From Traction to Production: Maturing your GenAIOps step by step

Your GenAI proof-of-concept is just the beginning. Learn the GenAIOps discipline to successfully scale, secure, and maintain your application in production.

#1about 4 minutes

Understanding the key challenges in operationalizing GenAI projects

Building GenAI applications is difficult due to challenges in model selection, specialized skills, data context, quality evaluation, and overall operationalization.

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Defining GenAIOps and its relationship to MLOps

GenAIOps is a discipline combining people, processes, and platforms to continuously deliver value, differing from MLOps in its focus on consuming pre-built models.

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Navigating the iterative lifecycle of GenAI development

GenAI projects follow a continuous loop of experimentation, building, deployment, and monitoring to ensure ongoing improvement and value delivery.

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Using the GenAIOps maturity model to assess your progress

The GenAIOps maturity model helps teams understand their current capabilities and provides a roadmap for advancing from initial exploration to operational excellence.

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How the Azure AI platform supports the GenAIOps journey

The Azure AI platform provides a comprehensive suite of tools, including Azure AI Foundry, to support the entire GenAIOps lifecycle from model discovery to enterprise-scale deployment.

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Selecting and deploying models using Azure AI Foundry

Azure AI Foundry simplifies model selection with a vast catalog and benchmarking tools, while the model inference service provides a unified API for deploying diverse models.

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Accelerating project setup with the Azure Developer CLI

The Azure Developer CLI (AZD) is a high-level tool that streamlines the process of setting up and deploying robust GenAI project templates from a repository to the cloud.

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Monitoring GenAI applications with Azure observability tools

Azure provides an SDK, Application Insights, and Azure Monitor with specialized dashboards to gain full observability into the performance and behavior of AI-infused applications.

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Three key steps to accelerate your GenAIOps journey

To mature your GenAIOps practice, start by assessing your current state, then review your strategy and tactics, and finally select the right tools for the job.