Cost Optimization

# Cloud Tagging Standards

## Required Tags

- `Environment`: dev, staging, production
- `Owner`: team or individual responsible for the workload
- `CostCenter`: finance or reporting identifier
- `Project`: product or initiative name
- `ManagedBy`: terraform, opentofu, pulumi, or manual

## Provider Notes

- AWS: standardize tags for Cost Explorer, CUR, and automation policies
- Azure: align tags with management groups, subscriptions, and Azure Policy
- GCP: combine labels and resource hierarchy for billing attribution
- OCI: apply defined tags at the compartment and resource level for chargeback

## Best Practices

1. Publish an approved tag dictionary and naming rules.
2. Enforce tags with policy and CI validation.
3. Inherit tags from shared modules whenever possible.
4. Audit for missing or inconsistent tags weekly.


---
name: cost-optimization
description: 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.
---

# 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

```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