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Overview

The AWS Metrics Dashboard provides visibility into cloud spending, cost optimization opportunities, resource commitments, budget forecasting, allocation coverage, and operational efficiency across AWS environments. It helps engineering, finance, and cloud operations teams monitor cloud expenditure, identify savings opportunities, and improve cost governance. The dashboard also covers Reservations & Savings Plans, Containers & AI, Unit Economics & ROI, a FinOps Scorecard, Governance & Compliance, and Sustainability. Engineering leaders, FinOps teams, cloud administrators, finance stakeholders, and compliance teams get a single place to track cost, risk, and efficiency across AWS.

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Actions

Executive Summary

A high-level view with an AI-generated analysis of AWS spending, cost allocation, commitments, forecasting, and optimization opportunities.

Export Report

Exports AWS dashboard data and reports. Supports auditing, reporting, budgeting, and external analysis.

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Dashboard tabs

Each tab appears in the Navigation Tabs bar. Overview is the default landing tab.

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Overview tab

The default landing tab, showing overall spend, spend trend, composition by service and region, and period-over-period movement. It gives an immediate top-level read on how much is being spent, where it’s trending, what’s driving it, and what changed versus the prior period, before you drill into a specific area.

KPIs

  • Spend MTD: Total month-to-date spend, including the amortized value and month-over-month change.
  • Forecast EOM: Forecasted end-of-month spend. Shows “No budget configured” if a budget hasn’t been set.
  • Active Services: Number of active AWS services in use, and number of linked subscriptions.
  • Untagged Spend: Percentage and dollar amount of spend with no cost-allocation tags applied.

Components

  • Monthly Spend: Trend line comparing actual vs. amortized spend over time.
  • Spend by Service: Ranked bar list of the top 10 services by spend.
  • Spend by Region: Donut chart of spend distribution across AWS regions.
  • Top Movers vs Prior Period: Table comparing each service’s current vs. prior period spend and percentage change, filterable by dimension (for example, Service).
Use cases: quick top-level spend check-ins, identifying which services drive cost, spotting untagged or unbudgeted spend, comparing spend period-over-period.

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Allocation & Ownership

Tracks how well cloud spend is allocated and owned across teams, cost centers, and business units. Unallocated or unowned spend makes cost accountability difficult. This view helps FinOps and engineering leaders find ownership gaps and drive better tagging and allocation practices.

KPIs

  • Allocation Coverage: Percentage of spend allocated to a team, project, or business unit.
  • Unallocated: Dollar amount of unallocated spend, and the number of resources involved.
  • Ownership Coverage: Percentage of resources with a defined owner.
  • Unowned Resources: Number of resources without an owner, and the associated unowned spend.
  • Cost Centers: Number of active cost centers.
  • Accountable Spend: Dollar amount of spend (actual and amortized) tied to an accountable owner.

Components

  • Spend by Scope: Bar breakdown of spend by Team, Owner, Cost Center, Account, Org Unit (OU), or Environment.
  • Tag Coverage by Key: Coverage of required tagging keys across resources.
  • Owned Resources by Team: Owned resources broken down by team.
  • Cost Allocation by Business Unit: Table of actual and amortized spend, and percentage of total, per business unit.
  • Top Unowned Spend ($/mo): Highest-spending resources that have no owner.
  • Ownership Coverage Trend (%): Ownership coverage over time.
Use cases: cost allocation governance, chargeback and showback reporting, team- and owner-level accountability, closing tagging and ownership gaps.

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Budgets & Guardrails

Tracks budgets, spend guardrails, and budget alerts across the organization. It helps finance and cloud teams stay ahead of overspend by tracking budget utilization, alert activity, and forecasted overruns before they happen.

KPIs

  • Total Budget: Total budget set for the current month.
  • Actual MTD: Actual month-to-date spend and percentage of budget used.
  • Forecasted Overrun: Forecasted amount by which spend is expected to exceed budget.
  • Active Alerts: Number of currently active budget alerts.
  • Utilization: Percentage of budget used to date.
  • Guardrail Compliance: Overall compliance rate against configured spending guardrails.

Components

  • Budget vs Actual by Month: Bar chart comparing budgeted, actual, and amortized spend by month, with an amortized line overlay.
  • Budget Alerts Fired by Type: Triggered budget alerts by alert type.
  • Configured Budget Alerts: Budget alerts currently configured.
  • Budget Entities: Table of individual budgets with scope, budgeted amount, actual spend, forecast, variance, and status (for example, OK).
  • 3-Month Forecast: Forward-looking forecast, toggleable between Cost, Usage, and CE-native (Cost Explorer-native) modes.
Use cases: budget monitoring and enforcement, proactive overrun prevention, alert configuration and review, budget-level variance analysis.

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Anomalies

Detects, investigates, and tracks unexpected cost anomalies. It helps teams catch spend spikes early, understand root causes, and track how quickly anomalies are detected and resolved.

