Azure Basics Flashcards
What is cloud computing?
It’s the delivery of computing services over the internet, which is otherwise known as the cloud. These services include servers, storage, databases, networking, software, analytics, and intelligence.
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:
- Lower 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. When you’re done using them, you give them back. You’re billed only for what you use.
List of commonly used categories of Azure Services
- Compute
- Networking
- Storage
- Mobile
- Databases
- Web
- Internet of Things (IoT)
- Big data
- AI
- DevOps
List of common Azure Compute Services
Compute services are often one of the primary reasons why companies move to the Azure platform. Azure provides a range of options for hosting applications and services. Here are some examples of compute services in Azure:
Azure Virtual Machines: Windows or Linux virtual machines (VMs) hosted in Azure.
Azure Virtual Machine Scale Sets: Scaling for Windows or Linux VMs hosted in Azure.
Azure Kubernetes Service: Cluster management for VMs that run containerized services.
Azure Service Fabric: Distributed systems platform that runs in Azure or on-premises.
Azure Batch: Managed service for parallel and high-performance computing applications.
Azure Container Instances: Containerized apps run on Azure without provisioning servers or VMs.
Azure Functions: An event-driven, serverless compute service.
List of common Azure Networking Services
Linking compute resources and providing access to applications is the key function of Azure networking. Networking functionality in Azure includes a range of options to connect the outside world to services and features in the global Azure datacenters.
Here are some examples of networking services in Azure:
Azure Virtual Network
Connects VMs to incoming virtual private network (VPN) connections.
Azure Load Balancer: Balances inbound and outbound connections to applications or service endpoints.
Azure Application Gateway: Optimizes app server farm delivery while increasing application security.
Azure VPN Gateway: Accesses Azure Virtual Networks through high-performance VPN gateways.
Azure DNS: Provides ultra-fast DNS responses and ultra-high domain availability.
Azure Content Delivery Network: Delivers high-bandwidth content to customers globally.
Azure DDoS Protection: Protects Azure-hosted applications from distributed denial of service (DDOS) attacks.
Azure Traffic Manager: Distributes network traffic across Azure regions worldwide.
Azure ExpressRoute: Connects to Azure over high-bandwidth dedicated secure connections.
Azure Network Watcher: Monitors and diagnoses network issues by using scenario-based analysis.
Azure Firewall: Implements high-security, high-availability firewall with unlimited scalability.
Azure Virtual WAN: Creates a unified wide area network (WAN) that connects local and remote sites.
List of Azure Storage Services
Azure provides four main types of storage services:
Azure Blob storage: Storage service for very large objects, such as video files or bitmaps.
Azure File storage: File shares that can be accessed and managed like a file server.
Azure Queue storage: A data store for queuing and reliably delivering messages between applications.
Azure Table storage: Table storage is a service that stores non-relational structured data (also known as structured NoSQL data) in the cloud, providing a key/attribute store with a schema-less design.
These services all share several common characteristics:
- Durable and highly available with redundancy and replication.
- Secure through automatic encryption and role-based access control.
-Scalable with virtually unlimited storage.
- Managed, handling maintenance and any critical problems for you.
- Accessible from anywhere in the world over HTTP or HTTPS.
Description of Azure Mobile Services
With Azure, developers can create mobile back-end services for iOS, Android, and Windows apps quickly and easily. Features that used to take time and increase project risks, such as adding corporate sign-in and then connecting to on-premises resources such as SAP, Oracle, SQL Server, and SharePoint, are now simple to include.
Other features of this service include:
- Offline data synchronization.
- Connectivity to on-premises data.
- Broadcasting push notifications.
- Autoscaling to match business needs.
List of Azure Database Services
Azure provides multiple database services to store a wide variety of data types and volumes. And with global connectivity, this data is available to users instantly.
Azure Cosmos DB: Globally distributed database that supports NoSQL options.
Azure SQL Database: Fully managed relational database with auto-scale, integral intelligence, and robust security.
Azure Database for MySQL: Fully managed and scalable MySQL relational database with high availability and security.
Azure Database for PostgreSQL: Fully managed and scalable PostgreSQL relational database with high availability and security.
SQL Server on Azure Virtual Machines: Service that hosts enterprise SQL Server apps in the cloud.
Azure Synapse Analytics: Fully managed data warehouse with integral security at every level of scale at no extra cost.
Azure Database Migration Service: Service that migrates databases to the cloud with no application code changes.
Azure Cache for Redis: Fully managed service caches frequently used and static data to reduce data and application latency.
Azure Database for MariaDB: Fully managed and scalable MariaDB relational database with high availability and security.
List of Azure Web Services
Having a great web experience is critical in today’s business world. Azure includes first-class support to build and host web apps and HTTP-based web services. The following Azure services are focused on web hosting.
