Last updated 8/2018
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.21 GB | Duration: 11h 37m

The perfect course to implementing cost-effective, and scalable Microservices using Serverless Computing on AWS
What you'll learn
Improve the reusability, composability, and maintainability of code.
Create a highly available serverlessmicroservice data API.
Build, deploy and run your serverless configuration and code.
Speed up delivery, flexibility and time to market using serverlessmicroservices.
Add your microservices to a continuous integration & continuous delivery pipeline.
Estimate, and reduce maintenance and running costs.
Implement over 15 microservices architecture patterns without needing containers or EC2 instances.
Scale up without significant changes to tooling, architecture, or development practices.
Reduce the risk and cost of operating a cloud platform.
Requirements
Prior experience to traditional application development is assumed.
Basic understanding of microservices and serverless architecture will be useful.
Description
Microservices are a popular new approach to building maintainable, scalable, cloud-based applications. AWS is the perfect platform for hosting Microservices. Recently, there has been a growing interest in Serverless computing due to the increase in developer productivity, built in auto-scaling abilities, and reduced operational costs. Building a microservices platform using virtual machines or containers, involves a lot of initial and ongoing effort. 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 combining both microservices and serverless computing, organizations will benefit from having the servers and capacity planning managed by the cloud provider, making them much easier to deploy and run at scale.This comprehensive 3-in-1 course is a step-by-step tutorial which is a perfect course to implementing Microservices using Serverless Computing on AWS. Build highly availableMicroservices to power applications of any size and scale. Get to grips with Microservices and overcome the limitations and challenges experienced in traditional monolithic deployments. Design a highly available and cost-efficient Microservices application using AWS. Create a system where the infrastructure, scalability, and security are managed by AWS. Finally, reduce your support, maintenance, and infrastructure costs.Contents and OverviewThis training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Building Microservices on AWS, covers building highly available Microservices to power applications of any size and scale. This course shows you how to build Microservices-based applications on AWS. Overcome the limitations and challenges you experience in traditional monolith deployments. By the end of the course, you'll have learned to apply AWS tools to create and deploy Microservices-based applications. You'll be able to make your applications cost-effective, easier to scale, and faster to develop.The second course, Building a Scalable ServerlessMicroservice REST Data API, covers practical solutions to building Serverless applications. In this course we show you how to build an end-to-end serverless application for your organization. We have selected a data API use case that could reduce costs and give you more flexibility in how you and your clients consume or present your application, metrics and insight data. We make use of the latest serverless deployment and build framework, share our experience on testing, and provide best practices for running a serverless stack in a production environment.The third course, Implementing ServerlessMicroservices Architecture Patterns, covers implementing Microservices using Serverless Computing on AWS. 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. 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.By the end of the course, you'll create a secure, scalable, and Serverless data API to build highly available Microservices to power applications of any size and scale.About the Authors● Alan Rodrigues has been working on software components such as Docker containers and Kubernetes for the last 2 years. He has extensive experience working on the AWS Platform, currently being certified as an AWS Solution Architect Associate, a SysOps Administrator, and a Developer Associate. He has seen that organizations are moving towards using containers as part of their Microservices architecture. And there is a strong need to have a container orchestration tool in place. Kubernetes is by far the most popular container orchestration on the market.● Richard T. Freeman, PhD currently works for JustGiving, a tech-for-good social platform for online giving that's helped 25 million users in 164 countries raise $5 billion for good causes. He is also offering independent and short-term freelance cloud architecture & machine learning consultancy services. Richard is a hands-on certified AWS Solutions Architect, Data & Machine Learning Engineer with proven success in delivering cloud-based big data analytics, data science, high-volume, and scalable solutions. At Capgemini, he worked on large and complex projects for Fortune Global 500 companies and has experience in extremely diverse, challenging and multi-cultural business environments. Richard has a solid background in computer science and holds a Master of Engineering (MEng) in computer systems engineering and a Doctorate (Ph.D.) in machine learning, artificial intelligence and natural language processing. See his website for his latest blog posts and speaking engagements. He has worked in nonprofit, insurance, retail banking, recruitment, financial services, financial regulators, central government and e-commerce sectors, where he: -Provided the delivery, architecture and technical consulting on client site for complex event processing, business intelligence, enterprise content management, and business process management solutions.-Delivered in-house production cloud-based big data solutions for large-scale graph, machine learning, natural language processing, serverless, cloud data warehousing, ETL data pipeline, recommendation engines, and real-time streaming analytics systems.-Worked closely with IBM and AWS and presented at industry events and summits, published research articles in numerous journals, presented at conferences and acted as a peer-reviewer.-Has over four years of production experience with Serverless computing on AWS.
