Role-Based Programme
RB1506

AI-Powered DevOps & Site Reliability Engineering

Smarter Automation, Reliability & Incident Management

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

Programme Objectives

  • Apply AI across DevOps and Site Reliability Engineering activities including CI/CD, infrastructure operations, observability, incident management, and reliability improvement.
  • Use AI-assisted techniques to analyse deployment data, logs, alerts, configuration information, operational metrics, and recurring service failures more efficiently.
  • Develop structured workflows for deployment reviews, incident triage, root-cause analysis, change coordination, reliability monitoring, and post-incident improvement.
  • Improve service reliability through AI-assisted SLI/SLO analysis, anomaly identification, capacity insights, automation planning, and operational reporting.
  • Apply responsible AI practices covering production safety, credentials, access control, configuration validation, sensitive technical data, and human oversight.

Tools covered

Generative AI AssistantsCI/CD Analysis SupportInfrastructure Automation SupportLog & Monitoring AnalysisIncident Response SupportReliability AnalyticsConfiguration ReviewDocumentation SupportReporting AssistanceWorkflow Automation

Who should attend

  • DevOps Engineers
  • Site Reliability Engineers
  • DevOps Leads
  • SRE Leads
  • Platform Engineers
  • Cloud Engineers
  • Infrastructure Engineers
  • Release Engineers
  • Build & Deployment Engineers
  • Cloud Operations Professionals
  • Production Support Engineers
  • Reliability Analysts
  • Automation Engineers
  • Information Technology Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of DevOps, cloud, infrastructure, application operations, or software delivery
  • Familiarity with CI/CD, monitoring, logs, deployments, incidents, or infrastructure concepts is helpful
  • Basic understanding of scripting, command-line tools, and technical documentation is helpful
  • Basic awareness of Generative AI is helpful
  • No advanced AI or machine-learning knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, automation, and their role in DevOps and SRE
  • Identifying AI applications across delivery pipelines, operations, observability, incidents, and reliability engineering
  • Understanding AI assistance versus DevOps Engineer and SRE accountability
  • Recognising risks related to production systems, credentials, unsafe commands, and uncontrolled automation
Practical activities
  • Mapping DevOps and SRE workflows to AI-assisted opportunities
  • Identifying repetitive operational and engineering tasks suitable for AI support
  • Comparing traditional and AI-assisted reliability workflows

Scenarios

Deployment Failure to Reliable Recovery

Deployment → AI-Assisted Log & Metric Review → Failure Detection → Incident Triage → Root-Cause Analysis → Rollback / Recovery → Post-Incident Review → Preventive Actions

Participants analyse a simulated production deployment failure, organise technical evidence, identify likely failure causes, coordinate safe recovery, and prepare a structured post-incident improvement plan.

Reliability Data to SRE Improvement Plan

Availability + Latency + Incident Data + Deployment Metrics + Capacity Data → AI Analysis → Reliability Gaps → SLO Risks → Priority Improvements → Automation Opportunities → Management Report

Participants consolidate SRE and DevOps performance information, identify recurring reliability concerns and operational bottlenecks, and prepare a management-ready reliability improvement plan with clear actions, owners, and priorities.

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