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Learn how to build a standardized MLOps stack for efficient AI model deployment through this 30-minute conference talk from Databricks. Discover how Vizient successfully implemented a comprehensive MLOps framework using Databricks and Azure DevOps to streamline model development, deployment, and monitoring processes. Explore the practical application of Databricks Asset Bundles for creating reproducible and scalable pipelines, while understanding how Infrastructure-as-Code principles can significantly accelerate onboarding for new AI projects. Gain insights into end-to-end MLOps stack setup that ensures both efficiency and governance, examine CI/CD pipeline architecture for automating model versioning and deployment, and understand strategies for standardizing AI model repositories to reduce development and deployment time. Benefit from real-world lessons learned, including common challenges and proven best practices from industry experts Adam Hasham, Lead Machine Learning Engineer at Vizient, and Ram Radhakrishnan, Director of Technology Delivery for Data & AI at Vizient Inc. Walk away with a practical roadmap for implementing a scalable, reusable MLOps framework that enhances operational efficiency across your organization's AI initiatives.
