Getting started with Greengrass connectors (console) - Amazon IoT Greengrass
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Amazon IoT Greengrass Version 1 no longer receives feature updates, and will receive only security patches and bug fixes until June 30, 2023. For more information, see the Amazon IoT Greengrass V1 maintenance policy. We strongly recommend that you migrate to Amazon IoT Greengrass Version 2, which adds significant new features and support for additional platforms.

Getting started with Greengrass connectors (console)

This feature is available for Amazon IoT Greengrass Core v1.7 and later.

This tutorial shows how to use the Amazon Web Services Management Console to work with connectors.

Use connectors to accelerate your development life cycle. Connectors are prebuilt, reusable modules that can make it easier to interact with services, protocols, and resources. They can help you deploy business logic to Greengrass devices more quickly. For more information, see Integrate with services and protocols using Greengrass connectors.

In this tutorial, you configure and deploy the Twilio Notifications connector. The connector receives Twilio message information as input data, and then triggers a Twilio text message. The data flow is shown in following diagram.

Data flow from Lambda function to Twilio Notifications connector to Twilio.

After you configure the connector, you create a Lambda function and a subscription.

  • The function evaluates simulated data from a temperature sensor. It conditionally publishes the Twilio message information to an MQTT topic. This is the topic that the connector subscribes to.

  • The subscription allows the function to publish to the topic and the connector to receive data from the topic.

The Twilio Notifications connector requires a Twilio auth token to interact with the Twilio API. The token is a text type secret created in Amazon Secrets Manager and referenced from a group resource. This enables Amazon IoT Greengrass to create a local copy of the secret on the Greengrass core, where it is encrypted and made available to the connector. For more information, see Deploy secrets to the Amazon IoT Greengrass core.

The tutorial contains the following high-level steps:

The tutorial should take about 20 minutes to complete.

Prerequisites

To complete this tutorial, you need:

  • A Greengrass group and a Greengrass core (v1.9.3 or later). To learn how to create a Greengrass group and core, see Getting started with Amazon IoT Greengrass. The Getting Started tutorial also includes steps for installing the Amazon IoT Greengrass Core software.

  • Python 3.7 installed on the Amazon IoT Greengrass core device.

  • Amazon IoT Greengrass must be configured to support local secrets, as described in Secrets Requirements.

    Note

    This requirement includes allowing access to your Secrets Manager secrets. If you're using the default Greengrass service role, Greengrass has permission to get the values of secrets with names that start with greengrass-.

  • A Twilio account SID, auth token, and Twilio-enabled phone number. After you create a Twilio project, these values are available on the project dashboard.

    Note

    You can use a Twilio trial account. If you're using a trial account, you must add non-Twilio recipient phone numbers to a list of verified phone numbers. For more information, see How to Work with your Free Twilio Trial Account.

Step 1: Create a Secrets Manager secret

In this step, you use the Amazon Secrets Manager console to create a text type secret for your Twilio auth token.

  1. Sign in to the Amazon Secrets Manager console.

    Note

    For more information about this process, see Step 1: Create and store your secret in Amazon Secrets Manager in the Amazon Secrets Manager User Guide.

  2. Choose Store a new secret.

  3. Under Choose secret type, choose Other type of secret.

  4. Under Specify the key/value pairs to be stored for this secret, on the Plaintext tab, enter your Twilio auth token. Remove all of the JSON formatting and enter only the token value.

  5. Keep aws/secretsmanager selected for the encryption key, and then choose Next.

    Note

    You aren't charged by Amazon KMS if you use the default Amazon managed key that Secrets Manager creates in your account.

  6. For Secret name, enter greengrass-TwilioAuthToken, and then choose Next.

    Note

    By default, the Greengrass service role allows Amazon IoT Greengrass to get the value of secrets with names that start with greengrass-. For more information, see secrets requirements.

  7. This tutorial doesn't require rotation, so choose disable automatic rotation, and then choose Next.

  8. On the Review page, review your settings, and then choose Store.

    Next, you create a secret resource in your Greengrass group that references the secret.

Step 2: Add a secret resource to a Greengrass group

In this step, you add a secret resource to the Greengrass group. This resource is a reference to the secret that you created in the previous step.

  1. In the Amazon IoT console navigation pane, under Manage, expand Greengrass devices, and then choose Groups (V1).

  2. Choose the group that you want to add the secret resource to.

  3. On the group configuration page, choose the Resources tab, and then scroll down to the Secrets section. The Secrets section displays the secret resources that belong to the group. You can add, edit, and remove secret resources from this section.

    Note

    Alternatively, the console allows you to create a secret and secret resource when you configure a connector or Lambda function. You can do this from the connector's Configure parameters page or the Lambda function's Resources page.

