DevOps and AI on AWS: CI/CD for Generative AI Applications

Overview

In this course, we focus on the DevOps practices of building, deploying, and managing applications enhanced with generative AI features. You’ll learn how to implement Continuous Integration and Continuous Deployment (CI/CD) pipelines, explore strategies for reliable automation, and improve monitoring and observability for your applications. The course emphasizes practical skills to streamline releases, reduce potential errors, and maintain high-quality, scalable systems in dynamic cloud environments. With dedicated modules for Automatic deployments, Infrastructure as Code, Monitoring, and Operations, you’ll improve your understanding and ability to execute as a Developer or DevOps Engineer. Get comfortable with AWS services by learning how to use Amazon CodeDeploy in a CI/CD pipeline and using the AWS Cloud Development Kit. You’ll then use AWS Services to help with observability and monitoring (Amazon CloudWatch Anomaly detection and AWS X-Ray insights) - both services with AI features to help with more effective monitoring and alarms. By the end of this course, you’ll have built a robust application that supports continuous releases, improves time to market for new features and fixes, and reduce potential for human error.

Syllabus

Introduction to DevOps

This module introduces the fundamentals of DevOps and its role in modern software development. It covers key principles such as Continuous Integration (CI), Infrastructure as Code (IaC), and automation, providing a foundation for managing infrastructure efficiently. You will explore how DevOps integrates with generative AI workflows, addressing unique challenges like AI model testing and deployment.

Release and Deploy

This module focuses on deployment strategies and automation in a DevOps pipeline. Learners gain hands-on insights into AWS CodeDeploy, AWS CloudFormation, and AWS CDK, understanding how to automate infrastructure provisioning and application releases. The module also explores best practices for reducing downtime, troubleshooting deployments, and ensuring smooth model rollouts in generative AI applications.

Monitor and Operate

This module explores the importance of monitoring, observability, and operational management in DevOps workflows. Learners discover how to use Amazon CloudWatch, AWS CloudTrail, AWS X-Ray, and AWS Systems Manager to track application performance, detect issues, and ensure infrastructure stability. Special focus is given to observability in generative AI applications, highlighting metrics, logging, and automated response strategies to maintain system reliability.