MICROSOFT AZURE

Microsoft  Azure is a Visionary Cloud Provider. The core product considered is Azure Machine Learning (Azure ML). The supporting portfolio of products for Azure ML includes Azure Data Factory, Azure Data Catalog, Azure HDInsight, Azure Databricks, Azure DevOps, Power BI and other components. Microsoft is geographically diversified, and its client base spans many industries and various business functions. Microsoft earns the highest Ability to Execute score of the large cloud providers. Microsoft has a strong combination of vision and tailored functionality for the full spectrum of data science professionals who contribute to multifunctional teams.

         By leveraging their existing install base Microsoft makes cloud migration a breeze. 

Strengths

• Azure stack support for  enterprise DSML: Azure ML and its supporting portfolio offer strong capabilities for the needs of enterprise data science. MLOps capabilities include a registry of packages and models and support for streamlined  creation of reproducible ML pipelines. Azure ML comes with differentiated  security and governance capabilities and, combined with Azure Cloud  management services, supports compute quota and cost management capabilities.

• Multi-persona vision and  offering: Microsoft's vision and current offering for multi-persona data science is stronger than those of its closest competitors. Azure ML provides augmented DSML and a drag-and-drop designer for citizen data scientists, and flexible notebook and SDK options for expert data scientists. Microsoft's suite of ancillary products provides a strong environment in which data engineers, ML engineers and architects, corporate developers and others can contribute to the DSML workflow.

• Openness and  partnerships: Microsoft goes beyond widespread support for popular      OSS by investing in and contributing to a number of prominent projects  (such as, Open Neural Network Exchange [ONNX], InterpretML and MLflow).  The Azure Databricks product and partnership has been successful for both  partners. Azure will also be the preferred cloud provider for the SAS Viya platform, which will be integrated with Azure and Azure ML services.

Cautions

• Requirement for Azure services  commitment and expertise: Azure ML relies on a variety of Azure services and modules and can work with data from any source. Azure ML      customers typically use Azure Data Factory for integration and  digital transformation, Azure Data Catalog for governance, and any DevOps system (often Azure DevOps or GitHub) for integration within web services and other services. Supporting this portfolio requires significant technical  expertise and understanding of the Azure ecosystem.

• Evolving on-premises, hybrid      and multicloud support: The majority of Azure ML customers operate in      purely cloud environments. Some capabilities within the Azure ML portfolio      change or become more complicated in hybrid, multicloud or on-premises      environments. Microsoft’s multicloud support is evolving, however, and      most of its customers manage data, models and ML workloads within Azure.

• Augmented DSML: Microsoft delivers solid support for citizen data scientists and likely lower total  cost of ownership (TCO) for augmentation capabilities, but still has room      to improve, compared with vendors that focus solely on data science.  Organizations seeking to broaden their data science talent base need to understand how much augmentation is offered by the visual designer in Azure ML, as opposed to the SDKs and Power BI.

Traditional Main Microsoft Cloud Based Services are;

• AZURE VMs
• AZURE APP SERVICES
• AZURE SQL
• AZURE TABLES
• DOCUMENT DB
• AZURE ACTIVE DIRECTORY

A lot of cloud services miror each other. The structure that a lot of services have dublicated from vendor to vendor to vendors, so you still have the same idea. You have zones and regions inside of Microsoft Azure.

With Azure you will have all the various different services such as elastic scaling. But one of the ways Azure separates itself. Microsoft's commitment and integration with enterprise technology solutions differ if you have an organization of any size, you probably use some Microsoft products. If you have a large organization, you may use a lot of Microsoft products. It is just simply the way it is. They have been doing this for more than 30 years. They are the deathstar to take current analogy of technology. As the deathstar when they want to focus that laser beam on something they can really have an impact. Over the past few years, they have been focusing their laser beam on cloud providers. Microsoft is an enterpirise solution, they are invloved in every line of business you can imagine; such as finance, healthcare,etc.  

The way they leverage that work is that they use their existing products to segue into the cloud products that they offer very seamlessly. When they started developing Azure, Microsoft recognized that thay had this huge install base. They recognized thay had all these products in the marketplace already and they have been able to develop cloud productsthat integrate with those existing on promise solutions very easily. That makes migration a breeze. You can integrate as your cloud products with your on site Microfost products very easily. It is the hybrid solutions. On the top of that, they made sure to implement their technologies that people are already using instead of the tools and the platforms. If you are programming or developing with .NET, you are using visible visual studio. Visual Studio is easily integrated with Azure. You can actually connect it right up to your Azure subscription. You can manage all your azure resources, all of your Azure web apps, you mobile APIs, your database right throug visual studio. Moreover, Microsoft has a reputation. Past few years they have really been, they have really been expanding their outreach into this open source software community. You can integrate it with all of the technologies used to use it. You can build Linux servers out you can connect, you can use Nodejs with Azure, and you can deploy Docker container clusters on Microsoft Azure. These make it very easy to kind of ON-RAMP and get on board with the cloud again. They are really the ultimate technology solution provider.

AZURE ACTIVE DIRECTORY

Identity Management solution, used for protecting your outside networks. You can set up a routine automized synchronization between your on-premises Active Directory and the Cloud Active Directory and essentially federate all of your on-site user identities into the cloud without any additional work. It just happens automatically. It has a deep user-based instead of enterprises inside organizations. They have also got a really tight integration with the system center service manager if you are familiar with that SCCM (Microsoft System Center Configuration Manager is a Windows product that enables the management, deployment, and security of devices and applications across an enterprise. Amongst other potential uses, administrators will commonly use SCCM for endpoint protection, patch management, and software distribution.) which is a configuration management tool for servers. Therefore you can manage from SCCM, you can manage your on-premise in your cloud at the same time through the same interface servers.

AZURE VMs

VMs is as your virtual machines which are highly scalable virtual machines in the cloud. They are easy to spin up as you might expect running Windows Server but equally, it is easy to spin up running Linux. You can interact with them through visual IDE inside of your browser through visual studio or through a command-line interface.

AZURE APP SERVICES

The platform as a service offering is called as your app services. This is comparable to Amazon's Elastic. They try to treat those as a sort of unified singular platform delivery service. 

AZURE SQL 

When it comes to storage, you may have the option to use as Azure SQL which is a cloud-based version of SQL Server Microsoft. These tools that you use to manage and connect to your Microsoft on-premise SQL servers that can be used to manage your in cloud Azure SQL Server. With this, you do not have to relearn any new technologies. You can even replicate your databases from on-premise out to the cloud if you need.  

AZURE TABLES AND DOCUMENT DB 

When it comes to new wave data storage solutions, Azure Tables and Document DB are too different NO-SQL storage solutions.