Kubiya AI for DevOps Automation Training is an advanced three-day program designed to help DevOps and platform teams use Kubiya AI to automate, standardize, and scale operational workflows through conversational AI. This course focuses on integrating Kubiya AI with cloud platforms, CI/CD pipelines, monitoring systems, and infrastructure tools to enable secure self-service DevOps, faster incident response, and governed automation across engineering organizations.

• Understand Kubiya AI for DevOps automation
• Learn AI-driven infrastructure management
• Understand automated operational workflows
• Gain knowledge of incident response automation
• Learn CI/CD automation concepts
• Understand AI-assisted monitoring workflows
• Explore cloud and DevOps integrations
• Identify enterprise DevOps AI use cases

• DevOps engineers and site reliability engineers
• Platform and cloud engineering teams
• IT operations and infrastructure professionals
• Engineering managers and technical leads
• Organizations adopting AI-driven DevOps automation

• DevOps engineers and site reliability engineers
• Platform and cloud engineering teams
• IT operations and infrastructure professionals
• Engineering managers and technical leads
• Organizations adopting AI-driven DevOps automation

• Understanding Kubiya AI architecture and automation capabilities
• Building conversational automation for DevOps workflows
• Integrating Kubiya AI with cloud, CI/CD, and monitoring tools
• Implementing secure, governed, and auditable automation
• Scaling AI-assisted DevOps across teams and environments

By the end of this training, participants will be able to design and deploy Kubiya AI–powered DevOps automation, integrate conversational AI with core DevOps tooling, enforce security and governance controls, and scale AI-assisted operations to improve reliability, efficiency, and team productivity.

Introduction to Kubiya AI for DevOps Automation
• Overview of Kubiya AI and its role in modern DevOps
• Conversational AI for infrastructure and operations
• Use cases for self-service DevOps automation
• Benefits and limitations of AI-driven operations

Kubiya AI Architecture and Core Components
• Agents, skills, and integrations overview
• Secure command execution and guardrails
• Role-based access control and approvals
• Audit logs and operational transparency

Automating Core DevOps Tasks with Kubiya AI
• Infrastructure queries and command execution
• Environment management and configuration checks
• Routine operational workflows automation
• Collaboration and shared operational knowledge

Integrating Kubiya AI with Cloud and CI/CD Platforms
• Cloud platform integrations and use cases
• CI/CD pipeline interaction and automation
• Deployment monitoring and rollback support
• Supporting release and change management workflows

Incident Response and Operational Intelligence
• Using Kubiya AI during incidents and outages
• Log analysis and system health queries
• Reducing mean time to detect and recover
• Coordinating incident workflows using AI

Custom Skills and Workflow Design
• Designing custom Kubiya AI skills
• Automating complex multi-step workflows
• Validation, error handling, and approvals
• Best practices for maintainable automation

Security, Governance, and Compliance
• Securing AI-driven operational access
• Preventing misuse and enforcing policies
• Compliance, auditing, and traceability
• Managing risk in automated DevOps environments

Scaling Kubiya AI Across Teams and Organizations
• Standardizing DevOps automation practices
• Enabling self-service for developers safely
• Managing environments and permissions at scale
• Measuring adoption and operational impact

Advanced Use Cases and Future Trends
• AIOps and predictive operations integration
• Autonomous and semi-autonomous DevOps workflows
• Human-in-the-loop operational models
• Future roadmap of conversational DevOps automation

• Kubiya AI platform fundamentals
• DevOps automation concepts
• Infrastructure management workflows
• Incident response automation
• CI/CD pipeline basics
• AI-assisted monitoring concepts
• Cloud and system integrations
• Security and access management
• Enterprise DevOps use cases
• Practical DevOps automation scenarios

• Hands-on Kubiya AI automation exercises
• DevOps workflow design and integration assessment
• Security and governance scenario evaluation
• Final knowledge evaluation quiz

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Kubiya AI for DevOps Automation, validating their expertise in designing, integrating, and governing AI-driven DevOps automation using Kubiya AI.