The Real-Time IoT Device Monitoring with Kinesis Data Analytics guidance automatically provisions the services necessary to collect, process, analyze and visualize IoT device connectivity and activity data in real-time. This guidance is designed to provide a framework for analyzing and visualizing metrics, allowing you to focus on adding new metrics rather than managing the underlying infrastructure.
Overview
The diagram below presents the architecture you can build using the example code on GitHub.
Real-Time IoT Device Monitoring with Kinesis Data Analytics guidance architecture
When AWS IoT ingests data from your connected devices, an AWS IoT rule sends the data to a Kinesis data delivery stream. The delivery stream archives the events in an Amazon S3 bucket and sends the data to a Kinesis Data Analytics application for processing.
The application sends the data to an AWS Lambda function that sends it in real-time to a DynamoDB table to be stored. The application also sends processed data to a second Kinesis data delivery stream which archives it in an Amazon S3 bucket.
The guidance also creates an Amazon Cognito user pool, an Amazon S3 bucket, an Amazon CloudFront distribution, and a real-time dashboard to securely read and display the account activity stored in the DynamoDB table.
Real-Time IoT Device Monitoring with Kinesis Data Analytics
Version 1.1.2
Last updated: 12/2019
Author: AWS
Features
Real-Time IoT Device Monitoring with Kinesis Data Analytics reference implementation
Amazon Kinesis data analytics application
Device monitoring dashboard
Anomaly detection
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