Orchestrate builder, reviewer, and tuner agent handoffs for solution plays — define roles, model routing, token budgets, and quality gates
Configure API rate limiting, APIM throttling, and retry behavior for AI endpoints — absorb bursts, isolate noisy tenants, and control 429 retries
Configure Application Insights, OpenTelemetry, and KQL dashboards for AI workloads — trace latency, token usage, failures, and cost signals
Implement immutable audit logging, PII redaction, and Sentinel monitoring for AI systems — preserve evidence, prove access history, and detect suspicious activity
Set up Azure OpenAI deployments, RBAC, and monitoring — harden inference endpoints and control latency, quota, and cost
Back up AI data, vector indexes, and configuration state — recover prompts, conversations, and search assets after failures
Create reusable Bicep modules, parameter files, and registry packages — standardize Azure infrastructure and reduce deployment drift
Implement canary deployment, rollout gates, and rollback automation for AI changes — catch latency or quality regressions before full release