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Course Outline

Introduction to Kubiya AI

  • Overview of Kubiya AI and its core capabilities.
  • AI-powered automation within cloud environments.
  • Key features of Kubiya AI tailored for cloud management.

Cloud Resource Automation

  • Automating resource provisioning using Kubiya AI.
  • Managing cloud environments through AI-driven processes.
  • Integrating with major cloud services (AWS, Azure, Google Cloud).

Optimizing Cloud Costs with AI

  • AI-based techniques for cost optimization.
  • Real-time monitoring of cloud usage and expenditures.
  • AI-generated recommendations for reducing cloud costs.

Security Enhancements Using Kubiya AI

  • AI-driven security monitoring and threat detection.
  • Automated responses to security incidents.
  • Implementing compliance checks using AI.

Hands-On with Kubiya AI

  • Setting up Kubiya AI for cloud operations.
  • Practical labs: Automating cloud resource management.
  • Practical labs: Implementing cost optimization techniques.

Challenges and Future Trends

  • Scalability and performance challenges in cloud AI automation.
  • Emerging trends in AI for cloud operations.
  • The future of AI-powered cloud management.

Advanced Kubiya AI Concepts

  • Exploring advanced AI features for cloud automation.
  • Implementing advanced security and cost-saving techniques.
  • Customizing Kubiya AI for specific cloud environments.

Summary and Next Steps

Requirements

  • Prior experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Fundamental understanding of DevOps methodologies.
  • Familiarity with automation tools.

Audience

  • Cloud engineers.
  • Operations managers.
 14 Hours

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