Status monitoring of geographically distributed devices

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Managed Service for PostgreSQL.

3. Click Create cluster.

4. Specify a name for the cluster, e.g., my-pg-database.

5. From the Environment list, select PRODUCTION.

6. From the Version list, select 15.

7. Under Host class, specify:

   • Platform: Intel Ice Lake.
   • Type: standard.
   • Class: s3-c2-m8 (2 vCPU, 8 GB).

8. Under Size of storage:

   • Select network-hdd.
   • Specify the size of 10 GB.

9. Under Database, specify:

   • DB name: db1.

   • Username: user1.

   • Password: Set a password to access the database.

     Note

     Save the password as you will need it for authentication.

   • Locale for sorting (LC_COLLATE): C.

   • Charset locale (LC_CTYPE): C.

10. Under Network settings:

    1. Select the cloud network where you created the my-pg-sg security group.
    2. Select the my-pg-sg security group.

11. Under Hosts:

    1. Leave a single host.
    2. Click .
    3. In the window that opens, enable Public access and click Save.

12. Under Advanced settings, enable DataLens access and Access from the management console.

13. Click Create cluster.

It may take a few minutes to create a cluster.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select IoT Core.

3. Click Create registry.

4. In the Name field, enter a name for the registry, e.g., my-registry.

5. In the Password field, set a password to access the registry. The password must be at least 14 characters long and contain lowercase letters, capital letters, and numbers. To create a password, you can use the password generator.

   Note

   Save the password as you will need it for authentication.

6. Click Create.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select IoT Core.

3. Select the registry you created in the previous step.

4. In the left-hand menu, select Devices.

5. Click Add device.

6. In the Name field, enter the device name: my-device-1.

7. In the Password field, set a password to access the device. The password must be at least 14 characters long and contain lowercase letters, capital letters, and numbers. To create a password, you can use the password generator.

   Note

   Save the password as you will need it for authentication.

8. Optionally, add an alias:

   1. Click Add alias.

   2. Fill in the fields: enter an alias, e.g., events, and the topic type after $devices/{id}, e.g., events.

      As the result, you will be able to use the events alias instead of the $devices/<device_ID>/events topic.

   3. Repeat the steps for each alias you add.

9. Click Create.

10. Similarly, create my-device-2 and my-device-3.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Cloud Functions.

3. Create a function:

   1. Click Create function.
   2. In the Name field, enter a name for the function, e.g., my-device-emulator-function.
   3. Click Create.

4. Create a function version:

   1. In the Editor window that opens, select Node.js 18.

   2. Disable the Add files with code examples option.

   3. Click Continue.

   4. In the Method field, select Code editor.

   5. Click Create file:

      • File name: device-emulator.js.
      • File contents: Function code from GitHub.

   6. Similarly, create a file named package.json with the following content:

      {
        "name": "my-app",
        "version": "1.0.0",
        "dependencies": {
          "yandex-cloud": "*"
        }
      }
      

   7. In the Entry point field, specify device-emulator.handler.

   8. Under Parameters, specify:

      • Timeout: 10

      • Memory: 128 MB

      • Service account: my-emulator-function-service-account

      • Environment variables:

        Key	Description	Value
        CASH_DRAWER_SENSOR_VALUE	Percentage of used cash box space	67.89
        TEMPERATURE_SENSOR_VALUE	Baseline temperature in the pickup box	10.34
        POWER_SENSOR_VALUE	Baseline mains voltage	24.12
        SERVICE_DOOR_SENSOR_VALUE	State of the open service door sensor	False
        ITEM1_SENSOR_VALUE	Stock of product 1	50.65
        ITEM2_SENSOR_VALUE	Stock of product 2	80.97
        ITEM3_SENSOR_VALUE	Stock of product 3	30.33
        ITEM4_SENSOR_VALUE	Stock of product 4	15.15
        REGISTRY_ID	ID of the registry you created	See the management console in Yandex IoT Core

   9. Click Save changes.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Cloud Functions.

3. In the left-hand panel, select Triggers.

4. Click Create trigger.

5. In the Name field, enter a name for the trigger, e.g., my-emulator-function-trigger.

6. In the Type field, select Timer.

7. In the Cron expression field, select Every minute.

8. Under Function settings, specify the function parameters:

   • Function: my-device-emulator-function.
   • Function version tag: $latest.
   • Service account: my-emulator-function-service-account.

