Scaling and Operating GenAI in Production

GenAI applications are easy to prototype, but production systems need controlled routing, failure isolation, measurable quality, safe release gates, and clear operator evidence.
GenAI applications are easy to prototype, but production systems need controlled routing, failure isolation, measurable quality, safe release gates, and clear operator evidence. In this course, Scaling and Operating GenAI in Production, you'll gain the ability to scale and operate GenAI services that can handle real traffic, provider failures, cost pressure, and model change safely. First, you'll explore dedicated AI service layers, multi-model routing, weighted load balancing, and payload-based routing policies. Next, you'll discover how queues, rate limits, fail-fast gates, circuit breakers, retries, traces, logs, metrics, and quality sampling protect GenAI integrations under production pressure. Finally, you'll learn how to manage prompt versions, model updates, canary releases, provider deprecations, readiness checks, and operational runbooks. When you're finished with this course, you'll have the skills and knowledge of production GenAI operations needed to scale, observe, release, and support GenAI systems with confidence.
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