Role-Based Programme
RB1493

AI-Powered Cloud Engineering & Operations

Smarter Provisioning, Monitoring, Cost Optimisation & Reliability

IMAGE REQUIRED
Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Cloud Engineering and Cloud Operations across provisioning, monitoring, troubleshooting, optimisation, and reporting.
  • Apply AI-assisted techniques to analyse cloud logs, alerts, utilisation data, configuration information, incidents, and operational metrics.
  • Use structured prompting for cloud troubleshooting, configuration review, capacity analysis, cost optimisation, and technical documentation.
  • Explore AI-supported approaches for identifying recurring failures, underutilised resources, performance bottlenecks, and cloud-governance gaps.
  • Build responsible AI-assisted cloud workflows while maintaining security, access control, cost governance, reliability, and human validation.

Tools covered

Generative AI AssistantsAI Search & ResearchCloud Operations AIInfrastructure AnalysisCloud Monitoring & Log AnalysisCost & Capacity AnalysisConfiguration ReviewIncident AnalysisDocumentation & Workflow Automation

Who should attend

  • Cloud Engineers
  • Cloud Operations Engineers
  • Cloud Administrators
  • Cloud Infrastructure Engineers
  • Cloud Support Engineers
  • Platform Engineers
  • DevOps Engineers
  • Site Reliability Engineers
  • Infrastructure Engineers
  • Cloud Architects
  • IT Operations Professionals
  • Cloud FinOps Professionals
  • Cloud Operations Managers
  • Cloud Engineering Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of cloud computing, infrastructure, or IT operations
  • Familiarity with virtual machines, storage, networking, monitoring, or cloud services is helpful
  • Basic computer and command-line awareness is beneficial
  • No AI or advanced programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to cloud engineering and operations
  • Identifying AI applications across provisioning, monitoring, troubleshooting, optimisation, and documentation
  • Understanding AI assistance versus Cloud Engineer and Operations professional judgement
  • Recognising limitations such as incomplete environment context, incorrect configurations, hallucinations, and unsafe recommendations
Practical activities
  • Mapping a typical Cloud Engineering & Operations workflow
  • Identifying repetitive and information-intensive cloud activities suitable for AI assistance
  • Comparing a traditional cloud-operations task with an AI-assisted approach

Scenarios

Cloud Performance Issue to Validated Resolution

Cloud Alert → AI-Assisted Log & Metric Review → Evidence Summary → Diagnostic Questions → Possible Causes → Engineer Validation → Resolution → Verification

Participants use AI to analyse sample cloud monitoring information, identify investigation areas, and prepare a structured troubleshooting workflow for technical validation.

Cloud Usage Data to Cost & Capacity Optimisation

Resource Usage + Cost Data + Performance Metrics + Incidents → AI Analysis → Underutilisation / Constraints → Optimisation Options → Validation → Management Summary

Participants use AI to analyse sample cloud-operational data, identify potential cost and capacity improvements, and prepare a management-ready Cloud Optimisation Plan.

Related programmes

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.