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- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Building efficient Python applications at minimal cost by adopting serverless architectures
Key Features 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 APIsBook 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.
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 LambdaWho this book is for
This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed.
Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultant—data science—and NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
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Seitenzahl: 136
Veröffentlichungsjahr: 2018
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Building Serverless Applications with Python
Copyright © 2018 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Commissioning Editor: Merint MathewAcquisition Editor: Sandeep MishraContent Development Editor: Rohit Kumar SinghTechnical Editor: Ruvika RaoCopy Editor: Safis EditingProject Coordinator: Vaidehi SawantProofreader: Safis EditingIndexer: Priyanka DhadkeGraphics: Jason MonteiroProduction Coordinator: Arvindkumar Gupta
First published: April 2018
Production reference: 1190418
Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.
ISBN 978-1-78728-867-6
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Contributors
About the author
Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultant—data science—and NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
About the reviewer
Sanjeev Jaiswal is a computer graduate from CUSAT with 9 years of industrial experience. He basically uses Perl, Python, AWS, and GNU/Linux for his day-to-day activities. He is currently working on projects involving penetration testing, source code review, security design and implementations in AWS, and cloud security projects.
He is learning DevSecOps and Security Automation currently as well. Sanjeev loves teaching engineering students and IT professionals. He has been teaching in his leisure time for the last 8 years.
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Table of Contents
Title Page
Copyright and Credits
Building Serverless Applications with Python
Packt Upsell
Why subscribe?
PacktPub.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Conventions used
Get in touch
Reviews
The Serverless Paradigm
Understanding serverless architectures
Understanding microservices
Serverless architectures don't have to be real-time only
Pros and cons of serverless
Summary
Building a Serverless Application in AWS
Triggers in AWS Lambda
Lambda functions
Functions as containers
Configuring functions
Testing Lambda functions
Versioning Lambda functions
Creating deployment packages
Summary
Setting Up Serverless Architectures
S3 trigger
SNS trigger
SQS trigger
CloudWatch trigger
Summary
Deploying Serverless APIs
API methods and resources
Setting up integration
Deploying the Lambda function for API execution
Handling authentication and user controls
Summary
Logging and Monitoring
Understanding CloudWatch
Understanding CloudTrail 
Lambda’s metrics in CloudWatch
Lambda's logs in CloudWatch
Logging statements in Lambda
Summary
Scaling Up Serverless Architectures
Third-party orchestration tools
The creation and termination of servers
Security best practices
Identifying and handling difficulties in scaling
Summary
Security in AWS Lambda
Understanding AWS Virtual Private Clouds (VPCs)
Understanding subnets in VPCs
Securing Lambda inside private subnets
Controlling access to Lambda functions
Using STS inside Lambda for secure session-based execution
Summary
Deploying a Lambda Function with SAM
Introduction to SAM
CloudFormation for serverless services
Deploying with SAM
Understanding security in SAM
Summary
Introduction to Microsoft Azure Functions
Introduction to Microsoft Azure Functions
Creating your first Azure Function
Understanding triggers
Understanding logging and monitoring in Azures Functions
Best practices for writing Azure Functions
Summary
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
Serverless engineering is a new domain of engineering that allows developers to write code and deploy infrastructures without having to worry about maintaining servers. This book explains the concepts of serverless engineering with Python examples on cloud architectures.
Who this book is for
This book is for Python developers who would like to learn about serverless architectures in cloud-based platforms such as Azure and Amazon Web Services (AWS). Python programming knowledge is assumed.
What this book covers
Chapter 1, The Serverless Paradigm, introduces the reader to the concepts of microservices and serverless architectures, and provides a clear understanding of the pros and cons.
Chapter 2, Building a Serverless Application in AWS, covers AWS Lambda and explains the concepts, workings, and the components involved in the tool in detail. It also explains the nuances involved in security, user controls, and versioning code inside Lambda.
Chapter 3, Setting Up Serverless Architectures, goes into further detail about the various triggers in AWS Lambda and how they integrate with the functions. The reader will learn what the event structure of each trigger will look like and how to modify the Lambda function with respect to the type of trigger used.
Chapter 4, Deploying Serverless APIs, explores the AWS API Gateway and also teaches the reader how to build efficient, scalable serverless APIs using the API Gateway and Lambda. It goes on to teach the reader how to improve the API by adding authorization and how to set up user-level controls such as throttling of requests.
