Microsoft Azure Cloud Development – An Overview

Microsoft Azure, codenamed “Project Red Dog” and formerly Windows Azure is a cloud computing service created by Microsoft on February 1, 2010 for building, testing, deploying, and managing applications and services through Microsoft-managed data centres.

It provides Software as a service (SaaS), platform as a service (PaaS) and Infrastructure as a service (IaaS) and supports many different programming languages, tools and frameworks, including both Microsoft-specific and third-party software and systems.

Azure was announced in October 2008 and released on 1st February 2010 as “Windows Azure” before being renamed “Microsoft Azure” on March 25, 2014.

                                 Microsoft Azure Services
-Virtual machines: Infrastructure as a service (IaaS) allowing users to launch general-purpose Microsoft Windows and Linux virtual machines, as well as preconfigured machine images for popular software packages.

-App services: platform as a service (PaaS) environment letting developers easily publish and manage websites.

-Websites: high density hosting of websites allows developers to build sites using ASP.NET, PHP, Node.js or Python and can be deployed using FTP, Git, Team Foundation Server or uploaded through the user portal. This was renamed Web Apps in April 2015.

-WebJobs: applications that can be deployed to an App Service environment to implement background processing that can be invoked on a schedule, on demand, or run continuously. The Blob, Table and Queue services can be used to communicate between WebApps and WebJobs and to provide state.

                                                         Mobile Services
-Mobile Engagement: collects real-time analytics that highlight user’s behaviours. It also provides notifications to mobile devices.

-HockeyApp: can be used to develop, distribute and beta-test mobile apps.   

                                         Storage Services
-Storage Services: provides REST and SDK APIs for storing and accessing data on the cloud.

-Table Services: lets programs store structured text in partitioned collections of entities that are accessed by partition key and primary key. It’s a NoSQL non-relational database.

-Blob Service: allows programs to store unstructured text and binary data as blobs that can be accessed by HTTP(S) path. Blob service also provides security mechanisms to control access to data.

-Queue Service: lets programs communicate asynchronously by message using queues.

-File Service: allows storing and access of data on the cloud using the REST APIs or the SMB protocol.
                                                Data Management
-Azure Search: provides text search and a subset of OData’s structured filters using REST and SDK APIs.

-Cosmos DB: is a NoSQL database service that implements a subset of the SQL SELECT statement on JSON documents.

-Redis Cache: is a managed implementation of Redis.

-StorSimple: manages storage tasks between on-premises devices and cloud storage.

-SQL Database: formerly known as SQL Azure Database, works to create, scale and extend applications into the cloud using Microsoft SQL Server technology. It also integrates with Active Directory and Microsoft System Center and Hadoop.

-SQL Data Warehouse: is a data warehousing service designed to handle computational and data intensive queries on datasets exceeding 1TB.

-Azure Data Factory: is a data integration service that allows creation of data-driven workflows in the cloud for orchestrating and automating data movement and data transformation.

-Waves Blockchain Platform : On May 11, 2017 the Waves platform became available on Microsoft Blockchain-as-a-service, integrated to enable developers build non-Turing complete dApps and smart contracts. 

As one of the major IT companies to recognize the potential of Blockchain technology, Microsoft aims this integration will help organizations deploy advanced solutions tailored to their needs with little resources. Companies will have the ability to create their own digital tokens, raise funds for projects and manage their own private or public Blockchain using Waves. 

-Azure Data Lake: is a scalable data storage and analytics service for big-data analytics workloads that require developers to run massively parallel queries.

-Azure HDInsight: is a bag data relevant service, that deploys Hortonworks Hadoop on Microsoft Azure, and supports the creation of Hadoop clusters using Linux Ubuntu.

-Azure Stream Analytics: is a serverless scalable event processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, websites, social media and other applications.

The Microsoft Azure Service Bus allows applications running on Azure premises or off premises devices to communicate with Azure. This helps to build scalable and reliable applications in a service-oriented architecture (SOA). The Azure service bus supports four different types of communication mechanisms;  

·         Event Hubs – which provides event and telemetry ingress to cloud at massive scale, with low latency and high reliability. Example an event hub can be used to track data from cell phones such as a GPS location coordinate in real-time.

