Implementing Serverless Microservices Architecture Patterns

Building a microservices platform using virtual machines or containers, involves a lot of initial and ongoing effort and there is a cost associated with having idle services running, maintenance of the boxes and a configuration complexity involved in scaling up and down.

In this course, We will show you how Serverless computing can be used to implement the majority of the Microservice architecture patterns and when put in a continuous integration & continuous delivery pipeline; can dramatically increase the delivery speed, productivity and flexibility of the development team in your organization, while reducing the overall running, operational and maintenance costs.

We start by introducing the microservice patterns that are typically used with containers, and show you throughout the course how these can efficiently be implemented using serverless computing. This includes the serverless patterns related to non-relational databases, relational databases, event sourcing, command query responsibility segregation (CQRS), messaging, API composition, monitoring, observability, continuous integration and continuous delivery pipelines.

By the end of the course, you’ll be able to build, test, deploy, scale and monitor your microservices with ease using Serverless computing in a continuous delivery pipeline.

What You Will Learn

• Implement over 15 microservices architecture patterns without needing containers or EC2 instances
• Build, test, deploy and maintain serverless microservices
• Speed up delivery, flexibility and time to market using serverless microservices
• Get serverless best practices and recommendation on scaling out and enforcing security
• Debug, monitor and observe your serverless stack
• Add your microservices to a continuous integration & continuous delivery pipeline
• Estimate, and reduce maintenance and running costs

Audience

This video course is for developers, architects, DevOps, administrators and operations who would like to deploy Serverless computing and microservices in their organization.

About The Author

Richard T. 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.