Cost Optimization

作者 wshobson46891e7e60da无许可证收录于 2026年10月8日更新于 2026年10月8日

Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

AI 生成的概览

指导 AWS、Azure、GCP 和 OCI 的云成本优化,涵盖资源规格调整、标签、定价模型和预算。

功能
该技能提供一套跨 AWS、Azure、GCP 和 OCI 降低云支出的结构化框架。内容涵盖成本可见性与成本分摊标签、资源规格调整、预留与承诺定价模型、竞价与可抢占实例、存储生命周期策略、预算告警和异常检测。还包含无服务器、合理规格数据库、多层存储和自动扩缩容等架构模式,以及成本优化检查清单和各云厂商成本工具列表。
适用场景
适用于降低云支出、分析基础设施成本,或实施成本治理与预算策略的场景。也适合多云成本审查和满足预算约束。
运行要求
仅为说明性内容,不附带脚本。技能文件夹中引用了一份标签标准文档。实际应用该指南需要访问云厂商控制台、成本管理工具以及 Terraform 等基础设施即代码工具。

Cloud Cost Optimization

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

Purpose

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

When to Use

  • 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-DemandTerm: 1 or 3 yearsPayment: All/Partial/No upfrontFlexibility: Standard or Convertible

Savings Plans

Compute Savings Plans: 66% savingsEC2 Instance Savings Plans: 72% savingsApplies to: EC2, Fargate, LambdaFlexible across: Instance families, regions, OS

Spot Instances

Savings: Up to 90% vs On-DemandBest for: Batch jobs, CI/CD, stateless workloadsRisk: 2-minute interruption noticeStrategy: Mix with On-Demand for resilience

S3 Cost Optimization

hcl
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

OCI Cost Optimization

Flexible Shapes

  • Scale OCPUs and memory independently
  • Match instance sizing to workload demand
  • Reduce wasted capacity from fixed VM shapes

Commitments and Budgets

  • Use annual commitments for predictable spend
  • Set compartment-level budgets with alerts
  • Track monthly forecasts with OCI Cost Analysis

Preemptible Capacity

  • Use preemptible instances for batch and ephemeral workloads
  • Keep interruption-tolerant autoscaling groups
  • Mix with standard capacity for critical services

Tagging Strategy

AWS Tagging

hcl
locals {  common_tags = {    Environment = "production"    Project     = "my-project"    CostCenter  = "engineering"    Owner       = "[email protected]"    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

hcl
# AWS Budgetresource "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 = ["[email protected]"]  }}

Cost Anomaly Detection

  • AWS Cost Anomaly Detection
  • Azure Cost Management alerts
  • GCP Budget alerts
  • OCI Budgets and Cost Analysis

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 RDSStaging: t3.large RDSProduction: r6g.2xlarge RDS with read replicas

Pattern 3: Multi-Tier Storage

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

Pattern 4: Auto-Scaling

hcl
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
  • OCI: Cost Analysis, Budgets, Cloud Advisor
  • Multi-cloud: CloudHealth, Cloudability, Kubecost

Related Skills

  • terraform-module-library - For resource provisioning
  • multi-cloud-architecture - For cloud selection

来源与署名

来源:wshobson/agents位于plugins/cloud-infrastructure/skills/cost-optimization提交46891e7

许可证: 无许可证

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