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PRD-STD-012: Inference Reliability & Cost Controls

Standard ID: PRD-STD-012
Version: 1.0
Status: Active
Compliance Level: Level 2 (Managed)
Effective Date: 2026-02-18
Last Reviewed: 2026-02-18

1. Purpose​

This standard defines mandatory runtime controls for AI inference reliability and cost. It ensures AI-powered features can meet production service objectives while maintaining sustainable unit economics.

Without explicit reliability and cost controls, AI features can degrade user experience, trigger incident cascades, and erode business value through unmanaged inference spend.

2. Scope​

This standard applies to:

  • All production AI inference services and dependent runtime paths
  • First-party, hosted, and third-party model inference integrations
  • User-facing and operational AI features with defined SLO/SLA obligations

3. Definitions​

TermDefinition
Inference SLOService-level objective for AI inference behavior (latency, availability, error rate)
Error BudgetMaximum acceptable SLO deviation in a defined period before action is required
Unit CostCost per AI request, per session, or per 1,000 requests/tokens
Graceful DegradationControlled fallback behavior preserving core functionality under stress/failure
Traffic GuardrailRuntime threshold that reduces, halts, or reroutes traffic when risk limits are breached

4. Requirements​

4.1 Service Objectives and Capacity Planning​

MANDATORY

REQ-012-01: Every production AI feature MUST define and publish inference SLOs for latency, availability, and error rate.

REQ-012-02: Teams MUST define error budgets and escalation triggers for each AI inference service.

REQ-012-03: Capacity planning MUST be validated pre-release through load and stress testing against expected peak traffic plus safety margin.

4.2 Runtime Resilience and Fallback​

MANDATORY

REQ-012-04: Inference paths MUST implement timeout, retry, and circuit-breaker controls aligned to SLO targets.

REQ-012-05: AI features MUST provide graceful degradation or fallback mode for upstream model/service failures.

REQ-012-06: Tier 2 and Tier 3 features MUST include tested rollback and traffic-shaping procedures.

4.3 Monitoring and Alerting​

MANDATORY

REQ-012-07: Production monitoring MUST include, at minimum:

  • request volume and success/error rates
  • latency percentiles (P50/P95/P99)
  • timeout and retry rates
  • fallback activation counts
  • unit-cost telemetry

REQ-012-08: Critical inference alerts MUST route to on-call owners within 5 minutes.

REQ-012-09: Sustained SLO breaches MUST trigger automatic mitigation (traffic reduction, fallback, or rollback) according to documented runbooks.

4.4 Cost Governance and Efficiency​

MANDATORY

REQ-012-10: AI features MUST define unit-cost budgets and monthly spend thresholds with named accountable owners.

REQ-012-11: Material cost threshold breaches MUST trigger corrective action plans and executive visibility at the appropriate governance level.

REQ-012-12: Changes that materially increase inference cost or latency MUST require controlled rollout with comparative baseline measurement.

RECOMMENDED

REQ-012-13: Organizations SHOULD maintain provider and model diversification strategies for high-criticality inference paths to reduce concentration risk.

5. Implementation Guidance​

Minimum Reliability and Cost Control Stack​

  1. SLO/error budget definitions per AI feature
  2. Runtime protection (timeouts, retries, circuit breakers, rate controls)
  3. Traffic policy (canary rollout, auto-halt, rollback)
  4. Fallback library (safe-mode behaviors by feature type)
  5. Unified observability dashboards for reliability and cost
  6. Monthly optimization review for latency/cost trends

Example Inference Gate Record​

Inference Gate Decision: PASS | CONDITIONAL | FAIL
Feature: <name>
Version: <model/prompt/runtime>
SLO Baseline: <latency/availability/error targets>
Load Test Result: <pass/fail + peak evidence>
Fallback Readiness: <tested/unverified>
Cost Budget Impact: <within threshold / breach risk>
Approvers: <platform, product, engineering>
Date: <ISO 8601>

Minimum Operational Metrics​

Track at least:

  • p95 and p99 latency trend by critical route
  • availability and error budget burn rate
  • fallback activation rate and recovery time
  • cost per 1,000 requests/tokens
  • monthly spend vs. approved budget

6. Exceptions & Waiver Process​

Waivers are permitted only for temporary non-critical procedural controls and MUST include expiration (maximum 30 days), compensating controls, and owner accountability.

No waivers are permitted for:

  • missing SLO definitions for production AI features
  • missing rollback/fallback readiness
  • missing critical alert routing
  • operating without cost visibility for production inference traffic

8. Revision History​

VersionDateAuthorChanges
1.02026-02-18AEEF Standards CommitteeInitial release