English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 2h 29m | 382 MB
Data-driven applications have their application flow governed by the data, and the serverless framework can serve as the web framework to create this kind of application. In this course, join instructor Marcia Villalba as she takes you through an overview of serverless applications and Kinesis. Learn how to design an event-driven application, how to integrate AWS Lambda and Kinesis streams, and how to set up necessary permissions. Also, discover how to leverage CloudFormation, API Gateway, SES, SNS, and SQS, and more.
Topics include:
- Backend as a service (BaaS)
- Function as a service (FaaS)
- Why infrastructure as code is so important
- Creating an order
- Setting up DynamoDB
- Saving into a DynamoDB table
- Using AWS SDK
- Sending a message to the stream
- Deploying and testing an application
- Cleaning up an AWS environment
Table of Contents
Introduction
1 AWS and serverless applications
2 What you should know
Get Started with Serverless
3 What is a serverless application
4 Backend as a service BaaS
5 Functions as a service FaaS
6 AWS Lambda basic concepts
7 Serverless Framework 101
8 Why is infrastructure as code so important
9 What we are going to build
10 Getting started with the project
Get Started with Kinesis
11 Kinesis introduction
12 Designing an event-driven application
13 Create stream with CloudFormation
14 Create an order
15 Setting up DynamoDB and saving into the table
16 Send a message to the stream using AWS SDK
17 Setting up all the permissions
18 Deploying and testing
19 Challenge – API Gateway and Lambda
20 Solution – API Gateway and Lambda
SNS SQS and Kinesis
21 AWS Lambda and Kinesis streams
22 Trigger a new Lambda
23 Configure SES
24 Send an SES message
25 Test out SES Message
26 Challenge – Kinesis
27 Solution – Kinesis
Lifecycle of a Message in the Stream
28 What is the difference between SNS SQS and Kinesis
29 Create a queue with CloudFormation
30 Send a message to SQS
31 Trigger a Lambda with a new SQS message
32 Challenge – SQS
33 Solution – SQS
Conclusion
34 Clean up the AWS environment
35 Next steps
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