# Cost Analysis > Infrastructure cost modeling, scaling projections, and optimization recommendations - Skill: `dtsong/cost-analysis` (Agent Skill) - Install (CLI): `npx skillmds@latest add dtsong/cost-analysis` - Raw SKILL.md: https://api.skillmd.com/api/skills/dtsong/cost-analysis/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools, Marketing & Growth - Author: dtsong (https://skillmd.com/u/dtsong) - Updated: 2026-09-10 - Page: https://skillmd.com/skills/dtsong/cost-analysis --- # Cost Analysis ## Purpose Model infrastructure costs at current and projected scale, identify optimization opportunities, and establish cost monitoring with budget alerting. Produces a cost breakdown that enables informed architecture and scaling decisions. ## Inputs - Current infrastructure inventory (services, providers, tiers) - Current usage metrics (requests/day, storage volume, compute hours) - Growth projections or scaling targets - Budget constraints or cost reduction goals ## Process ### Step 1: Inventory Infrastructure Components Catalog all cost-bearing components: - **Compute**: Application servers, serverless functions, background workers, build runners - **Storage**: Object storage, block storage, database storage, backup storage - **Database**: Managed database instances, read replicas, connection poolers - **CDN**: Bandwidth, edge compute, cache storage - **Third-party services**: Auth providers, email/SMS, payment processing, analytics, error tracking - **DNS and networking**: Domain registration, DNS queries, load balancers, NAT gateways, data transfer - **Email**: Transactional email, marketing email, inbound processing ### Step 2: Estimate Per-Unit Costs at Current Scale For each component, calculate: - **Monthly base cost**: Fixed costs regardless of usage (reserved instances, minimum tiers) - **Variable cost**: Per-request, per-GB, per-user marginal costs - **Cost per user**: Total infrastructure cost divided by active users - **Cost per request**: Total infrastructure cost divided by total requests - Document pricing tier thresholds and current utilization against limits ### Step 3: Model Cost Projections at Scale Project costs at growth milestones: - **2x scale**: Which components scale linearly vs step-function? Where do tier upgrades hit? - **5x scale**: Which pricing tiers break? Where do volume discounts apply? - **10x scale**: What architectural changes become necessary? Which components become dominant costs? - Identify cost cliffs — points where a small usage increase triggers a large cost jump ### Step 4: Identify Optimization Opportunities Evaluate cost reduction strategies: - **Right-sizing**: Over-provisioned instances, unused reserved capacity, oversized database tiers - **Reserved/committed use**: Savings from 1-year or 3-year commitments on stable workloads - **Spot/preemptible instances**: Suitable workloads for interruptible compute (batch jobs, builds) - **Caching to reduce compute**: CDN caching, application-level caching, database query caching - **Query optimization**: Slow queries consuming excess database resources, missing indexes - **Architecture changes**: Serverless for bursty workloads, edge compute for latency, static generation ### Step 5: Design Cost Monitoring and Alerting Establish ongoing cost visibility: - **Budget thresholds**: Alert at 50%, 75%, 90%, 100% of monthly budget - **Anomaly detection**: Unexpected cost spikes from runaway processes, misconfigured auto-scaling, or attacks - **Cost-per-user trending**: Track unit economics over time to catch efficiency degradation - **Tag-based allocation**: Cost attribution by service, team, environment, feature - **Review dashboard**: Real-time cost breakdown accessible to engineering and leadership ### Step 6: Plan Budget Allocation and Review Cadence Define the financial process: - **Budget allocation**: Per-service or per-team budget breakdown - **Review cadence**: Monthly cost review meetings, quarterly budget adjustments - **Cost ownership**: Which team owns which infrastructure costs - **Approval process**: Threshold for new infrastructure spending requiring approval - **Cost-benefit framework**: How to evaluate infrastructure investments against engineering time ## Output Format ```markdown # Cost Analysis: [Project/Service Name] ## Infrastructure Cost Table | Component | Provider | Tier | Monthly Cost | Cost Driver | Notes | |-----------|----------|------|-------------|-------------|-------| | App Server | [provider] | [tier] | $X | requests | ... | | Database | [provider] | [tier] | $X | storage + queries | ... | | CDN | [provider] | [tier] | $X | bandwidth | ... | | **Total** | | | **$X** | | | **Cost per user**: $X/month | **Cost per 1K requests**: $X ## Scaling Projections | Component | Current | 2x | 5x | 10x | |-----------|---------|-----|-----|------| | Compute | $X | $X | $X | $X | | Database | $X | $X | $X | $X | | Storage | $X | $X | $X | $X | | **Total** | **$X** | **$X** | **$X** | **$X** | ## Optimization Recommendations | Optimization | Estimated Savings | Effort | Risk | Priority | |-------------|-------------------|--------|------|----------| | [description] | $X/month (Y%) | Low/Med/High | Low/Med/High | P1/P2/P3 | ## Budget Alert Thresholds | Threshold | Monthly Amount | Action | |-----------|---------------|--------| | 50% | $X | Review dashboard | | 75% | $X | Investigate anomalies | | 90% | $X | Escalate to lead | | 100% | $X | Freeze non-critical spending | ``` ## Quality Checks - [ ] All cost-bearing infrastructure components are inventoried - [ ] Per-unit costs (per user, per request) are calculated for current scale - [ ] Scaling projections identify cost cliffs and tier boundaries - [ ] Optimization recommendations include estimated savings and effort - [ ] Cost monitoring covers budget alerts and anomaly detection - [ ] Budget review cadence and cost ownership are defined - [ ] Third-party service costs are included (not just cloud infrastructure) - [ ] Cost projections account for both linear and step-function scaling ## Evolution Notes