Windows Azure—no, that was not a typo… “Windows” and not “Microsoft” just yet—had its debut in 2008 at The Professional Developers Conference (PDC).  Ray Ozzie, Microsoft’s former chief software architect, revealed Windows Azure as “a service, hosted and maintained by Microsoft on an array of distributed data centers. Then two years later—on February 1, 2010— it was generally available.

A Windows Internet Operation Systems (OS)

The operating system designed to become Microsoft’s cloud launched as a PaaS offering (Platform as a Service). It had four pillars to the platform:

  1. Compute Service  had web role and work role components.
  2. Azure Blog storage is a service for storing large amounts of unstructured object data, such as text or binary data.
  3. Database Service or as known as SQL Azure similar to Microsoft SQL Server.
  4. Azure Service Bus is a fully managed enterprise integration message broker.

A community of developers was the first to build a precise class of web applications.

Open Source Software (OSS)

Developers found open source better because it allowed for redistributing and mutability.  A stellar system, OSS monitored, controlled, analyzed, and managed the services on its network. This showed Microsoft that while customers wanted better control while developers wanted an open cloud platform. In 2014, Microsoft made Azure a number one place to run Linux OS.

Internet of Things (IoT) and Big Data

Competitors, such as Amazon and Google, focused on data as the common denominator factor. Google’s BigQuery’s cloud was the data warehouse of the time. Close to the same time, Microsoft launched Azure Data Lake Store and Azure Data Lake Analytics, both offering end-to-end Big Data. Microsoft also invested in managing IoT services.

Containers and Kubernetes Preferred Platform

Google Kubernetes Engine (GKE) was the first managed Kubernetes Service in the cloud. Afterwards, in 2016, Microsoft made a smart move and hired a lead engineer at Google, He led other Microsoft engineers to the container strategy for Azure, which helped launch Azure Kubernetes Service (AKS).

Machine Learning and Artificial Intelligence (AI)

Microsoft made an early leap to machine learning and artificial intelligence, which resulted in having a designer for the public cloud platforms. They also set up an Azure ML studio for training and deploying ML models, and reinforced deep learning models.

Today, Microsoft Azure is in the lead and still transforming, but with two trends: a data center with Kubernetes, and assets in a multi-cloud platform.

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