Afrexai Cloud Cost Audit

# Cloud Cost Optimization Audit

Analyze cloud infrastructure spend across AWS, Azure, and GCP. Identify waste, rightsizing opportunities, and reserved instance savings.

## What This Skill Does

When given cloud spend data (billing exports, cost explorer screenshots, or manual input), this skill:

1. **Categorizes spend** across 8 cost domains (compute, storage, networking, databases, AI/ML, observability, security, licensing)
2. **Identifies waste patterns** using 12 common anti-patterns
3. **Calculates savings** with specific dollar amounts per optimization
4. **Prioritizes actions** by effort vs. impact (quick wins → strategic moves)
5. **Generates executive summary** with 90-day roadmap

## Cost Domains & Benchmarks (2026)

### 1. Compute (typically 40-55% of total)
- **Idle instances**: >30% idle = waste. Benchmark: <10% idle capacity
- **Rightsizing**: 60% of instances are oversized by 1+ size category
- **Spot/preemptible**: Batch workloads not on spot = 60-80% overpay
- **Reserved/savings plans**: On-demand for steady-state = 30-50% overpay
- **Container density**: <40% CPU utilization on nodes = poor bin-packing

### 2. Storage (typically 10-20%)
- **Tiering**: Data not accessed in 90 days still on hot storage = 60-80% overpay
- **Snapshot sprawl**: Orphaned snapshots older than 30 days
- **Duplicate data**: Cross-region replication without business justification
- **Object lifecycle**: No lifecycle policies = guaranteed bloat

### 3. Networking (typically 8-15%)
- **Cross-AZ traffic**: Unnecessary data transfer between zones ($0.01-0.02/GB)
- **NAT gateway abuse**: High-throughput through NAT vs. VPC endpoints
- **CDN miss rate**: >20% miss rate = CDN config issue
- **Egress optimization**: No committed use discounts on egress

### 4. Databases (typically 10-20%)
- **Over-provisioned RDS/Cloud SQL**: Multi-AZ for dev/staging environments
- **Read replica sprawl**: Replicas with <5% query load
- **DynamoDB/Cosmos over-provisioning**: Provisioned capacity 3...

# Cloud Cost Optimization Audit

Audit your AWS, Azure, or GCP spend in minutes. Identifies zombie resources, over-provisioned instances, storage hoarding, and 9 more waste patterns — with dollar savings for each finding.

## What You Get

- **8-domain analysis** covering compute, storage, networking, databases, AI/ML, observability, security, and licensing
- **12 waste anti-patterns** checked against your stack
- **Dollar-specific savings** per finding with ROI and payback period
- **90-day roadmap** prioritized by effort vs. impact
- **Executive summary** ready for leadership

## Typical Results

| Company Size | Monthly Spend | Waste Found | Annual Savings |
|-------------|--------------|-------------|---------------|
| Startup | $2K-$15K | 35-50% | $8K-$90K |
| Growth | $15K-$80K | 25-40% | $45K-$384K |
| Mid-market | $80K-$500K | 20-35% | $192K-$2.1M |

## Usage

Give your agent any cloud cost data — billing exports, architecture descriptions, or just your stack and team size. It handles the rest.

## Industry-Specific Optimization

Cloud costs vary wildly by industry. HIPAA compliance, PCI requirements, data residency — all change what you can optimize.

Get industry context packs with compliance-aware optimization frameworks:

🛒 https://afrexai-cto.github.io/context-packs/
🧮 https://afrexai-cto.github.io/ai-revenue-calculator/

By [AfrexAI](https://afrexai-cto.github.io/context-packs/)