Integrating Kubiya AI with DevOps Pipelines

• Basic understanding of CI/CD pipelines
• Experience with DevOps tools (e.g., Jenkins, GitLab)
• Familiarity with automation processes

Audience

• DevOps engineers
• CI/CD pipeline managers
• Infrastructure automation professionals

This course focuses on integrating Kubiya AI into continuous integration and continuous deployment (CI/CD) pipelines. Participants will learn how to leverage AI-driven automation and monitoring to streamline DevOps processes, improve efficiency, and reduce manual intervention in CI/CD workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level DevOps engineers and CI/CD managers who wish to enhance their pipelines with AI automation using Kubiya AI.

By the end of this training, participants will be able to:

• Understand the fundamentals of integrating AI into DevOps pipelines.
• Implement Kubiya AI within popular CI/CD tools such as Jenkins and GitLab CI.
• Automate CI/CD pipeline tasks with Kubiya AI.
• Monitor and manage CI/CD pipelines using AI for proactive problem detection.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to CI/CD Pipelines and Kubiya AI

• Overview of CI/CD concepts and processes
• Introduction to Kubiya AI and its role in DevOps automation
• Exploring key features of Kubiya AI

Integrating Kubiya AI with Popular CI/CD Tools

• Setting up Kubiya AI with Jenkins
• Integrating Kubiya AI with GitLab CI
• Connecting Kubiya AI with Docker-based pipelines

Automating CI/CD Pipeline Tasks with Kubiya AI

• AI-powered automation for build, test, and deploy stages
• Reducing manual intervention with AI automation
• Streamlining pipeline management and troubleshooting

Monitoring and Managing CI/CD Pipelines Using AI

• Real-time monitoring of pipeline health
• Proactive issue detection using AI analytics
• Automated notifications and problem resolution workflows

Advanced AI Applications in CI/CD Pipelines

• AI-driven optimization for resource allocation
• Predictive analytics for pipeline failures
• AI-based anomaly detection in CI/CD pipelines

CI/CD Pipeline Security Enhancement with AI

• Leveraging AI for detecting security vulnerabilities
• Enhancing code review processes using AI
• Ensuring compliance with automated AI-driven checks

Scaling CI/CD Pipelines with AI

• Using AI to manage large-scale DevOps environments
• Automating scaling of CI/CD infrastructure
• Case studies of AI-enabled scalability in production

Summary and Next Steps