How to deploy DSH-PREDMNTin proprietary AWS account

Agenda

1 Architecture

2 Configure and Deploy in your AWS account

2

Remove DSH-PREDMNT from your account3

Predictive Maintenance DashboardEnd to End architecture

3

Sensors/Actuators

IoT Node

Firmware

OpenSTlinux

Distribution

IoT Cloud Application User Dashboard

The Cloud Application collects data from IoT Node directly or from a Gateway

Predictive Maintenance Dashboard

Edge

AWS IoT Greengrass

4

SensorEdge node

AWS IoT

GreenGrass

Autonomous

sensor

Amazon

FreeRTOS

Data Acquisition Data Ingestion

IoT Core

Data Processing, Storage

and Services

Kinesis

DynamoDB

Dashboard

S3

CloudFront

Users

AWS Lambda

Simplified Architecture

ST IoT

Dashboard

API Gateway

5

Predictive Maintenance DashboardAWS services by class

AWS Lambda

Amazon DynamoDB

AWS IoT Core AWS IoT GreengrassAmazon CloudWatch AWS CloudFormation

Amazon API GatewayAmazon CloudFront

Amazon Cognito

AWS Identity and Access

Management (IAM)

AWS Shield

AWS WAF

Amazon Simple Storage

Service (S3)

User identify and securityApplication core modules:

IoT, Compute, Database and StorageManagement and Governance

Networking and Content Delivery

Kinesis

Predictive Maintenance DashboardHow can I access?

6

• dsh-predmnt.st.com

https://www.st.com/en/applications/factory-automation/condition-monitoring-predictive-

maintenance.html

ST.com/DSH-Predmnt

• Serverless deployment in

customer’s account

*regulated with terms of usage for free limited access

Configure and Deploy in proprietary account

Get the toolsTools required to install the project

• Account AWS

• NodeJS

• npm

• serverless

8Note: Please refer to the official tools instructions for installation.

To be able to run the automatic deploy the elements listed below are required.

Predictive Maintenance DashboardDeploy Application in own AWS account

9

• dsh-predmnt.st.com

ST.com/DSH-Predmnt

• Serverless deployment in

customer’s account

1. Accept License Agreement

2. Get the tools

3. Download .zip file

4. Configure

5. Deploy

Platforms Supported

Browser Required

Download the .zip filesWeb App project structure

• predictive_maintenance_fe

• lambda

• predictive_dashboard

• serverless

10

AWS Lambda lets you run

code without provisioning

or managing servers

This folder contains the

code of the Predictive

Maintenance DashboardThis is the main folder of

the Serverless project

Unzip the file in any folder of your file system and you will get the folders structure reported below.

ConfigureStep 1/3

11

https://serverless.com/framework/docs/providers/aws/guide/credentials/?rd=true

Official Serverless AWS credentials configuration instructions.

For more information about “Storing Credentials in the Config File” you can

check the aws official page:

https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html

• The Serverless Framework needs access

to your AWS cloud provider's account so

that it can create and manage resources

on your behalf.

In order to execute the automatic deploy the following configuration is required.

1

Follow the link below to allow serverless to deploy the Web App to AWS:

region: <aws_region>account_id: <aws_account_id>thingGroupName: <aws_iot_thingGroupName>polling_period: <iot_polling_period> # millisecondendpoint: <iot_core_endpoint>bucket_name:predictive-dashboard: <predictive-dashboard-bucket-name>predmnt-data-lake: <data-lake-bucket-name>weekly-lake: <weekly-lake-bucket-name>predmnt-zip-lake: <zip-lake-bucket-name>

env: <env>restricted_access: falseadmin_panel: falsesimulator_pool: falseSSO: falsezip_expiration: <zip-file-duration> # hoursTags:-

Key: "App-Name" # optional list of tagValue: “my-app-name"

12

• Once Serverless is configured, to

customize dashboards and AWS regions, you need to create a folder /config and

a file config.yml inside it.

predictive_maintenance_fe/serverless/config/config.yml

Replace the <text> with

the correct values.

