Adobe AD0-E902 Adobe Workfront Fusion Professional Exam Practice Test

Understanding the Scenario:

The image represents a Workfront Fusion scenario with a Workfront module, HTTP modules, and routers splitting the execution path.

The goal is to reuse multiple fields from the Workfront module (e.g., data extracted or processed earlier in the flow) as mapped expressions in HTTP PUT requests located in the bottom paths.

Why Option A is Correct:

Set Multiple Variables Module: This module allows you to define and store multiple variables at a single point in the scenario (e.g., after the Workfront module). These variables can then be reused throughout subsequent steps in the scenario.

Get Multiple Variables Module: By placing this module between the Text Parser and the bottom Router, you can retrieve all previously stored variables, ensuring consistent access across all branches of the flow. This avoids redundancy and ensures the data is easily accessible for each HTTP request in the bottom paths.

Why the Other Options are Incorrect:

Option B ("Set Multiple Variables after Workfront, Get Variables before each HTTP module"): This is partially correct but less efficient. Adding multiple Get Variable modules before each HTTP request results in repetitive configuration and increases maintenance complexity.

Option C ("Set Variable and Get Variable for each HTTP module"): Using individual Set and Get Variable modules increases duplication. This approach requires separate variables for each data point, which is inefficient compared to using the Set/Get Multiple Variables module for multiple fields at once.

Steps to Configure the Solution:

After the Workfront module:

Add aSet Multiple Variablesmodule.

Define all the fields required for the HTTP PUT requests as variables, mapping them from the Workfront module outputs.

Between the Text Parser and the bottom Router:

Add aGet Multiple Variablesmodule.

Retrieve the previously stored variables, ensuring they are accessible for all paths.

In the HTTP modules on each bottom path:

Use the retrieved variables for mapping in the PUT requests.

How This Solves the Problem:

This approach centralizes variable management, making it easier to access and modify data as needed.

It avoids redundancy, as variables are defined once and reused across all paths, reducing the risk of errors and ensuring consistency.

References and Supporting Documentation:

Adobe Workfront Fusion: Variables Module Overview

Workfront Community: Efficient Use of Variables in Fusion

Key Scenario Settings:

Adobe Workfront Fusion provides settings to control the execution of scenarios. These settings impact how the scenario behaves when it runs, especially under conditions such as errors or long-running processes.

Explanation of Correct Options:

Option A ("Number of consecutive errors"):

This setting determines the maximum number of consecutive errors allowed before the scenario execution halts.

By adjusting this value, users can define how resilient the scenario is to temporary failures in modules or external systems.

Option B ("Max number of cycles"):

This setting limits the maximum number of cycles (iterations) the scenario performs in a single run.

It prevents scenarios from running indefinitely or consuming excessive resources in cases of large datasets.

Why the Other Options are Incorrect:

Option C ("Number of bundles per run"): This value is not adjustable in the scenario settings. Instead, the system dynamically determines how many bundles (data packets) are processed per cycle.

Option D ("Number of consecutive runs"): Workfront Fusion does not have a setting for the number of consecutive runs. Scenarios are executed based on schedules, triggers, or manual execution.

Steps to Adjust Scenario Settings:

Open the scenario in Adobe Workfront Fusion.

Click thegear iconin the top-right corner to accessScenario Settings.

Locate and adjust the following fields:

Number of consecutive errors: Set a value based on acceptable failure tolerance.

Max number of cycles: Specify the maximum number of iterations allowed.

Save and activate the scenario.

References and Supporting Documentation:

Adobe Workfront Fusion Official Documentation: Scenario Settings

Workfront Community: Best Practices for Scenario Optimization

In this scenario, the error consistently arises due to the unavailability of a third-party service during high traffic times. This is a temporary issue and does not indicate a problem with the data or process. The recommended approach in such cases is to configure the scenario to retry failed executions:

Update Scenario Settings:

In Workfront Fusion, you can configure scenarios to automatically retry a failed execution.

This option ensures that temporary issues, like service unavailability, are retried after a delay, reducing the chances of the scenario being stopped permanently.

This is particularly useful when dealing with network traffic spikes or third-party API throttling.

Why Not Other Options?

B. Update the Module settings to automatically ignore failed executions: Ignoring failed executions would cause incomplete or incorrect data to flow through the scenario, leading to potential downstream issues.

C. Add an error handler to the Module and select a Break directive: While error handlers are useful, the Break directive stops the scenario from processing further, which is not ideal for a temporary issue.