Azure App Service: Quickly create powerful cloud web-based apps.
Azure Notification Hubs: Send push notifications to any platform from any back end.
Azure API Management: Publish APIs to developers, partners, and employees securely and at scale.
Azure Cognitive Search: Deploy this fully managed search as a service.
Web Apps feature of Azure App Service: Create and deploy mission-critical web apps at scale.
Azure SignalR Service: Add real-time web functionalities easily.
Description of Azure IoT Services
People are able to access more information than ever before. Personal digital assistants led to smartphones, and now there are smart watches, smart thermostats, and even smart refrigerators. Personal computers used to be the norm. Now the internet allows any item that’s online-capable to access valuable information. This ability for devices to garner and then relay information for data analysis is referred to as IoT.
Many services can assist and drive end-to-end solutions for IoT on Azure:
IoT Central: Fully managed global IoT software as a service (SaaS) solution that makes it easy to connect, monitor, and manage IoT assets at scale.
Azure IoT Hub: Messaging hub that provides secure communications between and monitoring of millions of IoT devices.
IoT Edge: Fully managed service that allows data analysis models to be pushed directly onto IoT devices, which allows them to react quickly to state changes without needing to consult cloud-based AI models.
Describe Azure Big Data Services
Data comes in all formats and sizes. When we talk about big data, we’re referring to large volumes of data. Data from weather systems, communications systems, genomic research, imaging platforms, and many other scenarios generate hundreds of gigabytes of data. This amount of data makes it hard to analyze and make decisions. It’s often so large that traditional forms of processing and analysis are no longer appropriate.
Open-source cluster technologies have been developed to deal with these large data sets. Azure supports a broad range of technologies and services to provide big data and analytic solutions.
Azure Synapse Analytics: Run analytics at a massive scale by using a cloud-based enterprise data warehouse that takes advantage of massively parallel processing to run complex queries quickly across petabytes of data.
Azure HDInsight: Process massive amounts of data with managed clusters of Hadoop clusters in the cloud.
Azure Databricks: Integrate this collaborative Apache Spark-based analytics service with other big data services in Azure.
Describe Azure AI Services
AI, in the context of cloud computing, is based around a broad range of services, the core of which is machine learning. Machine learning is a data science technique that allows computers to use existing data to forecast future behaviors, outcomes, and trends. Using machine learning, computers learn without being explicitly programmed.
Forecasts or predictions from machine learning can make apps and devices smarter. For example, when you shop online, machine learning helps recommend other products you might like based on what you’ve purchased. Or when your credit card is swiped, machine learning compares the transaction to a database of transactions and helps detect fraud. And when your robot vacuum cleaner vacuums a room, machine learning helps it decide whether the job is done.
Here are some of the most common AI and machine learning service types in Azure.
Azure Machine Learning Service: Cloud-based environment you can use to develop, train, test, deploy, manage, and track machine learning models. It can auto-generate a model and auto-tune it for you. It will let you start training on your local machine, and then scale out to the cloud.
Azure ML Studio: Collaborative visual workspace where you can build, test, and deploy machine learning solutions by using prebuilt machine learning algorithms and data-handling modules.
A closely related set of products are the cognitive services. You can use these prebuilt APIs in your applications to solve complex problems.
Vision: Use image-processing algorithms to smartly identify, caption, index, and moderate your pictures and videos.
Speech: Convert spoken audio into text, use voice for verification, or add speaker recognition to your app.
Knowledge mapping: Map complex information and data to solve tasks such as intelligent recommendations and semantic search.
Bing Search: Add Bing Search APIs to your apps and harness the ability to comb billions of webpages, images, videos, and news with a single API call.
Natural Language processing: Allow your apps to process natural language with prebuilt scripts, evaluate sentiment, and learn how to recognize what users want.
Describe Azure DevOps Services
DevOps brings together people, processes, and technology by automating software delivery to provide continuous value to your users. With Azure DevOps, you can create build and release pipelines that provide continuous integration, delivery, and deployment for your applications. You can integrate repositories and application tests, perform application monitoring, and work with build artifacts. You can also work with and backlog items for tracking, automate infrastructure deployment, and integrate a range of third-party tools and services such as Jenkins and Chef. All of these functions and many more are closely integrated with Azure to allow for consistent, repeatable deployments for your applications to provide streamlined build and release processes.
Azure DevOps: Use development collaboration tools such as high-performance pipelines, free private Git repositories, configurable Kanban boards, and extensive automated and cloud-based load testing. Formerly known as Visual Studio Team Services.
Azure DevTest Labs: Quickly create on-demand Windows and Linux environments to test or demo applications directly from deployment pipelines.