  4. Choose Add under the Secrets section.

  5. On the Add a secret resource page, enter MyTwilioAuthToken for the Resource name.

  6. For the Secret, choose greengrass-TwilioAuthToken.

  7. In the Select labels (Optional) section, the AWSCURRENT staging label represents the latest version of the secret. This label is always included in a secret resource.

    Note

    This tutorial requires the AWSCURRENT label only. You can optionally include labels that are required by your Lambda function or connector.

  8. Choose Add resource.

Step 3: Add a connector to the Greengrass group

In this step, you configure parameters for the Twilio Notifications connector and add it to the group.

  1. On the group configuration page, choose Connectors, and then choose Add a connector.

  2. On the Add connector page, choose Twilio Notifications.

  3. Choose the version.

  4. In the Configuration section:

    • For Twilio auth token resource, enter the resource that you created in the previous step.

      Note

      When you enter the resource, the ARN of Twilio auth token secret property is populated for you.

    • For Default from phone number, enter your Twilio-enabled phone number.

    • For Twilio account SID, enter your Twilio account SID.

  5. Choose Add resource.

Step 4: Create a Lambda function deployment package

To create a Lambda function, you must first create a Lambda function deployment package that contains the function code and dependencies. Greengrass Lambda functions require the Amazon IoT Greengrass Core SDK for tasks such as communicating with MQTT messages in the core environment and accessing local secrets. This tutorial creates a Python function, so you use the Python version of the SDK in the deployment package.

  1. From the Amazon IoT Greengrass Core SDK downloads page, download the Amazon IoT Greengrass Core SDK for Python to your computer.

  2. Unzip the downloaded package to get the SDK. The SDK is the greengrasssdk folder.

  3. Save the following Python code function in a local file named temp_monitor.py.

    import greengrasssdk import json import random client = greengrasssdk.client('iot-data') # publish to the Twilio Notifications connector through the twilio/txt topic def function_handler(event, context): temp = event['temperature'] # check the temperature # if greater than 30C, send a notification if temp > 30: data = build_request(event) client.publish(topic='twilio/txt', payload=json.dumps(data)) print('published:' + str(data)) print('temperature:' + str(temp)) return # build the Twilio request from the input data def build_request(event): to_name = event['to_name'] to_number = event['to_number'] temp_report = 'temperature:' + str(event['temperature']) return { "request": { "recipient": { "name": to_name, "phone_number": to_number, "message": temp_report } }, "id": "request_" + str(random.randint(1,101)) }
  4. Zip the following items into a file named temp_monitor_python.zip. When creating the ZIP file, include only the code and dependencies, not the containing folder.

    • temp_monitor.py. App logic.

    • greengrasssdk. Required library for Python Greengrass Lambda functions that publish MQTT messages.

    This is your Lambda function deployment package.

Now, create a Lambda function that uses the deployment package.

Step 5: Create a Lambda function in the Amazon Lambda console

In this step, you use the Amazon Lambda console to create a Lambda function and configure it to use your deployment package. Then, you publish a function version and create an alias.

  1. First, create the Lambda function.

    1. In the Amazon Web Services Management Console, choose Services, and open the Amazon Lambda console.

    2. Choose Create function and then choose Author from scratch.

    3. In the Basic information section, use the following values:

      • For Function name, enter TempMonitor.

      • For Runtime, choose Python 3.7.

      • For Permissions, keep the default setting. This creates an execution role that grants basic Lambda permissions. This role isn't used by Amazon IoT Greengrass.

    4. At the bottom of the page, choose Create function.

  2. Next, register the handler and upload your Lambda function deployment package.

    1. On the Code tab, under Code source, choose Upload from. From the dropdown, choose .zip file.

      
                The Upload from dropdown with .zip file highlighted.
    2. Choose Upload, and then choose your temp_monitor_python.zip deployment package. Then, choose Save.

    3. On the Code tab for the function, under Runtime settings, choose Edit, and then enter the following values.

      • For Runtime, choose Python 3.7.

      • For Handler, enter temp_monitor.function_handler

    4. Choose Save.

      Note

      The Test button on the Amazon Lambda console doesn't work with this function. The Amazon IoT Greengrass Core SDK doesn't contain modules that are required to run your Greengrass Lambda functions independently in the Amazon Lambda console. These modules (for example, greengrass_common) are supplied to the functions after they are deployed to your Greengrass core.

  3. Now, publish the first version of your Lambda function and create an alias for the version.

    Note

    Greengrass groups can reference a Lambda function by alias (recommended) or by version. Using an alias makes it easier to manage code updates because you don't have to change your subscription table or group definition when the function code is updated. Instead, you just point the alias to the new function version.

    1. From the Actions menu, choose Publish new version.

    2. For Version description, enter First version, and then choose Publish.

    3. On the TempMonitor: 1 configuration page, from the Actions menu, choose Create alias.

    4. On the Create a new alias page, use the following values:

      • For Name, enter GG_TempMonitor.