D. Add an additional route after the failing module with a repeater: Adding a repeater increases complexity and is unnecessary when the retry option is already available in scenario settings.

References:

Adobe Workfront Fusion Documentation: Scenario Settings and Error Handling

Experience League Community: Handling API Rate Limits and Errors in Workfront Fusion

Understanding the Requirement:

The desired output format for the project name in ServiceNow is:Two-Digit Year - Reference Number - Project Name

This requires dynamically constructing a string by combining:

The current year in a two-digit format.

ThereferenceNumber(a variable or input).

Thename(a variable or input, likely the project name).

Why Option C is Correct:

The concat function combines multiple strings into a single string.

Expression:

concat(formatDate(now;YY), " - ", referenceNumber, " - ", name)

This ensures proper formatting with hyphens and spaces between the elements.

Breaking Down the Components:

formatDate(now;YY): Retrieves the current year in a two-digit format (e.g., "23" for 2023).

" - ": Adds the required separator.

referenceNumber: Dynamically adds the reference number.

name: Dynamically adds the project name.

Why the Other Options are Incorrect:

Option A ("formatDate(now;YY) - referenceNumber - name"):

This is not valid because it does not explicitly use a string concatenation function.

Option B ("join(formatDate(now;YY) - referenceNumber - name"):

The join function is used for concatenating elements of an array, not individual strings. Since the inputs are not in an array, this function will not work.

How This Solves the Problem:

The concat function correctly constructs the string with the desired format, dynamically generating the project name for ServiceNow based on the given inputs.

References and Supporting Documentation:

Adobe Workfront Fusion Functions Documentation

Workfront Community: Using the concat Function

Step by Step Comprehensive Detailed Explanation:

Scenario Summary:

The source system provides a list of users, job roles, and departments.

The destination system requires a mapping of job roles to different departments.

Updates to this mapping are infrequent, and there is a concern for more security than a spreadsheet offers.

Option Analysis:

A. Switch: A switch function in Workfront Fusion is used to make decisions based on specific conditions but does not maintain persistent data like mappings over time. It is not suitable for storing mappings that require infrequent updates.

B. Spreadsheet: Spreadsheets may be simple to use but are less secure and not ideal for integrating with Workfront Fusion workflows due to their lack of direct integration features or control over changes.

C. Data store: Adata storein Workfront Fusion is specifically designed for storing persistent data, such as mappings or reference tables. It is secure, easy to manage, and integrates seamlessly with workflows, making it the best choice for this use case.

D. Table aggregator: A table aggregator is used for combining or processing data within a workflow but is not suitable for storing persistent mappings outside of a running scenario.

Why Data Store is Appropriate:

Persistence: A data store is ideal for maintaining the job role and department mappings across scenarios.

Security: It is managed within Workfront Fusion, offering better control and access restrictions compared to a spreadsheet.

Ease of Integration: Data stores can be directly queried or updated in Fusion workflows, allowing seamless handling of mappings.

Scalability: While updates are infrequent, the data store can handle changes easily and scale if the volume of mappings increases.

Implementation in Workfront Fusion:

Create adata storefor job roles and departments in Workfront Fusion.

Set up fields for Job Role and Department in the data store.

Use Workfront Fusion scenarios to retrieve and update mappings from this data store based on requirements.

References:This approach aligns with the Workfront Fusion documentation on data stores, which are designed for secure and efficient storage of persistent data used across scenarios. See Workfront Fusion resources for data store setup and use cases for further details.

Understanding the Requirement:

The user needs to view the exactAPI requestand the correspondingresponsea module executes in Adobe Workfront Fusion.

This is critical for debugging, troubleshooting, or validating API operations within scenarios.

Why Option B is Correct:

Execution History:

Theexecution historylogs detailed information about every module that runs in a scenario.

It provides access to theAPI requestsent, including the headers, parameters, and body.

It also displays theAPI responsereceived, including HTTP status codes, returned data, and error messages (if applicable).

This feature is indispensable for debugging and verifying the behavior of modules.

Why the Other Options are Incorrect:

Option A ("Using the Bundle Inspector"):

The Bundle Inspector provides a view of processed data bundles but does not include API request/response details.

Option C ("Using the Fusion DevTool scenario debugger"):

Fusion does not have a specific "DevTool debugger." The execution history serves this purpose.

Option D ("Using the Fusion DevTool error evaluator"):

While error logs help evaluate issues, they do not directly show the API request/response unless an error occurs. Execution history is a more comprehensive source of this data.

