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

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

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

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1 week to complete
at 10 hours a week
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Gain insight into a topic and learn the fundamentals.
4.4

12 reviews

Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Implement DevOps practices including automated builds, testing, and continuous integration pipelines.

  • Design and execute automatic deployments using Amazon CodeDeploy in a CI/CD pipeline.

  • Demonstrate how DevOps and AIOps practices improve continuous releases, time to market, and reduce human error in app development and operations.

  • Apply AI-enhanced monitoring and observability techniques using Amazon CloudWatch Anomaly Detection and AWS X-Ray Insights.

Details to know

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Assessments

5 assignments

Taught in English

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This course is part of the DevOps and AI on AWS Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

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.

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.

What's included

11 videos8 readings2 assignments1 app item2 plugins

11 videos•Total 67 minutes
  • Introduction to the Course•3 minutes
  • Introduction to DevOps•6 minutes
  • Module 1 Introduction•1 minute
  • The Role of IaC in DevOps•7 minutes
  • The Code Phase•6 minutes
  • GenAI Considerations for DevOps•4 minutes
  • The Build•10 minutes
  • The Test•7 minutes
  • Testing Generative AI Applications•6 minutes
  • Adding Tests to Continuous Integration•7 minutes
  • Continuous Integration•9 minutes
8 readings•Total 52 minutes
  • Welcome to the course•5 minutes
  • Pre-Course Survey•1 minute
  • Course Roadmap•5 minutes
  • DevOps and IaC•10 minutes
  • GenAI considerations for DevOps•10 minutes
  • Code build tools and services•10 minutes
  • Continuous Integration•10 minutes
  • Mid-Course Survey•1 minute
2 assignments•Total 30 minutes
  • Module 1 Quiz•10 minutes
  • Pre-Assessment•20 minutes
1 app item•Total 60 minutes
  • Set Up CI/CD Pipeline•60 minutes
2 plugins•Total 25 minutes
  • Pre-Course Survey•10 minutes
  • Mid-Course Survey•15 minutes

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.

What's included

12 videos4 readings1 assignment1 app item

12 videos•Total 72 minutes
  • Module 2 Introduction•3 minutes
  • Deployment Strategies for Amazon EC2•8 minutes
  • Understanding the AppSpec file•4 minutes
  • Using AWS CodeDeploy in a Pipeline•4 minutes
  • Troubleshooting Deployment Details and Errors•5 minutes
  • CI/CD Pipelines for Infrastructure Components•4 minutes
  • Introduction to AWS CloudFormation•6 minutes
  • Reviewing an AWS CloudFormation Template•8 minutes
  • AWS CloudFormation: How to Handle and Prevent Errors•6 minutes
  • Troubleshooting AWS CloudFormation•5 minutes
  • Using the AWS Cloud Development Kit•8 minutes
  • Deploying Our Application Stack Using the AWS CDK•11 minutes
4 readings•Total 45 minutes
  • Deployment Strategies for Serverless•10 minutes
  • AWS CloudFormation Extended Features•15 minutes
  • Troubleshooting AWS CloudFormation•10 minutes
  • AWS Cloud Development Kit•10 minutes
1 assignment•Total 10 minutes
  • Module 2 Quiz•10 minutes
1 app item•Total 60 minutes
  • Deploy Application Infrastructure Using CDK With a CI/CD Pipeline•60 minutes

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.

What's included

11 videos7 readings2 assignments2 app items1 plugin

11 videos•Total 74 minutes
  • Module 3 Introduction•1 minute
  • Cloud Monitoring with Amazon CloudWatch•9 minutes
  • AWS CloudTrail: Activity and Administrative API Monitoring on AWS•14 minutes
  • Instrumenting the Application with AWS X-Ray•10 minutes
  • Amazon CloudWatch Application Monitoring•8 minutes
  • Infrastructure Management and Operations•5 minutes
  • AWS Config: Detecting Configuration Changes to Your Cloud Resources•7 minutes
  • AWS Systems Manager: An Operations Hub for Cloud Environments•2 minutes
  • Exploring AWS Systems Manager•5 minutes
  • Remotely Run Commands on Your Servers•8 minutes
  • Node Management Features Powered by Systems Manager•7 minutes
7 readings•Total 66 minutes
  • Amazon CloudWatch•10 minutes
  • AWS CloudTrail•10 minutes
  • AWS X-Ray•10 minutes
  • AWS Config•10 minutes
  • AWS Systems Manager•5 minutes
  • Post-Course Survey•1 minute
  • Glossary•20 minutes
2 assignments•Total 25 minutes
  • Module 3 Quiz•10 minutes
  • Final Assessment•15 minutes
2 app items•Total 120 minutes
  • Amazon CloudWatch Anomaly Detection•60 minutes
  • Systems Manager for Diagnostics•60 minutes
1 plugin•Total 10 minutes
  • Post-Course Survey•10 minutes

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Amazon Web Services
21 Courses•139,316 learners

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SK
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Reviewed on May 13, 2025

I can understand more about AWS services that they can apply in GenAI projects. This course can help me to work in my project.

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