Overview of storage accounts

A storage account contains all of your Azure Storage data objects: blobs, files, queues, and tables. The storage account provides a unique namespace for your Azure Storage data that's accessible from anywhere in the world over HTTP or HTTPS. Data in your storage account is durable, highly available, secure, and massively scalable.

Learn how to create a storage account.

Types of storage accounts

Azure Storage offers several types of storage accounts. Each type supports different features and has its own pricing model.

The following table describes the types of storage accounts that we recommend for most scenarios. All of these types use the Azure Resource Manager deployment model.

¹ Data Lake Storage is a set of capabilities dedicated to big data analytics, built on Blob Storage. For more information, see Introduction to Data Lake Storage and Create a storage account to use with Data Lake Storage.

² ZRS, GZRS, and RA-GZRS are available only for standard general-purpose v2, premium block blobs, premium file shares, and premium page blobs accounts in certain regions. For more information, see Azure Storage redundancy.

³ Premium performance storage accounts use solid-state drives (SSDs) for low latency and high throughput.

Legacy storage accounts are also supported. For more information, see Legacy storage account types.

The service-level agreement (SLA) for Azure storage accounts is available on the SLA page for online services.

Storage account name

When you name your storage account, keep these rules in mind:

• Storage account names must be between 3 and 24 characters in length. They can contain only numbers and lowercase letters.
• Your storage account name must be unique within Azure. No two storage accounts can have the same name.

Storage account workloads

Azure Storage customers use various workloads to store data, access data, and derive insights to meet their business objectives. Each workload uses specific protocols for data operations based on its requirements and industry standards.

The following sections offer a high-level categorization of different primary workloads for your storage accounts.

Cloud native

Cloud-native apps are large-scale distributed applications that are built on a foundation of cloud paradigms and technologies. This modern approach focuses on cloud scale and performance capabilities.

Cloud-native apps can be based on microservices architecture, use managed services, and employ continuous delivery to achieve reliability. These applications are typically categorized into web apps, mobile apps, containerized apps, and serverless or function as a service (FaaS) types.

Analytics

Analytics is the systematic, computational analysis of data and statistics. This science involves discovering, interpreting, and communicating meaningful insights and patterns found in data.

The discovered data can be manipulated and interpreted in ways that can help a business further objectives and meet goals. These workloads typically consist of a pipeline that ingests large volumes of data. The data are prepped, curated, and aggregated for downstream consumption via Power BI, data warehouses, or applications.

Analytics workloads can require high ingress and egress, which drives higher throughput on your storage account. Analytics types include real-time analytics, advanced analytics, predictive analytics, emotional analytics, sentiment analysis, and more. For analytics, we guarantee that our customers have high throughput access to large amounts of data in distributed storage architectures.

High-performance computing

High-performance computing (HPC) is the aggregation of multiple computing nodes that act on the same set of tasks. They can achieve more than a single node can achieve in a specified time frame.

With HPC, powerful processors work in parallel to process massive, multidimensional datasets. HPC workloads require high-throughput read and write operations for workloads like gene sequencing and reservoir simulation. HPC workloads also include applications with high input/output operations per second (IOPS) and low-latency access to a large number of small files. They use these files for workloads like seismic interpretation, autonomous driving, and risk workloads.

The primary goal is to solve complex problems at ultra-fast speeds. Other examples of high-performance computing include fluid dynamics and other physical simulation or analysis that require scalability and high throughput. We help enable our customers to perform HPC by ensuring that large amounts of data are accessible with a large amount of concurrency.

Backup and archive

Business continuity and disaster recovery (BCDR) is a business's ability to remain operational after an adverse event. In terms of storage, this objective equates to maintaining business continuity across outages to storage systems.

With the introduction of backup-as-a-service offerings throughout the industry, BCDR data is increasingly migrating to the cloud. The backup and archive workload functions as the last line of defense against ransomware and malicious attacks. When there's a service interruption or accidental deletion or corruption of data, recovering the data in an efficient and orchestrated manner is the highest priority. Azure Storage makes it possible to store and retrieve large amounts of data in the most cost-effective fashion.

Machine learning and AI

AI is technology that simulates human intelligence and problem-solving capabilities in machines. Machine learning (ML) is a subdiscipline of AI that uses algorithms to create models that enable machines to perform tasks. AI and ML workloads are the newest on Azure and are growing at a rapid pace.

You can apply this type of workload across every industry to improve metrics and meet performance goals. These types of technologies can lead to discoveries of life-saving drugs and practices in the field of medicine and health, while also providing health assessments.

