Microsoft Exam AZ-305: Designing Microsoft Azure Infrastructure Solutions Interview Questions

The Microsoft Exam AZ-305: Designing Microsoft Azure Infrastructure Solutions certification course demonstrates your ability in devising designs for safe, scalable, and dependable Azure solutions, among other things. To pass the interview, candidates must have knowledge of Azure solutions including computing, network, storage, monitoring, and security. Moreover, you must be able to interact with stakeholders, convert business needs into designs for safe, scalable, and dependable Azure Solutions, and more. Additionally, if you want to revise the concepts and know about other preparation resources, you can go through the Microsoft Exam AZ-305 Online tutorial as well. 

Preparing for the Microsoft Exam AZ-305 interview may involve thinking about which questions will be asked. Even though you can’t predict what topics will be discussed, there are several common interview questions you ought to be prepared for. Here is a list of top Microsoft Exam AZ-305 Interview Questions. Let’s begin!

Advanced Interview Questions

Can you explain the different deployment models in Azure and which one would you recommend for a large enterprise organization?

There are four primary deployment models in Azure, which are as follows:

1. Public Cloud: The public cloud deployment model refers to hosting and managing resources in Azure’s public cloud environment. Organizations can use a range of services, such as virtual machines, storage, and databases, in this model.
2. Private Cloud: A private cloud deployment model refers to the use of dedicated resources for a specific organization. These resources can be hosted in a data center or on-premise and managed by the organization.
3. Hybrid Cloud: The hybrid cloud model combines both public and private cloud models. In this model, an organization can use both on-premises and cloud-based resources, thereby enjoying the advantages of both environments.
4. Multi-cloud: The multi-cloud model is similar to the hybrid cloud model, except that it involves using multiple cloud providers instead of just one.

When it comes to recommending a deployment model for a large enterprise organization, it’s essential to consider several factors, such as business requirements, compliance regulations, security, and scalability. In general, most large organizations prefer a hybrid cloud model that allows them to have better control over their sensitive data and applications while leveraging the benefits of public cloud resources. By using a hybrid cloud, an organization can also scale resources as needed, reduce latency, and achieve cost savings by optimizing resource utilization.

Overall, selecting the right deployment model for an organization depends on various factors and requires careful consideration. Still, a hybrid cloud model is often the best fit for large enterprise organizations.

How would you approach designing a disaster recovery plan for a mission-critical application in Azure?

Designing a disaster recovery plan for a mission-critical application in Azure involves several key steps. Here’s a high-level overview of how I would approach the process:

1. Identify the critical components of the application: The first step in designing a disaster recovery plan is to identify the critical components of the application. This includes everything from the application itself to the underlying infrastructure, such as databases, virtual machines, and networking components.
2. Determine the recovery objectives: Once you’ve identified the critical components of the application, the next step is to determine the recovery objectives. This involves defining the recovery point objective (RPO) and recovery time objective (RTO) for each component. The RPO defines the maximum amount of data loss that can be tolerated, while the RTO defines the maximum amount of downtime that can be tolerated.
3. Choose a disaster recovery strategy: With the recovery objectives in mind, the next step is to choose a disaster recovery strategy. There are several options available in Azure, including Azure Site Recovery, Azure Backup, and Azure VM replication. Each of these options has its own strengths and weaknesses, so it’s important to choose the one that best meets the recovery objectives.
4. Implement the disaster recovery plan: Once the disaster recovery strategy has been chosen, it’s time to implement the plan. This involves configuring the necessary components, such as setting up replication, configuring backup policies, and configuring failover mechanisms.
5. Test the disaster recovery plan: Testing the disaster recovery plan is crucial to ensure that it will work as expected when it’s needed. This involves running regular tests to simulate a disaster and verifying that the application can be recovered within the defined RPO and RTO.
6. Monitor and update the disaster recovery plan: Finally, it’s important to monitor the disaster recovery plan on an ongoing basis and update it as needed. This includes monitoring the health of the underlying infrastructure, ensuring that backups and replication are occurring as expected, and making changes to the plan as the application evolves over time.