KPIs

  • Anomalies Detected: Total anomalies detected in the selected period.
  • Critical: Anomalies classified as critical severity.
  • Est. Impact: Estimated dollar impact of detected anomalies.
  • MTTD: Mean time to detect an anomaly.
  • Resolved: Anomalies that have been resolved.
  • Open Investigations: Currently active investigations.

Components

  • Spend vs Expected Baseline: Actual spend against the expected baseline, showing where and when anomalies occurred.
  • Anomaly Severity Distribution: Detected anomalies by severity level.
  • Investigation Insights - Top Causes: Share of anomalies matching each identified root cause.
  • Anomaly Feed: Running feed of detected anomalies, ordered by impact.
Use cases: cost anomaly detection and triage, root-cause investigation, incident response for unexpected spend, tracking detection and resolution speed.

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Optimization

Surfaces cost-saving recommendations, rightsizing opportunities, and resource waste across the AWS environment. It consolidates optimization opportunities, from rightsizing to waste cleanup, so teams can reduce spend without digging through every service.

KPIs

  • Recommendations: Number of active recommendations, and their source (for example, Compute Optimizer).
  • Savings / Mo: Estimated monthly savings if all recommendations were adopted.
  • Avg CPU: Average CPU utilization and the number of rightsizing recommendations it’s based on.
  • Idle Resources: Resources flagged as idle.
  • Waste / Mo: Estimated monthly wasted spend.
  • Reclaimed: Spend reclaimed in the last 30 days.

Components

  • Savings Opportunity by Type ($K/mo): Bar breakdown of savings by type (for example, commitment opportunity).
  • Recommendations by Status: Donut chart of recommendations by status (for example, Pending).
  • Top Rightsizing Recommendations: Highest-impact rightsizing recommendations.
  • Waste by Type: Wasted spend by type, with total potential monthly savings.
  • Auto-Clean Rules: Configured rules for automatically cleaning up waste (for example, unused resources).
Use cases: rightsizing and resource optimization, idle resource identification, waste reduction, automating resource cleanup.

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Reservations & Savings Plans

Tracks Reserved Instance and Savings Plan performance, including coverage, utilization, pricing model mix, and upcoming expirations. It helps FinOps and cloud teams maximize the return on committed-use spend, avoid uncovered on-demand costs, and prevent waste from unused or expiring contracts.

KPIs

  • Commitment Coverage: Percentage of eligible usage covered by a commitment, with the number of commitments tracked.
  • Avg Utilization: Average utilization rate across active commitments.
  • On-Demand Uncovered: Spend still running at on-demand rates.
  • Annualized Savings: Net savings from commitments, annualized.
  • Expiring (90D): Number or value of commitments expiring within the next 90 days.
  • Unused Commitment: Committed spend that is going unused.

Components

  • Coverage vs Utilization Trend: Time series of coverage % and utilization % over the selected period, showing gaps between what’s committed and what’s used.
  • Portfolio by Term (Count): Commitment portfolio by contract term length.
  • Cost by Pricing Model: Bar chart of spend across pricing models (for example, On-Demand, Savings Plan).
  • Spot & Unused Commitment: Bar chart of Spot spend versus unused committed capacity.
  • Cost Explorer Recommendations: AWS Cost Explorer-sourced recommendations, such as increasing Savings Plan or RI coverage, with estimated effort and severity.
Lists upcoming commitment expirations. The Simulate action models the impact of renewing or resizing a commitment and returns:
  • Estimated monthly savings and savings percentage
  • Estimated ROI
  • Hourly commitment rate
  • Current on-demand spend
  • Estimated total cost
Use cases: Reserved Instance and Savings Plan planning, identifying uncovered on-demand spend, preventing commitment waste, renewal and expiration planning, cost optimization through commitment simulation.

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Containers & AI

Tracks costs and utilization for containerized workloads (EKS) alongside AI/ML spend and workload costs. Container and AI workloads are often variable and fast-growing, so this view gives engineering and FinOps teams visibility into cluster efficiency and AI spend before costs scale out of control.

KPIs

  • EKS Clusters: Active EKS clusters being tracked.
  • EKS Cost / Mo: Monthly cost attributed to EKS clusters.
  • Idle Capacity: Provisioned capacity not being utilized.
  • AI Spend MTD: Month-to-date AI spend, broken down by number of workloads and models in use.
  • AI Billed Cost: Total billed cost associated with AI usage.

Components

  • EKS Cost by Namespace: Kubernetes cost by namespace, to identify which teams or services drive container spend.
  • Cluster CPU Utilization (%): CPU utilization across clusters, to surface over- or under-provisioned capacity.
  • AI Spend by Model: AI spend by the underlying model in use.
  • Cost by AI Workload: AI cost by individual workload.
Use cases: Kubernetes cost allocation, identifying idle container capacity, AI/ML cost monitoring, model-level and workload-level cost accountability.

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Unit Economics & ROI

Translates cloud spend into business-relevant unit economics and tracks the return on FinOps and optimization initiatives. It connects infrastructure cost to business outcomes (cost per customer, per transaction, and per feature) and shows whether cost-saving initiatives deliver the results they were planned for.

