Role-Based Programme
RB1504

AI-Powered DevOps & Site Reliability Engineering

Smarter Automation, Incident Response & Reliability Operations

IMAGE REQUIRED
Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support DevOps and Site Reliability Engineering across automation, deployment, monitoring, incident response, and documentation.
  • Explore practical prompting techniques for CI/CD workflows, infrastructure troubleshooting, logs, incidents, runbooks, and reliability reporting.
  • Apply AI to organise technical information, summarise operational events, support troubleshooting, and improve recurring DevOps workflows.
  • Identify opportunities to improve engineering productivity, deployment visibility, incident handling, and operational reliability.
  • Recognise security, production safety, access control, technical validation, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted CI/CD SupportInfrastructure & Configuration AnalysisLog SummarisationIncident Response SupportSRE DocumentationReliability ReportingBasic Workflow Automation

Who should attend

  • DevOps Engineers
  • Site Reliability Engineers
  • Platform Engineers
  • Cloud Engineers
  • Infrastructure Engineers
  • Build & Release Engineers
  • CI/CD Engineers
  • DevSecOps Professionals
  • Production Support Engineers
  • Cloud Operations Professionals
  • Systems Engineers
  • Reliability Engineers
  • DevOps & SRE Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of DevOps, cloud, infrastructure, or software-delivery concepts
  • Familiarity with CI/CD pipelines, deployments, monitoring, incidents, or infrastructure operations is helpful
  • Basic computer and technical skills
  • No advanced AI or machine-learning knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to DevOps and Site Reliability Engineering
  • Identifying AI applications across CI/CD, infrastructure, monitoring, incidents, and documentation
  • Understanding AI assistance versus DevOps and SRE professional judgement
  • Recognising production-sensitive activities requiring validation, testing, and authorised access
Practical activities
  • Mapping common DevOps and SRE activities to potential AI applications
  • Comparing a traditional operational task with an AI-assisted approach

Scenarios

Deployment Change to Production Readiness Review

Deployment Request → AI-Assisted Review → Pipeline Stages → Dependencies → Risks → Validation Checks → Rollback Considerations → Readiness Summary

Participants use AI to organise a sample deployment request, identify dependencies and operational risks, and prepare a structured readiness summary before authorised production deployment.

Service Alert to Incident & Reliability Review

Alert → Logs & Metrics → AI-Assisted Triage → Possible Causes → Validation → Recovery Actions → Incident Timeline → Improvement Summary

Participants use AI to organise sample incident data, support investigation, prepare an incident timeline, and document follow-up improvements while retaining all production and recovery decisions with authorised engineering teams.

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