Apuntes Azure 2

Regions   Microsoft Azure is made up of datacenters located around the globe. These datacenters are organized and made available to end users by region. A region is a geographical area on the planet containing at least one, but potentially multiple datacenters that are in close proximity and networked together with a low-latency network. Azure is generally available in 54 regions and available in 140 countries.   Things to know about regions     Azure has more global regions than any other cloud provider.     Regions provide customers the flexibility and scale needed to bring applications closer to their users.     Regions preserve data residency and offer comprehensive compliance and resiliency options for customers.     For most Azure services, when you deploy a resource in Azure, you choose the region where you want your resource to be deployed.     Some services or virtual machine features are only available in certain regions, such as specific virtual machine sizes or storage types.     There are also some global Azure services that do not require you to select a region, such as Microsoft Azure Active Directory, Microsoft Azure Traffic Manager, or Azure DNS.   Region Pairs   Each Azure region is paired with another region within the same geography, together making a region pair. The exception is Brazil South, which is paired with a region outside its geography.   Things to know about regional pairs:     Physical isolation. When possible, Azure prefers at least 300 miles of separation between datacenters in a regional pair, although this isn't practical or possible in all geographies. Physical datacenter separation reduces the likelihood of natural disasters, civil unrest, power outages, or physical network outages affecting both regions at once.     Platform-provided replication. Some services such as Geo-Redundant Storage provide automatic replication to the paired region.     Region recovery order. In the event of a broad outage, recovery of one region is prioritized out of every pair. Applications that are deployed across paired regions are guaranteed to have one of the regions recovered with priority.     Sequential updates. Planned Azure system updates are rolled out to paired regions sequentially (not at the same time) to minimize downtime, the effect of bugs, and logical failures in the rare event of a bad update.     Data residency. A region resides within the same geography as its pair (except for Brazil South) to meet data residency requirements for tax and law enforcement jurisdiction purposes.   Geographies   A geography is a discrete market typically containing two or more regions that preserves data residency and compliance boundaries. Geographies allow customers with specific data-residency and compliance needs to keep their data and applications close. Geographies ensure that data residency, sovereignty, compliance, and resiliency requirements are honored within geographical boundaries. Geographies are fault-tolerant to withstand complete region failure through their connection to dedicated high-capacity networking infrastructure.

Availability options   A single virtual machine with premium storage has an SLA of 99.9%. You can quickly migrate existing virtual machines to Azure through “lift and shift”. Lift and shift is a no-code option where each application is migrated as-is providing the benefits of the cloud without the risks or costs of making code changes.   By placing virtual machines in an availability set you protect against datacenter failures and increases the SLA to 99.95%.   Adding virtual machines to availability zones protects from entire datacenter failures and increases the SLA to 99.99%. This is highest level of protection that is provided.   For multi-region disaster recovery region pairs protects and provides data residency boundaries.

Availability Sets   Availability sets are a way for you to ensure your application remains online if a high-impact maintenance event is required, or a hardware a failure occurs. Availability sets are made up of Update domains (UD) and Fault domains (FD).   Update domains. When a maintenance event occurs (such as a performance update or critical security patch applied to the host), the update is sequenced through update domains. Sequencing updates using update domains ensures that the entire datacenter isn't unavailable during platform updates and patching. Update domains are a logical section of the datacenter, and they are implemented with software and logic. Fault domains. Fault domains provide for the physical separation of your workload across different hardware in the datacenter. This includes power, cooling, and network hardware that supports the physical servers located in server racks. In the event the hardware that supports a server rack becomes unavailable, only that rack of servers would be affected by the outage.   Availability Zones Availability zones are physically separate locations within an Azure region that use availability sets to provide additional fault tolerance. Each availability zone is an isolation boundary containing one or more datacenters equipped with independent power, cooling, and networking. If one availability zone goes down, the other continues working. The availability zones are typically connected to each other through very fast, private fiber-optic networks. Availability zones allow customers to run mission-critical applications with high availability and low-latency replication. Availability zones are offered as a service within Azure, and to ensure resiliency, there’s a minimum of three separate zones in all enabled regions.

