Generate a capacity planning report covering current resource usage, growth projections, cost estimates, scaling recommendations, and bottleneck identification. Triggers: capacity report, capacity planning, resource usage, scaling plan, cost projection, infrastructure sizing
Document every service and its resource allocation:
| Service | Provider |
|---|
| Tier |
|---|
| CPU |
|---|
| Memory |
|---|
| Storage |
|---|
| Monthly Cost |
|---|
| Frontend | Vercel | Pro | - | - | - | $20 |
| API | Render | Starter | 0.5 CPU | 512MB | - | $7 |
| Database | Atlas | M10 | 2 vCPU | 2GB | 10GB | $57 |
For each service, capture current utilization:
Flag any metric above 70% utilization as approaching capacity.
Using the last 3-6 months of data:
Time to capacity = (Limit - Current) / Monthly Growth Rate
Determine which resource will hit its limit first:
Rank bottlenecks by time-to-capacity (shortest first).
Create projections for three scenarios:
| Scenario | Growth Rate | 3-Month Projection | 6-Month Projection | 12-Month Projection |
|---|---|---|---|---|
| Conservative | Current rate | ... | ... | ... |
| Expected | 1.5x current | ... | ... | ... |
| Aggressive | 3x current | ... | ... | ... |
For each scenario and time horizon, calculate infrastructure costs:
Produce a prioritized action plan:
| Priority | Action | Trigger | Estimated Cost | Lead Time |
|---|---|---|---|---|
| P0 | Upgrade Atlas to M20 | DB connections >80% | +$100/mo | 1 hour |
| P1 | Add Redis caching layer | API p95 >500ms | +$15/mo | 1 week |
| P2 | Enable Vercel Edge Functions | Cold starts >2s | +$0 | 2 days |
Include both reactive (fix when it breaks) and proactive (fix before it breaks) recommendations.