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Cost Optimization

Seth HobsonCommunityCreated by Seth Hobson

  • Skill
  • Guidelines
  • Cloud and DevOps
  • MIT
  • No issues found

From the author

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.
— the description by Seth Hobson

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to cloud cost optimization, focusing on visibility, resource rightsizing, pricing models, and architectural patterns. It covers specific strategies for major cloud providers, including reserved instances, savings plans, and spot instances, while emphasizing the importance of tagging strategies and automated monitoring to maintain budget control.

What it does

  • Provides strategies for rightsizing resources to eliminate waste.
  • Outlines pricing models like reserved instances and spot capacity.
  • Defines tagging standards for improved cost allocation and visibility.
  • Offers architectural patterns for serverless and multi-tier storage.
  • Includes a checklist for continuous cost monitoring and governance.
  • Details provider-specific tools for anomaly detection and budgeting.

When to use it

  • When you need to reduce monthly cloud expenditures.
  • When implementing cost governance policies across an organization.
  • When analyzing infrastructure utilization to identify over-provisioning.
  • When planning a multi-cloud strategy with budget constraints.
  • When setting up automated alerts for cost anomalies.

Advantages

  • Provides a unified approach across multiple cloud providers.
  • Includes actionable architectural patterns for immediate implementation.
  • Promotes a culture of continuous cost awareness.
  • Offers clear guidance on leveraging discount programs like savings plans.

Usage examples

“How can I reduce my AWS EC2 costs for batch processing jobs?”
The agent will recommend using Spot Instances for up to 90% savings, noting the risk of interruption and suggesting a mix with On-Demand instances for resilience.
“What is the best way to organize my cloud resources for better cost tracking?”
The agent will provide a tagging strategy using keys like Environment, Owner, and CostCenter, and explain how to enforce these tags for better billing attribution.
“How do I optimize storage costs for data that is rarely accessed?”
The agent will suggest implementing lifecycle policies to transition data from standard storage to colder tiers like S3 Glacier or equivalent.
“What are the main ways to save on GCP compute costs?”
The agent will explain Committed Use Discounts, Sustained Use Discounts, and the use of Preemptible VMs for batch workloads.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/wshobson/cost-optimization/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip cost-optimization.zip -d .agents/skills

Documentation by Seth Hobson

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-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

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
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
# 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 = ["[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 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

  • OCI: Cost Analysis, Budgets, Cloud Advisor

  • Multi-cloud: CloudHealth, Cloudability, Kubecost

  • terraform-module-library - For resource provisioning

  • multi-cloud-architecture - For cloud selection

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/cloud-infrastructure/skills/cost-optimization · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Seth Hobson.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download cost-optimization.zip