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A major benefit of cloud computing is the manageability options. There are two types of manageability for cloud computing that you’ll learn about in this series, and both are excellent benefits.

Management of the cloud

Management of the cloud speaks to managing your cloud resources. In the cloud, you can:

• Automatically scale resource deployment based on need.
• Deploy resources based on a preconfigured template, removing the need for manual configuration.
• Monitor the health of resources and automatically replace failing resources.
• Receive automatic alerts based on configured metrics, so you’re aware of performance in real time.

Management in the cloud

Management in the cloud speaks to how you’re able to manage your cloud environment and resources. You can manage these:

• Through a web portal.
• Using a command line interface.
• Using APIs.
• Using PowerShell.

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Whether you’re deploying infrastructure as a service or software as a service, cloud features support governance and compliance. Things like set templates help ensure that all your deployed resources meet corporate standards and government regulatory requirements. Plus, you can update all your deployed resources to new standards as standards change. Cloud-based auditing helps flag any resource that’s out of compliance with your corporate standards and provides mitigation strategies. Depending on your operating model, software patches and updates may also automatically be applied, which helps with both governance and security.

On the security side, you can find a cloud solution that matches your security needs. If you want maximum control of security, infrastructure as a service provides you with physical resources but lets you manage the operating systems and installed software, including patches and maintenance. If you want patches and maintenance taken care of automatically, platform as a service or software as a service deployments may be the best cloud strategies for you.

And because the cloud is intended as an over-the-internet delivery of IT resources, cloud providers are typically well suited to handle things like distributed denial of service (DDoS) attacks, making your network more robust and secure.

By establishing a good governance footprint early, you can keep your cloud footprint updated, secure, and well managed.

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Reliability and predictability are two crucial cloud benefits that help you develop solutions with confidence.

Reliability

Reliability is the ability of a system to recover from failures and continue to function. It’s also one of the pillars of the Microsoft Azure Well-Architected Framework.

The cloud, by virtue of its decentralized design, naturally supports a reliable and resilient infrastructure. With a decentralized design, the cloud enables you to have resources deployed in regions around the world. With this global scale, even if one region has a catastrophic event other regions are still up and running. You can design your applications to automatically take advantage of this increased reliability. In some cases, your cloud environment itself will automatically shift to a different region for you, with no action needed on your part. You’ll learn more about how Azure leverages global scale to provide reliability later in this series.

Predictability

Predictability in the cloud lets you move forward with confidence. Predictability can be focused on performance predictability or cost predictability. Both performance and cost predictability are heavily influenced by the Microsoft Azure Well-Architected Framework. Deploy a solution built around this framework and you have a solution whose cost and performance are predictable.

Performance

Performance predictability focuses on predicting the resources needed to deliver a positive experience for your customers. Autoscaling, load balancing, and high availability are just some of the cloud concepts that support performance predictability. If you suddenly need more resources, autoscaling can deploy additional resources to meet the demand, and then scale back when the demand drops. Or if the traffic is heavily focused on one area, load balancing will help redirect some of the overload to less stressed areas.

Cost

Cost predictability is focused on predicting or forecasting the cost of the cloud spend. With the cloud, you can track your resource use in real time, monitor resources to ensure that you’re using them in the most efficient way, and apply data analytics to find patterns and trends that help better plan resource deployments. By operating in the cloud and using cloud analytics and information, you can predict future costs and adjust your resources as needed. You can even use tools like the Total Cost of Ownership (TCO) or Pricing Calculator to get an estimate of potential cloud spend.

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When building or deploying a cloud application, two of the biggest considerations are uptime (or availability) and the ability to handle demand (or scale).

High availability

When you’re deploying an application, a service, or any IT resources, it’s important the resources are available when needed. High availability focuses on ensuring maximum availability, regardless of disruptions or events that may occur.

When you’re architecting your solution, you’ll need to account for service availability guarantees. Azure is a highly available cloud environment with uptime guarantees depending on the service. These guarantees are part of the service-level agreements (SLAs).

This short video describes Azure SLAs in more detail.