Steps to View Execution History:

Run the scenario or inspect a previously executed scenario.

Navigate to theExecution Historytab for the scenario.

Select a specific module to view itsdetails.

Inspect theAPI request and response, which includes all relevant parameters and data.

References and Supporting Documentation:

Adobe Workfront Fusion Documentation: Execution History

Workfront Community: Debugging with Execution History

Step by Step Comprehensive Detailed Explanation:

Understanding the Error:

The error message [403] The caller does not have permission is aGoogle API permission error.

It typically indicates that the user or application does not have the required access rights to perform the requested action on the Google Slide presentation.

Option Analysis:

A. Reauthorize their Google connection:

This step might be necessary if the user's credentials or token have expired, but this is not the primary issue here since the error specifically states apermission problem.

B. Update Google sharing permissions for the document:

Correct. The error suggests that the Google Slide document has not been shared with the user or service account being used in Fusion. Updating the sharing settings to grant proper permissions (e.g., "Editor" or "Viewer" access) will resolve the issue.

C. Contact Workfront Support to troubleshoot the root cause:

While Workfront Support can help with Fusion-related issues, this error originates from Google and is unrelated to Workfront's systems.

D. Search the Google status site to determine the cause:

The Google status site is useful for identifying system-wide outages, but this is a user-specific permission issue, not a Google platform-wide problem.

Steps to Resolve:

Open the Google Slide presentation.

Update the sharing permissions:

Grant access to the Google account or service account being used in Fusion.

Ensure the account has at leastEditoror appropriate access rights.

Save the changes and rerun the Fusion scenario.

Why Updating Permissions is Best:

This action directly addresses the root cause of the error, which is inadequate access rights.

Once permissions are updated, Fusion will be able to connect to and manipulate the Google Slide document as intended.

References:The [403] The caller does not have permission error is documented in Google API troubleshooting guides, which recommend verifying and updating document sharing settings for resolving access issues.

Understanding Instant and Polling Triggers:

Instant Triggers:

Rely on webhooks to receive real-time data from a third-party system.

The external system sends a notification (webhook) to Fusion whenever an event occurs, triggering the scenario immediately.

Polling Triggers:

Regularly check (poll) the third-party system for new or updated records at scheduled intervals.

These are slower because they involve repeated API requests.

Why Option B is Correct:

Speed and Efficiency:

Instant triggers process data faster because they act immediately upon receiving a webhook. Polling triggers, on the other hand, may take time depending on the polling frequency and can result in unnecessary delays.

Reduced Load on Systems:

Instant triggers generate fewer API calls than polling triggers, which continuously check for new records even if no changes have occurred.

Best Practice: Use instant triggers whenever supported by the third-party system to ensure faster and more efficient scenario execution.

Why the Other Options are Incorrect:

Option A ("Instant triggers store received webhooks in a queue"):

Webhooks do not store data in a queue; they simply notify Fusion of events in real-time. Polling triggers also do not store records but remember the last processed record.

Option C ("A user must set up a webhook in Fusion"):

Instant triggers require setting up webhooks in the external system, not in Fusion. Fusion provides the webhook endpoint, but the user must configure the source system to send data.

Option D ("Only polling triggers can be set to run on a schedule"):

This is incorrect because instant triggers do not rely on schedules; they operate in real-time. Polling triggers, however, run on schedules and are used when instant triggers are unavailable.

References and Supporting Documentation:

Adobe Workfront Fusion Triggers Documentation

Workfront Community: Differences Between Instant and Polling Triggers

Instant triggers are the preferred option when available, as they provide real-time data processing with greater speed and efficiency than polling triggers.

When dealing with intermittent errors, such as "service is not reachable," the default error handling in Adobe Workfront Fusion is often sufficient to improve execution success rates.

Default Error Handling:

Fusion automatically retries operations when transient errors, such as network or connection issues, occur.

By leveraging this built-in functionality, the system will attempt to re-execute the failing module after a brief delay, which is often enough for the external service to become reachable again.

Why Not Other Options?

A. Adding an error handler that will notify the system owner: While notifying the owner can be useful for monitoring purposes, it does not directly address improving the success rate of executions.

C. Adding a Break directive to the module: Adding a Break directive will stop the execution entirely, which is counterproductive in this case, as the service typically becomes reachable again after a short time.

References:

Adobe Workfront Fusion Documentation: Default Error Handling Mechanisms

Experience League Community: Managing Intermittent API Errors in Fusion

Understanding the Date Transformation:

Input:March 3, 2021, 10:34 AM

Output:March 1, 2021, 10:34 AM

The transformation subtracts2 daysfrom the input date without altering the time.

