Azure from Zero to Production

A Complete Guide to Modern Cloud Engineering. Learn to build, secure, and operate Azure workloads at enterprise scale with practical command-line examples.

1. About This Book

Introduction: Why Azure, Why Now?

Chapter 1: Azure Fundamentals — The Building Blocks

1. Global Infrastructure: Regions, Availability Zones, and Geographies
2. Azure CLI Reference: Essential Command-Line Operations
3. Identity Primitives: Microsoft Entra ID, Users, Groups, Service Principals
4. The Azure Toolchain: Portal, CLI, PowerShell, REST API
5. Cost Fundamentals: Pricing Models, Billing Accounts, and Cost Allocation

Chapter 2: Networking Deep Dive

1. Virtual Network Design: Address Spaces, Peering, and Subnet Strategy
2. DNS, Private Endpoints, and Hybrid Connectivity
3. Load Balancing: Application Gateway vs. Standard LB vs. Front Door
4. Traffic Manager, ExpressRoute, and VPN Gateways
5. Network Security Groups, Azure Firewall, and DDoS Protection
6. Real-World Patterns: Hub-and-Spoke, Spoke-to-Spoke, and Transit Gateways
7. Azure CLI: Networking Operations

Chapter 3: Identity and Access Management

1. Microsoft Entra ID: Core Concepts, Domains, and Tenants
2. RBAC vs. ACLs: When to Use Each
3. Managed Identities, Service Principals, and Certificate-Based Auth
4. Conditional Access, MFA, and Zero Trust Foundations
5. PIM for Production Workloads
6. Cross-Tenant Authentication and B2B/B2C Scenarios

Chapter 4: Compute Services — Choosing the Right Engine

1. Virtual Machines: Sizes, SKUs, and Availability Sets
2. Azure Container Instances vs. App Service vs. Functions
3. Dedicated Hosts, Spot VMs, and Reserved Instances
4. Performance Tuning: NUMA, Storage IOPS, and Network Throughput
5. Migration Strategies: Lift-and-Shift vs. Refactoring Compute
6. Production Best Practices: Patching, Monitoring, and Recovery
7. Azure CLI: Compute Operations

Chapter 5: Storage Architectures

1. Blob Storage: Hot, Cool, Archive Tiers and Lifecycle Management
2. Disk Storage: Premium SSD, Standard SSD, Ultra Disk — Choosing by IOPS and Throughput
3. Files and File Shares: NFS vs SMB, Azure NetApp Files
4. Queue and Table Storage: When (and When Not) to Use Them
5. Data Transfer: AzCopy, Data Box, ExpressRoute Global Routing
6. Production Patterns: Backup, Replication, Encryption, and Compliance
7. Azure CLI: Storage Operations

Chapter 6: Databases — From Relational to NoSQL

1. Azure SQL Database vs. SQL Managed Instance vs. SQL Server on VM
2. Cosmos DB: RU Model, Consistency Levels, and Multi-Region Writes
3. PostgreSQL (Flexible Server), MySQL, and MariaDB
4. Redis Cache, Apache Kafka, and Event Hubs
5. Database Migration Strategies and DR Patterns
6. Production Considerations: Backup, Scaling, Monitoring, and Cost
7. Azure CLI: Database Operations

Chapter 7: Containers and Kubernetes (AKS)

1. Docker Fundamentals in the Azure Context
2. AKS Architecture: Control Plane, Nodes, Networking Modes, and Storage
3. Node Pools, Autoscaling, and Pod Scheduling
4. Image Registry: ACR Integration and Security
5. Ingress, Service Mesh, and External Traffic Patterns
6. Production AKS: Upgrades, Troubleshooting, and Multi-Tenancy
7. Azure CLI: AKS Operations

Chapter 8: Serverless — Functions, Logic Apps, and Event-Driven Architecture

1. Azure Functions: Flex Consumption, Premium, and Dedicated Plans
2. Durable Functions and Stateful Workflows
3. Logic Apps, Event Grid, and Service Bus for Event-Driven Designs
4. Cold Starts, Concurrency Limits, and Scaling Behavior
5. Serverless + Container Hybrid Patterns
6. Cost Modeling: When Serverless Beats VMs and Vice Versa

Chapter 9: DevOps, CI/CD, and GitOps on Azure

1. Azure DevOps: Boards, Repos, Pipelines, Artifacts
2. GitHub Actions for Azure Deployments
3. CI/CD Pipeline Design: Build, Test, Stage, Deploy, Approve
4. GitOps with Argo CD on AKS
5. Environment Strategy: DEV to QA to STAGING to PROD
6. Deployment Strategies: Blue/Green, Canary, Rolling Updates
7. Azure CLI: DevOps Operations
8. Azure CLI: DevOps Operations

Chapter 10: Infrastructure as Code (IaC)

1. ARM Templates vs. Bicep vs. Terraform — Comparison and Migration
2. Bicep Deep Dive: Modules, Parameters, and Composite Templates
3. Terraform on Azure: Provider, State Management, and Workspaces
4. IaC Testing, Validation, and Policy Enforcement
5. CI/CD Integration for IaC Changes
6. Production Patterns: Module Registry, Versioning, and Rollbacks
7. Azure CLI: IaC Operations

Chapter 11: Observability — Logging, Monitoring, and Tracing

1. Azure Monitor Fundamentals: Metrics, Logs, and Alerts
2. Application Insights: Distributed Tracing and Performance
3. Log Analytics Workspaces, KQL Queries, and Custom Dashboards
4. Alerting Strategies: Noise Reduction and Escalation
5. OpenTelemetry Integration and Cross-Platform Observability
6. SRE Practices: SLIs, SLOs, and Error Budgets in Azure

Chapter 12: Governance, Policy, and Compliance

1. Azure Policy: Built-In Definitions, Custom Policies, and Assignments
2. Blueprints for Standardized Environments
3. Microsoft Defender for Cloud: Security Posture and Threat Protection
4. Compliance Certifications, Data Residency, and Regulatory Requirements
5. Resource Tagging, Cost Allocation, and Showback/Chargeback
6. Governance at Scale: Landing Zones and the Well-Architected Framework

Chapter 13: FinOps — Cloud Financial Management

1. Azure Cost Management Tools: Budgets, Alerts, and Recommendations
2. Reserved Instances, Savings Plans, and Commitment Discounts
3. Right-Sizing: VMs, Databases, and Storage
4. Spot Instances and Interruptible Workloads
5. Tagging Strategy for Cost Allocation
6. Building a FinOps Culture: Cross-Team Accountability

Chapter 14: AI and Machine Learning on Azure

1. Azure OpenAI Service: Models, Deployment, and Guardrails
2. Azure Machine Learning Studio: Pipelines, Compute, and Model Management
3. Cognitive Services for Vision, Speech, Language, and Decision
4. ML Infrastructure: GPU VMs, AmlCompute, and Real-Time Endpoints
5. Responsible AI and Model Governance
6. Production Patterns: RAG, Fine-Tuning, and Prompt Engineering

Chapter 15: Troubleshooting and Incident Response

1. The Troubleshooting Mindset: Hypothesis-Driven Debugging
2. Common Failure Modes: Network Timeouts, DNS, Auth, and Throttling
3. Using Azure Service Health, Status Pages, and Resource Diagnostics
4. Log Analysis, Trace Correlation, and Root Cause Identification
5. Incident Response Playbooks and Post-Mortems
6. Resilience Patterns: Retry, Circuit Breaker, Bulkhead, Fallback

Conclusion: The Production Mindset

References