Deploying LLMs to Production with DevOps

Event Overview

Deploying Large Language Models (LLMs) into production is far more complex than building a prototype. From infrastructure design and CI/CD pipelines to monitoring, scaling, and security, production-ready AI systems require a strong DevOps foundation. In this live Edu AI webinar, you will gain a practical, real-world understanding of how to operationalize LLM-powered applications with confidence.

This session is designed to bridge the gap between machine learning experimentation and reliable production systems. We will explore how modern DevOps practices integrate with LLM workflows, including containerization, automated testing, model versioning, and cloud deployment strategies. You will also discover how to manage performance, cost, and reliability while maintaining governance and compliance standards.

During this 2-hour interactive session, attendees will learn:

• How to design production-ready architectures for LLM applications
• Best practices for CI/CD pipelines tailored to AI and ML systems
• Containerization and orchestration using Docker and Kubernetes
• Monitoring, logging, and observability strategies for LLM APIs
• Managing model updates, version control, and rollback strategies
• Security considerations, access control, and data privacy best practices
• Cost optimization and scaling strategies in cloud environments

By the end of this webinar, you will understand how to transition from notebook experiments to scalable, resilient, and secure production deployments. We will also discuss common pitfalls teams face when deploying LLMs and how to avoid costly downtime or performance bottlenecks.

This webinar is ideal for machine learning engineers, DevOps engineers, MLOps practitioners, backend developers, AI architects, and technical team leads responsible for deploying AI systems. It is also valuable for CTOs and technology decision-makers who want to understand the operational requirements of LLM-powered products. A basic understanding of machine learning concepts and cloud infrastructure will help you get the most from this session.

To prepare, attendees should ensure they have a stable internet connection and access to Google Meet. Familiarity with Docker, cloud platforms (such as AWS, Azure, or GCP), and basic CI/CD concepts will be beneficial but not mandatory. We encourage participants to bring questions about their own deployment challenges, as a live Q&A session will be included at the end.

Join Edu AI on 22 Mar 2026 for this high-impact technical webinar and learn how to deploy LLMs with the reliability, scalability, and security that modern production systems demand.