Ai Agents For Devops Automate Ci cd, Incidents & Operations

Ai Agents For Devops: Automate Ci/cd, Incidents & Operations
Published 7/2026
Created by Sanad Academy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 30 Lectures ( 3h 58m ) | Size: 1.9 GB​

Build real AI agents to automate DevOps pipe, reduce incidents, and modernize CI/CD pipelines - Hands-on Agentic Systems
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.
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 betweenGenerative AI and Production Operations. You won't just learn theory; you will build a functional "AI DevOps Workforce" usingCrewAI 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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