Book Image

Learn AWS Serverless Computing

By : Scott Patterson
Book Image

Learn AWS Serverless Computing

By: Scott Patterson

Overview of this book

Serverless computing is a way to run your code without having to provision or manage servers. Amazon Web Services provides serverless services that you can use to build and deploy cloud-native applications. Starting with the basics of AWS Lambda, this book takes you through combining Lambda with other services from AWS, such as Amazon API Gateway, Amazon DynamoDB, and Amazon Step Functions. You’ll learn how to write, run, and test Lambda functions using examples in Node.js, Java, Python, and C# before you move on to developing and deploying serverless APIs efficiently using the Serverless Framework. In the concluding chapters, you’ll discover tips and best practices for leveraging Serverless Framework to increase your development productivity. By the end of this book, you’ll have become well-versed in building, securing, and running serverless applications using Amazon API Gateway and AWS Lambda without having to manage any servers.
Table of Contents (20 chapters)
Free Chapter
1
Section 1: Why We're Here
4
Section 2: Getting Started with AWS Lambda Functions
9
Section 3: Development Patterns
12
Section 4: Architectures and Use Cases

Summary

When it comes to data processing workloads, the possibilities are almost endless. The options that can be leveraged with the native integration between AWS services allow us to collect data at pretty much any point of any cloud application in a serverless manner. Using S3, Glue, Athena, and QuickSight is a very cost-effective way to process large volumes of data in a secure and fast way without having to commit to expensive hardware or upfront costs. This solution can be extended as much as required by adding tools such as EMR, Lambda, RDS, Redshift, DynamoDB, or API Gateway. S3 is an extremely reliable storage service and is used at enterprise scale as a foundational Data Lake solution. What's also important to point out is that a solid data management layer is key when implementing a successful data workload on the cloud. On top of that, data governance, data quality...