Resource Groups A resource group is a unit of management for your resources in Azure. You can think of your resource group as a container that allows you to aggregate and manage all the resources required for your application in a single manageable unit. This allows you to manage the application collectively over its lifecycle, rather than manage components individually. You can manage and apply the following resources at resource group level:     Metering and billing     Policies     Monitoring and alerts     Quotas     Access control Remember that when you delete a resource group you delete all resources contained within it.   When creating and placing resources within resource groups there are a few considerations:     Each resource must exist in one, and only one, resource group.     A resource group can contain resources that reside in different regions.     You decide how you want to allocate resources to resource groups based on what makes the most sense for your organization.     You can add or remove a resource to a resource group at any time.     You can move a resource from one resource group to another.     Resources for an application do not need to exist in the same resource group. However, it is recommended that you keep them in the same resource group for ease of management.

Azure Resource Manager   Is a management layer in which resource groups and all the resources within it are created, configured, managed, and deleted. Allows you automate the deployment and configuration of resources using different automation and scripting tools, such as Microsoft Azure PowerShell, Azure Command-Line Interface (Azure CLI), Azure portal, REST API, and client SDKs.   With Azure Resource Manager, you can: Deploy Application resources. Update, manage, and delete all the resources for your solution in a single, coordinated operation. Organize resources. Manage your infrastructure through declarative templates rather than scripts. You can view which resources are linked by a dependency, and you can apply tags to resources to categorize them for management tasks, such as billing. Control access and resources. You can control who in your organization can perform actions on the resources. You manage permissions by defining roles, adding users or groups to the roles, and applying policies at resource group level.  

Azure compute Is an on-demand computing service for running cloud-based applications. It provides computing resources such as disks, processors, memory, networking and operating systems.   You pay only for the resources you use and only for as long as you're using them.     Azure compute services: Azure virtual machines lets you create and use virtual machines in the cloud. It provides IaaS and can be used in a variety of different ways. When you need total control over an operating system and environment, Azure VMs are an ideal choice. Just like a physical computer, you're able to customize all the software running on the VM. This is particularly helpful when you are running custom software or custom hosting configurations. Virtual machine scale sets are an Azure compute resource that you can use to deploy and manage a set of identical VMs. With all VMs configured the same, VM scale sets are designed to support true auto-scale—no pre-provisioning of VMs is required—and as such makes it easier to build large-scale services targeting big compute, big data, and containerized workloads. So, as demand goes up more virtual machine instances can be added, and as demand goes down virtual machines instances can be removed. The process can be manual, automated, or a combination of both. With App services, you can quickly build, deploy, and scale enterprise-grade web, mobile, and API apps running on any platform. You can meet rigorous performance, scalability, security and compliance requirements while using a fully managed platform to perform infrastructure maintenance. App Services is a platform as a service (PaaS) offering. Azure Functions are ideal when you're concerned only about the code running your service and not the underlying platform or infrastructure. They're commonly used when you need to perform work in response to an event (often via a REST request), timer, or message from another Azure service, and when that work can be completed quickly, within seconds or less.      

Walkthrough-Create a virtual machine In this walkthrough, we will create a virtual machine in the Azure Portal, connect to the virtual machine, install the web server role and test. Task 1: Create the virtual machine In this task, we will create a Windows Server 2016 Datacenter virtual machine. Task 2: Connect to the virtual machine In this task, we will connect to our new virtual machine using RDP. Task 3: Install the web server role and test In this task, install the Web Server role on the server and ensure the default IIS welcome page can be displayed.

Container services Containers are a virtualization environment.     Containers reference the operating system of the host environment that runs the container.     Unlike virtual machines you do not manage the operating system.     Containers are lightweight and are designed to be created, scaled out, and stopped dynamically.     Containers allows you to respond to changes on demand and quickly restart in case of a crash or hardware interruption.     Azure supports Docker containers. There are two ways to manage both Docker and Microsoft-based containers in Azure. Azure Container Instances offers the fastest and simplest way to run a container in Azure without having to manage any virtual machines or adopt any additional services. It is a PaaS offering that allows you to upload your containers, which it will run for you. Azure Kubernetes Service (AKS) is a complete orchestration service for containers with distributed architectures and large volumes of containers. Orchestration is the task of automating and managing a large number of containers and how they interact.

Walkthrough-Deploy Azure Container Instances In this walkthrough we create, configure, and deploy a Docker container to Azure Container Instances (ACI) in the Azure Portal. The container is a Welcome to ACI web application that displays a static HTML page. Task 1: Create a container instance In this task, we will create a new container instance for the web application. Task 2: Deploy the container and test In this task, we will deploy the container instance and ensure the welcome page displays.

