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 Duration 14 hours

Course Outline

Overview of the Kubiya AI Platform

  • Summary of Kubiya AI functionalities and technical capabilities
  • Application of artificial intelligence in cloud automation workflows
  • Core components of Kubiya AI supporting cloud governance

Automation of Cloud Resource Allocation

  • Streamlining resource provisioning processes via Kubiya AI
  • Administering cloud ecosystems through intelligent, AI-guided procedures
  • Interoperability with major cloud providers (AWS, Azure, Google Cloud)

AI-Driven Cloud Cost Efficiency

  • Methodologies for cost optimization leveraging artificial intelligence
  • Continuous surveillance of cloud utilization and expenditure
  • Data-informed recommendations for minimizing cloud overhead

Strengthening Security Posture with Kubiya AI

  • Intelligent security monitoring and identification of potential threats
  • Automated remediation protocols for security events
  • Execution of compliance verification using AI frameworks

Practical Application of Kubiya AI

  • Configuration of Kubiya AI for cloud operational environments
  • Lab exercises: Automating the lifecycle of cloud resources
  • Lab exercises: Applying strategies for cost reduction

Operational Challenges and Emerging Trends

  • Scalability and performance considerations in cloud AI automation
  • Current developments in AI applications for cloud operations
  • Projections for the future of AI-assisted cloud management

Advanced Concepts in Kubiya AI

  • Examination of sophisticated AI features for cloud automation
  • Deployment of advanced security and fiscal efficiency measures
  • Tailoring Kubiya AI to specific organizational cloud requirements

Conclusion and Recommended Actions

Requirements

  • Prior experience with cloud platforms (AWS, Azure, or Google Cloud)
  • Foundational understanding of DevOps methodologies
  • Proficiency with automation tools

Target Audience

  • Cloud engineers
  • Operations managers

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