Book Image

Learning Azure Functions

By : Mitesh Soni, Manisha Yadav
Book Image

Learning Azure Functions

By: Mitesh Soni, Manisha Yadav

Overview of this book

Functions help you easily run small pieces of code in cloud with Azure functions without worrying about a whole application or the infrastructure to run it. With Azure functions, you can use triggers to execute your code and bindings to simplify the input and output of your code. This book will start with the basics of Azure Functions. You will learn the steps to set up the environment and the tools that we will be using in the further chapters. Once you have a better understanding of this, we will be creating our first hello world function app. Later you will be introduced to triggers, how they are used to activate a function, and how binding can be used to output results of a function.You will also explore the steps to create an assembly with complex functionality that can be used by functions. Next, this book will teach you to scale your functions and use them to process data, integrate systems, and build simple APIs and microservices. Finally, this book will cover some diagnostic techniques with Azure App services and best practices of working with Azure Functions. By the end of this book, you will be well-versed with the techniques of scaling your Azure functions and making the most of serverless architecture.
Table of Contents (17 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback

An overview of serverless architectures

Since the introduction of cloud computing, we have usedThe Blind Men and an Elephant story for different technology evolutions and trends. It becomes easier to convey that there is no clear definition of it and based on experience we define it differently based on our wisdom. There may not be any drastic difference but the view might be different. Reality is one, though wise men speak of it variously.

Let's understand serverless architecture by taking the story of blind men and an elephant:

According to this story of The Blind Men and an Elephant, the blind men decide to define an elephant by touching it and then come to their own conclusions:

  • The first person placed his hand upon the elephant's trunk and said, "It feels like ... a thick snake"
  • The second person placed his hand upon the elephant's ears and said, "It feels like ... a kind of fan"
  • The third person placed his hand upon the elephant's legs and said, "It feels like ... a tree-trunk"
  • The fourth person placed his hand upon the elephant's body and said, "It feels like ... a wall"
  • The fifth person placed his hand upon the elephant's tail and said, "It feels like ... a rope"
  • The sixth person placed his hand upon the elephant's tusks and said, "It feels like ... a spear"

So, there are different perspectives, but the elephant remains the same. There are many perspectives, views, and definitions available for serverless architectures or serverless computing.

Let's understand serverless architecture with respect to the evolution of computing:

Based on the pattern of usage, the use of an on-premise resource evolved into the use of to serverless computing.

Cloud computing and service models

Change is a step-by-step process to evolve and make the existing practices more effective with enhancements. If we can find a pattern, then change/evolution is a driving force behind all path-breaking innovations. Similarly, cloud computing is a disruptive innovation in the field of infrastructure in Information Technology.

George Bernard Shaw was wise enough to say that:

"Progress is impossible without change, and those who cannot change their minds cannot change anything."

This is very appropriate for cloud computing and its adoption in the small, medium, or even large organization.

Let's understand what cloud computing is! It is no longer the elephant in the room. There are many good definitions available in the market, but I will explain what I understand and what I have experienced.

Cloud computing and its basics

Cloud computing is a kind of system that provides on-demand and agile resources in a pay-as-you-go billing model, multitenant, or dedicated computing resource such as compute, storage, and network. As per NIST definitions, cloud computing comes with four cloud deployment models and three cloud service models as given in the following diagram:

Cloud deployment models define the way resources are deployed in the environment such as on-premise and exclusively for a specific organization, that is, a private cloud; or cloud resources that are accessible to all organizations and individuals over the internet, that is, a public cloud; or cloud resources that are accessible to a specific set of organizations that share similar interests or requirements, that is, a community cloud; or cloud resources that combine two or more cloud deployment models that is known as a hybrid cloud.

There are three cloud service models that define the way cloud resources are made available to users.

Infrastructure as a Service (IaaS): Cloud resources can be Infrastructure as a Service (IaaS), where the user is responsible for managing and maintaining resources/virtual machine starting, from package installation to security configuration and from upgrading packages to configuring resources for high availability as well.

Platform as a Service (PaaS): In PaaS, the cloud service provider gives flexibility to choose configuration and the user is only responsible for configuration and some troubleshooting options and monitoring options are made available by the cloud service provider.

Software as a Service (SaaS): In SaaS, the complete application is made available by the cloud service provider, where the responsibility of IaaS and PaaS remains with the cloud service provider. The user has to only use it and not worry about provisioning, monitoring, and managing the resources.