Azure network services   allows you to connect cloud and on-premises infrastructure and services to provide your customers and users the best possible experience. Once the resources move to Azure, they require the same networking functionality as an on-premises deployment. In specific scenarios, they may require some level of network isolation. Azure networking components offer a range of functionality and services that can help organizations design and build cloud infrastructure services that meet their requirements.   Azure Virtual Network enables many types of Azure resources such as Azure VMs to securely communicate with each other, the internet, and on-premises networks. A virtual network is scoped to a single region; however, multiple virtual networks from different regions can be connected using virtual network peering. With Azure Virtual Network you can provide isolation, segmentation, communication with on-premises and cloud resources, routing and filtering of network traffic. Azure Load Balancer can provide scale for your applications and create high availability for your services. Load Balancer supports inbound and outbound scenarios, provides low latency and high throughput, and scales up to millions of flows for all Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) applications. You can use Load Balancer with incoming internet traffic, internal traffic across Azure services, port forwarding for specific traffic, or outbound connectivity for VMs in your virtual network. A VPN gateway is a specific type of virtual network gateway that is used to send encrypted traffic between an Azure Virtual Network and an on-premises location over the public internet. It provides a more secure connection from on-premises to Azure over the internet. Azure Application Gateway is a web traffic load balancer that enables you to manage traffic to your web applications. It is the connection through which users connect to your application. With Application Gateway you can route traffic based on source IP address and port to a destination IP address and port. You also can help protect a web application with a web application firewall, redirection, session affinity to keep a user on the same server, and many more configuration options. A Content Delivery Network (CDN) is a distributed network of servers that can efficiently deliver web content to users. It is a way to get content to users in their local region to minimize latency. CDN can be hosted in Azure or any other location. You can cache content at strategically placed physical nodes across the world and provide better performance to end users. Typical usage scenarios include web applications containing multimedia content, a product launch event in a region, or any event where you expect a high bandwidth requirement in a region.

Walkthrough-Create a virtual network In this walkthrough, we will create a virtual network, deploy two virtual machines onto that virtual network and then configure them to allow one virtual machine to ping the other over that virtual network. Task 1: Create a virtual network In this task, we will create a new virtual network. Task 2: Create two virtual machines In this task, we will create two virtual machines in the virtual network. Task 3: Test the connection In this task, we will allow ICMP connections and test that the virtual machines can communicate (ping) each other.

Azure data categories You can generally think of data as structured, semi-structured, and unstructured. Structured data     Structured data is data that adheres to a schema, so all the data has the same fields or properties.     Structured data can be stored in a database table with rows and columns.     Structured data relies on keys to indicate how one row in a table relates to data in another row of another table.     Structured data is also known as relational data. The data's schema defines the table of data, the fields in the table, and the clear relationship between the two.     Structured data is easy to enter, query, and analyze because all the data follows the same format.     Examples of structured data include sensor data or financial data. Semi-structured data     Semi-structured data is less organized than structured data.     Semi-structured data is not stored in a relational format, meaning the fields do not neatly fit into tables, rows, and columns.     Semi-structured data contains tags that make the organization and hierarchy of the data apparent.     Semi-structured data is also known as non-relational or NoSQL data.     Examples of semi-structured data include books, blogs, and HTML documents. Unstructured data     Unstructured data has no designated structure.     Unstructured data can hold any kind of data.     Unstructured data is becoming more prominent as businesses try to tap into new data sources.     Examples of unstructured data include a PDF document, a JPG image, a JSON file, and video content.