List the types of cloud models available for deployment
There are three deployment models for cloud computing: public cloud, private cloud, and hybrid cloud. Each deployment model has different aspects that you should consider as you migrate to the cloud.
Public cloud: Services are offered over the public internet and available to anyone who wants to purchase them. Cloud resources, such as servers and storage, are owned and operated by a third-party cloud service provider, and delivered over the internet.
Private cloud: A private cloud consists of computing resources used exclusively by users from one business or organization. A private cloud can be physically located at your organization’s on-site (on-premises) datacenter, or it can be hosted by a third-party service provider.
Hybrid cloud: A hybrid cloud is a computing environment that combines a public cloud and a private cloud by allowing data and applications to be shared between them.
Cloud model comparison:
Public cloud -
No capital expenditures to scale up.
Applications can be quickly provisioned and deprovisioned.
Organizations pay only for what they use.
Private cloud -
Hardware must be purchased for start-up and maintenance.
Organizations have complete control over resources and security.
Organizations are responsible for hardware maintenance and updates.
Hybrid cloud -
Provides the most flexibility.
Organizations determine where to run their applications.
Organizations control security, compliance, or legal requirements.
Capital Expenses (CapEx) vs Operational Expenses (OpEx)
There are two different types of expenses that you should consider:
Capital Expenditure (CapEx) is the up-front spending of money on physical infrastructure, and then deducting that up-front expense over time. The up-front cost from CapEx has a value that reduces over time.
Operational Expenditure (OpEx) is spending money on services or products now, and being billed for them now. You can deduct this expense in the same year you spend it. There is no up-front cost, as you pay for a service or product as you use it.
In other words, when Tailwind Traders owns its infrastructure, it buys equipment that goes onto its balance sheets as assets. Because a capital investment was made, accountants categorize this transaction as a CapEx. Over time, to account for the assets’ limited useful lifespan, assets are depreciated or amortized.
Cloud services, on the other hand, are categorized as an OpEx, because of their consumption model. There’s no asset for Tailwind Traders to amortize, and its cloud service provider (Azure) manages the costs that are associated with the purchase and lifespan of the physical equipment. As a result, OpEx has a direct impact on net profit, taxable income, and the associated expenses on the balance sheet.
To summarize, CapEx requires significant up-front financial costs, as well as ongoing maintenance and support expenditures. By contrast, OpEx is a consumption-based model, so Tailwind Traders is only responsible for the cost of the computing resources that it uses.
Types of Cloud Service Models
If you’ve been around cloud computing for a while, you’ve probably seen the PaaS, IaaS, and SaaS acronyms for the different cloud service models. These models define the different levels of shared responsibility that a cloud provider and cloud tenant are responsible for.
IaaS: Infrastructure-as-a-Service : This cloud service model is the closest to managing physical servers; a cloud provider will keep the hardware up-to-date, but operating system maintenance and network configuration is up to you as the cloud tenant. For example, Azure virtual machines are fully operational virtual compute devices running in Microsoft datacenters. An advantage of this cloud service model is rapid deployment of new compute devices. Setting up a new virtual machine is considerably faster than procuring, installing, and configuring a physical server.
PaaS: Platform-as-a-Service: This cloud service model is a managed hosting environment. The cloud provider manages the virtual machines and networking resources, and the cloud tenant deploys their applications into the managed hosting environment. For example, Azure App Services provides a managed hosting environment where developers can upload their web applications, without having to worry about the physical hardware and software requirements.
SaaS: Software-as-a-Service: In this cloud service model, the cloud provider manages all aspects of the application environment, such as virtual machines, networking resources, data storage, and applications. The cloud tenant only needs to provide their data to the application managed by the cloud provider. For example, Microsoft Office 365 provides a fully working version of Microsoft Office that runs in the cloud. All you need to do is create your content, and Office 365 takes care of everything else.
Describe the organizing structure for resources in Azure
The organizing structure for resources in Azure has four levels: management groups, subscriptions, resource groups, and resources. The following image shows the top-down hierarchy of organization for these levels.
https://s3.amazonaws.com/brainscape-prod/system/cm/402/218/583/a_image_card.?1666406027
Having seen the top-down hierarchy of organization, let’s describe each of those levels from the bottom up:
Resources: Resources are instances of services that you create, like virtual machines, storage, or SQL databases.
Resource groups: Resources are combined into resource groups, which act as a logical container into which Azure resources like web apps, databases, and storage accounts are deployed and managed.
Subscriptions: A subscription groups together user accounts and the resources that have been created by those user accounts. For each subscription, there are limits or quotas on the amount of resources that you can create and use. Organizations can use subscriptions to manage costs and the resources that are created by users, teams, or projects.