By following these steps, you can design a disaster recovery plan for a mission-critical application in Azure that provides the level of protection and resilience that your organization requires.

How do you ensure high availability and reliability of Azure services for customers?

Microsoft Azure has a multi-layered approach to ensure high availability and reliability of its services for customers. Here are some ways:

1. Data center redundancy: Azure has multiple data centers in different regions across the globe. These data centers are equipped with redundant power supplies, cooling systems, and network connectivity. If one data center fails, traffic is automatically redirected to another one without any disruption to the service.
2. Load balancing: Azure uses load balancing to distribute traffic evenly across multiple servers. This ensures that no single server becomes overloaded, leading to performance degradation or downtime.
3. Auto-scaling: Azure allows customers to automatically scale their applications up or down based on demand. This ensures that there are always enough resources available to handle the workload.
4. Monitoring and alerting: Azure constantly monitors its services for issues and alerts customers if there is an outage or any other issue. This allows customers to take corrective action before the issue becomes a major problem.
5. Disaster recovery: Azure has built-in disaster recovery capabilities that allow customers to replicate their data and applications to another region. This ensures that in the event of a disaster, customers can quickly switch to the replicated resources without any loss of data or downtime.

Overall, Azure employs a combination of data center redundancy, load balancing, auto-scaling, monitoring and alerting, and disaster recovery to ensure high availability and reliability of its services for customers.

Can you describe the different storage options available in Azure and their use cases?

Azure offers various storage options for storing data, files, and objects. Each storage option serves different purposes and use cases. Here are some of the different storage options available in Azure:

1. Azure Blob Storage: Azure Blob Storage is a highly scalable and cost-effective storage option for unstructured data such as images, videos, documents, and logs. It supports different tiers of storage, including hot, cool, and archive, based on data access patterns and retention requirements. It also provides features such as encryption, versioning, and lifecycle management.
2. Azure Files: Azure Files is a fully managed cloud file share service that allows users to store and share files using the SMB protocol. It provides a simple and flexible way to migrate on-premises file shares to the cloud and enable hybrid scenarios. It also supports features such as encryption, snapshots, and backups.
3. Azure Table Storage: Azure Table Storage is a NoSQL key-value store that provides a schema-less data model and supports massive scalability. It is designed for storing structured data such as user profiles, product catalogs, and IoT telemetry data. It also provides features such as indexing, partitioning, and replication.
4. Azure Queue Storage: Azure Queue Storage is a messaging service that enables asynchronous communication between components or services. It provides a reliable and scalable way to decouple different parts of a distributed system and improve performance, resilience, and scalability. It also supports features such as visibility timeouts, message expiration, and poison message handling.
5. Azure Disk Storage: Azure Disk Storage is a persistent block storage service that provides high-performance and low-latency storage for virtual machines (VMs) and other compute resources. It supports different disk types such as Standard HDD, Standard SSD, and Premium SSD, based on performance and availability requirements. It also provides features such as snapshots, backups, and encryption.
6. Azure Archive Storage: Azure Archive Storage is a low-cost storage option for long-term data retention and compliance. It is designed for infrequently accessed data that needs to be stored for years or decades. It provides a secure and durable way to store data while reducing storage costs. However, it has longer retrieval times and access fees compared to other storage options.

Overall, the choice of storage option depends on the type of data, the access patterns, the performance requirements, the compliance and security needs, and the budget constraints. Azure provides a wide range of storage options to meet different use cases and scenarios.

How would you design a secure network architecture in Azure to protect against cyber threats and attacks?