Chapter 5, Logging and Monitoring, presents the concept of logging and monitoring in serverless applications. This is mostly still an unsolved problem in this domain. This chapter guides the reader through setting up logging and monitoring in the AWS environment with Python via custom metrics and logging. This chapter also goes into the details of best practices when it comes to logging and monitoring Lambda functions in Python.
Chapter 6, Scaling Up Serverless Architectures, discusses the practice of scaling up serverless architectures for large workloads using several third-party tools. This chapter also teaches the reader how to handle security, logging, and monitoring using the available Python modules.
Chapter 7, Security in AWS Lambda, teaches readers to deploy secure serverless applications by leveraging the AWS security features available. This involves having strict controls on components that the application can access, on the users who can handle or access the application, and so on. This also involves understanding AWS virtual private clouds and subnets for an in-depth understanding of the security features and best practices you can follow in AWS Lambda.
Chapter 8, Deploying a Lambda Function with SAM, looks at how to deploy Lambda functions as infrastructure as code via the Serverless Application Model, which is a new way of writing and deploying Lambda functions that makes it easier to integrate with other IaaS services, such as CloudFormation.
Chapter 9, Introduction to Microsoft Azure Functions, familiarizes the reader with Microsoft Azure Functions, and explains how to configure and understand the components of the tool.
To get the most out of this book
The reader should be comfortable with the Python programming language. So, prior experience with it is expected. Prior experience with cloud-based systems will also be helpful.
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "It is to be noted that the meta information should always be included for all SAM, which includes AWSTemplateFormatVersion and Transform. This would tell CloudFormation that the code you have written is an AWS SAM code and a serverless application."
A block of code is set as follows:
AWSTemplateFormatVersion: '2010-09-09'Transform: AWS::Serverless-2016-10-31
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "For creating a function, you need to click on the orange Create a function button on the right."
Get in touch
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Reviews
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The Serverless Paradigm
Most probably, if you are reading this book, you have already heard about the serverless paradigm and the terms serverless engineering and serverless architecture. Nowadays, the way developers deploy applications has changed drastically, especially in the domain of data engineering and web development, thanks to event-based architectural designs, also called serverless architectures.
It is not uncommon to have idle resources and servers in production idle after the server workload has finished, or waiting for the next workload to come. This introduces a bit of redundancy in the infrastructure. What if there was no need for idle resources lying around when there is no workload? What if resources can be created when necessary and be destroyed once the work is done?
At the end of this chapter, you will understand how serverless architectures and functions as a service work, and how you can build them into your existing software infrastructure. You will also learn what microservices are, and decide whether microservices or serverless operations are well-suited for your architecture or not. You will also learn how to build serverless applications with Python on major cloud service providers, such as Amazon Web Services (AWS) and Microsoft's Azure.
This chapter will cover the following points:
Understanding serverless architectures
Understanding microservices
Serverless architectures don't have to be real-time only
Pros and cons of serverless architectures
Understanding serverless architectures
The concept of serverless architectures or serverless engineering revolves entirely around understanding the concept of functions as a service. The most technical and accurate definition of serverless computing on the internet is as follows:
Now, let's go into the details of each part of that definition to understand the paradigm of serverless computing better. We shall start with the term function as a service. It means that every serverless model has a function that is executed on the cloud. These functions are nothing but blocks of code, that are executed depending on the trigger that is associated with the function. This is a complete list of triggers in the AWS Lambda environment:
Now let's understand what manages the starting and stopping of a function. Whenever a function is triggered via one of these available triggers, the cloud provider launches a container in which the function executes. Also, after the function is successfully executed the function has returned something, or if the function has run out of time, the container gets thatched away or destroyed. The thatching happens so that the container can be reused in the event of high demand and whenever there is very little time between two triggers. Now, we come to the next part of the sentence, the function's container. This means that the functions are launched and executed in containers. This is the standard definition of a container from Docker, a company that made the concept of containers very popular:
This helps in packaging the code, the runtime environment, and so on of the function into a single deployment package for seamless execution. The deployment package contains the main code file for the function, all the non-standard libraries which are required for the function to execute. The creation process of a deployment package looks very similar to that of a virtual environment in Python.
