This course helps you master AWS serverless app creation using AWS Lambda to decrease operational costs.

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RunChap6Processingrequestparameters

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RunChap6CreatingParameterisedCloudFormationStacks

RunChap7

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RunChap9AvoidingCircularReferences

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RunChap10InvokingSystemUtilities

RunChap10PublishingToSAR

RunChap11UploadingFilestoS3

RunChap12LambdaUtilityFunctions

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RunChap10PublishingToSAR-copy

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In the world of modern development, serverless computing has become table stakes. Serverless computing has seen a major uptake with AWS Lambda having an increased adoption of 667% in 2018. Companies are making the switch to serverless for shorter time to market and decreased operational costs, but for you the advantage lies in the ability to offload the burden of managing infrastructure to serverless platforms, so you can focus on building even better apps.

In this course, you will learn how to run serverless applications using AWS Lambda. You’ll start with the basics such as creating a web service where you’ll learn the steps to deploy an AWS Serverless Application Model (SAM). You’ll then move on to more advanced topics such as handling HTTP Requests, using external storage, and managing sessions and user workflows. By the end of this course, you will be ready to work with AWS Lambda in a professional setting, and you’ll have a great, transferable skill that employers will love to see.

Running Serverless Applications with AWS Lambda

Lambda never reuses existing container instances over a short period of time. This speeds up processing and avoids cold starts.

Lambda never reuses existing container instances over a short period of time. This speeds up processing and avoids cold starts.

Select all the things through which you can share configurations apart from having a single template:

Select all the things through which you can share configurations apart from having a single template:

Select all the ways needed by Lambda functions if they want to share behavior:

Select all the ways needed by Lambda functions if they want to share behavior:

starts and scales containers automatically based on demand, and charges you for actual usage only

automates workflow with AWS resources, taking up to a year

splits incoming events into shards and allows you to configure the partitioning data key

controls the total throughput of the system easily by configuring the number of shards.



What is the purpose of having a Kinesis Data Streams?

What is the purpose of having a Kinesis Data Streams?

Lambda charges for memory allocation multiplied by CPU time, so bundling tasks with different memory needs can be unnecessarily expensive.



Lambda charges for memory allocation multiplied by CPU time, so bundling tasks with different memory needs can be unnecessarily expensive.

It's quiz time! Answer the following questions to test your knowledge and understanding.

Getting Started

Setup Tools for Local Development

Creating a Web Service

Host a Serverless Application on AWS Lambda

Development and Troubleshooting

Core Features of AWS Lambda

Handling HTTP Requests

Using External Storage

Cheaper, Faster, Serverless

Handling Platform Events

Using Application Components

Managing Sessions and User Workflows

Designing Robust Applications

Deployment Options

Process Amazon SNS Notifications with AWS Lambda

Quiz