Architecture

Cost Allocation / Showback Platform

A generic pattern to convert cloud bills into reconciled showback datasets: ingest spend and telemetry, map ownership and dimensions, allocate shared pools using measurable drivers, publish curated outputs, and report with governance controls.

View Cost Model

Spend + Usage Ingest

  • —Billing exports + usage metering
  • —Normalize accounts, SKUs, tags, org mapping
  • —Completeness + freshness checks

Dimensions + Ownership

  • —Team / service catalog (owners)
  • —Cost centers + products + environments
  • —Tag rules + exceptions + fallbacks

Allocation Engine

  • —Direct mapping + shared pool allocation
  • —Drivers: TB, queries, requests, CPU-min
  • —Versioned methodology + rerunnable runs

Showback Datasets

  • —Curated tables by org / service / dataset
  • —Time-series rollups + drilldowns
  • —Reconciliation views (bill ↔ model)

Reporting + Governance

  • —Dashboards + scheduled reports
  • —Anomaly alerts + variance explanations
  • —Audit trail + controls
Component details(+ principles)

Billing + Usage Collector

Ingests billing exports and workload usage signals, then standardizes them into a consistent cost and usage schema.

Examples: ETL jobs, serverless ingest, data pipelines

Ownership + Dimension Catalog

Defines ownership and reporting dimensions (team/product/dataset) with rules for tags, fallbacks, and exceptions.

Examples: service registry, CMDB, governance catalog

Allocation Methodology

Applies direct mapping and driver-based allocations for shared pools, producing reproducible, versioned outputs.

Examples: rules engine, SQL transforms, batch compute

Reconciliation Layer

Ties the model back to the bill and explains variance, making exceptions explicit and defensible.

Examples: bridge tables, controls checks, variance reports

Showback Data Mart

Publishes curated, query-friendly datasets for dashboards, ad-hoc analysis, and finance reviews.

Examples: warehouse tables, lakehouse views, semantic layer

Reporting + Controls

Delivers dashboards and governance: alerts, approvals, audit logs, and recurring review cadence.

Examples: BI dashboards, ticketing, metrics, alerting

Key architectural principles

Reconcile to the bill (always explain variance)
Separate raw ingest vs modeled outputs (clean contracts)
Versioned methodology (repeatable + auditable)
Default rules + explicit exceptions (no hidden logic)
Driver-based allocations for shared pools (fair + scalable)
Automation by default (repeatable monthly cadence)

Outcomes

Decision-ready explainability

Drill down from dollars → cost buckets → drivers → owners without manual investigations.

Finance-grade reconciliation

Modeled outputs tie back to the bill with explicit variance explanations and controls checks.

Scalable allocation mechanics

Shared costs are allocated with measurable drivers that scale with growth and org changes.

Operational reliability

Automated pipelines with retries, DLQs, and data quality checks reduce manual toil and surprises.

Governance built in

Audit trails and methodology versioning enable repeatable monthly cadence and stakeholder trust.

Cloud-agnostic pattern

The same architecture works across vendors as long as you have billing exports + usage telemetry.

View Cost Model →

Note: This page is intentionally generic (no vendor or internal system names). Swap in your platform equivalents as needed.