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Capacity Planning with Historical Usage Trending

Goals

  • Surface system-wide capacity risk from historical API usage trends.
  • Keep dashboard calculations deterministic and fast enough for interactive paths.
  • Provide recommendations that operations can connect to autoscaling, alerting, and deployment gates.

Architecture

  1. Telemetry ingestion collects request volume, provisioned capacity, error counts, and latency percentiles per service/API key.
  2. Trend analysis orders historical samples, computes average positive growth, projects future utilization, and identifies time-to-saturation.
  3. Recommendation layer labels plans as stable, watch, or scale based on current and forecast utilization thresholds.
  4. Dashboard presentation shows utilization, historical growth, saturation risk, recommended capacity, and a forward-looking chart.

The current frontend uses mocked dashboard data while preserving a pure calculateCapacityPlan API that can be wired to backend telemetry without changing the rendering contract.

Operational thresholds

  • Watch threshold: 70% projected utilization.
  • Scale threshold: 85% current or projected utilization.
  • Safety headroom: recommended capacity includes 20% over the forecasted peak.

Deployment and monitoring notes

  • Deploy the telemetry-backed endpoint behind a feature flag and release with blue-green plus canary analysis.
  • Alert when the scale recommendation persists for two consecutive evaluation windows or any critical path P99 exceeds 100ms.
  • Add dashboard panels for service-level forecast utilization, days to saturation, and recommendation state.
  • Update runbooks with remediation steps: add capacity, shed non-critical traffic, validate error budgets, and rollback recent changes if growth is anomalous.