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Building Serverless Applications with Python
Building Serverless Applications with Python

Building Serverless Applications with Python: Develop fast, scalable, and cost-effective web applications that are always available

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Building Serverless Applications with Python

Building a Serverless Application in AWS

This chapter will introduce the concept of serverless applications using AWS Lambda as the tool of choice. This will help you understand the concept, intuition, and working components involved in a serverless tool. It will also explain the nuances involved in security, user-controls, and versioning code inside Lambda. You will be guided via hands-on tutorials and lessons for understanding and learning to use AWS Lambda. So, it is recommended that you follow along this chapter with a laptop and an AWS account setup to easily execute the given instructions.

This chapter will cover the following topics:

  • Triggers in AWS Lambda
  • Lambda functions
  • Functions as containers
  • Configuring functions
  • Testing Lambda functions
  • Versioning Lambda functions
  • Creating deployment packages

Triggers in AWS Lambda

Serverless functions are on-demand computational concepts. So, there has to be an event that needs to trigger a Lambda function so that the entire computational process is started. AWS Lambda has several events which can act as a trigger. Almost all services of AWS can act as AWS Lambda's triggers. Here is the list of services that you can use for generating events for Lambda to respond to:

  • API Gateway
  • AWS IoT
  • CloudWatch Events
  • CloudWatch Logs
  • CodeCommit
  • Cognito Sync Trigger
  • DynamoDB
  • Kinesis
  • S3
  • SNS

The triggers page of AWS Lambda looks like this:

Let's take a look at some of the following important and widely-used triggers that are available, and understand how they can be leveraged as FaaS in the serverless paradigm. They are as follows:

  • API Gateway: This trigger can be used to create efficient, scalable, and serverless APIs. One scenario...

Lambda functions

Lambda functions are the core operating parts of a serverless architecture. They contain the code which is supposed to be executed. These functions are executed whenever the trigger attached to it has been set off. We have already learned about some of the most popular Lambda triggers in the previous section.

Whenever a Lambda function is triggered, it creates a container with the respective settings set by the user. We'll learn more about the container in our next section.

The spinning up of containers takes a bit of time, which may result in a latency whenever a fresh invocation of a Lambda function is done, as it takes time to set up the environment and bootstrap the settings mentioned by the user in the Advanced settings tab. So, to overcome this latency, AWS thaws a container for some time for reuse in case of another Lambda invocation within the thawing...

Functions as containers

For understanding the concept of functions being executed as/inside containers, we need to properly understand the concept of containers. To cite the definition of a container from the Docker documentation (https://www.docker.com/what-docker):

A container image is a lightweight, stand-alone, executable package of a piece of software that includes everything needed to run it: code, runtime, system tools, system libraries, settings.

What is available for both Linux and Windows based applications; containerized software will always run the same, regardless of the environment.

Containers isolate software from its surroundings (for example, differences between development and staging environments) and help reduce conflicts between teams running different software on the same infrastructure.

So, the concept of containers is that they are self-sustainable isolated...

Configuring functions

In this section, we will go through the ways of configuring Lambda functions and understand all the settings in great detail. Like in the previous section, we will learn about each configuration and its settings, as follows:

  1. You can go to the page of AWS Lambda by selecting it from the drop-down menu that is present in the top-left corner of the AWS console. This can be done as follows:
  1. Once the Lambda option is selected, it redirects the user to the AWS Lambda console, which looks something like this:
  1. For creating a function, you need to click on the orange Create a function button on the right. This will open a console for the function creation. This looks something like this:
  1. Let's create a function from scratch in order to understand the configurations better. So, for doing that, click on the Author from scratch button on the top-right...

Testing Lambda functions

Just like every other software system and programming paradigm, proper testing of Lambda functions and serverless architectures is very important before deploying into production. We will try to understand the testing of Lambda functions in the following points:

  1. In the top-most bar of the Lambda console, one can observe the Save and test option, which is represented by an orange button. This button saves the Lambda function and then runs the configured tests on that function. This looks something like this in the console:
  1. Also, in the same bar, there exists a drop-down menu that reads Select a test event…. This contains a list of testing events available for testing Lambda functions. The drop-down looks like this:
  1. Now, for further configuration of test events for the Lambda function, the user needs to select the Configure test events option...

