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Course Outline

Introduction to Kubiya AI

  • Overview of Kubiya AI and its core capabilities
  • The role of AI-powered automation in cloud environments
  • Key features of Kubiya AI relevant to cloud management

Cloud Resource Automation

  • Automating resource provisioning processes with Kubiya AI
  • Managing cloud environments via AI-driven workflows
  • Integration strategies for major cloud services (AWS, Azure, Google Cloud)

Optimizing Cloud Costs with AI

  • AI-based methodologies for cost optimization
  • Real-time tracking of cloud usage and associated expenses
  • Leveraging AI recommendations to mitigate cloud costs

Security Enhancements Using Kubiya AI

  • AI-driven security monitoring and proactive threat detection
  • Automating responses to security incidents
  • Implementing AI-assisted compliance checks

Hands-On with Kubiya AI

  • Configuration and setup of Kubiya AI for cloud operations
  • Practical labs: Automating cloud resource management tasks
  • Practical labs: Applying cost optimization techniques

Challenges and Future Trends

  • Addressing scalability and performance challenges in cloud AI automation
  • Exploring emerging trends in AI for cloud operations
  • Prospects for the future of AI-powered cloud management

Advanced Kubiya AI Concepts

  • Delving into advanced AI features for cloud automation
  • Deploying sophisticated security and cost-saving strategies
  • Customizing Kubiya AI configurations for specific cloud environments

Summary and Next Steps

Requirements

  • Practical experience with major cloud platforms (AWS, Azure, or Google Cloud)
  • Foundational understanding of DevOps methodologies
  • Familiarity with standard automation tools

Target Audience

  • Cloud engineers
  • Operations managers
 14 Hours

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