1. Identify the critical assets: The first step is to identify the assets that are critical to the organization. These assets should be identified and then isolated from the rest of the network to reduce the attack surface.
2. Use a defense-in-depth strategy: Employ a multi-layered security approach by deploying different types of security controls at various layers of the network architecture. For example, use firewalls, intrusion detection and prevention systems, and network segmentation.
3. Encrypt data in transit and at rest: Ensure that data is encrypted both in transit and at rest. Use Transport Layer Security (TLS) to encrypt data in transit and encrypt data at rest using Azure Storage Service Encryption.
4. Use Azure Security Center: Azure Security Center provides a unified security management solution that enables you to monitor and improve the security of your Azure resources.
5. Monitor for threats: Implement continuous monitoring of the network and security controls to detect threats and attacks. Use Azure Security Center to monitor the network, identify threats, and take corrective action.
6. Update regularly: Regularly update software and security patches to ensure that the network is up-to-date and protected against new vulnerabilities.
7. Conduct security audits: Conduct regular security audits to identify and remediate security vulnerabilities.
8. Train employees: Train employees on how to identify and report potential cyber threats and attacks.

By following these tips, you can design a secure network architecture in Azure that is protected against cyber threats and attacks.

Can you explain the difference between Azure Virtual Machines and Azure Functions and when to use each one?

Azure Virtual Machines (VMs) and Azure Functions are two different services offered by Microsoft Azure for different purposes. Here’s a brief explanation of each service and when to use them:

Azure Virtual Machines (VMs): Azure VMs are essentially virtual computers that you can rent from Azure. They allow you to create and run a virtual machine in the cloud, with full control over the operating system, applications, and data. You can choose from a range of pre-configured VM sizes, or create custom VM sizes to suit your specific needs. Azure VMs are ideal for running applications that require full access to the underlying operating system and hardware resources, such as SQL Server, SharePoint, and other enterprise-level applications.

When to use Azure VMs:

• Running enterprise-level applications that require full access to the operating system and hardware resources
• Running legacy applications that cannot be easily migrated to a cloud-native architecture
• Hosting custom applications that require specific software configurations or dependencies

Azure Functions: Azure Functions is a serverless compute service that lets you run code on-demand without having to worry about managing the infrastructure. You can write code in a variety of programming languages, such as C#, Java, Python, and Node.js, and trigger it using various events, such as HTTP requests, timers, or messages from other Azure services. Azure Functions scales automatically to handle high volumes of requests, and you only pay for the time your code runs.

When to use Azure Functions:

• Building event-driven applications that respond to specific triggers or events
• Automating business processes or workflows using Azure Logic Apps
• Building microservices that can be easily scaled and deployed independently

In summary, Azure VMs are ideal for running enterprise-level applications that require full access to the operating system and hardware resources, while Azure Functions are ideal for building event-driven applications and automating business processes or workflows.

How do you monitor and optimize Azure resources to ensure cost-effectiveness and performance?

1. Use Azure Cost Management and Billing: Azure Cost Management and Billing can help you monitor and control your Azure spending. It provides a comprehensive view of your Azure costs and usage across all your subscriptions. You can use it to identify cost-saving opportunities, optimize your resource usage, and set up budget alerts to prevent overspending.
2. Right-size your resources: You can optimize your Azure resources by right-sizing them. This means that you should choose the appropriate size for your virtual machines, databases, and other resources based on your workload requirements. This will help you avoid paying for resources you don’t need, which can reduce your Azure spending.
3. Use Azure Advisor: Azure Advisor is a free service that provides personalized recommendations to help you optimize your Azure resources. It can help you identify unused resources, enable cost-saving features, and improve the performance of your applications.
4. Monitor your resource utilization: You can use Azure Monitor to track the performance and utilization of your Azure resources. This can help you identify performance issues and optimize your resource usage. Azure Monitor provides insights into the health and performance of your applications, as well as detailed telemetry data.
5. Use automation to optimize your resources: You can use automation tools like Azure Automation, Azure Functions, and Azure Logic Apps to automate resource provisioning, configuration, and management. This can help you optimize your resource usage, reduce manual errors, and improve the efficiency of your operations.

By implementing these strategies, you can ensure that your Azure resources are cost-effective and perform optimally.

Can you describe the benefits and limitations of using Azure DevOps for continuous integration and continuous deployment (CI/CD)?