      • For Version, choose 1.

      Note

      Amazon IoT Greengrass doesn't support Lambda aliases for $LATEST versions.

    5. Choose Create.

Now you're ready to add the Lambda function to your Greengrass group.

Step 6: Add a Lambda function to the Greengrass group

In this step, you add the Lambda function to the group and then configure its lifecycle and environment variables. For more information, see Controlling execution of Greengrass Lambda functions by using group-specific configuration.

  1. On the group configuration page, choose the Lambda functions tab.

  2. Under My Lambda functions, choose Add.

  3. On the Add Lambda function page, choose TempMonitor for your Lambda function.

  4. For Lambda function version, choose Alias: GG_TempMonitor.

  5. Choose Add Lambda function.

Step 7: Add subscriptions to the Greengrass group

In this step, you add a subscription that enables the Lambda function to send input data to the connector. The connector defines the MQTT topics that it subscribes to, so this subscription uses one of the topics. This is the same topic that the example function publishes to.

For this tutorial, you also create subscriptions that allow the function to receive simulated temperature readings from Amazon IoT and allow Amazon IoT to receive status information from the connector.

  1. On the group configuration page, choose the Subscriptions tab, and then choose Add Subscription.

  2. On the Create a subscription page, configure the source and target, as follows:

    1. For Source type, choose Lambda function, and then choose TempMonitor.

    2. For Target type, choose Connector, and then choose Twilio Notifications.

  3. For the Topic filter, choose twilio/txt.

  4. Choose Create subscription.

  5. Repeat steps 1 - 4 to create a subscription that allows Amazon IoT to publish messages to the function.

    1. For Source type, choose Service, and then choose IoT Cloud.

    2. For Select a target, choose Lambda function, and then choose TempMonitor.

    3. For Topic filter, enter temperature/input.

  6. Repeat steps 1 - 4 to create a subscription that allows the connector to publish messages to Amazon IoT.

    1. For Source type, choose Connector, and then choose Twilio Notifications.

    2. For Target type, choose Service, and then choose IoT Cloud.

    3. For Topic filter, twilio/message/status is entered for you. This is the predefined topic that the connector publishes to.

Step 8: Deploy the Greengrass group

Deploy the group to the core device.

  1. Make sure that the Amazon IoT Greengrass core is running. Run the following commands in your Raspberry Pi terminal, as needed.

    1. To check whether the daemon is running:

      ps aux | grep -E 'greengrass.*daemon'

      If the output contains a root entry for /greengrass/ggc/packages/ggc-version/bin/daemon, then the daemon is running.

      Note

      The version in the path depends on the Amazon IoT Greengrass Core software version that's installed on your core device.

    2. To start the daemon:

      cd /greengrass/ggc/core/ sudo ./greengrassd start
  2. On the group configuration page, choose Deploy.

    1. In the Lambda functions tab, under the System Lambda functions section, select IP detector and choose Edit.

    2. In the Edit IP detector settings dialog box, select Automatically detect and override MQTT broker endpoints.

    3. Choose Save.

      This enables devices to automatically acquire connectivity information for the core, such as IP address, DNS, and port number. Automatic detection is recommended, but Amazon IoT Greengrass also supports manually specified endpoints. You're only prompted for the discovery method the first time that the group is deployed.

      Note

      If prompted, grant permission to create the Greengrass service role and associate it with your Amazon Web Services account in the current Amazon Web Services Region. This role allows Amazon IoT Greengrass to access your resources in Amazon services.

      The Deployments page shows the deployment timestamp, version ID, and status. When completed, the status displayed for the deployment should be Completed.

      For troubleshooting help, see Troubleshooting Amazon IoT Greengrass.

Note

A Greengrass group can contain only one version of the connector at a time. For information about upgrading a connector version, see Upgrading connector versions.

Test the solution

  1. On the Amazon IoT console home page, choose Test.

  2. For Subscribe to topic, use the following values, and then choose Subscribe. The Twilio Notifications connector publishes status information to this topic.

    Property

    Value

    Subscription topic

    twilio/message/status

    MQTT payload display

    Display payloads as strings

  3. For Publish to topic, use the following values, and then choose Publish to invoke the function.

    Property

    Value

    Topic

    temperature/input

    Message

    Replace recipient-name with a name and recipient-phone-number with the phone number of the text message recipient. Example: +12345000000

    { "to_name": "recipient-name", "to_number": "recipient-phone-number", "temperature": 31 }

    If you're using a trial account, you must add non-Twilio recipient phone numbers to a list of verified phone numbers. For more information, see Verify your Personal Phone Number.

    If successful, the recipient receives the text message and the console displays the success status from the output data.

    Now, change the temperature in the input message to 29 and publish. Because this is less than 30, the TempMonitor function doesn't trigger a Twilio message.

See also