Scalability

Another major benefit of cloud computing is the scalability of cloud resources. Scalability refers to the ability to adjust resources to meet demand. If you suddenly experience peak traffic and your systems are overwhelmed, the ability to scale means you can add more resources to better handle the increased demand.

The other benefit of scalability is that you aren’t overpaying for services. Because the cloud is a consumption-based model, you only pay for what you use. If demand drops off, you can reduce your resources and thereby reduce your costs.

Scaling generally comes in two varieties: vertical and horizontal. Vertical scaling is focused on increasing or decreasing the capabilities of resources. Horizontal scaling is adding or subtracting the number of resources.

Vertical scaling

With vertical scaling, if you were developing an app and you needed more processing power, you could vertically scale up to add more CPUs or RAM to the virtual machine. Conversely, if you realized you had over-specified the needs, you could vertically scale down by lowering the CPU or RAM specifications.

Horizontal scaling

With horizontal scaling, if you suddenly experienced a steep jump in demand, your deployed resources could be scaled out (either automatically or manually). For example, you could add additional virtual machines or containers, scaling out. In the same manner, if there was a significant drop in demand, deployed resources could be scaled in (either automatically or manually), scaling in.

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When comparing IT infrastructure models, there are two types of expenses to consider. Capital expenditure (CapEx) and operational expenditure (OpEx).

CapEx is typically a one-time, up-front expenditure to purchase or secure tangible resources. A new building, repaving the parking lot, building a datacenter, or buying a company vehicle are examples of CapEx.

In contrast, OpEx is spending money on services or products over time. Renting a convention center, leasing a company vehicle, or signing up for cloud services are all examples of OpEx.

Cloud computing falls under OpEx because cloud computing operates on a consumption-based model. With cloud computing, you don’t pay for the physical infrastructure, the electricity, the security, or anything else associated with maintaining a datacenter. Instead, you pay for the IT resources you use. If you don’t use any IT resources this month, you don’t pay for any IT resources.

This consumption-based model has many benefits, including:

• No upfront costs.
• No need to purchase and manage costly infrastructure that users might not use to its fullest potential.
• The ability to pay for more resources when they’re needed.
• The ability to stop paying for resources that are no longer needed.

With a traditional datacenter, you try to estimate the future resource needs. If you overestimate, you spend more on your datacenter than you need to and potentially waste money. If you underestimate, your datacenter will quickly reach capacity and your applications and services may suffer from decreased performance. Fixing an under-provisioned datacenter can take a long time. You may need to order, receive, and install more hardware. You’ll also need to add power, cooling, and networking for the extra hardware.

In a cloud-based model, you don’t have to worry about getting the resource needs just right. If you find that you need more virtual machines, you add more. If the demand drops and you don’t need as many virtual machines, you remove machines as needed. Either way, you’re only paying for the virtual machines that you use, not the “extra capacity” that the cloud provider has on hand.

Compare cloud pricing models

Cloud computing is the delivery of computing services over the internet by using a pay-as-you-go pricing model. You typically pay only for the cloud services you use, which helps you:

• Plan and manage your operating costs.
• Run your infrastructure more efficiently.
• Scale as your business needs change.

To put it another way, cloud computing is a way to rent compute power and storage from someone else’s datacenter. You can treat cloud resources like you would resources in your own datacenter. However, unlike in your own datacenter, when you’re done using cloud resources, you give them back. You’re billed only for what you use.

Instead of maintaining CPUs and storage in your datacenter, you rent them for the time that you need them. The cloud provider takes care of maintaining the underlying infrastructure for you. The cloud enables you to quickly solve your toughest business challenges and bring cutting-edge solutions to your users.

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What are cloud models? The cloud models define the deployment type of cloud resources. The three main cloud models are: private, public, and hybrid.

Private cloud

Let’s start with a private cloud. A private cloud is, in some ways, the natural evolution from a corporate datacenter. It’s a cloud (delivering IT services over the internet) that’s used by a single entity. Private cloud provides much greater control for the company and its IT department. However, it also comes with greater cost and fewer of the benefits of a public cloud deployment. Finally, a private cloud may be hosted from your on site datacenter. It may also be hosted in a dedicated datacenter offsite, potentially even by a third party that has dedicated that datacenter to your company.