Benefits of using Azure DevOps for CI/CD:

1. Integration: Azure DevOps provides a comprehensive set of tools that can be integrated seamlessly with various development platforms, including GitHub, Bitbucket, and Azure Repos. This enables developers to work in their preferred environment while still taking advantage of Azure DevOps’ features.
2. Continuous delivery: Azure DevOps enables continuous delivery by automating the entire deployment process, including testing, deployment, and release. This helps reduce the time and effort required to deploy software updates, ensuring faster time-to-market and higher customer satisfaction.
3. Agile methodologies: Azure DevOps supports agile methodologies, enabling developers to collaborate efficiently and streamline their workflows. This results in faster and more effective software development and deployment.
4. Scalability: Azure DevOps is highly scalable and can accommodate projects of any size, from small teams to enterprise-level applications.
5. Customization: Azure DevOps provides a high degree of customization, enabling developers to configure their CI/CD pipelines according to their specific requirements.

Limitations of using Azure DevOps for CI/CD:

1. Learning curve: Although Azure DevOps is user-friendly, it can be challenging for developers who are not familiar with the platform. Developers may need to undergo training to effectively use the platform.
2. Cost: Azure DevOps can be costly, especially for small organizations or startups. However, Microsoft provides various pricing plans that cater to different budgets.
3. Limited third-party integrations: While Azure DevOps provides a range of integration options, it may not support all third-party tools and platforms.
4. Complex projects: Azure DevOps may not be suitable for complex projects with multiple dependencies and intricate workflows. Developers may need to explore other options or use a combination of tools to manage such projects effectively.
5. Security concerns: As with any cloud-based platform, security concerns may arise when using Azure DevOps for CI/CD. Developers need to take appropriate measures to ensure the security of their applications and data.

Can you explain how Azure supports hybrid cloud deployments and what considerations should be taken when designing hybrid architectures?

Azure provides robust support for hybrid cloud deployments, allowing businesses to seamlessly integrate on-premises infrastructure with Azure services. With Azure, businesses can run applications on either Azure or on-premises servers and manage them through a unified console. Here are some of the ways Azure supports hybrid cloud deployments:

1. Hybrid connectivity: Azure offers a range of connectivity options, including site-to-site VPN, ExpressRoute, and Azure Virtual WAN, that enable businesses to establish secure connections between on-premises infrastructure and Azure.
2. Hybrid identity: Azure Active Directory (Azure AD) enables businesses to extend on-premises Active Directory to the cloud, providing a single identity for users across both environments.
3. Hybrid data: Azure provides a range of data services that can be used to store and manage data in hybrid environments, including Azure SQL Database, Azure Cosmos DB, and Azure Data Lake Storage.
4. Hybrid management: Azure offers a unified management console that allows businesses to manage both on-premises infrastructure and Azure services from a single interface.

When designing hybrid architectures, there are several considerations to keep in mind:

1. Security: Security should be a top consideration when designing a hybrid architecture. Businesses must ensure that data is secure both in transit and at rest and that access to resources is tightly controlled.
2. Performance: Hybrid architectures can introduce latency and other performance issues. Businesses must ensure that their hybrid architectures are designed to minimize these issues.
3. Scalability: Hybrid architectures must be designed to scale as demand grows. Businesses must consider how to scale both on-premises infrastructure and Azure services to meet demand.
4. Data integration: Businesses must ensure that data is integrated seamlessly across on-premises and cloud environments. This may require the use of integration services such as Azure Logic Apps or Azure Data Factory.

Overall, Azure provides a robust platform for hybrid cloud deployments, enabling businesses to leverage the benefits of both on-premises infrastructure and cloud services. By carefully considering the above factors, businesses can design hybrid architectures that are secure, performant, scalable, and well-integrated.

How do you ensure compliance with regulatory and industry standards when deploying applications in Azure?