Azure storage Azure Storage is a service that you can use to store files, messages, tables, and other types of information. You can use Azure Storage on its own (for example as a file share), but developers also often use it as a store for working data. Such stores can be used by websites, mobile apps, desktop applications, and many other types of custom solutions. Azure Storage is also used by IaaS virtual machines, and PaaS cloud services.   Disk storage Disk storage provides disks for virtual machines, applications, and other services to access and use as they need, similar to how they would in on-premises scenarios. Disk storage allows data to be persistently stored and accessed from an attached virtual hard disk. Typical scenarios for using disk storage are if you want to lift and shift applications that read and write data to persistent disks, or if you are storing data that is not required to be accessed from outside the virtual machine to which the disk is attached.   Containers (Blobs) Azure Blob storage is Microsoft's object storage solution for the cloud. Blob storage is optimized for storing massive amounts of unstructured data, such as text or binary data. Blob storage is ideal for:     Serving images or documents directly to a browser.     Storing files for distributed access.     Streaming video and audio.     Storing data for backup and restore, disaster recovery, and archiving.     Storing data for analysis by an on-premises or Azure-hosted service.   Files Azure Files enables you to set up highly available network file shares that can be accessed by using the standard Server Message Block (SMB) protocol. That means that multiple VMs can share the same files with both read and write access. You can also read the files using the REST interface or the storage client libraries. You can access the files from anywhere in the world using a URL that points to the file and includes a shared access signature (SAS) token. You can generate SAS tokens; they allow specific access to a private asset for a specific amount of time. File shares can be used for many common scenarios:     Many on-premises applications use file shares. This feature makes it easier to migrate those applications that share data to Azure. If you mount the file share to the same drive letter that the on-premises application uses, the part of your application that accesses the file share should work with minimal, if any, changes.     Configuration files can be stored on a file share and accessed from multiple VMs. Tools and utilities used by multiple developers in a group can be stored on a file share, ensuring that everybody can find them, and that they use the same version.     Diagnostic logs, metrics, and crash dumps are just three examples of data that can be written to a file share and processed or analyzed later.   Queues The Azure Queue service is used to store and retrieve messages. Queue messages can be up to 64 KB in size, and a queue can contain millions of messages. Queues are generally used to store lists of messages to be processed asynchronously. For example, say you want your customers to be able to upload pictures, and you want to create thumbnails for each picture. You could have your customer wait for you to create the thumbnails while uploading the pictures. An alternative would be to use a queue. When the customer finishes their upload, write a message to the queue. Then have an Azure Function retrieve the message from the queue and create the thumbnails. Each of the parts of this processing can be scaled separately, giving you more control when tuning it for your usage.   Tables Azure Table storage stores large amounts of structured data. The service is a NoSQL datastore which accepts authenticated calls from inside and outside the Azure cloud. Azure tables are ideal for storing structured, non-relational data. Common uses of Table storage include:     Storing TBs of structured data capable of serving web scale applications.     Storing datasets that don't require complex joins, foreign keys, or stored procedures and can be denormalized for fast access.     Quickly querying data using a clustered index. You can use Table storage to store and query huge sets of structured, non-relational data, and your tables will scale as demand increases.      

Walkthrough-Create Blob storage In this walkthrough, we will create a storage account, then work with blob storage files. Task 1: Create a storage account In this task, we will create a new storage account. Task 2: Work with blob storage In this task, we will create a Blob container and upload a blob file. Task 3: Monitor the storage account In this task, we will review the storage troubleshooter and Insights pages.

Azure Database Services Azure database services are fully managed PaaS database services that free up valuable time you’d otherwise spend managing your database. Enterprise-grade performance with built-in high availability means you can scale quickly and reach global distribution without worrying about costly downtime. Developers can take advantage of industry-leading innovations such as built-in security with automatic monitoring and threat detection, automatic tuning for improved performance, and turnkey global distribution.   Azure Cosmos DB Is a globally distributed database service that enables you to elastically and independently scale throughput and storage across any number of Azure's geographic regions. It supports schema-less data that lets you build highly responsive and Always On applications to support constantly changing data. You can use Cosmos DB to store data that is updated and maintained by users around the world. It makes it easy to build scalable, highly responsive applications at global scale.   Azure SQL Database is a relational database as a service (DaaS) based on the latest stable version of Microsoft SQL Server database engine. SQL Database is a high-performance, reliable, fully managed and secure database that you can use to build data-driven applications and websites in the programming language of your choice without needing to manage infrastructure.   Azure Database Migration is a fully managed service designed to enable seamless migrations from multiple database sources to Azure data platforms with minimal downtime (online migrations). The service uses the Microsoft Data Migration Assistant to generate assessment reports that provide recommendations to help guide you through required changes prior to performing a migration. Once you assess and perform any remediation required, you're ready to begin the migration process. The Azure Database Migration Service performs all of the required steps.      

Walkthrough-Create a SQL database In this walkthrough, we will create a SQL database in Azure and then query the data in that database. Task 1: Create the database. In this task, we will create a new SQL database using the AdventureWorksLT sample database. Task 2: Query the database. In this task, we will configure the SQL server and run a SQL query.

