AI service operations
Generative AI Cost Control Runbook
Attribute, forecast, constrain, investigate, and optimize AI usage without trading away required quality, safety, or reliability.
- Format
- Playbook
- Level
- Intermediate
- Audience
- Developer, Operator, Leader
- Owner
- Project42 Editorial
- Review cadence
- Every 30 days
- Prerequisites
- Provider usage and billing access; Application telemetry with workload attribution; Quality, safety, latency, and cost objectives
Build cost from observed workload units
Record provider, exact model and feature, region or service tier, input, cached input, output and reasoning usage where exposed, tool and search charges, storage, batch or priority multipliers, retries, and gateway or hosting costs. Price pages are volatile; store the verified date and pricing source with every forecast.
Attribute usage to environment, product, feature, team, and approved pseudonymous tenant or user dimension. Reconcile application estimates against provider billing because token counting alone can omit features, caching, storage, or failed and retried operations.
Use layered controls and an anomaly response
Apply model allowlists, per-request output and tool budgets, concurrency and rate limits, retry limits, caching where semantically safe, per-workload spend alerts, and a tested block or degraded mode. Optimize prompts, context, routing, and batching only against the same quality and safety gate.
For a cost spike, identify the first divergent workload, model, prompt, tool, release, credential, or traffic source. Contain before optimizing: pause the feature, reduce a bounded limit, block an abusive identity, or route to a verified fallback.
Task: [FORECAST, CONTROL, OR INVESTIGATE AI COST]
Scope: [PROVIDERS, MODELS, FEATURES, ENVIRONMENTS, AND TIME WINDOW]
Permissions: [WHO MAY VIEW BILLING, CHANGE LIMITS, ROUTE, OR SUSPEND]
Pricing evidence: [SOURCE, VERIFIED DATE, CURRENCY, AND RATE DIMENSIONS]
Usage equation: [REQUESTS x INPUT/CACHED/OUTPUT/FEATURE UNITS + INFRASTRUCTURE]
Attribution: [ENVIRONMENT, PRODUCT, FEATURE, TEAM, AND SAFE TENANT DIMENSION]
Controls: [ALLOWLIST, REQUEST BUDGET, RATE, CONCURRENCY, RETRY, SPEND, AND BLOCK]
Stop conditions: [CRITICAL QUALITY LOSS, UNATTRIBUTED SPIKE, COMPROMISED KEY, OR BUDGET]
Verification: [PROVIDER RECONCILIATION, ALERT/BLOCK TEST, AND QUALITY GATE]
Recovery: [CONTAIN, REVOKE/ROUTE, RECONCILE CHARGES, RESTORE VERIFIED CONFIG]Expected result and verification
Expected evidence includes a dated pricing snapshot, observed usage distribution, unit-cost equation, forecast ranges, attribution coverage, reconciliation variance, controls, alert and block tests, quality impact, owners, and response runbook.
Stop an optimization that violates a critical quality or safety threshold. When usage is unexplained, contain the affected route or identity, preserve billing and request evidence, rotate compromised credentials, reconcile delayed provider data, and restore the last verified configuration before reopening traffic.