Let’s talk about Azure storage solutions

What is Azure Cloud?

Azure is a cloud computing platform and service created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers. It offers a wide range of services, including computing power, storage, and networking, as well as services for analytics, artificial intelligence, and Internet of Things (IoT) applications. Developers can use Azure to build and deploy applications using a variety of programming languages, frameworks, and tools. It also offers services for data management, security, and compliance.

Let’s see now what azure storage account

An Azure storage account is a service provided by Microsoft Azure that enables users to store and manage data in the cloud. It provides a place to store various types of data, such as blobs(Binary Large OBject storage), files, queues, tables, and disks, and allows users to access the data through various methods, such as HTTP/HTTPS, SMB, NFS, and REST.

A storage account can be used to store unstructured data, such as text and binary data, as well as structured data in the form of tables and queues. It also provides features for data management, such as data replication, backup, and archival. Additionally, Azure storage accounts offer a high degree of durability and availability and can be configured to meet specific compliance and regulatory requirements.

A storage account can be used in combination with other Azure services, such as Azure Virtual Machines, Azure Databases, and Azure Kubernetes Services to build and run complex application architectures in a secure, scalable and highly available environment.

Let’s seen each of the storage services a little bit more

  • Blob storage: A service for storing unstructured data, such as images, videos, audio files, documents, and backups. It is optimized for streaming and storing large amounts of data. Examples of unstructured data that can be stored in blob storage include:
  • Images: JPEG, PNG, GIF, BMP, TIFF, etc.
  • Videos: MP4, AVI, MOV, WMV, etc.
  • Audio files: MP3, WAV, OGG, etc.
  • Documents: PDF, Word, Excel, PowerPoint, etc.
  • Backup files: VHD, VMDK, etc.
  • Log files: text files containing log data from an application or service
  • JSON and XML files: containing data in a semi-structured format

These are just a few examples of the types of unstructured data that can be stored in blob storage. Essentially, any type of binary data can be stored as a blob, regardless of its format or structure.

Azure Blob storage provides different storage access tiers that allow you to optimize storage costs based on the access patterns of your data. These tiers include:

  • Hot: intended for frequently accessed data that is stored for at least 30 days on SSDs to provide fast read and write performance.
  • Cool: intended for data that is not accessed as frequently as Hot data, but is still stored for at least 30 days on HDDs to provide lower-cost storage for infrequently accessed data.
  • Archive: intended for data that is rarely accessed and stored for at least 180 days on low-cost storage media such as magnetic tape to provide the lowest-cost storage option for infrequently accessed data.

The cost of Azure Blob storage varies depending on the storage access tier that is used, with Hot storage tier having the highest cost, Cool storage tier having cost lower than the Hot tier, and Archive storage tier having the lowest cost.

In addition to the storage costs, there are also retrieval costs associated with transitioning data from the Archive tier to the Hot or Cool tiers, as well as costs for features such as data replication and data archival.

  • File storage: A service for storing and accessing files using the SMB protocol. It allows users to mount file shares in the cloud and access them as if they were on-premises. also includes support for NFS v3, which allows Linux and UNIX-based systems to mount an Azure file share and access files as if they were stored on-premises. This enables users to choose the protocol that best fits their use case.
  • Queue storage: A service for storing and processing messages in a queue. It allows for reliable messaging between applications and services. Here is an example scenario of how Azure Queue storage can be used:

1.A website receives orders from customers and needs to process them in the background.

2. When a customer places an order, the website adds a message to an Azure Queue storage queue that contains the details of the order.

3. A worker process running in a separate application or service, such as an Azure function, reads messages from the queue and processes them.

4. The worker process retrieves the order details from the message, performs the necessary processing (e.g. charge the customer’s credit card, update inventory, etc.), and then deletes the message from the queue.

5. If the worker process is unable to process a message (e.g. due to a system failure), the message remains in the queue and can be retrieved and processed later.

6. As the orders are processed, the worker process updates the order status in a database and sends notifications to the customer.

