AD0-E902 Exam Dumps : Adobe Workfront Fusion Professional

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

Understanding the Issue:

The customer is syncing20,000+ Salesforce Opportunitieswith Workfront projects using a scheduled Fusion scenario.

After running for 40 minutes, the scenario unexpectedly stops.

Why Option C is Correct:

Workfront Fusion Execution Timeout:

Fusion scenarios have a default execution timeout of40 minutesper run.

If the scenario exceeds this time limit, Fusion automatically stops the execution to avoid resource overuse.

Handling Large Data Sets:

Scenarios involving large datasets (like syncing 20,000+ records) may require optimizations, such as breaking the data into smaller chunks using paginated requests or iterators.

In this case, the scenario stopped because the execution timeout was reached, not due to API limits or webhook restrictions.

Why the Other Options are Incorrect:

Option A ("Workfront API call limit"):

While Workfront does have API rate limits, they are generally generous and not the reason for the scenario stopping. Fusion scenarios are designed to manage API calls efficiently.

Option B ("Fusion times out if processing over 2000 records in 40 minutes"):

This is incorrect because Fusion does not have a hard limit on the number of records processed in 40 minutes. The timeout is time-based, not record-based.

Option D ("Workfront API stops webhooks after 2000 hits in 10 minutes"):

This does not apply to Fusion scenarios. Webhooks are separate from the API calls initiated by Fusion.

How to Resolve the Issue:

Split the Data: Use pagination or batch processing to divide the 20,000+ records into smaller chunks (e.g., 1,000 or 2,000 records per run).

Adjust Scheduling: Schedule the scenario to run more frequently with smaller batches, ensuring all records are synced over multiple runs.

Use Iterators: Add an Iterator module to loop through smaller subsets of data, preventing the scenario from exceeding the execution timeout.

Steps to Optimize the Scenario:

Add aSearch Moduleto retrieve opportunities in smaller batches (e.g., using limits or pagination parameters).

Use aRepeater Moduleto process each batch iteratively.

Save the scenario and schedule it to run nightly or more frequently, depending on the sync requirements.

References and Supporting Documentation:

Adobe Workfront Fusion: Execution Timeout Limits

Workfront Community: Managing Large Data Sets in Fusion Scenarios

By optimizing the scenario to handle smaller batches of data, the admin can avoid the execution timeout issue and ensure successful syncing of Salesforce Opportunities with Workfront projects.

Understanding the Scenario:

The scenario includes two modules:

Workfront Search Module: Fetches data (likely project details).

Tools Module: Manipulates and sets multiple variables.

What the Images Show:

Workfront Search Module (First Module):

The output indicates29 bundlesof project data were retrieved.

Each bundle contains fields such asID,name, andplannedCompletionDate.

Tools Module (Second Module):

The data from the Workfront module is processed to set variables likeProject NameandProject Due Date.

Output includes transformed values, such as appending the approver’s name ("Joan Harris") to the project name and updating the project due date.

Why Option C is Correct:

Delivery of 29 Bundles: The Workfront module retrieved 29 project bundles and passed them to the Tools module.

Data Manipulation in Tools Module: The second module modified the data, such as appending "Joan Harris" to the project name and updating the due date to a different value. This is evident from the changes in the output of the Tools module compared to the input from the Workfront module.

Why the Other Options are Incorrect:

Option A:

Incorrect because theWorkfront moduleretrieved 29 bundles, not just 1 bundle. Additionally, the project name and planned completion date were manipulated in the second module, not the first.

Option B:

Incorrect because the retrieved data pertains to projects, not tasks.

Option D:

Incorrect because theinput and output fields in the Tools moduleare not identical. The data was clearly manipulated within the Tools module.

How This Scenario Operates:

The Workfront module fetches raw data, which is then processed in the Tools module. The processed variables (e.g., modified project names and due dates) are prepared for further use in subsequent scenario steps.

References and Supporting Documentation:

Adobe Workfront Fusion Documentation: Bundle Inspector

Workfront Community: Using Tools Module for Data Manipulation

The correct interpretation is that the first module delivered 29 bundles to the second module, where data manipulations occurred to modify the project name and planned completion date.