Deploying applications in Azure requires adherence to regulatory and industry standards. Here are some steps to ensure compliance:

1. Identify the applicable regulations and industry standards for the application. These could include HIPAA, GDPR, ISO 27001, and others.
2. Review Azure’s compliance certifications and attestations to determine whether they cover the regulations and industry standards that apply to your application.
3. Implement Azure’s built-in security features and configurations. Azure provides a range of security features, such as network security groups, role-based access control, and Azure Security Center, that can help you meet compliance requirements.
4. Use encryption for data at rest and in transit. Azure offers encryption for both types of data, and it’s crucial to enable it to protect sensitive information from unauthorized access.
5. Establish monitoring and auditing procedures to detect and report any potential security breaches or compliance violations. Azure’s auditing and monitoring tools can be used to track and analyze events and logs and enable compliance reporting.
6. Conduct regular compliance assessments and audits to ensure ongoing adherence to regulations and industry standards.

In conclusion, deploying applications in Azure while ensuring regulatory and industry standards compliance requires proper identification of the applicable regulations, implementing security features, encrypting data, monitoring and auditing, and regular assessments and audits.

Basic Interview Questions

1. What is meant by the term Gateway Routing pattern?

Gateway routing is a pattern for exposing multiple microservices on a single endpoint and routing those requests to internal backend microservices based on the request. The gateway routing pattern exposes a single endpoint to the external world while routing different requests to different internal microservices.

2. What is the minimum log level for minimum debug?

System-level ERROR is the minimum value to see any debug logs. However,  most people usually make use of the default logging level. Therefore, the usual recommendation is DEBUG.

3. What data does Azure monitor collect?

• Logs and metrics from the Azure platform and resources
• Custom applications
• Agents running on virtual machines

4. Could you tell me what all can be monitored with Azure monitor?

Azure Virtual Desktop Insights leverages Azure Monitor dashboards to provide information about the performance, health, and dependencies of a deployment’s VMs and other resources. Azure Monitor Workbooks can help IT professionals understand the performance and health of their virtual machines (VMs) in Azure Virtual Desktops, as well as monitor their processes and dependencies on other resources.

5. What is the difference between Azure Monitor and log analytics?

The Azure Monitor name reflects the fact that it is one of the solutions for monitoring Azure resources and hybrid environments. Current applications included in Application Insights have been re-named Log Analytics and moved to Azure Monitor (along with other features), to give a single integrated experience.

6. How would you explain the role-based access control RBAC in Azure?

Azure role-based access control (Azure RBAC) is a system that allows you to manage permissions for Azure resources. It does this by providing a way to segregate duties within your team and grant only the amount of access to users that they need to perform their jobs.

7. What are the three types of RBAC controls in Azure?

• Reader
• Contributor
• Owner

8. Could you elaborate on the use of Microsoft Identity Manager?

In essence, MIM synchronizes identity data between various systems. It is highly flexible in what it connects to—any directory service, email system, ERP system, or others. And which objects are synchronized: users, groups, roles and permissions, computers, etc.

9. What is replacing Microsoft MIM?

MIM is getting replaced entirely with Microsoft cloud functionality (Azure AD)

10. Can you tell me something about the top-level organizational structure in Azure?

The root Management Group is the top level of your Azure subscription. It contains all managed subscriptions and the various Azure resources. The root Management Group cannot be removed or moved. You can create up to six levels of management groups.

11. What is Azure resource hierarchy?

Azure provides four levels of management: 

• Management groups
• Subscriptions
• Resource groups
• Resources

12. Why do we use Azure key vault?

• Secrets Management – Azure Key Vault is primarily used for securely storing and strictly controlling the access to tokens, passwords, certificates, API keys, and other secrets.
• Key Management – Azure Key Vault is also used as a Key Management solution

13. Could you explain the working of a key vault?

Key Vault provides a cloud-based key management solution. It allows users to create and control keys used to encrypt data. It then allows them to combine Key Vault with other services, which allows for the decryption of secrets without the knowledge of the encryption keys.