Why Option A is Correct:

subDays(now,2) subtracts exactly 2 days from the given date and time.

It preserves the time component of the input (10:34 AM) while shifting the date backward by 2 days, which matches the given output.

Why the Other Options are Incorrect:

Option B ("addHours(now; -48)"): While subtracting 48 hours also results in a 2-day difference, this approach directly modifies the time. The resulting time could shift if the operation crosses daylight saving changes or edge cases with leap seconds. It is less reliable compared to subDays.

Option C ("addDays(today; -4)"): This would subtract 4 days, which does not match the transformation shown in the example.

References and Supporting Documentation:

Adobe Workfront Fusion: Date and Time Functions

Workfront Community: Using Date and Time Expressions

Understanding the Requirement:

The query returns only a partial list of possible values.

The task is to ensure that all results are processed by iterating through multiple queries or pages of data.

Why Option B ("Repeater") is Correct:

TheRepeatermodule is designed to repeat an operation a specified number of times or until a condition is met.

It is commonly used for querying paginated data or when a system limits the number of records returned in a single request.

In this case, the Repeater ensures all possible values are queried by making additional requests to retrieve subsequent pages or results.

Why the Other Options are Incorrect:

Option A ("Aggregator"):

The Aggregator combines multiple data bundles into a single output. It does not handle iterative queries or pagination.

Option C ("Iterator"):

The Iterator splits an array into individual items for processing. It does not handle querying for additional data or looping through requests.

Option D ("Router"):

The Router splits the flow of a scenario into multiple paths based on conditions. It is unrelated to iterative querying.

Steps to Configure the Repeater:

Add theRepeatermodule to your scenario.

Configure the number of repetitions or the condition to continue querying (e.g., based on the presence of additional data).

Link the Repeater to the module responsible for retrieving the data, ensuring it processes all available results.

How This Solves the Problem:

The Repeater module ensures that all possible results are queried by iteratively sending requests until no more data is available.

References and Supporting Documentation:

Adobe Workfront Fusion: Repeater Module Documentation

Workfront Community: Using Flow Control Modules

Understanding the Requirement:

The input is an array containing objects, and the goal is to extract all the stat.name values into acomma-separated string.

Example Input:

[

{

"base_stat": 48,

"effort": 1,

"stat": {

"name": "hp",

"url": "https://pokeapi.co/api/v2/stat/1/"

}

},

{

"base_stat": 48,

"effort": 0,

"stat": {

"name": "attack",

"url": "https://pokeapi.co/api/v2/stat/2/"

}

}

]

Example Output:"hp, attack"

Why Option B is Correct:

The expressionjoin(map(2.data: stats[]; stats.stat.name); ", "):

map: Iterates through each object in the array (2.data: stats[]) and extracts the stat.name field.

join: Combines the extracted values into a single string, separated by a comma and space (", ").

Breaking it down:

map(2.data: stats[]; stats.stat.name) → Creates an array of names: ["hp", "attack"].

join(...; ", ") → Converts the array into the string "hp, attack".

Why the Other Options are Incorrect:

Option A: join(2.data: stats[]; stat.name; ", ")

This syntax is incorrect because it attempts to directly access stat.name within the join function without first mapping the values.

Option C: join(map(2.data: stats[]; stat.name); ", ")

The mapping references stat.name directly but does not account for the nested structure (stats.stat.name).

Option D: join(flatten(2.data: stats[]); ", ")

The flatten function is unnecessary here as the data is already structured. It would not properly extract the stat.name values.

Steps to Implement in Workfront Fusion:

Add aMapping/Transformation Module.

Use the join(map(...)) function as described to transform the input array into a comma-separated string.

Test the output to ensure it correctly generates the desired format.

How This Solves the Problem:

The map function ensures the proper extraction of nested stat.name values.

The join function combines these values into the desired format efficiently.

References and Supporting Documentation:

Adobe Workfront Fusion Functions Documentation

Workfront Community: Using Map and Join Functions

The combination of map and join ensures that the stat names are extracted and formatted into a single comma-separated string, as required.

Step-by-Step Explanation

Purpose of the Query:

The task is to retrievefield optionsfrom acustom form field. This operation involves fetching data, not creating or modifying it, which requires a GET method.

