Building a Scalable Serverless Microservice REST Data API

Building a Scalable Serverless Microservice REST Data API, available at $34.99, has an average rating of 3.8, with 23 lectures, based on 5 reviews, and has 77 subscribers.

You will learn about Understand how microservices compares with existing architectures Understand how to create a serverless application in AWS Learn how to 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 This course is ideal for individuals who are This video is for developers who need practical solutions to common problems while building their serverless application. It is particularly useful for This video is for developers who need practical solutions to common problems while building their serverless application.

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Summary

Title: Building a Scalable Serverless Microservice REST Data API

Price: $34.99

Average Rating: 3.8

Number of Lectures: 23

Number of Published Lectures: 23

Number of Curriculum Items: 23

Number of Published Curriculum Objects: 23

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

Understand how microservices compares with existing architectures

Understand how to create a serverless application in AWS

Learn how to 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

Who Should Attend

This video is for developers who need practical solutions to common problems while building their serverless application.

Target Audiences

This video is for developers who need practical solutions to common problems while building their serverless application.

In the past few years, there has been a shift away from monolithic architecture (with for example its large centralized deployments) to microservice architectures with small independent deployments, allowing much more flexibility and agile delivery. Traditionally virtual machines and containers were the main options for deploying microservices but they involve a lot of operational effort, configuration, and maintenance. More 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. 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.
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.

About the Author

Richard T. Freeman, Ph.D. currently works for JustGiving, a tech-for-good company and the world’s most trusted social platform for online giving that’s helped 22 million users in 164 countries raise $4.5 billion for over 27,000 good causes. He is also offering short-term freelance cloud architecture & machine learning consultancy.
He is a highly accomplished results-driven hands-on certified AWS Solutions Architect, Data Engineer and Data Scientist with proven success in delivering cloud-based big data analytics, unstructured data, 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.
He has worked in charity, insurance, retail banking, recruitment, financial services, financial regulators, central government and e-commerce sectors, where he:

??? Provided design, 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, 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 three years of production experience with Serverless computing on AWS

Course Curriculum

Chapter 1: Overview of Monolithic and Microservice Architectures

Lecture 1: The Course Overview

Lecture 2: Monolithic and Microservice Architectures

Chapter 2: AWS Building Blocks for Creating Serverless Microservices

Lecture 1: Virtual Machines, Containers, and Serverless Computing

Lecture 2: Serverless Computing in AWS

Lecture 3: Setting Up Your Serverless Environment in AWS

Chapter 3: Securing Your Microservice

Lecture 1: Overview of Security in AWS

Lecture 2: Overview of AWS Identity and Access Management (IAM)

Lecture 3: Securing Your Serverless Microservice

Chapter 4: Creating Your First Serverless Microservice

Lecture 1: Building a Serverless Microservice Data API

Lecture 2: Setting Up a Lambda in the AWS Management Console

Lecture 3: Setting Up the API Gateway and Integrating It with a Lambda Proxy

Lecture 4: Creating and Writing to a NoSQL Database Called DynamoDB

Lecture 5: Creating a Lambda to Query DynamoDB

Lecture 6: Connecting API Gateway, Lambda, and DynamoDB

Chapter 5: Testing Your Serverless Microservice

Lecture 1: Unit Testing Your Python Lambda Code

Lecture 2: Running and Debugging Your AWS Lambda Code Locally

Lecture 3: Integration Testing Using Real Test Data

Lecture 4: Performance and End-to-End Testing at Scale

Chapter 6: Building and Deploying Your Serverless Stack

Lecture 1: Overview of Serverless Stack Build and Deploy Options

Lecture 2: Creating an S3 Bucket, IAM Policies, and IAM Roles Resources

Lecture 3: Building and Deploying API Gateway, Lambda, and DynamoDB

Chapter 7: Conclusion

Lecture 1: Building a Scalable Serverless Microservice Data API Conclusions

Lecture 2: Next Course

Instructors

Packt Publishing
Tech Knowledge in Motion

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