14. What is Azure SQL managed instance used for?

Through Azure Active Directory integration, SQL Managed Instance allows you to manage the identities of database users and other Microsoft services centrally.

15. What are the options for managed SQL databases on Azure?

Azure SQL is available via three deployment models:

• Single Database – Managed with a SQL database server and deployed to an Azure VM. 
• Elastic Pool – An association of connected databases sharing resources.
• Managed Instance – An instance of the database that is fully managed.

16. Is Microsoft Dataverse the same as the Common data service?

Common Data Service (CDS) which is primarily the data storage system that is used for intensifying Dynamics 365 and Power Platform has undergone a name change and is now called a Dataverse as a part of a bigger rebrand at Microsoft. Essentially it does the same thing as CDS, however, with a different name.

17. How are NoSQL databases different from relational databases?

NoSQL designs prioritize non-relational data storage over relational databases. In other words, NoSQL databases use any number of methods—or a combination of methods—to store data in a decentralized, non-traditional way.

18. How would you explain RTO and RPO in disaster recovery?

RPO represents how long data will be protected after it has been recovered. In practice, the RPO indicates the amount of time (amount of downtime) it will take a business to re-enter or type in data that was lost due to a system outage. RTO is the amount of time that a business can tolerate being down.

19. Which Azure storage option is better for storing data for Backup and restore disaster recovery and archiving?

Microsoft Azure Blob Storage provides all the capabilities of a fully hosted and managed object store, including backup and disaster recovery for Azure IaaS disks. You can also use Blob Storage to back up other resources in Azure, like on-premises or virtual machines, or you can use Blob Storage to back up other resources on-premises or on computers running Windows Server. 

20. Could you differentiate between the Azure SQL Database and Azure SQL managed instance?

SQL Managed Instance enables native Virtual Network integration, whereas Azure SQL Database allows for restricted Virtual Network access via VNet Endpoints. The former solution is based on an instance-scoped configuration model, similar to that of an on-premises SQL Server, whereas the latter is available over a cloud-based service.

21. What is a virtual machine in cloud computing?

Virtual machines are computers that exist only as software. Virtual machines can run applications, store data, connect to networks, and do other computing functions. VMs require maintenance such as updates and system monitoring.

22. What are the main stages to migrate into the Azure cloud?

• Discovering: Cataloging the software and workloads.
• Assessing: Categorizing the applications and workloads.
• Targeting: Identifying the destination(s) for each workload.
• Migrating: Making the actual move.

23. Could you explain why we use serverless computing?

Compared to traditional cloud-based infrastructure or server-centric infrastructure, serverless computing offers many advantages. These advantages include scalability, flexibility, and quick time to release. All of these things are possible at a reduced cost.

24. What is the difference between cloud computing and serverless computing?

A cloud computing infrastructure is a shared network of remote servers that can be accessed from different locations. Serverless computing is a pay-as-you-go model. Only the part of the application that runs on a serverless service is paid for.

25. What are the six perspectives presented in the cloud adoption framework?

• Business
• People
• Governance
• Platform
• Security
• Operations

26. What is the benefit of using the Azure database migration service?

Azure Database Migration Service helps you migrate from multiple database sources to Azure Data platforms with minimal downtime. The service generates assessment reports that provide recommendations for changes you may need to make before migration begins.

27. What are the valid destination services for Azure database migration service?

• SQL Server
• MySQL
• PostgreSQL
• MongoDB
• Oracle

28. How would you describe network performance tuning?

Network performance tuning/configuring facilities enable administrators to configure combinations of LANs and WANs centrally and automatically based on anticipated traffic volumes. This results in optimal use of the available bandwidth.

29. What are the types of load balancers in Azure?

• Public load balancers
• Internal load balancers

30. Could you explain how the load balancer work in Azure?

• Health probes can be used to monitor load-balanced resources
• It also supports port forwarding for accessing virtual machines in a virtual network by public IP address and port
• Filters, groups, and breaks out metrics for a specific dimension on a multidimensional basis