🚀 Your Concise 30-Day Azure DevOps & GitOps Learning Journey This roadmap provides a structured, hands-on path to master key DevOps tools and concepts on Azure. We focus on building practical skills that directly apply to production environments, emphasizing why each step is crucial for reliable and efficient software delivery.

Goal: Gain confidence to provision infrastructure, manage configurations, containerize applications, and automate deployments on Azure using GitOps principles.

Time Commitment: ~30 minutes per day. Consistency is key!

✨ Learning Objectives Infrastructure as Code (IaC): Provision Azure resources with Terraform.

Configuration Management: Automate server setup with Ansible.

Containerization & Orchestration: Package apps with Docker and deploy on Azure Kubernetes Service (AKS).

Continuous Integration/Delivery (CI/CD): Automate builds and pushes with GitLab CI/CD & GitHub Actions.

GitOps: Implement declarative deployments to AKS using Argo CD.

End-to-End Workflow: Integrate all tools for a complete DevOps pipeline.

🛠️ Essential Tools & Prerequisites Ensure these are installed and familiar before starting:

Foundational Knowledge: Basic Linux CLI, Git fundamentals, Docker basics, Cloud concepts (VMs, Networks).

Local Tools: Git, Azure CLI, Terraform CLI, Ansible, kubectl, Helm CLI, VS Code.

Cloud Account: Azure Free Tier or Subscription.

🗺️ The Learning Path: Building Production-Ready Skills Each module builds foundational skills, culminating in an integrated, automated pipeline.

Phase 1: Infrastructure as Code (IaC) on Azure (Days 1-7) Goal: Confidently provision Azure infrastructure using Terraform. This is the bedrock of reproducible environments.

Day 1: Azure CLI & Git Basics

Concept: Directly manage Azure resources; version control CLI commands.

Challenge: Login az login, create/delete Azure Resource Group. Commit CLI commands to Git.

Reasoning: Manual tasks are error-prone. Versioning commands starts IaC thinking.

Day 2-3: Terraform Core & Azure RGs

Concept: Declarative IaC with Terraform (providers, resources). Automate RG creation.

Challenge: Write main.tf for Azure RM provider, define RG. terraform init, plan, apply, destroy.

Reasoning: Automates infrastructure setup, ensuring consistency across environments.

Day 4-5: Terraform Variables, Outputs & Networking

Concept: Parameterize Terraform with variables; extract useful data with outputs. Build VNETs.

Challenge: Add variables.tf, outputs.tf. Create Azure VNet and subnets. Output VNet details.

Reasoning: Variables make code reusable. Outputs expose critical info for other tools. Networking is fundamental.

Day 6: Terraform Azure VMs & Remote State

Concept: Provisioning compute (VMs); storing Terraform state safely for collaboration.

Challenge: Add Azure VMs to subnets. Configure Azure Storage Account for remote state backend. terraform init -reconfigure.

Reasoning: VMs are common app hosts. Remote state prevents conflicts and provides a single source of truth for your infrastructure's current state.

Day 7: Terraform Practice & Cleanup

Concept: Reinforce Terraform workflow.

Challenge: Modify VM specs, apply. Full terraform destroy (except state backend).

Reasoning: Practice confirms understanding. Clean-up prevents unexpected cloud costs.

Phase 2: Configuration Management with Ansible (Days 8-12) Goal: Automate software installation and configuration on your provisioned VMs.

Day 8-9: Ansible Playbooks & Modules

Concept: Agentless configuration automation via YAML playbooks (tasks, modules).

Challenge: Create ansible/inventory.ini with VM IPs. Write playbook to install Nginx on web-vm. ansible-playbook.

Reasoning: Automates repeatable setup tasks, ensuring consistent server configurations.

Day 10-11: Ansible Variables, Handlers & Roles

Concept: Flexible playbooks with variables; triggered actions with handlers; reusable roles.

Challenge: Use variables for Nginx package. Add handler to restart Nginx on config change. Convert playbook to an nginx role.

Reasoning: Variables enhance reusability. Handlers ensure actions only run when needed. Roles standardize and modularize automation.

Day 12: Dynamic Inventory (Azure)

Concept: Automatically discovering target machines from cloud providers.

Challenge: Configure Ansible's Azure dynamic inventory plugin. Run Nginx role using dynamic inventory.

Reasoning: Eliminates manual inventory updates, essential for scalable cloud environments.

Phase 3: Containerization & Orchestration (Days 13-17) Goal: Package applications into containers and deploy them on a managed Kubernetes cluster.

Day 13-14: Dockerizing App & Azure Container Registry (ACR)

Concept: Packaging apps into portable Docker images; storing images privately.

Challenge: Create app/web-app/Dockerfile for a simple app. Build locally. Terraform for ACR. Push image to ACR.

Reasoning: Containers provide consistent runtime environments. ACR is a secure, scalable registry for production images.

Day 15: Terraform for Azure Kubernetes Service (AKS)

Concept: Automating the deployment of a managed Kubernetes cluster.

Challenge: Extend Terraform to provision an AKS cluster. Output kube_config.

Reasoning: AKS simplifies Kubernetes management, reducing operational overhead in production.

Day 16-17: Basic Kubernetes Deployment & Scaling on AKS

Concept: Deploying applications to Kubernetes using YAML manifests (Deployment, Service); managing pods.

Challenge: Connect kubectl to AKS. Write deployment.yaml and service.yaml for your app (from ACR). kubectl apply. Scale app.

Reasoning: Kubernetes orchestrates containers, providing high availability and scalability. Namespaces organize resources for different environments/teams.

Phase 4: Continuous Integration & Delivery (CI/CD) (Days 18-24) Goal: Automate the build, test, and initial deployment/push stages of your application and infrastructure. This phase drives your GitOps strategy.