KPIs

  • Cost / Customer: Average cloud cost attributable to a single customer.
  • Cost / 1K Txns: Cloud cost per 1,000 transactions.
  • AI % of Revenue: AI spend as a percentage of revenue.
  • Gross Margin: Gross margin after accounting for cloud costs.
  • Savings Pipeline: Total value of identified but not-yet-realized savings initiatives.
  • Realized (MTD): Savings realized month-to-date.
  • ROI (Realized): Return on investment from realized savings initiatives.
  • Payback: Estimated payback period for optimization investments.

Components

  • Planned vs Realized Savings: Planned savings compared with what has been realized.
  • Cloud Cost per Product Line ($/Customer): Cloud cost per customer by product line.
  • Cost per Feature: Cloud cost by individual product feature.
  • ROI by Initiative Type: ROI across categories of optimization initiatives.
  • Initiative Tracker: Status of active cost-optimization initiatives.
  • Top Recommendations by Estimated Savings: Table of recommendations (for example, “Increase Savings Plan / RI coverage”) with estimated savings, priority, and current state (for example, Open).
Use cases: cost-to-revenue analysis, product- and feature-level cost accountability, tracking initiative ROI and payback, prioritizing optimization initiatives by savings impact.

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FinOps Scorecard

Summarizes the organization’s overall FinOps maturity, spend run-rate, forecast accuracy, and savings realization. It gives leadership a single, trackable measure of how mature and effective the FinOps practice is over time, and where capability gaps remain.

KPIs

  • Monthly Run-Rate: Current monthly spend run-rate.
  • Budget Variance: Variance between actual spend and budget.
  • Realized Savings: Total savings realized in the period.
  • Forecast Accuracy: Accuracy of prior spend forecasts against actuals.
  • Allocation Coverage: Percentage of spend allocated to a team, project, or business unit.
  • FinOps Score: Composite score of overall FinOps maturity.
  • Compliance Score: Composite score of governance and policy compliance.

Components

  • Monthly Run-Rate Trend ($M): Line chart of the monthly spend run-rate over time.
  • Maturity by FinOps Capability (%): Maturity across the five core capabilities: Allocate, Govern, Inform, Operate, and Optimize.
  • Forecast Accuracy by Closed Month: Forecast-vs-actual accuracy for each closed reporting month.
  • Cost by Business Unit: Donut chart of total spend by business unit, including unallocated spend.
  • Savings Funnel ($M): Funnel of savings that were Planned, Actioned, and Realized.
Use cases: tracking FinOps program maturity over time, executive FinOps reporting, identifying capability gaps (for example, low “optimize” maturity), monitoring forecast accuracy and budget discipline.

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Governance & Compliance

Tracks policy compliance, control health, and open governance findings across the AWS environment. It helps cloud governance and security teams monitor policy adherence, track remediation of failing controls, and maintain audit readiness.

KPIs

  • Compliance Score: Overall compliance score, based on the number of controls evaluated.
  • Open Violations: Open policy violations, out of total findings.
  • Tags Enforced: Rate of required tagging policy enforcement.
  • Policy Pass Rate: Percentage of policy checks currently passing.
  • Failed Controls: Failed controls, out of total controls reviewed.
  • Audit Readiness: Indicator of overall audit readiness.

Components

  • Compliance Score Trend: Line chart of the compliance score over time.
  • Remediation Aging (Open Issues): Bar chart of how long open issues have remained unresolved.
  • Score by Business Unit (/100): Compliance score by business unit.
  • Policy Pass / Fail by Control Family: Horizontal bar chart of pass/fail counts across control families (for example, S3, EC2, Cloud Config).
  • Recent Failing Findings: Table of recent failing findings with control family, policy, affected resource, severity, and detection timestamp.
Shows the health of the data pipelines that feed the dashboard (for example, cost usage, commitment coverage, recommendations, anomalies, forecast). It displays an overall status (for example, Degraded) and a per-pipeline status (OK, Failed, Stale) with data freshness lag.
Use cases: policy and control compliance monitoring, audit preparation, remediation tracking, identifying which business units or control families need attention, monitoring the health and freshness of dashboard data pipelines.

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Sustainability

Tracks the carbon footprint of AWS usage, including regional emissions, per-service breakdowns, and trends over time. It helps organizations understand and reduce the environmental impact of their cloud usage, and supports sustainability and low-carbon region adoption goals.

KPIs

  • Emissions: Total emissions (tCO2e) for the selected reporting period.
  • **Per $1K Spend**: Emissions normalized per $1,000 of cloud spend.
  • Low-Carbon Region Adoption: Percentage of workloads running in low-carbon AWS regions.
  • MoM Change: Month-over-month change in emissions.

Components

  • Emissions by Region (tCO2e): Emissions by AWS region.
  • Emissions by Service (tCO2e): Emissions by AWS service.
  • Monthly Emissions Trend (tCO2e): Emissions over time, monthly.
Use cases: carbon footprint tracking, sustainability reporting, low-carbon region migration planning, ESG and corporate sustainability initiatives.