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Level 9 / Project 13 - Platform Cost Estimator

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— This project — — Flashcards — —

Focus

  • Strategy pattern for cloud pricing models (on-demand, reserved, spot)
  • Tiered pricing calculation with volume discounts
  • Resource usage modeling: compute, storage, network, database
  • What-if scenario analysis for cost optimization
  • Cost optimization recommendations based on usage patterns

Why this project exists

Cloud infrastructure costs can spiral without visibility — a team discovers their monthly AWS bill doubled because someone left GPU instances running over a holiday weekend. This project models resource consumption across compute, storage, network, and database tiers, projects monthly costs using different pricing models, and runs what-if scenarios to find optimization opportunities. It teaches the same FinOps (financial operations) approach used by cloud cost management platforms like CloudHealth and Kubecost.

Run (copy/paste)

cd <repo-root>/projects/level-9/13-platform-cost-estimator
python project.py --demo
pytest -q

Expected terminal output

{
  "total_monthly": 12450.00,
  "by_resource": {...},
  "what_if_savings": {...},
  "recommendations": [...]
}
7 passed

Expected artifacts

  • Console JSON output with cost estimates and optimization recommendations
  • Passing tests
  • Updated notes.md

Alter it (required)

  1. Add a SAVINGS_PLAN pricing tier with even lower rates than reserved.
  2. Add a by_tag breakdown that groups costs by resource tags (e.g. team, environment).
  3. Add a --budget flag that compares estimated costs against a monthly budget limit.

Break it (required)

  1. Create a ResourceUsage with quantity=-100 — does the cost calculation handle negatives?
  2. Use a PricingTier.SPOT for a resource type with no spot pricing rule — what fallback occurs?
  3. Set volume tier thresholds in non-ascending order — does PricingRule.calculate break?

Fix it (required)

  1. Validate that quantity >= 0 in resource usage.
  2. Sort volume tiers by threshold in PricingRule.calculate to handle unsorted input.
  3. Add a test for the fallback-to-on-demand pricing behavior.

Explain it (teach-back)

  1. How do cloud pricing tiers (on-demand, reserved, spot) differ in cost and commitment?
  2. What are volume discount tiers and how does tiered pricing work in practice?
  3. Why is what-if analysis important for infrastructure cost optimization?
  4. How do real FinOps teams use cost estimators to manage cloud spend?

Mastery check

You can move on when you can: - explain on-demand vs reserved vs spot pricing with real-world examples, - run a what-if scenario that shows savings from switching pricing tiers, - describe how volume tiers apply different rates to different usage ranges, - add a new resource type with custom pricing rules.

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