Overview
Section 1: Building Microservices on AWS
Lecture 1 The Course Overview
Lecture 2 The Concepts of Microservices
Lecture 3 Benefits of Microservices
Lecture 4 Key Design Elements for Microservices
Lecture 5 Understanding AWS EC2 and ELB
Lecture 6 Decentralizing AWS Data Options
Lecture 7 AWS Elastic Beanstalk
Lecture 8 Working with AWS Lambda
Lecture 9 AWS API Gateway
Lecture 10 AWS Route 53
Lecture 11 Monitoring Microservices
Lecture 12 Exploring Blue Green Deployments
Lecture 13 Using Elastic Load Balancer for Blue Green Deployments
Lecture 14 Using Elastic Beanstalk for Blue Green Deployments
Lecture 15 Getting Started with Continuous Integration
Lecture 16 Using AWS CodeCommit
Lecture 17 Implementing AWS CodeBuild
Lecture 18 Using AWS CodePipeline
Lecture 19 The Complete Continuous Integration Pipeline
Lecture 20 Working with Containers
Lecture 21 Using Orchestration
Lecture 22 Exploring Kubernetes
Lecture 23 Using AWS Elastic Container Service
Section 2: Building a Scalable Serverless Microservice REST Data API
Lecture 24 The Course Overview
Lecture 25 Monolithic and Microservice Architectures
Lecture 26 Virtual Machines, Containers, and Serverless Computing
Lecture 27 Serverless Computing in AWS
Lecture 28 Setting Up Your Serverless Environment in AWS
Lecture 29 Overview of Security in AWS
Lecture 30 Overview of AWS Identity and Access Management (IAM)
Lecture 31 Securing Your Serverless Microservice
Lecture 32 Building a Serverless Microservice Data API
Lecture 33 Setting Up a Lambda in the AWS Management Console
Lecture 34 Setting Up the API Gateway and Integrating It with a Lambda Proxy
Lecture 35 Creating and Writing to a NoSQL Database Called DynamoDB
Lecture 36 Creating a Lambda to Query DynamoDB
Lecture 37 Connecting API Gateway, Lambda, and DynamoDB
Lecture 38 Unit Testing Your Python Lambda Code
Lecture 39 Running and Debugging Your AWS Lambda Code Locally
Lecture 40 Integration Testing Using Real Test Data
Lecture 41 Performance and End-to-End Testing at Scale
Lecture 42 Overview of Serverless Stack Build and Deploy Options
Lecture 43 Creating an S3 Bucket, IAM Policies, and IAM Roles Resources
Lecture 44 Building and Deploying API Gateway, Lambda, and DynamoDB
Lecture 45 Building a Scalable Serverless Microservice Data API Conclusions
Lecture 46 Next Course
Section 3: Implementing Serverless Microservices Architecture Patterns
Lecture 47 The Course Overview
Lecture 48 Overview of Microservice Integration Patterns
Lecture 49 Communication Styles and Decomposition Microservice Patterns
Lecture 50 Serverless Computing to Implement Microservice Patterns
Lecture 51 Implementing Database Per Service and Shared Database Patterns
Lecture 52 Accessing DynamoDB from API Gateway Via a Lambda Function
Lecture 53 Accessing DynamoDB Directly from API Gateway
Lecture 54 Implementing the Transaction Log Tailing Pattern
Lecture 55 Implementing the Saga Pattern
Lecture 56 Securing Your DynamoDB Databases
Lecture 57 Relational Versus Non-Relational Databases
Lecture 58 Overview of Amazon Virtual Private Cloud
Lecture 59 Setting Up Amazon Virtual Private Cloud for Accessing RDS and Aurora
Lecture 60 Setting Up RDS and Accessing It from Your Local Network
Lecture 61 Accessing RDS from API Gateway Via a Lambda Function
Lecture 62 Accessing Aurora from API Gateway Via a Lambda Function
Lecture 63 Securing Your RDS and Aurora Databases
Lecture 64 API Gateway and API Composition Patterns
Lecture 65 Implementing the Serverless API Composition Patterns
Lecture 66 Event Sourcing and CQRS Patterns
Lecture 67 Architectures of the Serverless Event Sourcing Pattern
Lecture 68 Implementing the Serverless Event Sourcing Pattern
Lecture 69 Architectures of the Serverless CQRS Pattern
Lecture 70 Implementing the Serverless CQRS Pattern
Lecture 71 Securing Your Event Streams and Queries
Lecture 72 Monitoring and Observability Patterns
Lecture 73 Implementing Serverless Metrics and Health Check API Patterns
Lecture 74 Implementing the Serverless Centralized Logging Pattern
Lecture 75 Implementing the Serverless Audit Logging Pattern
Lecture 76 Implementing the Serverless Distributed Tracing Pattern
Lecture 77 Creating a Serverless Discovery Service and Catalogue
Lecture 78 Continuous Integration and Continuous Delivery
Lecture 79 Serverless Continuous Integration and Continuous Delivery Setup
Lecture 80 Using CodeCommit for the Serverless Data API Code
Lecture 81 Using CodeBuild to Build-Test the Serverless Data API Stack
Lecture 82 Using CodePipeline as CI/CD for the Serverless Data API Stack
Lecture 83 Using Other CI/CD Solutions with the Serverless Data API Stack
Lecture 84 When to Use and Not Use Serverless Computing?
Lecture 85 Estimating Serverless Stack Costs
Lecture 86 Database and Event Streaming Scalability
Lecture 87 Web Scale Best Practices
Lecture 88 Conclusion
Developers, software architects, and software engineers. Developers familiar with traditional application development but interested in using Microservices in a DevOps environment will also benefit. Microservices are appropriate to large-scale enterprise environments so this course should appeal to people interested in developing for those environments.,Developers who need practical solutions to common problems while building their serverless application. Programming knowledge is assumed.,Developers, architects, DevOps, administrators and operations who would like to deploy Serverless computing and microservices in their organization.
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