RUM Roku Channel Monitoring Setup

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Overview

Datadog Real User Monitoring (RUM) enables you to visualize and analyze the real-time performance and user journeys of your channel’s individual users.

The Datadog Roku SDK supports BrightScript channels for Roku OS 10 and higher.

Setup

Declare the SDK as a dependency.
Specify application details in Datadog.
Initialize the library.
Instrument the channel.

Declare the SDK as a dependency

Using ROPM (recommended)

ROPM is a package manager for the Roku platform (based on NPM). If you’re not already using ROPM in your Roku project, read their Getting started guide. Once your project is set up to use ROPM, you can use the following command to install the Datadog dependency:

ropm install datadog-roku

Setup manually

If your project does not use ROPM, install the library manually by downloading the Roku SDK zip archive, and unzipping it in your project’s root folder.

Make sure you have a roku_modules/datadogroku subfolder in both the components and source folders of your project.

Specify application details in Datadog

Navigate to Digital Experience > Add an Application.
Select Roku as the application type and enter an application name to generate a unique Datadog application ID and client token.
To disable automatic user data collection for either client IP or geolocation data, uncheck the boxes for those settings. For more information, see RUM Roku Data Collected.

To ensure the safety of your data, you must use a client token. If you used only Datadog API keys to configure the dd-sdk-roku library, they would be exposed client-side in the Roku channel’s BrightScript code.

For more information about setting up a client token, see the Client Token documentation.

Initialize the library

In the initialization snippet, set an environment name. For more information, see Using Tags.

sub RunUserInterface(args as dynamic)
    screen = CreateObject("roSGScreen")
    scene = screen.CreateScene("MyScene")
    screen.show()

    datadogroku_initialize({
        clientToken: "<CLIENT_TOKEN>",
        applicationId: "<APPLICATION_ID>"
        site: "us1",
        env: "<ENV_NAME>",
        sessionSampleRate: 100, ' the percentage (integer) of sessions to track
        launchArgs: args
    })

    ' complete your channel setup here
end sub

sub RunUserInterface(args as dynamic)
    screen = CreateObject("roSGScreen")
    scene = screen.CreateScene("MyScene")
    screen.show()

    datadogroku_initialize({
        clientToken: "<CLIENT_TOKEN>",
        applicationId: "<APPLICATION_ID>"
        site: "eu1",
        env: "<ENV_NAME>",
        sessionSampleRate: 100, ' the percentage (integer) of sessions to track
        launchArgs: args
    })

    ' complete your channel setup here
end sub

sub RunUserInterface(args as dynamic)
    screen = CreateObject("roSGScreen")
    scene = screen.CreateScene("MyScene")
    screen.show()

    datadogroku_initialize({
        clientToken: "<CLIENT_TOKEN>",
        applicationId: "<APPLICATION_ID>"
        site: "us3",
        env: "<ENV_NAME>",
        sessionSampleRate: 100, ' the percentage (integer) of sessions to track
        launchArgs: args
    })

    ' complete your channel setup here
end sub

sub RunUserInterface(args as dynamic)
    screen = CreateObject("roSGScreen")
    scene = screen.CreateScene("MyScene")
    screen.show()

    datadogroku_initialize({
        clientToken: "<CLIENT_TOKEN>",
        applicationId: "<APPLICATION_ID>"
        site: "us5",
        env: "<ENV_NAME>",
        sessionSampleRate: 100, ' the percentage (integer) of sessions to track
        launchArgs: args
    })

    ' complete your channel setup here
end sub

sub RunUserInterface(args as dynamic)
    screen = CreateObject("roSGScreen")
    scene = screen.CreateScene("MyScene")
    screen.show()

    datadogroku_initialize({
        clientToken: "<CLIENT_TOKEN>",
        applicationId: "<APPLICATION_ID>"
        site: "ap1",
        env: "<ENV_NAME>",
        sessionSampleRate: 100, ' the percentage (integer) of sessions to track
        launchArgs: args
    })

    ' complete your channel setup here
end sub

Sample RUM sessions

To control the data your application sends to Datadog RUM, you can specify a sampling rate for RUM sessions while initializing the RUM Roku SDK as a percentage between 0 and 100. You can specify the rate with the sessionSampleRate parameter.

Instrument the channel

See Track RUM Resources to enable automatic tracking of all your resources, and Enrich user sessions to add custom global or user information to your events.

Track RUM Views

To split user sessions into logical steps, manually start a View using the following code. Every navigation to a new screen within your channel should correspond to a new RUM View.

    viewName = "VideoDetails"
    viewUrl = "components/screens/VideoDetails.xml"
    m.global.datadogRumAgent.callfunc("startView", viewName, viewUrl)

Track RUM Actions

RUM Actions represent the interactions your users have with your channel. You can forward actions to Datadog as follows:

    targetName = "playButton" ' the name of the SG Node the user interacted with
    actionType = "click" ' the type of interaction, should be one of "click", "back", or "custom" 
    m.global.datadogRumAgent.callfunc("addAction", { target: targetName, type: actionType})

Track RUM errors

Whenever you perform an operation that might throw an exception, you can forward the error to Datadog as follows:

    try
        doSomethingThatMightThrowAnException()
    catch error
        m.global.datadogRumAgent.callfunc("addError", error)
    end try

Sending data when device is offline

RUM ensures availability of data when your user device is offline. In case of low-network areas, or when the device battery is too low, all the RUM events are first stored on the local device in batches.

Each batch follows the intake specification. They are sent as soon as the network is available, and the battery is high enough to ensure the Datadog SDK does not impact the end user’s experience. If the network is not available while your application is in the foreground, or if an upload of data fails, the batch is kept until it can be sent successfully.

This means that even if users open your application while offline, no data is lost. To ensure the SDK does not use too much disk space, the data on the disk is automatically discarded if it gets too old.