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Skill
cost-optimization
Strategies and patterns for optimizing cloud costs across AWS, Azure, and GCP.
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Install
skills CLI
npx skills add https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/cost-optimization
Claude Code
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install sickn33-agentic-awesome-skills@llmmart
Git
git clone https://github.com/sickn33/agentic-awesome-skills.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole sickn33/agentic-awesome-skills collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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 conventionsassets/cost-analysis-template.xlsx- Cost analysis spreadsheet
Related Skills
terraform-module-library- For resource provisioningmulti-cloud-architecture- For cloud selection
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.
Files (agentic-awesome-skills)
-
SKILL.md 6.8 KB
--- name: cost-optimization description: "Strategies and patterns for optimizing cloud costs across AWS, Azure, and GCP." risk: critical source: community date_added: "2026-02-27" --- # 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 ```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 ## Tagging Strategy ### AWS Tagging ```hcl 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 ```hcl # 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 ```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 - **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 ## 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.
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