Session 1 — DevOps Foundations

• DevOps principles and benefits

• DevOps lifecycle and CALMS model • CI/CD overview and toolchain landscape

• DevOps vs Agile vs SRE — Comparison and use cases

Session 2 — Version Control with Git

• Git architecture and concepts

• Repository creation and management • Branching and merging strategies

• Conflict resolution and Git workflows — GitFlow and trunk-based development • AI-Assisted Capability (GitHub Copilot) — Using Copilot to generate clear, conventional commit messages from staged changes — Copilot Chat to explain merge conflicts and suggest resolution approaches — Generating pull request descriptions and summaries with Copilot — Reviewing branch dif s with Copilot to spot risky changes before merging

Session 3 — Continuous Integration (CI)

• CI concepts and best practices

• Jenkins and GitHub Actions overview

• Pipeline stages and build triggers

• Webhooks and artifact management • AI-Assisted Capability (GitHub Copilot) — Generating and refining Jenkinsfiles and GitHub Actions workflow YAML with Copilot — Using Copilot to interpret build logs and suggest fixes for failing pipeline steps — Drafting webhook configurations and pipeline trigger conditions with AI assistance

Session 4 — Continuous Delivery and Deployment (CD)

• CD vs Continuous Deployment — Core differences

• Pipeline automation and environment promotion strategy

• Deployment strategies — Blue-Green and Canary

• Rollback techniques and recovery planning

• AI-Assisted Capability (GitHub Copilot) — Generating deployment and rollback scripts for Blue-Green and Canary strategies withCopilot — Using Copilot to draft environment promotion configurations and approval gates — AI-assisted review of deployment logs to identify failure points and recovery steps

Session 5 — Azure DevOps Essentials

• Azure DevOps overview — Boards, Repos, Pipelines, Artifacts, Test Plans

• Boards — Work items, backlogs, and sprint planning

• Repos — Branch policies and pull requests

• Pipelines — YAML vs Classic, service connections, and agent pools

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to draft work item descriptions, acceptance criteria, and sprint task

breakdowns — Generating and optimizing Azure Pipelines YAML with Copilot suggestions — Copilot-assisted pull request reviews against branch policy requirements

Session 6 — Build and Dependency Management

• Maven, Gradle, and npm concepts

• Dependency lifecycle and versioning strategies

• Repository managers — Azure Artifacts and Nexus

• Build optimization techniques and hands-on lab

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to diagnose build errors and dependency conflicts from Maven/Gradle/npmlogs — AI-suggested dependency upgrade paths and version compatibility checks — Copilot-assisted build script optimization for faster, leaner builds

Session 7 — Containerization with Docker

• Containers vs Virtual Machines — Architecture comparison

• Docker architecture and core components

• Images, containers, volumes, and networks

• Dockerfile creation and container registry usage — ACR concept • AI-Assisted Capability (GitHub Copilot) — Generating and optimizing multi-stage Dockerfiles with Copilot — Using Copilot Chat to troubleshoot image build failures and runtime errors — AI-assisted recommendations for image size reduction and security hardening

Session 8 — Kubernetes Introduction

• Kubernetes architecture and core components

• Pods, Deployments, and Services

• ConfigMaps, Secrets, and environment configuration

• Scaling, self-healing, and rolling updates

• AI-Assisted Capability (GitHub Copilot) — Generating and validating Kubernetes YAML manifests (Deployments, Services, ConfigMaps)

with Copilot — Using Copilot Chat to explain pod crash events and suggest fixes from kubectl describe/logsoutput — AI-assisted configuration of scaling policies and rolling update strategies

Session 9 — Infrastructure as Code (IaC)

• IaC principles and Terraform fundamentals

• Azure provider basics and resource provisioning

• State management and remote backends

• Provisioning environments — Hands-on lab

• AI-Assisted Capability (GitHub Copilot) — Generating Terraform resource blocks and modules for Azure with Copilot — Using Copilot to explain Terraform plan/apply errors and propose corrections — AI-assisted setup of remote state backends and state troubleshooting

Session 10 — Configuration Management and DevOps Security

• Configuration Management concepts and Ansible fundamentals

• Inventory, playbooks, idempotency, and automation patterns

• DevSecOps mindset, CI/CD security risks, and secrets management • Dependency and container image scanning, least privilege, and IAM basics

• AI-Assisted Capability (GitHub Copilot) — Generating Ansible playbooks and roles with Copilot, including idempotency checks — Using Copilot to draft secrets management and secret-scanning configurations — AI-assisted recommendations for least-privilege IAM policy definitions

Session 11 — Ticket-Based Scenarios Part 1

• Git and branching conflict resolution tickets

• CI pipeline failure diagnostics

• CD deployment rollback scenarios

• Azure DevOps pipeline troubleshooting tickets

• AI-Assisted Capability (GitHub Copilot) — Using Copilot Chat to triage ticket details — pasting error logs and conflict dif s to get

suggested root causes — Comparing Copilot-suggested fixes against manual resolution to build participant judgment

Session 12 — Ticket-Based Scenarios Part 2

• Docker container failure and debugging

• Kubernetes pod crash and service unavailability

• Terraform state and provisioning issue resolution

• Security misconfiguration identification and remediation

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to analyze container, pod, and Terraform error output and propose remediationsteps — AI-assisted identification of security misconfigurations from scan results and config files

Session 13 — End-to-End Pipeline Lab

• Design and plan a full CI/CD pipeline from scratch

• Implement source control, branching strategy, and PR workflow

• Build and test automation with Jenkins or GitHub Actions

• Artifact publishing and environment promotion

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to scaf old pipeline YAML, build scripts, and test stubs from the pipeline design— Generating PR descriptions and documentation for the end-to-end pipeline with Copilot

Session 14 — Containerized Deployment Lab

• Dockerize a sample application

• Push image to Azure Container Registry

• Deploy to Kubernetes cluster with YAML manifests

• Configure scaling, health checks, and rolling updates

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to generate the Dockerfile and Kubernetes manifests for the sample

application — AI-assisted troubleshooting of registry push errors and deployment failures

Session 15 — Terraform and Ansible Lab

• Write Terraform scripts to provision Azure resources

• Manage state files and remote backend configuration

• Write Ansible playbook for configuration management • Integrate Ansible with CI/CD pipeline

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to scaf old Terraform modules and Ansible playbooks from natural-languagerequirements — AI-assisted debugging of state file and remote backend configuration errors

Session 16 — DevSecOps Integration Lab

• Add secret scanning to a CI/CD pipeline

• Implement container image vulnerability scanning

• Configure IAM roles and least privilege access in Azure

• Security audit and documentation of pipeline findings

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to generate secret-scanning and vulnerability-scanning pipeline configurations— AI-assisted drafting of IAM least-privilege role definitions and security audit documentationSession 17 — Monitoring and Observability

• Introduction to monitoring in DevOps — metrics, logs, and traces

• Azure Monitor and Application Insights overview

• Setting up alerts and dashboards

• Log analysis and incident response basics

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to write and refine KQL queries for Azure Monitor and Application Insights — AI-assisted generation of alert rules and dashboard configurations — Summarizing log data and incident timelines with Copilot for faster response

Session 18 — Pipeline Optimization and Best Practices

• Pipeline performance review and bottleneck identification

• Caching, parallelism, and build speed improvement techniques

• Documentation standards and runbook creation

• Code review best practices and team collaboration workflows

• AI-Assisted Capability (GitHub Copilot) — Using Copilot to review pipeline configurations and suggest caching/parallelismimprovements — Generating runbook and documentation drafts with Copilot — AI-assisted code review suggestions to support team collaboration workflows