Cloud computing has few characteristics defined by NIST, which are noteworthy such as multitenancy, pay-as-you-use (similar to electricity or gas connection), on-demand self-service, resource pooling for better utilization of resources, rapid elasticity for scaling up and scaling down resources based on usage in an automated manner, and measured service for billing.

In the last few years, usage of different cloud deployment models has varied based on use cases and priorities of different organizations. Initially, a public cloud was used for noncritical applications, while a private cloud was utilized for business-critical applications, where security was a major concern. Hybrid cloud usage evolved over time with experiments, experience, and confidence in the services provided by cloud service providers.

As usual in a normal traditional environment for infrastructure management, installation, configuration, and monitoring, it was easier to adopt IaaS as there is complete control. Over time, organizations realized the pain or work behind the management of resources available in the cloud and the cost of managing resources in the cloud as the efforts are the same in managing resources considering security configurations and other configurations.

Hence, PaaS is getting popular day by day with the evolvement of Platform as a Service. PaaS has matured over the years and the scope is much wider and the services allow us to configure different programming languages such as .Net, Java, PHP, Python, and Ruby.

The following is a diagram representing different Cloud Service Models:

In plain English, PaaS provides an infrastructure as well as a runtime environment in combination to deploy an application. The difference is that the end user doesn't have control on the infrastructure while they can configure a runtime environment most of the time. Some service providers allow access to resources created in PaaS but not all. Features such as the ability to debug applications remotely and troubleshoot issues, up to some extent, are also provided. There are PaaS offerings, where you can have dedicated infrastructure resources for application deployment, but even in that case, control of the infrastructure is in the hands of cloud service providers.

Considering the definition of PaaS, everything is managed by the cloud service provider up to the runtime environment. For example, in the case of Java, we don't need to worry about which Java version will be installed and available to update the Java version, the web server version, and so on. Over the years, PaaS has gained its momentum and many organizations have realized that the lower the number of complexities, lesser will be the management overhead. PaaS offerings manage load balancer and high availability with little configuration and hence save lot of time and the architecture is clearer. We need to remember one thing: that most of the control lies with the cloud service provider and hence we do not have much to manage and cloud service providers have more control and they implement all best practices and standard patterns to fulfil the service level agreements (SLAs) attached with PaaS offering.

In short, those who know more about infrastructures and platforms, manage them efficiently, so we have less overhead.

Cloud service providers will handle all resource and version management of all the packages.

However, it means that it is the choice in terms of packages and other options lies with the service provider and not with the cloud consumers. Yes, cloud consumers' choices are considered based on market trends, so indirectly, users have their say in the services offered by the cloud service provider.

In a traditional environment, the infrastructure provisioning process takes place in a different manner than the acquisition of virtual machines in cloud subscription. Additionally, if there are any issues during the steps, then it takes more time in to and fro communication between different stakeholders. Let's visualize how the process workflow is executed in terms of a traditional model or in IaaS and then we will compare it with PaaS:

In the case of PaaS, the flow has fewer complications than the traditional or IaaS process to acquire resources as given as follows:

However, the approval process exists in the cloud environment too as the cost is associated with it and organizations can keep different sets of approval processes to create a virtual machine or to provision any PaaS offering such as email notification.

Having said that, there are many cloud service providers in the market that provide different types of services in an improved and innovative manner. Microsoft Azure is one of the leading cloud service providers available in the market. In the next section, we will explore some important concepts related to Microsoft Cloud to build a base of understanding on which we can kick off with Azure Functions.

Serverless computing

Serverless is not actually serverless. It means that users only need to manage code/application and not servers. The server will be managed by the service provider. We as a user only pay when our code or function is executed in the serverless or in the server that is not managed by us. Scaling is based on the request and pricing differs based on the service provider. AWS Lambda and Azure Functions are two examples of serverless computing or Function as a Service (FaaS). AWS provides a pay-as-you-go billing model, while Microsoft Azure provides a consumption plan as well as an App Service plan for Azure Functions. We will cover this in detail in a comparison table later in the chapter.


The following are some of the benefits of serverless computing:

  • Faster time to market as you can write code in the functions editor in the Azure portal and click on Run for execution
  • No need to worry about the infrastructure and provisioning resources
  • Easy bindings to services and external services
  • Create functions in multiple languages as supported by the cloud service provider
  • Pay only for what you use
  • More cost-effective than IaaS and PaaS
  • No configuration is required to set up scaling in and scaling out policies

In the next section, we will cover an overview of the Azure Functions.