AZ-900 Microsoft Azure Fundamentals Exam

Evaluate Azure Table Storage

Azure Table Storage is a NoSQL service for storing structured, non-relational data. It uses a schemaless design, meaning you can store different types of data in the same table without a fixed structure, which makes it easy to adapt as your application changes. It is a cost-effective choice for storing large volumes of data that don't require complex relationships like those in a traditional SQL database.

Data in Table Storage is organized into tables inside a storage account. Each table contains entities, which are like rows. Every entity has properties, which are simple name-value pairs. The system uses two special properties to organize and find data quickly: the PartitionKey groups related entities together, and the RowKey uniquely identifies an entity within that partition.

This service is best for scenarios that need simple, fast lookups and flexible data, such as storing user profiles, device information for IoT, or application metadata. Choose Azure Table Storage when you need a straightforward, low-cost way to manage structured NoSQL data within a single region. For more advanced features like global distribution, you might consider Azure Cosmos DB, which offers a compatible Table API.

Analyze Azure Queue Storage

Azure Queue Storage is a messaging service that helps different parts of an application communicate asynchronously. It stores messages (up to 64 KB each) in a queue, allowing one component to send a message without waiting for another component to process it immediately. This decoupling makes applications more scalable and resilient because work can wait in the queue if a processing component is busy or fails.

You access Queue Storage through an Azure storage account. The flow is simple: a producer application sends a message to a named queue. Later, a consumer application retrieves and processes that message. Since messages are durable, they remain in the queue until successfully processed, even if the consumer restarts. This pattern is ideal for creating backlogs of work, like in web-queue-worker architectures, or for load leveling between microservices.

Developers work with queues using REST APIs or client libraries, performing operations like creating queues, sending messages, and reading message counts. Use Azure Queue Storage when you need a reliable, high-throughput service for point-to-point messaging that helps your application handle variable loads and recover from failures smoothly.

Differentiate Azure Disk Storage

Azure Disk Storage provides virtual hard disks for Azure virtual machines (VMs). It comes in two main management types: managed disks and unmanaged disks. Managed disks are the recommended and simpler option because Azure handles the underlying storage accounts, scaling, and redundancy for you. Unmanaged disks require you to manage storage accounts yourself and are being phased out.

Disks are also offered in several performance tiers to match different workload needs and budgets. Standard HDD disks are the most cost-effective, suited for backup or infrequently accessed data. Standard SSD disks offer better performance for general-purpose workloads like web servers. Premium SSD disks deliver high, consistent performance for production workloads like databases. Ultra Disk provides the highest configurable performance for the most demanding, input/output-intensive applications.

When you create a VM, Azure also provides a temporary local SSD at no extra cost. This disk is ephemeral, meaning data on it is not persistent and is lost if the VM is stopped or moved. You should only use it for temporary files like swap space. For all persistent data, you must attach a managed data disk. Choosing the right disk tier involves balancing your application's performance requirements against your budget.

Examine Azure File Storage

Azure File Storage provides fully managed file shares in the cloud using the standard SMB protocol. This means it works like a traditional Windows file server, allowing you to create shared drives that can be accessed by Windows, Linux, or macOS clients. You can mount these shares directly to Azure VMs or even to on-premises machines over the internet, making it easy to migrate applications that rely on shared file systems.

A key feature for hybrid environments is Azure File Sync. This service caches your Azure file shares on a Windows Server in your own data center. It keeps the cloud and on-premises data in sync, which is useful for migration or for providing local fast access to files while using the cloud for centralized backup and storage.

Azure Files preserves important file details, including the actual data and metadata like NTFS permissions and timestamps. For security, it supports identity-based authentication, letting users sign in with their existing Active Directory or Microsoft Entra credentials to access shares and files. You can also use Azure's role-based access control for share-level security. This combination makes Azure Files a secure and flexible solution for shared storage needs across cloud and on-premises environments.

Understand Azure Blob Storage

Azure Blob Storage is Microsoft's object storage service for unstructured data, such as images, videos, log files, and backup archives. It is designed to store massive amounts of data, scaling from small files to petabytes. Data is organized inside containers, which are like folders that hold the individual data objects called blobs.

A major feature of Blob Storage is its access tiers, which let you optimize costs based on how often you need to access your data. The Hot tier is for frequently accessed data and has higher storage costs but lower access costs. The Cool tier is for infrequently accessed data and has lower storage costs. The Archive tier offers the lowest storage cost for data you rarely need, but retrieving it takes several hours.

Blob Storage is built for durability and availability. You can configure how your data is replicated, from within a single data center to across geographically separate regions, protecting against local or regional outages. Common use cases include serving static website content, storing data for big data analytics, and forming the backbone for backup and disaster recovery solutions. Its scalability and cost-management features make it a versatile foundation for many cloud applications.