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Course Outline

Kubiya AI Fundamentals

  • General overview of Kubiya AI
  • Core features and value propositions
  • Practical applications in DevOps

Kubiya AI Deployment

  • Installation procedures and configuration
  • Preparing the operational environment
  • Initial setup and parameter tuning

Core Use Cases and Applications

  • Automating repetitive tasks
  • Utilizing Kubiya AI for monitoring and alerts
  • Strengthening CI/CD pipelines

Connecting Kubiya AI to the DevOps Ecosystem

  • Linking with CI/CD tools (Jenkins, GitLab CI, etc.)
  • Syncing with cloud platforms (AWS, Azure, GCP)
  • Collaborating with container orchestration tools (Kubernetes, Docker)

Advanced Setup and Customization

  • Sophisticated workflow automation
  • Tailoring Kubiya AI to specific business needs
  • Addressing security and compliance standards

Practical Projects

  • Setting up real-world scenarios
  • Applying and testing implementations
  • Debugging and performance optimization

Recap and Future Directions

Requirements

  • Foundational knowledge of DevOps concepts
  • Proficiency with CI/CD pipelines
  • Basic familiarity with cloud infrastructure

Intended Audience

  • DevOps practitioners
  • IT Managers
  • System Administrators
 14 Hours

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