Day 18-19: GitLab CI/CD - Basics & Docker Build

Concept: Automating code pipelines with .gitlab-ci.yml (stages, jobs); building Docker images in CI.

Challenge: Push app/web-app/ to GitLab. Create .gitlab-ci.yml with build stage to build your app's Docker image.

Reasoning: Automates repeatable development tasks, reducing manual errors and speeding up feedback.

Day 20: GitLab CI/CD - Docker Push to ACR

Concept: Authenticating and pushing built Docker images to your cloud registry from CI.

Challenge: Enhance .gitlab-ci.yml to log into ACR and push the built image with a unique tag (e.g., using $CI_COMMIT_SHORT_SHA).

Reasoning: Automated image promotion ensures only tested, versioned images reach the registry for deployment.

Day 21-22: GitHub Actions - Terraform Plan & Apply

Concept: Automating infrastructure changes with GitHub's CI/CD; secure authentication to Azure.

Challenge: Push infra/aks-cluster/ Terraform to GitHub. Create .github/workflows/terraform.yml. Authenticate to Azure using GitHub Secrets (Service Principal). Run terraform plan and then a conditional terraform apply.

Reasoning: Automates infrastructure changes, ensuring consistency and auditability for production infrastructure. Conditional apply prevents accidental changes.

Day 23-24: Application CI/CD Integration

Concept: A CI/CD pipeline that builds an application, pushes its image, and then automatically updates the Kubernetes manifest for GitOps.

Challenge: In your app-code-repo's GitLab CI pipeline (.gitlab-ci.yml): After building/pushing Docker image, add a job to clone your K8s config repo (k8s-config-repo). Use sed (or a Python script) to update the image tag in your deployment.yaml. Commit and push this change to k8s-config-repo.

Reasoning: This is the critical "bridge" for GitOps, where CI produces a new artifact and automatically declares the desired state in Git.

Phase 5: GitOps Deployment with Argo CD (Days 25-28) Goal: Implement a fully declarative, reconciled application deployment model for AKS. This is your production deployment strategy.

Day 25: GitOps Principles & Argo CD Setup

Concept: Git as the single source of truth for desired state. Argo CD's role in continuous reconciliation.

Challenge: Install Argo CD into your AKS cluster (if not done by Terraform in Phase 4). Access Argo CD UI/CLI. Create a new remote Git repository (k8s-config-repo) for your Kubernetes manifests.

Reasoning: GitOps ensures that what's in Git is exactly what's deployed, improving reliability, auditability, and rollback capabilities in production.

Day 26: Argo CD Application Definition & Sync

Concept: Telling Argo CD what to deploy from where.

Challenge: Move your app/web-app's Kubernetes manifests (deployment.yaml, service.yaml) into your k8s-config-repo. Define an Argo CD Application resource in a separate file (e.g., argocd-app.yaml) that points to this k8s-config-repo path. Apply this Application to AKS.

Reasoning: Argo CD automates deployment by continuously syncing your cluster to the state defined in your Git repository.

Day 27: Argo CD Reconciliation & Self-Healing

Concept: Argo CD automatically correcting cluster state drift.

Challenge: Manually delete your my-web-app deployment from AKS (kubectl delete). Observe Argo CD immediately redeploying it.

Reasoning: Ensures your production environment never deviates from its desired state defined in Git.

Day 28: GitOps Driven Updates

Concept: Changes to your application's desired state are made only in Git.

Challenge: Modify the replica count in your deployment.yaml in the k8s-config-repo Git repository. Commit and push. Observe Argo CD automatically updating the replicas on AKS.

Reasoning: All production changes go through Git, providing a full audit trail and easy rollbacks.

Phase 6: End-to-End Orchestration (Days 29-30) Goal: Connect all the pieces to demonstrate a complete, automated DevOps workflow.

Day 29: Infrastructure & Application Pipeline Kickoff

Concept: Reviewing and orchestrating the full flow.

Challenge: Trigger your GitHub Actions workflow in infra-repo to deploy/update your AKS cluster and ACR. Then, make a small code change in your app-code-repo. Observe the GitLab CI pipeline running.

Reasoning: This simulates a real development scenario where infrastructure is updated and new application versions are pushed.

Day 30: Full GitOps Deployment Validation & Review

Concept: Confirming the entire pipeline, from code change to live application, is automated and GitOps-driven.

Challenge: After Challenge 29.1, verify in Argo CD UI that the new image from GitLab CI was detected and deployed to AKS. Access your application's public IP to confirm the new version is live. Clean up all resources using Terraform (destroying AKS, ACR, VMs, etc.).

Reflect: Discuss the full cycle, the role of each tool, and how this process contributes to production stability, speed, and reliability. This is where your confidence solidifies.

💡 Keys to Success & Production Confidence Problem-Solving Focus: Every error is an opportunity to learn. Master reading error messages and searching for solutions. This is a top skill for production engineers.

Version Control Everything: Treat infrastructure, configuration, and application manifests as code. This provides audit trails, rollback capabilities, and collaboration.

Automation First: Automate repetitive tasks. Manual steps introduce human error in production.

Declarative vs. Imperative: Understand when to declare (Terraform, K8s manifests) and when to imperatively script (Ansible, CI/CD steps). GitOps is heavily declarative.

Security Mindset: From secrets management in CI/CD to network security in Azure and AKS, always consider security.

Observability: Think about how you would monitor and log what your pipeline and applications are doing in a real environment.

Small, Iterative Changes: Make small changes, commit often, and test continuously. This reduces risk in production.

This journey will provide you with a robust foundation to confidently tackle production-level DevOps challenges. Enjoy the process of building and automating!