Other everyday uses of ML and AI include fraud detection, image recognition, and flagging misinformation. These workloads typically need:

• Highly specialized compute (a lot of GPUs).
• High throughput and IOPS.
• Low-latency access to storage.
• POSIX file system access.

Azure Storage supports these types of workloads by storing checkpoints and providing storage for large-scale datasets and models. These datasets and models read and write at a pace to keep GPUs utilized.

Recommended workload configurations

The following table illustrates Microsoft's suggested storage account configurations for each workload. When you change configuration options (associated with each workload), there are cost implications.

View pricing at Block blob pricing.

¹ ZRS is a good default for analytics workloads because it offers more redundancy compared to LRS. It protects against zonal failures while remaining fully compatible with analytics frameworks. Customers that require more redundancy for an analytics workload can also use geo-redundant storage (GRS or RA-GRS).

² The hierarchical namespace is a core capability of Data Lake Storage. It enhances data organization and access efficiency for large amounts of data, making it ideal for analytics workloads.

³ The cool access tier offers a cost-effective solution for storing infrequently accessed data (typical for a backup and archive workload). Customers can also consider the cold access tier after evaluating costs.

Storage account endpoints

A storage account provides a unique namespace in Azure for your data. Every object that you store in Azure Storage has a URL address that includes your unique account name. The combination of the account name and the service endpoint forms the endpoints for your storage account.

You can configure your storage account to use a custom domain for the Blob Storage endpoint. For more information, see Map a custom domain to an Azure Blob Storage endpoint.

Standard endpoints

A standard service endpoint in Azure Storage includes:

• The protocol. (We recommend HTTPS.)
• The storage account name as the subdomain.
• A fixed domain that includes the name of the service.

The following table lists the format for the standard endpoints for each of the Azure Storage services.

You can easily construct the URL for an object in Azure Storage. Append the object's location in the storage account to the endpoint. For example, the URL for a blob is similar to:

https://<mystorageaccount>.blob.core.chinacloudapi.cn/<mycontainer>/<myblob>

Migrating a storage account

The following table summarizes and points to guidance on how to move, upgrade, or migrate a storage account:

Transferring data into a storage account

Azure provides services and utilities to import your data from on-premises storage devices or third-party cloud storage providers. Which solution you use depends on the quantity of data you're transferring. For more information, see Azure Storage migration overview.

Storage account encryption

All data in your storage account is automatically encrypted on the service side. For more information about encryption and key management, see Azure Storage encryption for data at rest.

Storage account billing

Azure Storage bills based on your storage account usage. All objects in a storage account are billed together as a group. Storage costs are calculated according to the following factors:

• Region: The geographical region in which your account is based.
• Account type: The type of storage account you're using.
• Access tier: The data usage pattern that you specified for your general-purpose v2 or Blob Storage account.
• Capacity: How much of your storage account allotment you're using to store data.
• Redundancy: How many copies of your data are maintained at one time, and in what locations.
• Transactions: All read and write operations to Azure Storage.
• Data egress: Any data transferred out of an Azure region. When an application that isn't running in the same region accesses the data in your storage account, you're charged for data egress. For information about using resource groups to group your data and services in the same region to limit egress charges, see What is an Azure resource group?

The Azure Storage pricing page provides detailed pricing information based on account type, storage capacity, replication, and transactions. The Data Transfers pricing details provides detailed pricing information for data egress. You can use the Azure Storage pricing calculator to help estimate your costs.

Retired storage account types

The following account types are retired or scheduled for retirement. They aren't recommended for new deployments. If you still have these accounts, plan to migrate to a supported account type.

¹ Classic denotes the Azure Service Management deployment model.

Scalability targets for standard storage accounts

The following table describes default limits for Azure general-purpose v2 (GPv2), general-purpose v1 (GPv1), and Blob Storage accounts.

A few entries in the table also apply to disk access and are explicitly labeled. Disk access is a resource that is exclusively used for importing or exporting managed disks through private links.

Customers should use a GPv2 storage account, because GPv1 is being retired. You can easily upgrade a GPv1 or Blob Storage account to a GPv2 account with no downtime and no need to copy data. For more information, see Upgrade to a GPv2 storage account.

The ingress limit refers to all data sent to a storage account or disk access. The egress limit refers to all data received from a storage account or disk access.

¹ Azure Storage standard accounts support higher capacity limits and higher limits for ingress and egress by request. To request an increase in account limits, contact Azure Support.

Related content

• Create a storage account
• Upgrade to a general-purpose v2 storage account
• Recover a deleted storage account