Management groups: These groups help you manage access, policy, and compliance for multiple subscriptions. All subscriptions in a management group automatically inherit the conditions applied to the management group.
Azure availability zones
You want to ensure your services and data are redundant so you can protect your information in case of failure. When you host your infrastructure, setting up your own redundancy requires that you create duplicate hardware environments. Azure can help make your app highly available through availability zones.
What is an availability zone?
Availability zones are physically separate datacenters within an Azure region. Each availability zone is made up of one or more datacenters equipped with independent power, cooling, and networking. An availability zone is set up to be an isolation boundary. If one zone goes down, the other continues working. Availability zones are connected through high-speed, private fiber-optic networks.
Diagram showing three datacenters connected in a single Azure region representing an availability zone.
(see attachment)
https://s3.amazonaws.com/brainscape-prod/system/cm/402/219/292/a_image_card.?1666406772
Availability zones are primarily for VMs, managed disks, load balancers, and SQL databases. The following categories of Azure services support availability zones:
* Zonal services: You pin the resource to a specific zone (for example, VMs, managed disks, IP addresses).
* Zone-redundant services: The platform replicates automatically across zones (for example, zone-redundant storage, SQL Database).
* Non-regional services: Services are always available from Azure geographies and are resilient to zone-wide outages as well as region-wide outages.
Describe Azure Region Pairs
Azure region pairs
Availability zones are created by using one or more datacenters. There’s a minimum of three zones within a single region. It’s possible that a large disaster could cause an outage big enough to affect even two datacenters. That’s why Azure also creates region pairs.
What is a region pair?
Each Azure region is always paired with another region within the same geography (such as US, Europe, or Asia) at least 300 miles away. This approach allows for the replication of resources (such as VM storage) across a geography that helps reduce the likelihood of interruptions because of events such as natural disasters, civil unrest, power outages, or physical network outages that affect both regions at once. If a region in a pair was affected by a natural disaster, for instance, services would automatically failover to the other region in its region pair.
Examples of region pairs in Azure are West US paired with East US and SouthEast Asia paired with East Asia.
Diagram showing relationship between geography, region pair, region, and datacenter.
https://s3.amazonaws.com/brainscape-prod/system/cm/402/219/574/a_image_card.?1666407104
Because the pair of regions is directly connected and far enough apart to be isolated from regional disasters, you can use them to provide reliable services and data redundancy. Some services offer automatic geo-redundant storage by using region pairs.
Additional advantages of region pairs:
If an extensive Azure outage occurs, one region out of every pair is prioritized to make sure at least one is restored as quickly as possible for applications hosted in that region pair.
Planned Azure updates are rolled out to paired regions one region at a time to minimize downtime and risk of application outage.
Data continues to reside within the same geography as its pair (except for Brazil South) for tax- and law-enforcement jurisdiction purposes.
Having a broadly distributed set of datacenters allows Azure to provide a high guarantee of availability.
Describe about Azure Resource Groups and Azure Resource Manager
Azure resource groups
Resource groups are a fundamental element of the Azure platform. A resource group is a logical container for resources deployed on Azure. These resources are anything you create in an Azure subscription like VMs, Azure Application Gateway instances, and Azure Cosmos DB instances. All resources must be in a resource group, and a resource can only be a member of a single resource group. Many resources can be moved between resource groups with some services having specific limitations or requirements to move. Resource groups can’t be nested. Before any resource can be provisioned, you need a resource group for it to be placed in.
Life cycle
If you delete a resource group, all resources contained within it are also deleted. Organizing resources by life cycle can be useful in nonproduction environments, where you might try an experiment and then dispose of it. Resource groups make it easy to remove a set of resources all at once.
Authorization
Resource groups are also a scope for applying role-based access control (RBAC) permissions. By applying RBAC permissions to a resource group, you can ease administration and limit access to allow only what’s needed.
Azure Resource Manager
Azure Resource Manager 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. You use management features like access control, locks, and tags to secure and organize your resources after deployment.
When a user sends a request from any of the Azure tools, APIs, or SDKs, Resource Manager receives the request. It authenticates and authorizes the request. Resource Manager sends the request to the Azure service, which takes the requested action. Because all requests are handled through the same API, you see consistent results and capabilities in all the different tools.
The following image shows the role Resource Manager plays in handling Azure requests.
Diagram showing a Resource Manager request model.
https://s3.amazonaws.com/brainscape-prod/system/cm/402/220/186/a_image_card.?1666407926
All capabilities that are available in the Azure portal are also available through PowerShell, the Azure CLI, REST APIs, and client SDKs. Functionality initially released through APIs will be represented in the portal within 180 days of initial release.
With 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.