Public cloud

A public cloud is built, controlled, and maintained by a third-party cloud provider. With a public cloud, anyone that wants to purchase cloud services can access and use resources. The general public availability is a key difference between public and private clouds.

Hybrid cloud

A hybrid cloud is a computing environment that uses both public and private clouds in an inter-connected environment. A hybrid cloud environment can be used to allow a private cloud to surge for increased, temporary demand by deploying public cloud resources. Hybrid cloud can be used to provide an extra layer of security. For example, users can flexibly choose which services to keep in public cloud and which to deploy to their private cloud infrastructure.

The following table highlights a few key comparative aspects between the cloud models.

Multi-cloud

A fourth, and increasingly likely scenario is a multi-cloud scenario. In a multi-cloud scenario, you use multiple public cloud providers. Maybe you use different features from different cloud providers. Or maybe you started your cloud journey with one provider and are in the process of migrating to a different provider. Regardless, in a multi-cloud environment you deal with two (or more) public cloud providers and manage resources and security in both environments.

Azure Arc

Azure Arc is a set of technologies that helps manage your cloud environment. Azure Arc can help manage your cloud environment whether it’s a public cloud solely on Azure, a private cloud in your datacenter, a hybrid configuration, or even a multi-cloud environment running on multiple cloud providers at once.

Azure VMware Solution

What if you’re already established with VMware in a private cloud environment but want to migrate to a public or hybrid cloud? Azure VMware Solution lets you run your VMware workloads in Azure with seamless integration and scalability.

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You may have heard of the shared responsibility model, but you may not understand what it means or how it impacts cloud computing.

Start with a traditional corporate datacenter. The company is responsible for maintaining the physical space, ensuring security, and maintaining or replacing the servers if anything happens. The IT department is responsible for maintaining all the infrastructure and software needed to keep the datacenter up and running. They’re also likely to be responsible for keeping all systems patched and on the correct version.

With the shared responsibility model, these responsibilities get shared between the cloud provider and the consumer. Physical security, power, cooling, and network connectivity are the responsibility of the cloud provider. The consumer isn’t collocated with the datacenter, so it wouldn’t make sense for the consumer to have any of those responsibilities.

At the same time, the consumer is responsible for the data and information stored in the cloud. (You wouldn’t want the cloud provider to be able to read your information.) The consumer is also responsible for access security, meaning you only give access to those who need it.

Then, for some things, the responsibility depends on the situation. If you’re using a cloud SQL database, the cloud provider would be responsible for maintaining the actual database. However, you’re still responsible for the data that gets ingested into the database. If you deployed a virtual machine and installed an SQL database on it, you’d be responsible for database patches and updates, as well as maintaining the data and information stored in the database.

With an on-premises datacenter, you’re responsible for everything. With cloud computing, those responsibilities shift. The shared responsibility model is heavily tied into the cloud service types (covered later in this learning path): infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). IaaS places the most responsibility on the consumer, with the cloud provider being responsible for the basics of physical security, power, and connectivity. On the other end of the spectrum, SaaS places most of the responsibility with the cloud provider. PaaS, being a middle ground between IaaS and SaaS, rests somewhere in the middle and evenly distributes responsibility between the cloud provider and the consumer.

The following diagram highlights how the Shared Responsibility Model informs who is responsible for what, depending on the cloud service type.

When using a cloud provider, you’ll always be responsible for:

• The information and data stored in the cloud
• Devices that are allowed to connect to your cloud (cell phones, computers, and so on)
• The accounts and identities of the people, services, and devices within your organization

The cloud provider is always responsible for:

• The physical datacenter
• The physical network
• The physical hosts

Your service model will determine responsibility for things like:

• Operating systems
• Network controls
• Applications
• Identity and infrastructure

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Microsoft Azure is a cloud computing platform with an ever-expanding set of services to help you build solutions to meet your business goals. Azure services support everything from simple to complex. Azure has simple web services for hosting your business presence in the cloud. Azure also supports running fully virtualized computers managing your custom software solutions. Azure provides a wealth of cloud-based services like remote storage, database hosting, and centralized account management. Azure also offers new capabilities like artificial intelligence (AI) and Internet of Things (IoT) focused services.

