Production Deployment Strategies

Rollout architecture

Separate deployment from release. Deploy the code path behind feature flags, then release by cohorts. This gives you room to validate performance and behavior before broad exposure.

• - Cohort 1: internal and QA devices with expanded diagnostics.
• - Cohort 2: low-risk user slice with strict rollback thresholds.
• - Cohort 3: regional or persona-based expansion.
• - Cohort 4: general availability once SLOs remain stable.

Runtime safety controls

Add controls that can be toggled without app update where possible: disable model variant, reduce concurrency, or force fallback mode in specific environments.

struct RuntimeAIFlags {
    var enabled: Bool
    var maxConcurrentRequests: Int
    var forcedProfile: ModelProfile?
    var telemetrySamplingRate: Double
}

actor RuntimeConfig {
    private(set) var flags = RuntimeAIFlags(enabled: true, maxConcurrentRequests: 2, forcedProfile: nil, telemetrySamplingRate: 0.1)
}

Observability and incident response

• - Track p50/p95/p99 latency by model profile and feature path.
• - Track fallback ratio, cancellation ratio, and thermal downgrade ratio.
• - Track crash-free session delta before and after feature enablement.
• - Document incident runbook for rollback and communication.

App Store submission readiness

1. 1. Validate App Privacy Details declarations against actual runtime behavior.
2. 2. Include reviewer notes describing on-device inference boundaries.
3. 3. Verify entitlement and capability consistency across targets.
4. 4. Freeze model artifacts and checksums for release candidate reproducibility.
5. 5. Keep support FAQ prepared for model limitations and known edge cases.

Interactive Example Links