7. Once all the orders are processed, the worker process can stop or keep running and waiting for new messages to be added to the queue

  • Table storage: A service for storing structured, non-relational data in the form of tables. It allows for flexible data modeling and querying. Here’s an example scenario of how Azure Table storage can be used

1. A website that allows users to create and manage events, such as conferences and meetups.

2. The website stores information about events, such as the name, location, date, and attendees, in an Azure Table storage table.

3. Each event is represented as an entity in the table, with properties for the event name, location, date, and attendees.

4. The website can use Azure Table storage to query the table for events that match certain criteria, such as events that are taking place in a specific location or events that have a certain number of attendees.

5. The website can also use Azure Table storage to retrieve information about a specific event, update an event’s details, or delete an event.

6. As the number of events and attendees grows, Azure Table storage can automatically scale to handle the increased load.

  • Disk storage: A service for storing and managing virtual hard disks (VHDs) in the cloud. It can be used to create and manage virtual machines, and to backup and restore data.

Azure Disk storage provides different types of disks, each optimized for a specific use case:

  • Ultra Disk: A high-performance, scalable and low-latency storage solution for Azure Virtual Machines (VMs) and Azure Kubernetes Service (AKS) workloads. It is designed for I/O-intensive workloads such as databases, big data analytics, and large-scale file shares.
  • Premium SSD: A high-performance disk that is suitable for I/O-intensive workloads, such as databases and high-performance computing.
  • Standard SSD: A balance of performance and cost that is suitable for most workloads, including virtual machines, databases, and file shares.
  • Standard HDD: A lower-performance disk that is suitable for infrequently accessed data, such as backups and archival data.

Azure Disk storage provides a different kind of roles:

  • Data Disk: A disk that is used to store data for a virtual machine.
  • Operating System Disk: A disk that is used to store the operating system for a virtual machine.
  • Temporary Disk: A disk that is used to store temporary data for a virtual machine.

When coming to the cost of VHDs is based on the amount of data stored, the type of disk used, and the storage redundancy options.

  • Standard HDD: The cost of a standard HDD is based on the amount of data stored and the storage redundancy option. The prices for standard HDD are lower than the other types.
  • Standard SSD: The cost of a standard SSD is based on the amount of data stored and the storage redundancy option. The prices for standard SSD are higher than the standard HDD but lower than the other types.
  • Premium SSD: The cost of a premium SSD is based on the amount of data stored and the storage redundancy option. Premium SSDs are optimized for I/O-intensive workloads and are more expensive than standard SSDs.
  • Ultra Disk: The cost of an Ultra Disk is based on the amount of data stored and the storage redundancy option. The prices for Ultra Disk is higher than the other types because it’s designed to provide high-performance, scalable and low-latency storage.
  • Archive storage: A service for storing data that is infrequently accessed and for which retrieval times of several hours are acceptable. It is designed for long-term data retention and for use cases such as digital preservation and regulatory compliance.
  • Data Lake Storage

A service for big data analytics and storage solution that allows to store and analyze large amounts of data in its raw format.Azure Data Lake Storage (DL) Gen2 is built on top of Azure Blob storage, and it uses the same underlying technology and infrastructure as Azure Blob storage. However, Data Lake Storage (DL) Gen2 provides additional features and functionality that are specifically designed for big data scenarios and analytics workloads.

One of the key differences between Data Lake Storage (DL) Gen2 and Blob storage is that Data Lake Storage (DL) Gen2 is organized as a hierarchical file system, similar to the Hadoop Distributed File System (HDFS), whereas Blob storage is organized as a flat container of blobs. This hierarchical file system structure in Data Lake Storage (DL) Gen2 allows for easy organization, management and access of large amounts of data and metadata.

Another key difference is that Data Lake Storage (DL) Gen2 provides built-in data governance features such as data cataloging, data lineage and data discovery, that make it easy to find, understand, and manage your data.

Additionally, Data Lake Storage (DL) Gen2 also provides enhanced security features, such as Azure Active Directory-based authentication and authorization, and data encryption at rest, which allows you to control access to your data using Azure AD identities.

In summary, Azure Data Lake Storage (DL) Gen2 is built on top of Azure Blob storage and shares many of the same features and capabilities, but it provides additional features and functionality that are specifically designed for big data scenarios and analytics workloads.