Azure Marketplace is a service on Azure that helps connect end users with Microsoft partners, independent software vendors (ISVs), and start-ups that are offering their solutions and services, which are optimized to run on Azure. Azure Marketplace allows customers—mostly IT professionals and cloud developers—to find, try, purchase, and provision applications and services from hundreds of leading service providers, all certified to run on Azure. The solution catalog spans several industry categories, including but not limited to: open-source container platforms, virtual machine images, databases, application build and deployment software, developer tools, threat detection, and blockchain. Using Azure Marketplace, you can provision end-to-end solutions quickly and reliably, hosted in your own Azure environment. At the time of writing, this includes over 8,000 listings.    

Internet of Things (IoT) People can access more information than ever before. It began with personal digital assistants (PDAs), then morphed into smartphones. Now there are smart watches, smart thermostats, even smart refrigerators. Personal computers used to be the norm. Now the internet allows any item that's online capable to access valuable information. The Internet of Things (IoT) is the ability for devices to garner and then relay information for data analysis.   IoT Central Is a fully managed global IoT software as a service (SaaS) solution that makes it easy to connect, monitor, and manage your IoT assets at scale. No cloud expertise is required to use IoT Central. As a result, you can bring your connected products to market faster while staying focused on your customers.   Azure IoT Hub is a managed service hosted in the cloud that acts as a central message hub for bi-directional communication between your IoT application and the devices it manages. You can use Azure IoT Hub to build IoT solutions with reliable and secure communications between millions of IoT devices and a cloud-hosted solution backend. You can connect virtually any device to your IoT Hub. IoT Hub supports communications both from the device to the cloud and from the cloud to the device. It also supports multiple messaging patterns such as device-to-cloud telemetry, file upload from devices, and request-reply methods to control your devices from the cloud. IoT Hub monitoring helps you maintain the health of your solution by tracking events such as device creation, device failures, and device connections.  

Walkthrough-Implement the Azure IoT Hub In this walkthrough, we will configure a new Azure IoT Hub in Azure Portal, and then authenticate a connection to an IoT device using the online Raspberry Pi device simulator. Sensor data and messages are passed from the Raspberry Pi simulator to your Azure IoT Hub, and you view metrics for the messaging activity in Azure Portal. Task 1: Create an IoT hub In this task, we will create an IoT hub. Task 2: Add an IoT device In this task, we will add an IoT device to the IoT hub. Task 3: Test the device using the Raspberry Pi Simulator In this task, we will test our device using the Raspberry Pi Simulator.

Big Data and Analytics Data comes in all types of forms and formats. When we talk about Big Data, we're referring to large volumes of data. Data from weather systems, communications systems, imaging platforms, and many other scenarios generate large amounts of data. This amount of data becomes increasingly hard to make sense of and make decisions around. The volumes are so large that traditional forms of processing and analysis are no longer appropriate. Open source cluster technologies have been developed, over time, to try to deal with these large data sets. Microsoft Azure supports a broad range of technologies and services to provide big data and analytic solutions.   Azure Synapse Analytics Azure Synapse Analytics (formerly Azure SQL Data Warehouse) is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics.   Azure HDInsight is a fully managed, open-source analytics service for enterprises. It is a cloud service that makes it easier, faster, and more cost-effective to process massive amounts of data. HDInsight allows you run popular open-source frameworks and create cluster types such as Apache Spark, Apache Hadoop, Apache Kafka, Apache HBase, Apache Storm, Machine Learning Services. HDInsight also supports a broad range of scenarios such as extraction, transformation, and loading (ETL); data warehousing; machine learning; and IoT.   Azure Data Lake Analytics is an on-demand analytics job service that simplifies big data. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights. The analytics service can handle jobs of any scale instantly by setting the dial for how much power you need. You only pay for your job when it is running, making it more cost-effective.    

Azure Artificial Intelligence Artificial Intelligence, 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 cleaner vacuums a room, machine learning helps it decide whether the job is done. Some of the most common Artificial Intelligence and Machine Learning service types in Azure are:   Azure Machine Learning Service provides a cloud-based environment you can use to develop, train, test, deploy, manage, and track machine learning models. It fully supports open-source technologies, so you can use tens of thousands of open-source Python packages with machine learning components such as TensorFlow and scikit-learn. Rich tools, such as Jupyter notebooks or the Visual Studio Code Tools for AI, make it easy to interactively explore data, transform it, and then develop, and test models. Azure Machine Learning service also includes features that automate model generation and tuning to help you create models with ease, efficiency, and accuracy. The Azure Machine Learning service 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. When you have the right model, you can easily deploy it in a container such as Docker in Azure. Use Machine Learning service if you work in a Python environment, you want more control over your machine learning algorithms, or you want to use open-source machine learning libraries.   Azure Machine Learning Studio is a collaborative, drag-and-drop visual workspace where you can build, test, and deploy machine learning solutions without needing to write code. It uses pre-built and pre-configured machine learning algorithms and data-handling modules. Use Machine Learning Studio when you want to experiment with machine learning models quickly and easily, and the built-in machine learning algorithms are enough for your solutions. It does not provide as much control over machine learning algorithms as the Machine Learning Service we discussed earlier.    