9. (Optional) In the Repeat request settings and Dead Letter Queue settings sections, set parameters to prevent data loss in case of failure:

   • Repeat request settings allow you to repeatedly call the function if the current function call fails.

   • Dead Letter Queue settings allow you to redirect messages that the trigger sends to the function.

     You can use a standard message queue as a dead-letter queue. If you do not have a message queue, create one in Yandex Message Queue.

10. Click Create trigger.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Cloud Functions.

3. In the left-hand panel, select Functions.

4. Create a function:

   1. Click Create function.
   2. In the Name field, enter a name for the function, e.g., my-db-function.
   3. Click Create.

5. Create a function version:

   1. In the Editor window that opens, select Python 3.12.

   2. Disable the Add files with code examples option.

   3. Click Continue.

   4. In the Method field, select Code editor.

   5. Click Create file:

      • File name: myfunction.py.
      • File contents: Function code from GitHub.

   6. In the Entry point field, specify myfunction.msgHandler.

   7. Under Parameters, specify:

      • Timeout: 10.

      • Memory: 128 MB.

      • Service account: my-db-function-service-account.

      • Environment variables:

        Key	Description	Value
        VERBOSE_LOG	Enables and disables writing data	True
        DB_HOSTNAME	Host FQDN in Managed Service for PostgreSQL	See the management console in Managed Service for PostgreSQL
        DB_PORT	Port to connect to the cluster in Managed Service for PostgreSQL	6432
        DB_NAME	Cluster name in Managed Service for PostgreSQL	db1
        DB_USER	Username to connect to the cluster in Managed Service for PostgreSQL	user1
        DB_PASSWORD	Password to connect to the DB in Managed Service for PostgreSQL	Password you set in Managed Service for PostgreSQL

   8. Click Save changes.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Cloud Functions.

3. Select the my-db-function function.

4. In the left-hand menu, select Testing.

5. In the Version tag list, select $latest, the most recent version of the function.

6. In the Payload field, paste the following data:

   {
     "messages": [
     {
       "event_metadata": {
         "event_id": "160d239876d9714800",
         "event_type": "yandex.cloud.events.iot.IoTMessage",
         "created_at": "2020-05-08T19:16:21.267616072Z",
         "folder_id": "b112345678910"
       },
       "details": {
         "registry_id": "are1234567890",
         "device_id": "are0987654321",
         "mqtt_topic": "$devices/are0987654321/events",
         "payload": "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"
       }
     }]
   }
   

7. Click Run test.

   If the function is successful, you will see the Done status in the Function status field and the Function output field will display this result:

   {
     "statusCode" : 200 ,
     "headers" : {
       "Content-Type" : "text/plain"
     },
   "isBase64Encoded" : false
   }
   

1. In the management console, select the folder you are using to complete this tutorial.
2. From the list of services, select Managed Service for PostgreSQL.
3. Select the my-pg-database cluster.
4. In the left-hand menu, select SQL.
5. In the Password field, enter the password you set to access the database and click Connect.
6. Select the public folder.
7. View the data processing result in the iot_events and iot_position tables.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select Cloud Functions.

3. In the left-hand panel, select Triggers.

4. Click Create trigger.

5. In the Name field, enter a name for the trigger, e.g., my-db-func-trigger.

6. In the Type field, select IoT Core (device).

7. Under IoT Core message settings, specify the registry and device parameters:

   • Registry: my-registry.
   • Device: Any device.
   • MQTT topic: $devices/#.

8. Under Function settings, specify the function parameters:

   • Function: my-db-function.
   • Function version tag: $latest.
   • Service account: my-db-function-service-account.

9. (Optional) In the Repeat request settings and Dead Letter Queue settings sections, set parameters to prevent data loss in case of failure:

   • Repeat request settings allow you to repeatedly call the function if the current function call fails.

   • Dead Letter Queue settings allow you to redirect messages that the trigger sends to the function.

     You can use a standard message queue as a dead-letter queue. If you do not have a message queue, create one in Yandex Message Queue.

