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PluginsResource Forecaster

Resource Forecaster: Deterministic FinOps Control Plane 💰

A regression-driven FinOps Assurance Engine that validates compute expenditure against projected demand and codifies budget guardrails directly into IaC. It delivers the Deterministic Cost-to-Serve (CTS) transparency required to manage AI at enterprise scale.

ML Task: RegressionDomain: FinOps & capacity planningRMSE monitor: Active
Domain FocusFinOps & Capacity Governance
Target AudienceFinance / Platform / SRE Leaders
Platform Fee$1,950/mo fixed
FocusSpend JustificationBudget envelopes by environment.
GuardrailRMSE ≤ 4.7%Auto-alerts on anomaly windows.
OutcomeSavings surfacedRecommends rightsizing + SP buys.

FinOps Budget Certainty: Regression Envelope vs. Guardrail

The Forecasted Regression Envelope bounds expected consumption while the Budget Guardrail represents a distinct, hard spending limit. Actual consumption is presented to show adherence to these guarantees.

Resource Forecaster regression vs. actual consumptionJanFebMarAprMayJun249290331372Monthly normalized compute hoursSpend envelope (k$)
Forecasted regression envelopeActual consumptionBudget Guardrail (hard limit)

Model Fidelity & Cost Assurance Scorecard

Finance, platform, and SRE teams rely on deterministic guarantees. This scorecard surfaces fidelity, budget compliance, and realized optimization impact.

  • Forecast Fidelity (RMSE)3.9%Keeps the blended regression stack under the 5% variance threshold, guaranteeing high-confidence projections.
  • Budget Compliance0 BreachesZero instances of deployments or consumption exceeding committed budget envelopes.
  • Resource Optimization-41% DeltaQuantifiable reduction in monthly compute spend versus baseline after automated rightsizing and SP adjustments.

Policy Enforcement & Budget Governance

  • Model Auditability: SageMaker Feature Store captures complete enrichment lineage so finance teams can audit every input driver used in the forecast.
  • Deployment Blockers: Infra-as-Code PR checks prevent resource rollouts that breach forecast guardrails without explicit executive override and justification.
  • Immutable Retraining: Cross-environment retrains sign manifest hashes and promote through CodePipeline only once RMSE proves stable for 14 days.

Forecast pipeline blueprint

Blueprinted to operationalize budget certainty: feature hygiene, bounded regression envelopes, and enforced guardrails run in concert so forecasts are auditable and actionable from day one.

  • Trusted Feature Curation. Tag validators reconcile AWS Config, Cost Explorer, and custom metadata to ensure 100% feature hygiene before model ingestion.
  • Regression Envelope & Guardrail. Per-environment regression envelopes produce bounded forecasts with explicit budget guardrails and RMSE-based fidelity contracts.
  • Recommendation Automation. Rightsizing, Savings Plan utilization, and reserved instance recommendations convert into owner-assigned, dollar-impact tickets.

Operational KPIs

Dial in success metrics and how every alert or recommendation converts to owner-assigned actions with dollar impact.

  • Forecast Fidelity - RMSE 3.9%. Keeps the blended regression stack under the 5% variance threshold.
  • Budget Compliance - 0 Breaches. Zero instances of consumption exceeding committed budget envelopes.
  • Resource Optimization - -41% Delta. Quantifiable monthly compute spend reduction after automated rightsizing and SP adjustments.

Governance baked into IaC

Governance elements are embedded in the pipeline so policy enforcement is automatic and auditable.

  • Trusted feature curation and tag validators reconcile AWS Config, Cost Explorer, and custom metadata to ensure feature hygiene before ingestion.
  • Recommendations convert to Jira tickets with owner, quantifiable dollar impact, and due date.
  • Budgets and anomaly notifications align with Service Control Policies (SCPs) to maintain org-level financial guardrails.

What ships with the accelerator

  • Historical telemetry, tagging metadata, and workload calendars hydrate a regression model that forecasts compute spend envelopes per environment.
  • RMSE tracking feeds CloudWatch dashboards so FinOps teams can prove model fidelity and trigger retraining when error budgets drift.
  • Recommendations flow into AWS Budgets and Cost Explorer playbooks, pairing projections with just-in-time savings plan guidance.