Serverless computing is a cloud-hosted execution environment that runs your code but abstracts the underlying hosting environment. You create an instance of the service and you add your code. No infrastructure configuration or maintenance is required, or even allowed. You configure your serverless apps to respond to events. An event could be a REST endpoint, a periodic timer, or even a message received from another Azure service. The serverless app runs only when it's triggered by an event. Scaling and performance are handled automatically, and you are billed only for the exact resources you use. You don't even need to reserve resources.   Azure Functions are ideal when you're only concerned with the code running your service and not the underlying platform or infrastructure. Azure Functions are commonly used when you need to perform work in response to an event—often via a REST request, timer, or message from another Azure service—and when that work can be completed quickly, within seconds or less. Azure Functions scale automatically, and charges accrue only when a function is triggered, so they're a solid choice when demand is variable. For example, you may be receiving messages from an IoT solution that monitors a fleet of delivery vehicles. You'll likely have more data arriving during business hours. Azure Functions can scale out to accommodate these busier times. Furthermore, Azure Functions are stateless; they behave as if they're restarted every time they respond to an event. This is ideal for processing incoming data. And if state is required, they can be connected to an Azure storage service.   Azure Logic Apps is a cloud service that helps you automate and orchestrate tasks, business processes, and workflows when you need to integrate apps, data, systems, and services across enterprises or organizations. Logic Apps simplifies how you design and build scalable solutions—whether in the cloud, on premises, or both—for app integration, data integration, system integration, enterprise application integration (EAI), and business-to-business (B2B) integration. Logic Apps are designed in a web-based designer and can execute logic triggered by Azure services without writing any code. To build enterprise integration solutions with Azure Logic Apps, you can choose from a growing gallery of over 200 connectors. These include services such as Salesforce, SAP, Oracle DB, and file shares.   Azure Event Grid Event Grid allows you to easily build applications with event-based architectures. It's a fully managed, intelligent event routing service that uses a publish-subscribe model for uniform event consumption. Event Grid has built-in support for events coming from Azure services, such as storage blobs and resource groups. You can use Event Grid to support your own non-Azure-based events in near-real time, using custom topics. You can use filters to route specific events to different endpoints, and ensure your events are reliably delivered.  

Walkthrough-Implement Azure Functions In this walkthrough, we will create a Function App to display a Hello message when there is an HTTP request. Task 1: Create a Function app In this task, we will create a Function app. Task 2: Create a HTTP triggered function and test In this task, we will use the Webhook + API function to display a message when there is an HTTP request. Congratulations! You have created a Function App to display a Hello message when there is an HTTP request. Note: To avoid additional costs, you can remove this resource group. Search for resource groups, click your resource group, and then click Delete resource group. Verify the name of the resource group and then click Delete. Monitor the Notifications to see how the delete is proceeding.

Azure DevOps DevOps (Deployment and Operations) brings together people, processes, and technology, automating software delivery to provide continuous value to your users. Azure DevOps Services allows you to 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 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 Services provides development collaboration tools including high-performance pipelines, free private Git repositories, configurable Kanban boards, and extensive automated and cloud-based load testing. DevOps Services was formerly known as Visual Studio Team Services (VSTS).   Azure Lab Services Is a service that helps developers and testers quickly create environments in Azure, while minimizing waste and controlling cost. Users can test their latest application versions by quickly provisioning Windows and Linux environments using reusable templates and artifacts. You can easily integrate your deployment pipeline with DevTest Labs to provision on-demand environments. With DevTest Labs you can scale up your load testing by provisioning multiple test agents and create pre-provisioned environments for training and demos. Lab Services was formally known as DevOps Test.

