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To create and use Azure services, you need an Azure subscription. When you’re working with your own applications and business needs, you need to create an Azure account, and a subscription will be created for you. After you’ve created an Azure account, you’re free to create additional subscriptions. For example, your company might use a single Azure account for your business and separate subscriptions for development, marketing, and sales departments. After you’ve created an Azure subscription, you can start creating Azure resources within each subscription.

If you’re new to Azure, you can sign up for a free account on the Azure website to start exploring at no cost to you. When you’re ready, you can choose to upgrade your free account. You can also create a new subscription that enables you to start paying for Azure services you need beyond the limits of a free account.

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Azure is a continually expanding set of cloud services that help you meet current and future business challenges. Azure gives you the freedom to build, manage, and deploy applications on a massive global network using your favorite tools and frameworks.

What does Azure offer?

Limitless innovation. Build intelligent apps and solutions with advanced technology, tools, and services to take your business to the next level. Seamlessly unify your technology to simplify platform management and to deliver innovations efficiently and securely on a trusted cloud.

• Bring ideas to life: Build on a trusted platform to advance your organization with industry-leading AI and cloud services.
• Seamlessly unify: Efficiently manage all your infrastructure, data, analytics, and AI solutions across an integrated platform.
• Innovate on trust: Rely on trusted technology from a partner who’s dedicated to security and responsibility.

What can I do with Azure?

Azure provides more than 100 services that enable you to do everything from running your existing applications on virtual machines to exploring new software paradigms, such as intelligent bots and mixed reality.

Many teams start exploring the cloud by moving their existing applications to virtual machines (VMs) that run in Azure. Migrating your existing apps to VMs is a good start, but the cloud is much more than a different place to run your VMs.

For example, Azure provides artificial intelligence (AI) and machine-learning (ML) services that can naturally communicate with your users through vision, hearing, and speech. It also provides storage solutions that dynamically grow to accommodate massive amounts of data. Azure services enable solutions that aren’t feasible without the power of the cloud.

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As your cloud usage grows, it’s increasingly important to stay organized. A good organization strategy helps you understand your cloud usage and can help you manage costs.

One way to organize related resources is to place them in their own subscriptions. You can also use resource groups to manage related resources. Resource tags are another way to organize resources. Tags provide extra information, or metadata, about your resources. This metadata is useful for:

• Resource management Tags enable you to locate and act on resources that are associated with specific workloads, environments, business units, and owners.
• Cost management and optimization Tags enable you to group resources so that you can report on costs, allocate internal cost centers, track budgets, and forecast estimated cost.
• Operations management Tags enable you to group resources according to how critical their availability is to your business. This grouping helps you formulate service-level agreements (SLAs). An SLA is an uptime or performance guarantee between you and your users.
• Security Tags enable you to classify data by its security level, such as public or confidential.
• Governance and regulatory compliance Tags enable you to identify resources that align with governance or regulatory compliance requirements, such as ISO 27001. Tags can also be part of your standards enforcement efforts. For example, you might require that all resources be tagged with an owner or department name.
• Workload optimization and automation Tags can help you visualize all of the resources that participate in complex deployments. For example, you might tag a resource with its associated workload or application name and use software such as Azure DevOps to perform automated tasks on those resources.

How do I manage resource tags?

You can add, modify, or delete resource tags through Windows PowerShell, the Azure CLI, Azure Resource Manager templates, the REST API, or the Azure portal.

You can use Azure Policy to enforce tagging rules and conventions. For example, you can require that certain tags be added to new resources as they’re provisioned. You can also define rules that reapply tags that have been removed. Resources don’t inherit tags from subscriptions and resource groups, meaning that you can apply tags at one level and not have those tags automatically show up at a different level, allowing you to create custom tagging schemas that change depending on the level (resource, resource group, subscription, and so on).

An example tagging structure

A resource tag consists of a name and a value. You can assign one or more tags to each Azure resource.

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Microsoft Azure is a global cloud provider, meaning you can provision resources anywhere in the world. You can provision resources rapidly to meet a sudden demand, or to test out a new feature, or on accident. If you accidentally provision new resources, you may not be aware of them until it’s time for your invoice. Cost Management is a service that helps avoid those situations.

What is Cost Management?

Cost Management provides the ability to quickly check Azure resource costs, create alerts based on resource spend, and create budgets that can be used to automate management of resources.

Cost analysis is a subset of Cost Management that provides a quick visual for your Azure costs. Using cost analysis, you can quickly view the total cost in a variety of different ways, including by billing cycle, region, resource, and so on.

You use cost analysis to explore and analyze your organizational costs. You can view aggregated costs by organization to understand where costs are accrued and to identify spending trends. And you can see accumulated costs over time to estimate monthly, quarterly, or even yearly cost trends against a budget.

Cost alerts

Cost alerts provide a single location to quickly check on all of the different alert types that may show up in the Cost Management service. The three types of alerts that may show up are:

• Budget alerts
• Credit alerts
• Department spending quota alerts.

Budget alerts

Budget alerts notify you when spending, based on usage or cost, reaches or exceeds the amount defined in the alert condition of the budget. Cost Management budgets are created using the Azure portal or the Azure Consumption API.

In the Azure portal, budgets are defined by cost. Budgets are defined by cost or by consumption usage when using the Azure Consumption API. Budget alerts support both cost-based and usage-based budgets. Budget alerts are generated automatically whenever the budget alert conditions are met. You can view all cost alerts in the Azure portal. Whenever an alert is generated, it appears in cost alerts. An alert email is also sent to the people in the alert recipients list of the budget.