10. Click Create trigger.

1. In the management console, select the folder you are using to complete this tutorial.
2. From the list of services, select Managed Service for PostgreSQL.
3. Select the my-pg-database cluster.
4. In the left-hand menu, select SQL.
5. In the Password field, specify the password you set to access the database and click Connect.
6. Select the public folder.
7. View the changes in the iot_events table.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select DataLens.

3. Click Create connection.

4. Select the PostgreSQL connector.

   When connecting to an external data source (which is not a Yandex Cloud resource), grant access to the source for the DataLens IP address ranges.

5. Select a cloud and folder.

6. Select the my-pg-database cluster and a host.

7. In the Port field, specify 6432.

8. Select db1 as the database and user1 as the user.

9. In the Password field, specify the password you set to access the database in Managed Service for PostgreSQL.

10. Click Create connection.

11. In the window that opens, specify the MyPGConnection name for the connection and click Create.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select DataLens.

3. Click Create dataset.

4. In the left-hand panel, click Add.

5. Select a MyPGConnection connection.

6. In the left-hand menu, select the public.iot_events and public.iot_position tables and drag them to the right.

7. Click Save.

8. In the window that opens, specify My-pg-dataset and click Create.

   The dataset will appear in the list.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select DataLens.

3. Click Create chart.

4. In the left-hand panel, click Select dataset and select My-pg-dataset, which you created previously.

5. Select Line chart as your chart type.

6. From the Dimensions section in the left-hand menu, drag the dimensions to the Line chart section as follows:

   • event_datetime, to the X section.

     A timeline will appear in the lower part of the chart on the X-axis.

   • temperature and power_voltage, to the Y section.

   The temperature and mains voltage values will appear on the Y-axis of the chart.

7. Click Save.

8. In the window that opens, specify the chart name or use the generated My-pg-dataset — Line chart name and click Save.

1. In the management console, select the folder you are using to complete this tutorial.
2. From the list of services, select DataLens.
3. Create a field to define device coordinates:
   1. In the left-hand menu, select Datasets.
   2. Select My-pg-dataset from the list of datasets.
   3. Go to the Fields tab.
   4. In the right part of the window, click Add field.
   5. In the window that opens, in the Field name field, enter Position.
   6. In the Formula field, insert GEOPOINT([latitude],[longitude]).
   7. Click Create.
   8. Click Save.
4. Create a chart:
   1. At the top right, click Create chart.
   2. Select Map as the chart type.
   3. From the Dimensions section in the left-hand menu, drag the dimensions to the Map section as follows:

      • Position, to the Geopoints section.

      • item1_fullness, item2_fullness, item3_fullness, item4_fullness, and cash_drawer, to the Tooltips section.

        On the right side of the window, you will see a scalable map with vending machines displayed as dots on the map and tooltips displayed as legend lines when you hover over the dots.

   4. Click Save.
   5. In the window that opens, specify the chart name or use the generated My-pg-dataset — Map name and click Save.

1. In the management console, select the folder you are using to complete this tutorial.

2. From the list of services, select DataLens.

3. Click Create dashboard.

4. Add the My-pg-dataset — Map and My-pg-dataset — Line chart charts, which you created at the previous steps, to the dashboard:

   1. In the bottom panel, click Chart.
   2. In the Chart field of the window that opens, click Select and select My-pg-dataset — Map.
   3. Click Add.
   4. Repeat the steps to add My-pg-dataset — Line chart.

5. Configure the selector:

   1. In the bottom panel, click Selector.
   2. In the Dataset field, click Select and select My-pg-dataset.
   3. In the Field list, select device_id.
   4. In the Default value list, select the ID of any one device you created in Yandex IoT Core.
   5. In the Header field, enter Device.
   6. Click Add.

6. Configure links:

   1. At the top right, click Links.

   2. In the window that opens, select the My-pg-dataset — Map chart from the list.

   3. In the In.link drop-down list, select Ignore.

      Maps do not support the Links parameter.

   4. In the list, select My-pg-dataset — Line chart.

   5. In the In.link drop-down list, select In.link.

   6. Click Save.

7. Click Save.

8. In the window that opens, enter a name for the dashboard: MyDash.

9. Click Create.