Azure App Service With Azure App Service you can quickly and easily build web and mobile apps for any platform or device. Azure App Service enables you to build and host web apps, mobile back ends, and RESTful APIs in the programming language of your choice without managing infrastructure. It offers auto-scaling and high availability, supports both Windows and Linux, and enables automated deployments from GitHub, Azure DevOps, or any Git repo.   Key features of Azure App Service     Multiple languages and frameworks. App Service has first-class support for ASP.NET, ASP.NET Core, Java, Ruby, Node.js, PHP, or Python. You can also run PowerShell and other scripts or executables as background services.     DevOps optimization. Set up continuous integration and deployment with Azure DevOps, GitHub, BitBucket, Docker Hub, or Azure Container Registry. Promote updates through test and staging environments. Manage your apps in App Service by using Azure PowerShell or the cross-platform command-line interface (CLI).     Global scale with high availability. Scale up or out manually or automatically. Host your apps anywhere in Microsoft's global datacenter infrastructure, and the App Service SLA promises high availability.     Connections to SaaS platforms and on-premises data. Choose from more than 50 connectors for enterprise systems (such as SAP), SaaS services (such as Salesforce), and internet services (such as Facebook). Access on-premises data using Hybrid Connections and Azure Virtual Networks.     Security and compliance. App Service is ISO, SOC, and PCI compliant. Authenticate users with Azure Active Directory or with social login (Google, Facebook, Twitter, and Microsoft). Create IP address restrictions and manage service identities.     Application templates. Choose from an extensive list of application templates in the Azure Marketplace, such as WordPress, Joomla, and Drupal.     Visual Studio integration. Dedicated tools in Visual Studio streamline the work of creating, deploying, and debugging.     API and mobile features. App Service provides turn-key CORS support for RESTful API scenarios, and simplifies mobile app scenarios by enabling authentication, offline data sync, push notifications, and more.     Serverless code. Run a code snippet or script on-demand without having to explicitly provision or manage infrastructure, and pay only for the compute time your code actually uses.

Walkthrough-Create a Web App In this walkthrough, we will create a new web app that runs a Docker container. The container displays a Welcome message. Task 1: Create a Web App that uses a Docker container. In this task, you will create an Azure App Service Web App that uses a Docker container. Task 2: Test the Web App In this task, we will test the web app. Congratulations! You have created and tested a web app.

Azure Management tools You can configure and manage Azure using a broad range of tools and platforms. There are tools available for the command line, language-specific Software Development Kits (SDKs), developer tools, tools for migration, and many others.   Azure portal The Azure portal is a public website that you can access with any web browser. After you sign in with your Azure account, you can create, manage, and monitor any available Azure services. You can identify a service you're looking for, get links for help on a topic, and deploy, manage, and delete resources. It also guides you through complex administrative tasks using wizards and tooltips. The dashboard view provides high-level details about your Azure environment. You can customize the portal view as you need by moving and resizing tiles, displaying particular services of interest, accessing links for help and support, and providing feedback. The portal does not provide any way to automate repetitive tasks. For example, to set up multiple VMs, you would need to create them one at a time by completing the wizard for each VM. Completing a wizard can be time-consuming and error-prone for complex tasks.   Azure PowerShell Azure PowerShell is a module that you add to Windows PowerShell or PowerShell Core that enables you to connect to your Azure subscription and manage resources. Azure PowerShell requires Windows PowerShell to function. PowerShell provides services such as the shell window and command parsing. Azure PowerShell then adds the Azure-specific commands.   Azure Command Line Interface (CLI) Azure CLI is a cross-platform command-line program that connects to Azure and executes administrative commands on Azure resources. Cross platform means that it can be run on Windows, Linux, or macOS.   Azure Cloud Shell Azure Cloud Shell is a browser-based scripting environment in your portal. It provides the flexibility of choosing the shell experience that best suits the way you work. Linux users can opt for a Bash experience, while Windows users can opt for PowerShell. A storage account is required to use the Cloud Shell and you will be prompted to create one when accessing the Azure Cloud Shell.   Azure Mobile App The Microsoft Azure mobile app allows you to access, manage, and monitor all your Azure accounts and resources from your iOS or Android phone or tablet. Once installed, you can:     Check the status and important metrics of your services     Stay informed with notifications and alerts about important health issues     Quickly diagnose and fix issues anytime, anywhere     Review the latest Azure alerts     Start, stop, and restart virtual machines or web apps     Connect to your virtual machines     Manage permissions with role-based access control (RBAC)     Use the Azure Cloud Shell to run saved scripts or perform unplanned administrative tasks   Azure REST API Representational State Transfer (REST) APIs are service endpoints that support sets of HTTP operations (methods), which provide create, retrieve, update, or delete access to the service's resources. A REST API defines a set of functions which developers can perform requests and receive responses via HTTP protocol such as GET and POST.  

