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Course Outline
Introduction to Kubiya AI
- Overview of Kubiya AI
- Key features and benefits
- Use cases in DevOps
Setting Up Kubiya AI
- Installation and configuration
- Setting up the environment
- Initial setup and configuration
Basic Use Cases and Applications
- Automating routine tasks
- Monitoring and alerting with Kubiya AI
- Enhancing CI/CD pipelines
Integrating Kubiya AI with Existing DevOps Tools
- Integration with CI/CD tools (Jenkins, GitLab CI, etc.)
- Connecting with cloud platforms (AWS, Azure, GCP)
- Using Kubiya AI with container orchestration tools (Kubernetes, Docker)
Advanced Configurations and Customizations
- Advanced workflow automation
- Customizing Kubiya AI for specific needs
- Security and compliance considerations
Hands-on Projects
- Real-world project setup
- Practical implementation and testing
- Troubleshooting and optimization
Summary and Next Steps
Requirements
- An understanding of DevOps principles
- Experience with CI/CD pipelines
- Basic knowledge of cloud infrastructure
Audience
- DevOps professionals
- IT managers
- System administrators
14 Hours
Testimonials (1)
There were many practical exercises supervised and assisted by the trainer
