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
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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