Azure Advisor Azure Advisor is a free service built into Azure that provides recommendations on high availability, security, performance, and cost. Advisor analyzes your deployed services and looks for ways to improve your environment across those four areas. With Azure Advisor, you can:     Get proactive, actionable, and personalized best practices recommendations.     Improve the performance, security, and high availability of your resources as you identify opportunities to reduce your overall Azure costs.     Get recommendations with proposed actions inline. You can access Azure Advisor through the Azure portal. After you sign in to the portal, either select Advisor from the navigation menu, or search for it in the All services menu.  

Walkthrough-Create a VM with a Template In this walkthrough, we will deploy a virtual machine with a QuickStart template and examine monitoring capabilities. Task 1: Explore the gallery and deploy a template In this task, we will browse the Azure QuickStart gallery and deploy a template to create a virtual machine. Task 2: Verify and monitor your virtual machine deployment In this task, we will verify the virtual machine deployed correctly.   Walkthrough-Create a VM with PowerShell In this walkthrough, we will install PowerShell locally, create a resource group and virtual machine, access and use the Cloud Shell, and review Azure Advisor recommendations. Task 1: Configure PowerShell locally In this task, we will configure PowerShell to run from your local machine. Task 2: Create a resource group and virtual machine In this task, we will use PowerShell to create a resource group and a virtual machine. Task 3: Execute commands in the Cloud Shell In this task, we will practice executing PowerShell commands from the Cloud Shell. Task 4: Review Azure Advisor Recommendations Note: This same task is in the Create a VM with Azure CLI. In this task, we will review Azure Advisor recommendations for our virtual machine.   Walkthrough-Create a VM with the CLI In this walkthrough, we will install the Azure CLI locally, create a resource group and virtual machine, use the Cloud Shell, and review Azure Advisor recommendations. Note: The following steps are based on a Windows installation, however they could equally be applicable to a Mac or Linux environment. However, there are specific installation steps for each environment. Task 1: Install the CLI locally In this task, we will install the Azure CLI on your local machine. Task 2: Create a resource group and a virtual machine In this task, we will create a resource group and a virtual machine using the CLI locally. Task 3: Execute commands in the Cloud Shell In this task, we will practice executing CLI commands from the Cloud Shell. Task 4: Review Azure Advisor Recommendations In this task, we will review Azure Advisor recommendations. Note: If you have done the previous lab (Create a VM with PowerShell) then you have already completed this task.  

Module 2 Summary In this module you've learned about core Microsoft Azure architectural components, core Azure services and solutions, and various management tools that are available to manage and configure Azure. Core Azure architectural components In this lesson we learned about how Azure datacenters and services are located and organized in regions and geographies. We also learned how availability is achieved using availability zones and availability sets. We gained an understanding of how to automate deployments and configuration of resources and services using declarative JSON templates that utilize the Azure Resource Manager layer to create and configure resources. And finally, we learned how to use resource groups for managing resources in Azure. Core Azure services and products In this lesson we learned about compute services, and the use of virtual machines and containers. We gained an understanding of some of the services that make up the compute service such as Azure VMs, VM scale sets, app services and functions, Azure Container Instances, and Azure Kubernetes Service. We also learned about networking services such as Virtual Network, Azure Load Balancer, VPN Gateway, Application Gateway, and Azure Content Delivery Network. Azure solutions In this lesson we learned about solutions such as IoT, and services that form part of the service offering such as Azure IoT Hub and Microsoft IoT Central. We discussed big data analytics services such as Azure SQL Data Warehouse, HDInsight, and Azure Data Lake Analytics. We also learned about AI and how it utilizes machine learning services such as Azure Machine Learning and Azure Machine Learning Studio. We also learned about serverless computing services such as Azure Functions, Azure Logic Apps, and Azure Event Grid. Finally we learned about DevOps services such as Azure DevOps and Azure DevTest Labs. Azure management tools In this lesson we learned about the management tools available for managing and configuring Azure, such as Azure Portal, Azure PowerShell, Azure CLI, and Azure Cloud Shell. It also includes Azure Advisor, which provides recommendations on high availability, security, performance, and cost.