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AI Agents for DevOps: Automate CI/CD, Incidents & Operations
Role Play
New

AI Agents for DevOps: Automate CI/CD, Incidents & Operations

Build real AI agents to automate DevOps pipe, reduce incidents, and modernize CI/CD pipelines - Hands-on Agentic Systems
Role Play
New
Created bySanad Academy
Last updated 7/2026
English

What you'll learn

  • Distinguish agentic workflows from traditional DevOps automation and scripting
  • Understand how AI agents fit into DevOps
  • Identify automation opportunities in your organization
  • Design AI-enhanced DevOps workflows
  • Implement safety guardrails and human-approval gates for agentic actions.

Course content

6 sections • 32 lectures • 3h 54m total length

  • The Agentic Era: Why Traditional DevOps is No Longer Enough5:18
  • Meet your instructor3:00
  • DevOps Foundations2:48
  • Anatomy of an AI Agent: Brain, Tools, and Memory4:28
  • The Evolution: From Static Scripts to Autonomous Agents4:35
  • AI vs. Traditional Automation2:48
  • The Context Commandment: Why Documentation is the Fuel of AI3:20
  • The Script That Knew Everything — Except What Actually Changed8:56
  • The Cargo Cult Trap: When AI Looks Smart but Is Dangerous3:00
  • The Million Dollar Pipeline Nobody Used11:40
  • Tooling Setup for Agentic DevOps Labs9:17
  • Your First AI Agent (Hello Agent)17:19
  • Foundation Check — The Agentic Mindset

Requirements

  • Basic knowledge of DevOps and AI

Description

Traditional DevOps is hitting a bottleneck. We have automated the deployment, but troubleshooting and governance still rely on human engineers staring at screens during 3:00 AM outages. Agentic DevOps is the next evolution. It’s the shift from rigid "If-This-Then-That" scripts to autonomous agents that can reason, use tools, and resolve production issues before the on-call engineer even wakes up.

This is a hands-on, technical masterclass for the modern engineer. We bridge the gap between Generative AI and Production Operations. You won't just learn theory; you will build a functional "AI DevOps Workforce" using CrewAI and LangChain. We focus on the "Agentic Loop": how an AI perceives a system failure, reasons through the logs, and executes a safe, governed rollback or fix.

What You Will Learn:

  • Architecting the Agentic Loop: Transition from passive monitoring to proactive, reasoning agents.

  • Incident Autopilot: Build agents that analyze CloudWatch/ELK logs to perform root-cause analysis in seconds.

  • Agentic CI/CD: Integrate AI into GitHub Actions for intelligent code reviews and self-repairing builds.

  • Multi-Agent Orchestration: Design "Swarms" where specialized agents (Security, Ops, QA) collaborate on complex tasks.

  • Safety & Governance: Implement "Guardrails-as-Code" to ensure AI operates within strict compliance and blast-radius limits.

Course Objectives:

  • Distinguish agentic workflows from traditional DevOps automation and legacy scripting.

  • Construct multi-agent pipelines that handle end-to-end incident lifecycles.

  • Integrate AI agents with the enterprise stack: GitHub, Jira, Slack, and AWS/Azure.

  • Implement human-approval gates to maintain accountability in autonomous systems.

  • Evaluate agent reliability using "Chaos Engineering" failure scenarios in staging.

What You’ll Be Able To Do After This Course:

  • Understand how AI agents fit into DevOps

  • Identify automation opportunities in your organization

  • Design AI-enhanced DevOps workflows

  • Speak confidently about AI in engineering discussions

Who this course is for:

  • IT Engineers
  • IT students
  • Platform Engineers
  • Cloud Engineers
  • DevOps profiles
  • SRE Engineer
  • AI profiles

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