Versioning Lambda functions

The concept of the Version Control System (VCS) is for controlling and managing versions of code. This functionality is available directly from the main Lambda console. Let's try and learn how to version our Lambda functions:

  1. The first option in the Actions drop-down in the Lambda console is the Publish new version option. This option can be seen here:
  1. When the Publish new version option is selected, the versioning popup of the Lambda console would be seen on the console. This would ask about the name for the new version of your Lambda function. The popup looks something like this:
  1. After clicking the Publish button, you will be re-directed to the main Lambda console. The successfully created Lambda version in the console looks something like this:
  1. In the bottom half of the page, the following message can be noticed: Code and handler editing...

Creating deployment packages

Lambda functions that have external libraries as dependencies can be packaged as deployment packages and be uploaded into the AWS Lambda console. This is very similar to creating a virtual environment in Python. So in this section, we shall learn and understand the process of creating Python deployment for using in the Lambda functions. We shall try and understand the process of creating deployment packages in detail, as follows:

  1. Deployment packages are generally in the format of ZIP packages. The contents of the ZIP package is exactly the same as a normal library of any programming language.
  2. The package structure should be such that the library folders and the function file are in the same destination or in the same hierarchy inside the folder structure of the deployment package. The layout looks something like this:
  1. The Python libraries can...

Summary

In this chapter, we have learned the concepts of how triggers work for AWS Lambda and how to select triggers depending on the problem statement and time intervals, in case of cron job triggers. We understood what Lambda functions are, along with understanding their functionalities and settings related to memory, VPCs, security, and fault tolerance. We also learned about the way container reuse is done under the hood specifically for AWS Lambda. Then, we covered event-driven functions and how they are implemented under the hood, the concept of containers, and their uses and applications in the domain of software engineering in general. Most importantly, from the concepts we learned regarding containers, we can now appreciate the options for choosing containers for running the Lambda functions.

After that, we talked about all the configuration settings available in the AWS...

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Key benefits

  • Design and set up a data flow between cloud services and custom business logic
  • Make your applications efficient and reliable using serverless architecture
  • Build and deploy scalable serverless Python APIs

Description

Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework.

Who is this book for?

This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed.

What you will learn

  • Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application
  • Explore various triggers and how to select them, based on the problem statement
  • Build deployment packages for Lambda functions
  • Master the finer details about building Lambda functions and versioning
  • Log and monitor serverless applications
  • Learn about security in AWS and Lambda functions
  • Scale up serverless applications to handle huge workloads and serverless distributed systems in production
  • Understand SAM model deployment in AWS Lambda

Product Details

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Publication date : Apr 20, 2018
Length: 272 pages
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Language : English
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Length: 272 pages
Edition : 1st
Language : English
ISBN-13 : 9781787288676
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Table of Contents

10 Chapters
The Serverless Paradigm Chevron down icon Chevron up icon
Building a Serverless Application in AWS Chevron down icon Chevron up icon
Setting Up Serverless Architectures Chevron down icon Chevron up icon
Deploying Serverless APIs Chevron down icon Chevron up icon
Logging and Monitoring Chevron down icon Chevron up icon
Scaling Up Serverless Architectures Chevron down icon Chevron up icon
Security in AWS Lambda Chevron down icon Chevron up icon
Deploying a Lambda Function with SAM Chevron down icon Chevron up icon
Introduction to Microsoft Azure Functions Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Half star icon Empty star icon Empty star icon Empty star icon 1.5
(2 Ratings)
5 star 0%
4 star 0%
3 star 0%
2 star 50%
1 star 50%
philipbergen Sep 16, 2019
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
There is no real substance, he walks you through the different flows to set things up. It's a nice kickstart but as soon as the aws user interface changes this book will just be misleading.
Amazon Verified review Amazon
Mr Mark V Day May 21, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
To say this is a book about Building Serverless Applications with Python is misleading, there is very little python code and the code is out weighted by screenshots of the lambda console, if you compare it to serverless architecture on AWS it is a poor comparison and the book was returned after 10 minutes of receiving the package.
Amazon Verified review Amazon
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