In this series, you’ll cover cloud computing basics, be introduced to some of the core services provided by Microsoft Azure, and will learn more about the governance and compliance services that you can use.

What is Azure Fundamentals?
Azure Fundamentals is a series of three learning paths that familiarize you with Azure and its many services and features.

Whether you’re interested in compute, networking, or storage services; learning about cloud security best practices; or exploring governance and management options, think of Azure Fundamentals as your curated guide to Azure.

Azure Fundamentals includes interactive exercises that give you hands-on experience with Azure. Many exercises provide a temporary Azure portal environment called the sandbox, which allows you to practice creating cloud resources for free at your own pace.

Technical IT experience isn’t required; however, having general IT knowledge will help you get the most from your learning experience.

Why should I take Azure Fundamentals?
If you’re just beginning to work with the cloud, or if you already have cloud experience, Azure Fundamentals provides you with everything you need to get started.

No matter your goals, Azure Fundamentals has something for you. You should take this course if you:

Have general interest in Azure or in cloud computing
Want to earn official certification from Microsoft (AZ-900)
The Azure Fundamentals learning path series can help you prepare for Exam AZ-900: Microsoft Azure Fundamentals. This exam includes three knowledge domain areas:

AZ-900 Domain Area Weight
Describe cloud concepts 25-30%
Describe Azure architecture and services 35-40%
Describe Azure management and governance 30-35%
Each domain area maps to a learning path in Azure Fundamentals. The percentages shown indicate the relative weight of each area on the exam. The higher the percentage, the more questions that part of the exam will contain. Be sure to read the exam page for specifics about what skills are covered in each area.

This training helps you develop a broad understanding of Azure.

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Azure Resource Manager (ARM) is the deployment and management service for Azure. It provides a management layer that enables you to create, update, and delete resources in your Azure account. Anytime you do anything with your Azure resources, ARM is involved.

When a user sends a request from any of the Azure tools, APIs, or SDKs, ARM receives the request. ARM authenticates and authorizes the request. Then, ARM sends the request to the Azure service, which takes the requested action. You see consistent results and capabilities in all the different tools because all requests are handled through the same API.

Azure Resource Manager benefits

With Azure Resource Manager, you can:

• Manage your infrastructure through declarative templates rather than scripts. A Resource Manager template is a JSON file that defines what you want to deploy to Azure.
• Deploy, manage, and monitor all the resources for your solution as a group, rather than handling these resources individually.
• Re-deploy your solution throughout the development life-cycle and have confidence your resources are deployed in a consistent state.
• Define the dependencies between resources, so they’re deployed in the correct order.
• Apply access control to all services because RBAC is natively integrated into the management platform.
• Apply tags to resources to logically organize all the resources in your subscription.
• Clarify your organization’s billing by viewing costs for a group of resources that share the same tag.

The following video provides an overview of Azure Resource Manager.

Infrastructure as code

Infrastructure as code is a concept where you manage your infrastructure as lines of code. At an introductory level, it’s things like using Azure Cloud Shell, Azure PowerShell, or the Azure CLI to manage and configure your resources. As you get more comfortable in the cloud, you can use the infrastructure as code concept to manage entire deployments using repeatable templates and configurations. ARM templates and Bicep are two examples of using infrastructure as code with the Azure Resource Manager to maintain your environment.

ARM templates

By using ARM templates, you can describe the resources you want to use in a declarative JSON format. With an ARM template, the deployment code is verified before any code is run. This ensures that the resources will be created and connected correctly. The template then orchestrates the creation of those resources in parallel. That is, if you need 50 instances of the same resource, all 50 instances are created at the same time.

Ultimately, the developer, DevOps professional, or IT professional needs only to define the desired state and configuration of each resource in the ARM template, and the template does the rest. Templates can even execute PowerShell and Bash scripts before or after the resource has been set up.