Credit alerts

Credit alerts notify you when your Azure credit monetary commitments are consumed. Monetary commitments are for organizations with Enterprise Agreements (EAs). Credit alerts are generated automatically at 90% and at 100% of your Azure credit balance. Whenever an alert is generated, it’s reflected in cost alerts, and in the email sent to the account owners.

Department spending quota alerts

Department spending quota alerts notify you when department spending reaches a fixed threshold of the quota. Spending quotas are configured in the EA portal. Whenever a threshold is met, it generates an email to department owners, and appears in cost alerts. For example, 50 percent or 75 percent of the quota.

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The pricing calculator is a calculator that helps you understand potential Azure expenses. The pricing calculator is accessible from the internet and allows you to build out a configuration. The Total Cost of Ownership (TCO) calculator has been retired.

Pricing calculator

The pricing calculator is designed to give you an estimated cost for provisioning resources in Azure. You can get an estimate for individual resources, build out a solution, or use an example scenario to see an estimate of the Azure spend. The pricing calculator’s focus is on the cost of provisioned resources in Azure.

With the pricing calculator, you can estimate the cost of any provisioned resources, including compute, storage, and associated network costs. You can even account for different storage options like storage type, access tier, and redundancy.

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Azure shifts development costs from the capital expense (CapEx) of building out and maintaining infrastructure and facilities to an operational expense (OpEx) of renting infrastructure as you need it, whether it’s compute, storage, networking, and so on.

That OpEx cost can be impacted by many factors. Some of the impacting factors are:

• Resource type
• Consumption
• Maintenance
• Geography
• Subscription type
• Azure Marketplace

Resource type

A number of factors influence the cost of Azure resources. The type of resources, the settings for the resource, and the Azure region will all have an impact on how much a resource costs. When you provision an Azure resource, Azure creates metered instances for that resource. The meters track the resources’ usage and generate a usage record that is used to calculate your bill.

Examples

With a storage account, you specify a type such as blob, a performance tier, an access tier, redundancy settings, and a region. Creating the same storage account in different regions may show different costs and changing any of the settings may also impact the price.

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It’s important for software engineers to consider the impact of their software on users, and society in general; including considerations for its responsible use. When the application is imbued with artificial intelligence, these considerations are particularly important due to the nature of how AI systems work and inform decisions; often based on probabilistic models, which are in turn dependent on the data with which they were trained.

The human-like nature of AI solutions is a significant benefit in making applications user-friendly, but it can also lead users to place a great deal of trust in the application’s ability to make correct decisions. The potential for harm to individuals or groups through incorrect predictions or misuse of AI capabilities is a major concern, and software engineers building AI-enabled solutions should apply due consideration to mitigate risks and ensure fairness, reliability, and adequate protection from harm or discrimination.

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While you can perform many of the tasks needed to develop an AI solution directly in the Azure AI Foundry portal, developers also need to write, test, and deploy code.

Development tools and environments

There are many development tools and environments available, and developers should choose one that supports the languages, SDKs, and APIs they need to work with and with which they’re most comfortable. For example, a developer who focuses strongly on building applications for Windows using the .NET Framework might prefer to work in an integrated development environment (IDE) like Microsoft Visual Studio. Conversely, a web application developer who works with a wide range of open-source languages and libraries might prefer to use a code editor like Visual Studio Code (VS Code). Both of these products are suitable for developing AI applications on Azure.

The Azure AI Foundry for Visual Studio Code extension

When developing Azure AI Foundry based generative AI applications in Visual Studio Code, you can use the Azure AI Foundry for Visual Studio Code extension to simplify key tasks in the workflow, including:

• Creating a project.
• Selecting and deploying a model.
• Testing a model in the playground.
• Creating an agent.

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Azure AI Foundry is a platform for AI development on Microsoft Azure. While you can provision individual Azure AI services resources and build applications that consume them without it, the project organization, resource management, and AI development capabilities of Azure AI Foundry makes it the recommended way to build all but the most simple solutions.

Azure AI Foundry provides the Azure AI Foundry portal, a web-based visual interface for working with AI projects. It also provides the Azure AI Foundry SDK, which you can use to build AI solutions programmatically.

Azure AI Foundry projects

In Azure AI Foundry, you manage the resource connections, data, code, and other elements of the AI solution in projects. There are two kinds of project:

Foundry projects

Foundry projects are associated with an Azure AI Foundry resource in an Azure subscription. Foundry projects provide support for Azure AI Foundry models (including OpenAI models), Azure AI Foundry Agent Service, Azure AI services, and tools for evaluation and responsible AI development.

An Azure AI Foundry resource supports the most common AI development tasks to develop generative AI chat apps and agents. In most cases, using a Foundry project provides the right level of resource centralization and capabilities with a minimal amount of administrative resource management. You can use Azure AI Foundry portal to work in projects that are based in Azure AI Foundry resources, making it easy to add connected resources and manage model and agent deployments.

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Microsoft Azure provides a wide range of cloud services that you can use to develop, deploy, and manage an AI solution. The most obvious starting point for considering AI development on Azure is Azure AI services; a set of out-of-the-box prebuilt APIs and models that you can integrate into your applications. The following table lists some commonly used Azure AI services (for a full list of all available Azure AI services, see Available Azure AI services).

Considerations for Azure AI services resources

To use Azure AI services, you create one or more Azure AI resources in an Azure subscription and implement code in client applications to consume them. In some cases, AI services include web-based visual interfaces that you can use to configure and test your resources – for example to train a custom image classification model using the Custom Vision service you can use the visual interface to upload training images, manage training jobs, and deploy the resulting model.

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