Correct API Structure:

The URL must follow Workfront's API structure:

ruby

Copy

https://{your-workfront-domain}/attask/api/{version}/{endpoint}

OptionBfollows this standard structure, where:

wfdomain.workfront.com is the placeholder for the Workfront instance.

/attask/api/v12.0 specifies the API version.

/PARAM/search is the endpoint to search for parameters or fields.

Why Not Other Options?

A: The use of POST is incorrect because it is meant for creating or updating resources, not retrieving data. Additionally, the URL structure is incorrect and includes unnecessary query strings (username, password) not relevant for this operation.

C: While the method GET is correct, the URL (PARAM/search) is incomplete and lacks the required Workfront API structure, making it invalid.

References

Workfront API Documentation: Querying and Retrieving Custom Form Field Data

Experience League Community: Best Practices for Using GET Methods in Workfront API=========================

Step by Step Comprehensive Detailed Explanation:

Problem Summary:

A trigger module is causing excessive iteration processing thousands of bundles unnecessarily.

The goal is to optimize the scenario by reducing the number of processed bundles.

Option Analysis:

A. Configure the trigger module to reduce the maximum number of results:

Reducing the maximum number of results processed per cycle limits the number of bundles processed at a time, but it does not solve the root issue of processing unnecessary records.

B. Configure the trigger module to filter out unnecessary records:

Filtering at the trigger level ensures that only the required records are fetched for processing, addressing the root cause of excessive bundle processing. This is the correct answer.

C. Configure scenario settings to reduce cycles per execution:

Limiting execution cycles reduces the overall runtime but does not directly address the number of bundles being processed unnecessarily.

Why Filtering at the Trigger is Best:

Efficiency: By setting up filters directly in the trigger, you ensure that only relevant data is retrieved.

Performance: Reducing the number of unnecessary bundles improves processing speed and reduces resource usage.

Accuracy: Filtering ensures only actionable data enters the workflow, maintaining scenario integrity.

How to Implement:

Open the trigger module settings.

Add appropriate filters to exclude unnecessary records. For example:

Add conditions to filter out old data or irrelevant statuses.

Use fields like updatedDate, status, or any other criteria relevant to the workflow.

Test the trigger module to verify that only relevant bundles are retrieved.

References:These answers are based on Workfront Fusion best practices for optimizing scenarios, as outlined in the Fusion documentation. Proper use of mapping panel functions and trigger filters ensures scenarios are efficient and scalable.

Step by Step Comprehensive Detailed Explanation:

Understanding the Scenario:

The diagram shows two routes, each leading to an aggregator module (Aggregator 1 and Aggregator 2).

The bundle inspector indicates different output counts for the two aggregators: Aggregator 1 displays 1, and Aggregator 2 displays 10.

Option Analysis:

A. Aggregator 1’s route is set to process the 1st bundle only, and Aggregator 2's route is set to process all bundles:

Incorrect. Aggregators process data from their input modules based on their configuration. While filters or limits might be applied earlier in the flow, the scenario does not suggest that the aggregator's configuration explicitly limits bundles in this way.

B. The source module for the aggregators are different:

Correct. The two aggregators receive input from different modules. For example, Aggregator 1 might aggregate bundles from "Projects," which outputs a single bundle, while Aggregator 2 aggregates bundles from "Issues," which outputs 10 bundles. This explains the differing numbers in the bundle inspector.

C. Aggregator 2 displays a 10 in the bundle inspector because it is set to repeat 10 times:

Incorrect. Aggregators do not "repeat" a specific number of times. Instead, they process the input bundles passed to them and output a result based on the aggregation logic.

D. The scenario's router is set to only allow projects through the route to Aggregator 1 and only allows tasks through the route to Aggregator 2:

Incorrect. While the router might direct specific bundles (e.g., "Projects" to Aggregator 1 and "Issues" to Aggregator 2), the difference in bundle counts is determined by the source modules, not by the router's configuration alone.

Why Source Modules Determine Bundle Counts:

Each aggregator processes data from a source module. If the source module outputs different numbers of bundles, the aggregators will show different bundle counts.

In this example, "Projects" might output only 1 bundle (e.g., 1 project), while "Issues" outputs 10 bundles (e.g., 10 issues).

How to Verify:

Inspect the source modules feeding into each aggregator. Check the number of bundles they produce during the scenario run.

Confirm that the aggregators are aggregating based on their respective inputs.

References:This explanation aligns with Workfront Fusion's handling of bundles and aggregation logic. Differences in bundle counts at the aggregator level are typically due to differences in the source module outputs, as shown in the scenario.