AZ-305 Designing Microsoft Azure Infrastructure Solutions Exam

Evaluate a Migration Solution That Leverages the Microsoft Cloud Adoption Framework for Azure

The Microsoft Cloud Adoption Framework (CAF) is a set of best practices and tools that guide organizations through each stage of cloud adoption. It helps teams align business objectives with technical strategies to ensure migrations deliver value. By following CAF, you can reduce risks and improve the predictability of migration outcomes.

CAF breaks the migration journey into five key phases:

• Strategy: Define business goals and expected benefits.
• Plan: Assess readiness and determine the migration approach.
• Ready: Build landing zones and set up governance.
• Migrate: Move workloads using automated tools.
• Innovate: Optimize and modernize after migration.

When evaluating a migration solution using CAF, teams should map workloads to the right phase and choose appropriate Azure services. This ensures that each workload is treated according to its complexity and criticality. Stakeholder engagement during each phase is critical to address concerns and validate progress.

Key tools that support CAF migrations include Azure Migrate, Azure Site Recovery, and Azure Well-Architected Review. These tools help with discovery, assessment, and continuous improvement. Together, they form a cohesive framework that drives a successful and controlled migration to Azure.

Evaluate On-Premises Servers, Data, and Applications for Migration

Before migrating, it’s essential to conduct a thorough assessment of on-premises environments. This evaluation identifies dependencies, performance baselines, and potential roadblocks. A clear inventory of servers, data stores, and applications forms the foundation for choosing the right migration path.

Use discovery and assessment tools to gather detailed information:

• Azure Migrate: Discovers and assesses server workloads.
• Data Migration Assistant: Checks database compatibility.
• Application Insights: Analyzes application performance and dependencies.

During assessment, focus on workload characteristics such as resource utilization, network dependencies, and compliance requirements. This helps prioritize workloads and choose between rehosting, refactoring, or rearchitecting. Creating a readiness report with cost estimates and risk levels allows stakeholders to approve a migration plan confidently.

The final output of this evaluation is a comprehensive migration blueprint. It outlines workload mappings, required Azure services, and any optimization opportunities. With this blueprint, teams can move forward knowing each workload has a clear and justified migration path.

Recommend a Solution for Migrating Workloads to Infrastructure as a Service and Platform as a Service

When moving workloads to Azure, you must choose between Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). IaaS offers virtual machines and networking control, while PaaS provides managed runtimes and scaling. Each model shifts different levels of management responsibility to Azure.

Common Azure services for these migration models include:

• IaaS: Azure Virtual Machines, Azure Virtual Network.
• PaaS: Azure App Service, Azure Functions, Azure Service Fabric.

Evaluate workload requirements such as operating system support, middleware compatibility, and SLA needs. For example, a simple web app may benefit from PaaS to reduce management overhead. In contrast, legacy applications with strict customization demands might require IaaS.

Choose an appropriate migration strategy—lift-and-shift, replatform, or refactor—based on business priorities. Lift-and-shift moves workloads with minimal changes, while replatform and refactor involve code and architecture updates. Align each workload’s target environment with its long-term maintenance and scalability goals.

Recommend a Solution for Migrating Databases

Database migrations often face challenges around compatibility, downtime, and data integrity. Planning must address schema differences, version mismatches, and customer expectations for availability. A clear cutover plan ensures minimal disruption.

Key Azure services for database migration:

• Azure Database Migration Service (DMS): Handles both offline and online migrations.
• Data Migration Assistant (DMA): Assesses schema and feature compatibility.
• Azure SQL Managed Instance: Provides near-complete SQL Server compatibility in a fully managed service.

Select between offline migration for short databases or online migration for critical systems that need minimal downtime. Online migrations use continuous data sync to keep source and target in sync until cutover. After migration, perform functional testing, performance tuning, and index optimization to validate the new environment.

A successful database migration also includes rollback plans and data validation steps. Automating schema changes and data movement reduces human error. Monitoring tools like Azure Monitor ensure post-migration performance meets or exceeds on-premises levels.

Recommend a Solution for Migrating Unstructured Data

Unstructured data includes files, documents, images, and logs that don’t fit into a database schema. Migrating this data requires solutions that handle large volumes and varied file sizes. Planning should address throughput, security, and consistency.

Azure offers specialized tools for unstructured data:

• Azure Data Box: Physical appliance for large-scale offline transfers.
• AzCopy: Command-line tool for high-performance uploads to Azure Blob Storage.
• Azure File Sync: Synchronizes on-premises file shares with Azure Files.

When designing the migration, consider network bandwidth and transfer windows. For streaming transfers, use AzCopy or Azure Data Factory to move data continuously. For bulk migrations, Data Box can speed up large transfers without saturating network links.

Implement encryption at rest and in transit, and validate checksums after each transfer. Use Azure Storage lifecycle policies to optimize storage tiers post-migration. Finally, establish monitoring alerts for transfer failures and capacity thresholds to maintain data integrity.

Conclusion

In this section, we explored how to design migrations using the Microsoft Cloud Adoption Framework, ensuring a structured approach from strategy through innovation. We covered assessing on-premises servers, data, and applications to build a solid migration blueprint, identifying the right Azure services for discovery and readiness.

Next, we discussed choosing between IaaS and PaaS for different workloads, balancing control with managed services. We then focused on database migrations, highlighting tools like Azure DMS and techniques for minimizing downtime. Finally, we addressed unstructured data migration using services such as Azure Data Box and AzCopy to handle volume and security.

Together, these concepts form a cohesive migration strategy that aligns technical requirements with business goals. By leveraging Azure’s tools and following best practices, migrations can be predictable, secure, and efficient.