• region: your AWS region where IoT Core service lives

• account_id: your AWS account id

• thingGroupName: IoT things group name

• polling_period: disconnection timeout (in seconds) after last data transmission of the IOT device

• endpoint: AWS IoT Core endpoint

• bucket_name:

• predictive-dashboard: name of your AWS bucket S3 containing web code

• predmnt-data-lake: name of your S3 bucket that will contain telemetry data

• weekly-lake: name of your S3 bucket that will contain aggregated data by week

• predmnt-zip-lake: name of your S3 bucket that will contain zip file to be downloaded

• env : environment name, if “dev” allowed_ip_range must be valorized with the allowed ip range

• zip_expiration: how many hours zip with telemetry data remain available to be downloaded

2 ConfigureStep 2/3

In order to execute the automatic deploy the following configuration is required.

.yml

!

It is not possible to have two or more buckets S3 with

same name. It is strongly recommended to compose this

name using a combination of region, account id and static

string as suffix.

ConfigureStep 3/3

13

npm install

• Before to start the deploy, you need to download from npm all the node modules requested.

• To do this execute the following command from a

terminal shell inside the serverless folder

If you want you can use the

abbreviation commandnpm i

Deploy 1/4

14

serverless deploy

• To start the automatic deploy procedure we need to

execute this command from a shell like prompt or

powershell within the folder predictive_dashboard_fe/serverless/

If you want a log more

verbose please use the options -–verbose.

Lambda

function

Amazon

DynamoDBAmazon S3

bucket

Deploy 2/4

15

C:\...\predictive_maintenance_fe\serverless\sls_invoke_params.env

• After that the command launched in the previously slide is done, it

is necessary to lunch a final command in order to trigger a

function that sets some configuration on our aws account.

• Open the file below using a text editor

1

Set these environmental variables on current command shell

Deploy 3/4

16

How to set Environmental variables

Microsoft Windows user

Unix / Mac user

Deploy 4/4

17

Launch the configuration command

C/.../predictive_maintenance_fe/serverless>serverless invoke --function ${PRDMNT_FUNC} --

region ${PRDMNT_REGION} --stage ${PRDMNT_STAGE} --data ${PRDMNT_DATA}

C:\...\predictive_maintenance_fe\serverless>serverless invoke --function $Env:PRDMNT_FUNC --

region $Env:PRDMNT_REGION --stage $Env:PRDMNT_STAGE --data $Env:PRDMNT_DATA

Register your user

18

Using the AWS web

console, edit the Cognito

service and add a new

user to the users pool

Fill the fields as reported

below with your new user

In the first login on the dashboard, you have to confirm the sign up procedure replacing the

temporary password with the final one.

Dashboard Link

19

Via AWS web console, go

to Cloudfront service

You will find the link to the

dashboard just deployed

associated with the bucket

name chosen during the

configuration procedure

Now you can work with DSH-PREDMNT

20

• User login and data segregation

• Assets Map

• Device and AWS Greengrass Edge

registration and configuration:

• Provisioning

• Association to assets

• Streaming time

• Live data visualization

• Add a device to live monitoring

• Asset Health Monitoring

• Collect data

• Analyse Historical trends

• Apply failure thresholds for alerts and warnings

• English and Chinese

Info Panel for the

user about its terms

Monitor live events or

check events history

Download telemetry data

sent filtering by device

Remove DSH-PREDMNT from your account

Remove main stack 1/2

22

serverless remove

• To remove the services and clear the entire

dashboard and AWS setup environment we execute

this serverless command within the folder predictive_dashboard_fe/serverless/

If you want a verbose log please use the options -–

verbose.

• Resources deletion is composed by two parts:

1. Main stack deletion

2. Additional stacks deletion

Remove additional stacks 2/2

23

serverless remove additionalstacks

• After this, additional stacks containing all Lambda

functions, IoT rules, policies, identity pools and S3

buckets are erased and a new deploy can be done

from scratch.

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