More Information
Learn
  • Discover what microservices offer above and beyond other architectures
  • Create a serverless application with AWS
  • Gain secure access to data and resources
  • Run tests on your configuration and code
  • Create a highly available serverless microservice data API
  • Build, deploy, and run your serverless configuration and code
About

Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity.

Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices.

By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning.

Features
  • Create a secure, cost-effective, and scalable serverless data API
  • Use identity management and authentication for a user-specific and secure web application
  • Go beyond traditional web hosting to explore the full range of cloud hosting options
Page Count 168
Course Length 5 hours 2 minutes
ISBN 9781789535297
Date Of Publication 29 Mar 2019

Authors

Richard Takashi Freeman

Richard Takashi Freeman has an M.Eng. in computer systems engineering and a Ph.D. in machine learning and natural language processing from the University of Manchester, UK. He is currently a lead big data and machine learning engineer at JustGiving; and a cloud architect, serverless computing, and machine learning freelance SME and consultant at Starwolf. He previously worked at PageGroup and Capgemini, and has been delivering cloud-based, big data, machine learning, serverless, and scalable solutions for over 14 years across different sectors. He is a blogger; a speaker, presenting at various events; and the author of two video courses. You can visit his website, titled Richard Freeman, PhD, for his blog posts, presentations, and courses.