Ops Cost Optimization

SaaS/PaaS Cost Optimization

Use this skill to audit, reduce, and monitor infrastructure and SaaS spending. Keep the output operational: cost breakdown, waste identification, optimization actions, and monitoring setup.

Quick Reference

Workflow

1. inventory — list all paid services, current plans, billing cycles, and monthly spend
2. audit — for each service: pull usage data, compare to plan limits, identify top cost drivers by dollar amount
3. diagnose — classify each cost line:
   • necessary: directly supports revenue or product function
   • reducible: supports function but can be lowered via architecture or configuration
   • wasteful: unused, over-provisioned, or cheaper alternative exists
4. optimize — load the platform-specific reference file and apply the highest-impact tactics first
5. monitor — set up budget alerts, usage dashboards, and a monthly review cadence using references/cost-monitoring-setup.md

ASCII Flow

Cost concern or bill review
  -> Inventory paid services, owners, plans, cycles, and spend
  -> Rank cost lines by monthly dollar impact
  -> Classify each line
     +-- necessary -> protect and monitor
     +-- reducible -> tune architecture, usage, seats, or plan tier
     +-- wasteful -> cancel, consolidate, or downgrade
  -> Load platform guide for top drivers
  -> Apply highest-impact optimizations first
  -> Add budget alerts, dashboards, and monthly review cadence

Decision Rules

• start with the highest-cost service and work down
• distinguish usage-based charges (optimizable) from flat subscriptions (right-size or cancel)
• check if the free tier covers actual usage before paying for a plan
• prefer architecture changes (caching, CDN, SSG, on-demand ISR) over plan upgrades
• compare annual vs monthly pricing — annual often saves 15-20%
• consolidate services when one platform covers multiple needs (e.g., Cloudflare for DNS + CDN + storage)
• never optimize a $2/month line before a $20/month line
• when in doubt, measure for one billing cycle before cutting
• never buy a commitment (Savings Plan, RI, CUD, Reservation) against usage that hasn't been stable for 4-6+ weeks, or during an active migration/re-platform — see references/cloud-commitment-and-k8s-cost-guide.md
• separate zero-risk waste elimination from margin/durability trade-offs before cutting — a cut that reduces headroom or DR posture needs an explicit risk owner, not just a plan-tier downgrade
• weigh implementation and ongoing operational cost (engineer-time, new on-call burden) against savings before recommending a migration — a cheaper service that costs six weeks to adopt often doesn't pay back for a year

Cost Categories

When to Use This Skill

• monthly bill is higher than expected and you want to find what's driving it
• launching new projects and want to forecast infrastructure costs
• comparing free tier vs paid tier for a service
• setting up cost alerts and budget monitoring
• annual cost review and plan right-sizing
• evaluating whether to switch or consolidate services
• deciding whether to buy a Savings Plan, Reserved Instance, or Committed Use Discount, and how much
• allocating shared Kubernetes cluster cost back to teams or features
• governing AI/LLM spend before a new model-backed feature ships

Route Elsewhere

• company-level burn rate, runway, and financial operations -> startup-operating-system
• infrastructure architecture and platform design -> ops-devops-platform
• choosing between managed backend platforms -> software-baas-platforms
• AI API integration patterns (not cost) -> software-ai-integration
• payment system design (not cost) -> software-payments

Optimization Playbook

Quick wins (do first)

• remove unused projects, environments, and preview deployments
• switch time-based ISR revalidation to on-demand revalidation
• enable image optimization and compression
• check for services still on paid plans but no longer used
• consolidate DNS to a provider that includes it free (Cloudflare)

Architecture changes (do next)

• move static content to CDN or SSG to reduce function invocations
• add response caching at edge to reduce origin transfer
• batch API calls and email sends instead of per-request
• use prompt caching for repeated AI API calls
• implement connection pooling to reduce database compute

Plan optimization (do quarterly)

• compare current usage against plan tier limits
• evaluate annual vs monthly billing
• check if usage has dropped below the free tier threshold
• negotiate volume pricing when crossing tier boundaries
• remove unused seats and add-ons

Anti-Patterns

• optimizing $1 costs while ignoring $50 costs
• switching to a cheaper service without accounting for migration effort
• cutting costs that directly support revenue-generating features
• skipping monitoring setup — costs drift back up within months
• over-provisioning "just in case" without measuring actual usage
• paying for annual plans on services you might stop using

Navigation

Platform references

• references/vercel-cost-guide.md
• references/supabase-cost-guide.md
• references/resend-cost-guide.md
• references/domain-registrar-cost-guide.md
• references/stripe-cost-guide.md
• references/ai-api-cost-guide.md
• references/github-cicd-cost-guide.md
• references/monitoring-analytics-cost-guide.md
• references/cloudflare-cost-guide.md
• references/cloud-commitment-and-k8s-cost-guide.md

Cross-platform

• references/cost-monitoring-setup.md
• references/unit-economics-guide.md
• assets/monthly-cost-review-checklist.md
• data/sources.json

Agents

• agents/cost-auditor.md

Related Skills

• startup-operating-system
• ../ops-devops-platform/SKILL.md
• ../software-baas-platforms/SKILL.md
• ../software-payments/SKILL.md
• ../software-ai-integration/SKILL.md

Fact-Checking

• Verify current pricing, tier limits, and free-tier inclusions before final recommendations.
• Pricing changes frequently — prefer official pricing pages over cached knowledge.
• If web access is unavailable, mark pricing-sensitive guidance as unverified and include the official pricing URL from data/sources.json.

Learnings Loop

Before applying this skill on a non-trivial task, read learnings.consolidated.md in this directory (and learnings.md if present).

After applying it, if you encountered a pattern worth remembering, a mistake worth preventing, or a domain fact that surprised you, append one dated bullet to learnings.md via agents-skills-feedback-loop/scripts/append_learning.py. Do not modify SKILL.md itself.