cloud-cost-optimization

name	cloud-cost-optimization
description	Cloud spending reduction strategies
license	MIT
compatibility	opencode
metadata	{"audience":"devops-engineer, platform-engineer, finance","category":"devops"}

What I do

• Analyze cloud spending patterns and identify waste
• Implement cost optimization strategies across services
• Design right-sizing policies for compute resources
• Leverage reserved instances and savings plans
• Implement auto-scaling and resource scheduling
• Build cost allocation and showback models

When to use me

• When cloud costs are higher than expected
• When you need to optimize existing cloud usage
• When planning new cloud deployments on a budget
• When implementing FinOps practices
• When needing visibility into cloud spending
• When allocating costs to teams or projects

Key Concepts

Cost Analysis Queries

-- AWS Cost Explorer - Daily costs by service
SELECT 
  line_item_usage_start_date,
  line_item_product_code,
  SUM(line_item_unblended_cost) as cost
FROM aws_cost_and_usage
WHERE line_item_usage_start_date 
  BETWEEN DATE_TRUNC('month', CURRENT_DATE) 
  AND CURRENT_DATE
GROUP BY 1, 2
ORDER BY 3 DESC;

Right-Sizing Recommendations

# GCP Recommender API example
from google.cloud import recommender_v1

client = recommender_v1.RecommenderClient()
project_id = "my-project"

# Get idle resource recommendations
recommendations = client.list_recommendations(
    parent=f"projects/{project_id}/locations/-/recommenders/"
           f"google.compute.instance.IdleResourceRecommender"
)

for rec in recommendations:
    print(f"Recommendation: {rec.description}")
    print(f"Potential savings: {rec.primary_impact.cost_forecast.amount}")

Cost Optimization Strategies

Category	Strategy	Potential Savings
Compute	Right-sizing instances	20-40%
Compute	Reserved/Savings Plans	30-60%
Storage	Lifecycle policies	50-70%
Data Transfer	CDN usage	40-60%
Database	Reserved instances	30-50%
Serverless	Pay-per-use optimization	20-30%

Resource Scheduling

# Kubernetes pod scheduling for cost savings
apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: low-priority
value: -10
globalDefault: false
description: "Non-production workloads"
---
apiVersion: v1
kind: Pod
metadata:
  name: batch-job
spec:
  priorityClassName: low-priority
  tolerations:
    - key: "spot"
      operator: "Equal"
      value: "true"
      effect: "NoSchedule"

Budget Alerts

# Terraform AWS Budgets
resource "aws_budgets_budget" "monthly" {
  name         = "monthly-cost-budget"
  budget_type  = "COST"
  limit_amount = "5000"
  limit_unit   = "USD"
  time_period_start = "2024-01-01"
  time_unit    = "MONTHLY"

  notification {
    comparison_operator = "GREATER_THAN"
    threshold          = 80
    threshold_type     = "PERCENTAGE"
    notification_type  = "FORECASTED"
  }
}

FinOps Framework

1. Inform: Provide cost visibility to teams
2. Optimize: Act on optimization opportunities
3. Operate: Maintain cost efficiency over time
4. Govern: Establish policies and guardrails

Key Metrics

• Cost per user or transaction
• Cost per environment (dev, staging, prod)
• Idle resource percentage
• Savings plan coverage
• Resource utilization rates
• Cloud waste percentage