flexibility: Standard or Convertible

    Savings Plans


    Compute Savings Plans: 66% savings
    EC2 Instance Savings Plans: 72% savings
    Applies to: EC2, Fargate, Lambda
    Flexible across: Instance families, regions, OS

    Spot Instances


    Savings: Up to 90% vs On-Demand
    Best for: Batch jobs, CI/CD, stateless workloads
    Risk: 2-minute interruption notice
    Strategy: Mix with On-Demand for resilience

    S3 Cost Optimization


    resource "aws_s3_bucket_lifecycle_configuration" "example" {
    bucket = aws_s3_bucket.example.id

    rule {
    id = "transition-to-ia"
    status = "Enabled"

    transition {
    days = 30
    storage_class = "STANDARD_IA"
    }

    transition {
    days = 90
    storage_class = "GLACIER"
    }

    expiration {
    days = 365
    }
    }
    }

    Azure Cost Optimization

    Reserved VM Instances


  • 1 or 3 year terms

  • Up to 72% savings

  • Flexible sizing

  • Exchangeable
  • Azure Hybrid Benefit


  • Use existing Windows Server licenses

  • Up to 80% savings with RI

  • Available for Windows and SQL Server
  • Azure Advisor Recommendations


  • Right-size VMs

  • Delete unused resources

  • Use reserved capacity

  • Optimize storage
  • GCP Cost Optimization

    Committed Use Discounts


  • 1 or 3 year commitment

  • Up to 57% savings

  • Applies to vCPUs and memory

  • Resource-based or spend-based
  • Sustained Use Discounts


  • Automatic discounts

  • Up to 30% for running instances

  • No commitment required

  • Applies to Compute Engine, GKE
  • Preemptible VMs


  • Up to 80% savings

  • 24-hour maximum runtime

  • Best for batch workloads
  • Tagging Strategy

    AWS Tagging


    locals {
    common_tags = {
    Environment = "production"
    Project = "my-project"
    CostCenter = "engineering"
    Owner = "team@example.com"
    ManagedBy = "terraform"
    }
    }

    resource "aws_instance" "example" {
    ami = "ami-12345678"
    instance_type = "t3.medium"

    tags = merge(
    local.common_tags,
    {
    Name = "web-server"
    }
    )
    }

    Reference: See references/tagging-standards.md

    Cost Monitoring

    Budget Alerts


    # AWS Budget
    resource "aws_budgets_budget" "monthly" {
    name = "monthly-budget"
    budget_type = "COST"
    limit_amount = "1000"
    limit_unit = "USD"
    time_period_start = "2024-01-01_00:00"
    time_unit = "MONTHLY"

    notification {
    comparison_operator = "GREATER_THAN"
    threshold = 80
    threshold_type = "PERCENTAGE"
    notification_type = "ACTUAL"
    subscriber_email_addresses = ["team@example.com"]
    }
    }

    Cost Anomaly Detection


  • AWS Cost Anomaly Detection

  • Azure Cost Management alerts

  • GCP Budget alerts
  • Architecture Patterns

    Pattern 1: Serverless First


  • Use Lambda/Functions for event-driven

  • Pay only for execution time

  • Auto-scaling included

  • No idle costs
  • Pattern 2: Right-Sized Databases


    Development: t3.small RDS
    Staging: t3.large RDS
    Production: r6g.2xlarge RDS with read replicas

    Pattern 3: Multi-Tier Storage


    Hot data: S3 Standard
    Warm data: S3 Standard-IA (30 days)
    Cold data: S3 Glacier (90 days)
    Archive: S3 Deep Archive (365 days)

    Pattern 4: Auto-Scaling


    resource "aws_autoscaling_policy" "scale_up" {
    name = "scale-up"
    scaling_adjustment = 2
    adjustment_type = "ChangeInCapacity"
    cooldown = 300
    autoscaling_group_name = aws_autoscaling_group.main.name
    }

    resource "aws_cloudwatch_metric_alarm" "cpu_high" {
    alarm_name = "cpu-high"
    comparison_operator = "GreaterThanThreshold"
    evaluation_periods = "2"
    metric_name = "CPUUtilization"
    namespace = "AWS/EC2"
    period = "60"
    statistic = "Average"
    threshold = "80"
    alarm_actions = [aws_autoscaling_policy.scale_up.arn]
    }

    Cost Optimization Checklist

  • [ ] Implement cost allocation tags

  • [ ] Delete unused resources (EBS, EIPs, snapshots)

  • [ ] Right-size instances based on utilization

  • [ ] Use reserved capacity for steady workloads

  • [ ] Implement auto-scaling

  • [ ] Optimize storage classes

  • [ ] Use lifecycle policies

  • [ ] Enable cost anomaly detection

  • [ ] Set budget alerts

  • [ ] Review costs weekly

  • [ ] Use spot/preemptible instances

  • [ ] Optimize data transfer costs

  • [ ] Implement caching layers

  • [ ] Use managed services

  • [ ] Monitor and optimize continuously
  • Tools

  • AWS: Cost Explorer, Cost Anomaly Detection, Compute Optimizer

  • Azure: Cost Management, Advisor

  • GCP: Cost Management, Recommender

  • Multi-cloud: CloudHealth, Cloudability, Kubecost
  • Reference Files

  • references/tagging-standards.md - Tagging conventions

  • assets/cost-analysis-template.xlsx - Cost analysis spreadsheet
  • Related Skills

  • terraform-module-library - For resource provisioning

  • multi-cloud-architecture - For cloud selection