SKILL: FinOps Review

Purpose

Identify and annotate the cloud cost implications of architectural decisions.

Cost Driver Categories

Compute

• Lambda/Functions: invocation count x duration x memory
• EC2/VMs: instance type x hours + data transfer
• Containers: CPU/memory reservation x hours
• Edge functions: request count x execution time

Storage

• Object storage (S3/GCS/Blob): GB stored + requests + egress
• Database: instance size + storage + IOPS + backups
• Cache: node size x hours

Networking

• Egress: GB transferred out (most expensive)
• CDN: requests + GB served
• Load balancer: hours + LCU

Third-party APIs

• Stripe: 2.9% + $0.30 per transaction
• Supabase: row reads/writes, storage, Edge Function invocations
• Vercel: bandwidth, function invocations, seats

Annotation Format (Terraform)

resource "aws_db_instance" "main" {
  # finops: ~$180/mo (db.t3.medium, 100GB gp3, 1 AZ)
  # finops: scale-trigger: >70% CPU or >80% storage
  instance_class = "db.t3.medium"
  ...
}

Architecture Review Questions

1. What scales with user count? What scales with data volume?
2. Are there N+1 API calls that will cost $$ at scale?
3. Is egress minimized? (Cache aggressively, colocate services)
4. Are reserved instances/savings plans applicable?
5. What is the cost at 10x current load?

Monthly Estimate Template

## Cost Estimate: {Feature}

| Service | Config | Est. Monthly |
|---------|--------|-------------|
| RDS PostgreSQL | db.t3.medium, 100GB | $180 |
| ElastiCache Redis | cache.t3.micro | $25 |
| ECS Fargate | 2 tasks, 0.5 vCPU, 1GB | $30 |
| ALB | 1 ALB, ~1M requests | $20 |
| **Total** | | **~$255/mo** |

Scales linearly with: [traffic volume / data volume]