Benefits of using ARM templates

ARM templates provide many benefits when planning for deploying Azure resources. Some of those benefits include:

• Declarative syntax: ARM templates allow you to create and deploy an entire Azure infrastructure declaratively. Declarative syntax means you declare what you want to deploy but don’t need to write the actual programming commands and sequence to deploy the resources.
• Repeatable results: Repeatedly deploy your infrastructure throughout the development lifecycle and have confidence your resources are deployed in a consistent manner. You can use the same ARM template to deploy multiple dev/test environments, knowing that all the environments are the same.
• Orchestration: You don’t have to worry about the complexities of ordering operations. Azure Resource Manager orchestrates the deployment of interdependent resources, so they’re created in the correct order. When possible, Azure Resource Manager deploys resources in parallel, so your deployments finish faster than serial deployments. You deploy the template through one command, rather than through multiple imperative commands.
• Modular files: You can break your templates into smaller, reusable components and link them together at deployment time. You can also nest one template inside another template. For example, you could create a template for a VM stack, and then nest that template inside of templates that deploy entire environments, and that VM stack will consistently be deployed in each of the environment templates.
• Extensibility: With deployment scripts, you can add PowerShell or Bash scripts to your templates. The deployment scripts extend your ability to set up resources during deployment. A script can be included in the template or stored in an external source and referenced in the template. Deployment scripts give you the ability to complete your end-to-end environment setup in a single ARM template.

Bicep

Bicep is a language that uses declarative syntax to deploy Azure resources. A Bicep file defines the infrastructure and configuration. Then, ARM deploys that environment based on your Bicep file. While similar to an ARM template, which is written in JSON, Bicep files tend to use a simpler, more concise style.

Some benefits of Bicep are:

• Support for all resource types and API versions: Bicep immediately supports all preview and GA versions for Azure services. As soon as a resource provider introduces new resource types and API versions, you can use them in your Bicep file. You don’t have to wait for tools to be updated before using the new services.
• Simple syntax: When compared to the equivalent JSON template, Bicep files are more concise and easier to read. Bicep requires no previous knowledge of programming languages. Bicep syntax is declarative and specifies which resources and resource properties you want to deploy.
• Repeatable results: Repeatedly deploy your infrastructure throughout the development lifecycle and have confidence your resources are deployed in a consistent manner. Bicep files are idempotent, which means you can deploy the same file many times and get the same resource types in the same state. You can develop one file that represents the desired state, rather than developing lots of separate files to represent updates.
• Orchestration: You don’t have to worry about the complexities of ordering operations. Resource Manager orchestrates the deployment of interdependent resources so they’re created in the correct order. When possible, Resource Manager deploys resources in parallel so your deployments finish faster than serial deployments. You deploy the file through one command, rather than through multiple imperative commands.
• Modularity: You can break your Bicep code into manageable parts by using modules. The module deploys a set of related resources. Modules enable you to reuse code and simplify development. Add the module to a Bicep file anytime you need to deploy those resources.

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Managing hybrid and multi-cloud environments can rapidly get complicated. Azure provides a host of tools to provision, configure, and monitor Azure resources. What about the on-premises resources in a hybrid configuration or the cloud resources in a multi-cloud configuration?

In utilizing Azure Resource Manager (ARM), Arc lets you extend your Azure compliance and monitoring to your hybrid and multi-cloud configurations. Azure Arc simplifies governance and management by delivering a consistent multi-cloud and on-premises management platform.

Azure Arc provides a centralized, unified way to:

• Manage your entire environment together by projecting your existing non-Azure resources into ARM.
• Manage multi-cloud and hybrid virtual machines, Kubernetes clusters, and databases as if they are running in Azure.
• Use familiar Azure services and management capabilities, regardless of where they live.
• Continue using traditional ITOps while introducing DevOps practices to support new cloud and native patterns in your environment.
• Configure custom locations as an abstraction layer on top of Azure Arc-enabled Kubernetes clusters and cluster extensions.

What can Azure Arc do outside of Azure?

Currently, Azure Arc allows you to manage the following resource types hosted outside of Azure:

• Servers
• Kubernetes clusters
• Azure data services
• SQL Server
• Virtual machines (preview)

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