Maxim Salnikov
From Traction to Production: Maturing your GenAIOps step by step
#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.
#2about 4 minutes
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.
#3about 2 minutes
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.
#4about 2 minutes
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.
#5about 4 minutes
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.
#6about 3 minutes
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.
#7about 1 minute
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.
#8about 1 minute
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.
#9about 1 minute
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.
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