Implementing Serverless Microservices Architecture Patterns [Video]
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.
Parts of the source code linked to this course are available at https://github.com/PacktPublishing/Implementing-Microservice-Architecture-using-Serverless-Computing-on-AWSStyle and Approach
This video tutorial is one of the most complete and practical courses on serverless microservices, with a lot of original content and offered through a recipe-based approach that teaches you the skills required to build, test, deploy and monitor Serverless microservices at scale on AWS. I’ve split the source code, packages and bash shell scripts into self contained examples that allow you to quickly grasp how to deploy individual patterns. The serverless configuration, IAM policies, source code and shell scripts will help you quickly understand the commands, so that you can adapt them for you needs. I’ve also mixed full code deployments with alternative AWS Console user interface steps in the screencasts for key areas, so you get to know both. This will give you a good grasp of all steps involved, giving you good working intuition, and allowing you to quickly and directly replicate what is shown. I only use the native AWS SDKs, SAM and CLI to do this, so any improvement and fixes will be available as soon as AWS releases them.
|Course Length||7 hours 16 minutes|
|Date Of Publication||29 May 2018|