specificationVersion: "1.0"
id: montecarlodata-finops
name: Monte Carlo FinOps Framework
description: >
  FOCUS-aligned FinOps guidance for managing Monte Carlo Data + AI Observability
  platform costs. Monte Carlo pricing is based on a pay-per-table model with optional
  commitment-based discounts. Key cost drivers are the number of monitored tables,
  daily API call consumption, and plan tier. Enterprise buyers with 30-100 tables
  across 2-3 data sources typically see annual contract values between $25,000 and $50,000.
url: https://info.montecarlodata.com/solutions/data-observability-platform-pricing
provider: Monte Carlo
framework: FinOps Framework 1.0
costDrivers:
  - name: Monitored Tables
    description: >
      The primary billing dimension. Costs scale with the number of data tables
      actively monitored across connected data sources. The Start plan caps at
      1,000 tables; Scale and Enterprise plans use unlimited pay-per-table pricing.
    unit: table
    billingModel: pay-per-table
    impactLevel: high
  - name: Daily API Call Volume
    description: >
      Each plan tier includes a fixed daily quota of API calls (10K / 50K / 100K).
      Exceeding plan-level quotas may require a plan upgrade.
    unit: API request
    billingModel: included-in-plan
    quotas:
      - plan: Start
        dailyLimit: 10000
      - plan: Scale
        dailyLimit: 50000
      - plan: Enterprise
        dailyLimit: 100000
    impactLevel: medium
  - name: Plan Tier
    description: >
      Plan selection (Start / Scale / Enterprise) determines feature access,
      user count, supported data source types, and support SLA. Upgrading tiers
      increases cost but unlocks data lake, database, and EDW monitoring.
    impactLevel: high
  - name: Commitment Discount
    description: >
      Opting into commitment-based pricing rather than pay-as-you-go provides
      cost predictability and discounted rates. Recommended for teams with stable
      or growing table counts.
    impactLevel: medium
optimization:
  - recommendation: Right-size monitored table count
    description: >
      Audit which tables are actively monitored and remove low-priority or
      rarely-queried tables to minimize per-table costs.
    effort: low
  - recommendation: Use commitment-based pricing
    description: >
      If table volume is predictable, commit to a fixed term to receive
      discounted rates versus pay-as-you-go.
    effort: low
  - recommendation: Manage API call budgets per team
    description: >
      Track daily API call consumption by team or integration to avoid hitting
      plan quotas, which could degrade monitoring coverage. Use the SDK's
      built-in retry handling to minimize wasted calls.
    effort: medium
  - recommendation: Consolidate data sources per workspace
    description: >
      Enterprise multi-workspace configurations may carry separate per-workspace
      costs. Consolidate where governance allows to reduce overhead.
    effort: medium
  - recommendation: Negotiate enterprise pricing for large deployments
    description: >
      For deployments exceeding 100 tables or requiring EDW support, negotiate
      a custom enterprise contract. Annual ACVs of $25K-$50K are typical for
      30-100 table deployments across 2-3 sources.
    effort: high
visibility:
  - type: UsageMonitoring
    description: Monitor daily API call consumption against plan quotas via the Monte Carlo UI or API.
    url: https://getmontecarlo.com/settings/api
  - type: CostReporting
    description: Request itemized usage reports from Monte Carlo customer success for table-level cost attribution.
  - type: BudgetAlerts
    description: Set internal alerts when daily API call consumption exceeds 80% of plan quota to avoid service degradation.