Azure services overview

1. Azure services overview

In this video, we’ll dive deeper into Azure’s services.

2. Cloud service types

With Azure, it’s important to distinguish between the three different cloud service types. Infrastructure as a Service, Platform as a Service, and Software as a Service. Each service type has different levels of responsibility between the cloud provider (in this case, Microsoft Azure) and the customer.

3. Infrastructure as a Service (IaaS)

IaaS is the most flexible category of services as it gives the user maximum control. An example in Azure would be a virtual machine - a customer would be responsible for installing the operating system, configuration, maintenance, etc., and Azure would be responsible for maintaining the hardware, network connectivity, and physical security.

4. Platform as a Service (PaaS)

PaaS is the middle ground between Infrastructure as a Service and Software as a Service. With PaaS services, Azure maintains the physical infrastructure similar to IaaS but is also responsible for the operating system, middleware, development tools, etc., that comprise a cloud solution. Azure App Service is an example of a PaaS solution for web and mobile development.

5. Software as a Service (SaaS)

SaaS is the most complete solution. With SaaS, the customer pays a subscription fee to use and connect to applications such as email, financial software, messaging apps, etc. With this model, most responsibility falls with Azure and the least with the user - with SaaS, the customer is responsible for the data, devices, and accounts/identities. Microsoft Office 365 is an example of a SaaS solution.

6. Services by cloud service type

Each cloud service type has different services that fall underneath it's umbrella from different categories. Here we can see some different examples such as Azure functions which falls under Compute and is based on the Platform as a Service model.

7. Availability of services

The availability of services across Azure regions is dependent upon the region type. There are two types in Azure: recommended and alternate. Recommended is regions that provided the broadest range of services and support availability zones. Alternate on the other hand is regions that extend Azure's footprint within a data residency boundary where a recommended region exists. These regions help optimize latency and provide a second region for recovery but doesn't support availability zones. In Azure, services are grouped into: foundational, mainstream and strategic. Foundational services are available in all regions and alternate regions when they become generally available. Mainstream services that are accessible in all recommended regions for deployment. Finally, there are Strategic services which are targeted service offerings aimed at a particular industry. Some examples of services that fall under these 3 categories are listed here.

8. Ecosystem

Azure has a remarkably versatile ecosystem suitable for diverse applications, from modernizing urban infrastructures in smart cities to powering innovative business solutions and cutting-edge intelligence services. Let's look at a couple of examples: Analytics and Big Data and AI and Machine Learning.

9. Big data and analytics

Azure has a suite of tools tailored to big data and analytics. The Azure Data Lake acts as a vast reservoir for your data. HDInsight processes and sifts through this reservoir. Azure Synapse integrates the strengths of data warehousing with big data analytics and creates a unified platform. Finally, when it comes to real-time insights - Stream Analytics delivers. Together, these tools empower businesses to manage and leverage their data efficiently.

10. AI & Machine Learning

Looking further ahead, Azure offers an advanced suite of AI & Machine Learning tools. Azure Machine Learning streamlines building, training, and deploying machine learning models. Azure Cognitive Services provides pre-built AI functions such as language understanding, computer vision, and speech recognition. Azure Databricks is an analytics platform tailored for Azure and is ideal for big data and Machine Learning. Azure AI services augment applications with features like language comprehension and speech recognition.

11. Let's practice!

Next, let's test your knowledge of Azure’s service offerings!

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