·         Queues – which allows one-directional communication. A sender application would send the message to the service bus queue, and a receiver would read from the queue. Though there can be multiple readers from the queue, only one would process a single message.

·         Topics – which provide one-directional communication using a subscriber pattern. It is similar to a queue; however, each subscriber will receive a copy of the message sent to a Topic. Optionally the subscriber can filter out messages based on specific criteria defined by the subscriber.

·         Relays – which provide bi-directional communication. Unlike queues and topics, a relay doesn’t store in-flight messages in its own memory. Instead, it just passes them on the destination application.

                                             Media Services 
A PaaS offering that can be used for encoding, content protection, streaming, or analytics.

                                  CDN (Content Delivery Network) 
A global content delivery network (CDN) for audio, video, applications, images, and other static files. It can be used to cache static assets of websites geographically closer to users to increase performance. The network can be managed by a REST based HTTP API.

Azure has 54 point of presence locations worldwide (also known as Edge locations) as of August 2018.

Applications Insights and Azure DevOps

-Azure Automation: provides a way for users to automate the manual, long-running, error-prone, and frequently repeated tasks that are commonly performed in a cloud and enterprise environment. It saves time and increases the reliability of regular administrative tasks and even schedules them to be automatically performed at regular intervals.

You can automate processes using RunBooks or automate configuration management using Desired State Configuration.

                                          Machine Learning
Azure Machine Learning is a cloud-based data science platform on the Azure cloud ecosystem. Azure Machine Learning studio also supports coding in Python, SQL and R.

-Microsoft Azure Machine Learning (Azure ML): service is part of Cortana Intelligence Suite that enables predictive analytics and interaction with data using natural language and speech through Cortana

                                                                                             Source: Microsoft

-Cognitive Services (formerly Project Oxford): are a set of APIs, SDKS and services available to developers to make their applications more intelligent, engaging and discoverable.  

You can signup for a free account to get started with Azure Machine Learning.

Azure functions are used in serverless computing architectures, where subscribers can execute code as a Function-as-a-Service (FaaS) without managing the underlying server resources.
                                                  IoT (Internet of Things)
Internet of Things are increasingly advancing daily, with countless start-ups such as IOTA racing to develop Blockchain technologies like Tangle for the predicted 75 billion devices by 2025.

Microsoft have released a handful of technologies targeting IoT for businesses;

-Azure IoT Hub service announced on February 4, 2016
-Azure IoT Central SaaS on December 5, 2017
-Microsoft Azure IoT Developer Kit (DevKit) board, manufactured by MXChip
-On April 16, 2018 Microsoft announced Azure Sphere, an end-to-end IoT product that focusses on microcontroller-based devices and uses Linux
-Azure IoT Edge, used to run Azure services and artificial intelligence on IoT devices 

                                          Microsoft Azure Design
The cloud computing platform uses a specialized operating system, called Microsoft Azure, to run its ‘Fabric Layer’, a cluster hosted at Microsoft’s data centers that manages computing and storage resources of the computers, and provisions the resources (or a subset of them) to applications running on top of Microsoft Azure.

Azure has been described as a “cloud layer” on top of a number of Windows Server systems, which use Windows Server 2008 and a customized version of Hyper-V, known as the Microsoft Azure Hypervisor to provide virtualization of services.

Scaling and reliability are controlled by the Microsoft Azure Fabric Controller, which ensures the services and environment do not fail if one or more of the servers fails within the data center, and provides the management of the user’s Web application such as memory allocation and load balancing.

                                                        Final Thoughts

We hope this article helps as a general overview of Microsoft Azure cloud computing platform, and the possibilities the service offers in new fields like machine learning, artificial intelligence, big data analytics and IoTs.  

You can create a free account to get started familiarizing with the interface and tools of Azure.

We would like to thank you for investing your time with us.
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         Credits to all organisations and development teams at Microsoft Corporation


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16 June 2019 at 04:08 comment-delete

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26 August 2019 at 00:33 comment-delete
25 May 2020 at 04:14 comment-delete

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