Venture into the world of Azure Infrastructure, where design meets functionality. Harness your skills and gain mastery over complex cloud structures to ace the AZ-305 Designing Microsoft Azure Infrastructure Solutions exam!
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Migrating workloads to Azure requires choosing between Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) based on workload requirements and architectural constraints. The lift-and-shift pattern moves applications directly to Azure Virtual Machines with minimal changes, offering a fast transition but keeping management overhead high. In contrast, replatforming makes minor optimizations to leverage managed services like Azure App Service, while refactoring involves re-architecting applications to run on container-based services like Azure Kubernetes Service (AKS). Each approach represents a trade-off: lift-and-shift minimizes migration effort and initial downtime, whereas refactoring requires significant development time but delivers superior long-term cost efficiency and scalability.
To automate the relocation of Azure resources, you can use Infrastructure as Code (IaC) or Azure Resource Mover. When using IaC, you export Azure Resource Manager templates or convert them to Bicep to deploy matching infrastructure in a target region. However, IaC templates only deploy structural resources and do not move underlying data, which means you must plan separate data-relocation steps. For direct resource transfers, Azure Resource Mover identifies dependencies and orchestrates the relocation of supported assets across regions, subscriptions, or resource groups.
Relocating stateful services requires selecting an automation tool based on the acceptable downtime and data type. For a hot relocation with minimal downtime, synchronous data replication copies data in near real-time across boundaries. Services like Azure SQL Database and Azure Cosmos DB provide built-in geo-replication to synchronize databases natively, though specific failover behaviors depend on the resource. For warm or cold migrations, Azure Site Recovery replicates virtual machines and their local storage continuously until the final cutover. File and object storage can be migrated using utility tools such as AzCopy, Azure Storage Explorer, or Azure Backup, while complex, large-scale data movements are best orchestrated by Azure Data Factory pipelines.
Selecting the ideal migration strategy requires assessing application dependencies, performance profiles, and compliance standards. Simple legacy workloads with tight operating system dependencies often remain on virtual machines, while web workloads benefit from the operational savings of PaaS. Security boundaries, data residency laws, and network latency goals dictate which target services and migration pathways are viable. By aligning these technical characteristics with organization-wide cost, security, and operational objectives, you can design a robust and predictable migration lifecycle.
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