[cs615asa] HW-N - AWS IoT builders day Summary

[Devesh Jain]

Hi all,
For the HW-N we choose the AWS IoT builders day event that took place on March 15 in NYC.

Event Details:
AWS IOT Builder's Day Workshop: Monitoring Energy Utilization
[Approach to build IoT Solutions]

Event Link: (https://pages.awscloud.com/NAMER-field-T3-IoT-Builders-Day-NYC-2019-reg-event.html?sc_channel=em&sc_campaign=NAMER_field_T3_iot-builders-day-nyc_20190315.campaign-invite&sc_publisher=aws&sc_medium=em_137679&sc_content=event_ev_field&sc_country=us&sc_geo=namer&sc_outcome=event&trk=em_137679&.)

Summary:
This was a full-day event where we learnt how we can extend the AWS IOT Cloud capabilities to the edge. We got an overview of AWS IOT architecture which consists of:
1.      Data Services: How we can extract values from the IOT data.
2.      Control Services: How we can control, manage, and secure our devices.
3.      Devices software How can we connect our devices and operate at the edge.

The primary focus of the event was on Amazon's IOT service called "Greengrass". We learnt that for communication, devices and the AWS IoT platform use the HTTPS and MQTT protocols. And the AWS IoT message broker, a core embedded service-enabling message exchange, also supports MQTT over the WebSocket. The problem statement that they defined was deploying a robust, scalable, cost-effective infrastructure to power smart device functionality. We learnt to build a solution that helps to perform analytics on appliance energy usage in a smart building and forecast energy utilization to optimize consumption. We configured AWS IoT Core to ingest stream data from AWS Greengrass enabled devices, built an analytics pipeline using AWS IOT Analytics, processed batch data using Amazon ECS, visualized the data using Amazon QuickSight, and performed machine learning using Jupyter Notebooks.
AWS IOT Services follow high security standards. To ensure that data exchange between the AWS IoT platform and connected devices is secure all the way, there are multiple authorizations, authentication, and encryption levels. Both authorization methods-the AWS method (SigV4) and the traditional approach using X.509 certificates-are used with HTTPS communications. MQTT uses the certification-based approach while SigV4 connectivity protects the WebSocket connection. Moreover, product owners can form and enforce their own security policies through the AWS Console or using an API.

Relation to class:
A sysadmin's role varies a lot. They could be doing backups one day and analyzing data for a security breach the other. This event showed us how to use the AWS services for both. In the first model, we used three smart home devices and gathered real time data which we immediately backed up to the cloud. In the second model, we migrated stored data into the amazon storage containers. We then used Jupyter notebooks to analyze all of this data and gain insight into the functioning of these devices. As a sysadmin, this information would prove valuable for system performance, reliability and security as we had seen in the "Backup and Disaster Recovery / Monitoring" class. Greengrass acts as a gateway to connect the device to the cloud. If the device loses its connection, the greengrass device acts as a backup for the information. We used the MQTT protocol which can be related with the networking part of the course. The MQTT protocol powers the Internet of Things (IoT). AWS IoT message broker implementation is based on MQTT version 3.1.1 but deviates from the specification to some extent. At the AWS IoT builders day event, we used just that. The lightweightness of the protocol makes it an ideal choice for IoT applications. We also addressed some real world use cases for ex.: Self-driving vehicles: continuous data stream to gather real-time location information and send updates to the vehicle; like upcoming weather and traffic alerts. Issues regarding latency in communication were also discussed, and how latency can affect system performance.

Reason for choosing this event:
The event dealt with AWS IoT services like GreenGrass, IoT Core, IoT Analytics, ECS, QuickSight and SageMaker which provide services and support like back-up, communication protocols, Analytics. These are the things a sysadmin typically uses on a daily basis. It explained integration of different services which is a fundamental requirement to build a system architecture. There were hands-on labs that taught us creating and analyzing packets sent from an IoT device using the MQTT protocol (MQTT is a light-weight transmission protocol) using AWS CloudFormation stack. This shall be fundamental to a sysadmin while deploying a cloud-integrated system.

Learnings from the event:
*       MQTT protocol
*       IoT services(tools) on the AWS cloud platform
*       Multi-service integration
*       Onboard Edge Devices and stream data to the Cloud.
*       Analyze, transform, store, and stream data in the Data Lake
*       Migrate time series data in bulk to the Data Lake
*       Visualize the time series data using charts & bars
*       Build, Train, and Evaluate the ML models

Group members:
1.      Rozy Gupta (CWID: 10442449)
2.      Aleeza Shaikh (CWID: 10432328)
3.      Devesh Jain (CWID: 10442449)


Best

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