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
Compute
-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.
-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.
-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.
Messaging
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.
Developer
Applications Insights and
Azure DevOps
Management
-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.
Functions
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.
We would
like to thank you for investing your time with us.
Learn The Blockchain Technology
Written By: www.codexploitcybersecurity.com Facebook: https://www.facebook.com/icybersecure
Credits to all organisations and development teams at Microsoft
Corporation
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