Role-Based Programme
RB1494

AI-Powered Cloud Engineering & Cloud Operations

Smarter Cloud Management, Automation & Reliability

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Cloud Engineering and Cloud Operations activities including provisioning, monitoring, troubleshooting, configuration management, capacity planning, and operational reporting.
  • Use AI-assisted techniques to analyse cloud metrics, logs, incidents, configuration information, resource utilisation, and recurring operational issues more efficiently.
  • Develop structured workflows for cloud deployment support, incident triage, change management, reliability monitoring, optimisation, and recovery.
  • Improve cloud-platform visibility through AI-assisted anomaly detection support, cost and capacity analysis, operational documentation, and management reporting.
  • Apply responsible AI practices covering cloud credentials, access control, sensitive configuration data, production safety, technical validation, and human oversight.

Tools covered

Generative AI AssistantsCloud Operations AnalyticsInfrastructure Automation SupportMonitoring & Log AnalysisConfiguration ReviewCost & Capacity AnalysisIncident Management SupportCloud DocumentationReporting AssistanceWorkflow Automation

Who should attend

  • Cloud Engineers
  • Cloud Operations Engineers
  • Cloud Administrators
  • Cloud Infrastructure Engineers
  • Cloud Platform Engineers
  • Cloud Support Engineers
  • Cloud Reliability Engineers
  • DevOps Engineers
  • Site Reliability Engineers
  • Infrastructure Engineers
  • Cloud Operations Analysts
  • Platform Operations Professionals
  • Technical Cloud Leads
  • Information Technology Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of cloud computing, infrastructure, IT operations, or platform management
  • Familiarity with virtual machines, storage, networking, monitoring, cloud services, or infrastructure automation is helpful
  • Basic understanding of cloud security and access-control concepts
  • Basic awareness of Generative AI is helpful
  • No advanced programming or AI knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, automation, and their role in cloud engineering and operations
  • Identifying AI applications across provisioning, monitoring, troubleshooting, optimisation, and reporting
  • Understanding AI assistance versus Cloud Engineer and Cloud Operations professional accountability
  • Recognising risks related to credentials, production systems, configuration errors, and unsafe recommendations
Practical activities
  • Mapping the cloud-operations lifecycle to AI-assisted activities
  • Identifying repetitive operational tasks suitable for AI support
  • Comparing traditional and AI-assisted cloud workflows

Scenarios

Cloud Performance Incident to Stable Recovery

Cloud Alert → AI-Assisted Metrics & Log Review → Dependency Analysis → Bottleneck Identification → Incident Triage → Controlled Remediation → Validation → Monitoring

Participants analyse a simulated cloud-performance incident, organise technical evidence, identify likely bottlenecks, and develop a controlled service-recovery and monitoring plan.

Cloud Operations Data to Cost & Reliability Improvement Plan

Cloud Usage + Cost Data + Incidents + Capacity Metrics + Access Information → AI Analysis → Operational Gaps → Cost & Reliability Opportunities → Priority Actions → Management Report

Participants consolidate cloud operational information, identify recurring reliability issues, inefficient resource usage, and capacity concerns, and prepare a management-ready Cloud Improvement Plan with actions, owners, and priorities.

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