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| Section | Objectives |
|---|---|
| Data Integration and Management | - Data transformation and mapping
|
| API and Connectivity | - Salesforce APIs
|
| Integration Architecture Fundamentals | - Integration concepts and patterns
|
| Middleware and Integration Platforms | - Integration middleware
|
| Security and Identity | - Authentication mechanisms
|
| Event-Driven Architecture | - Asynchronous integration
|
>> Integration-Architect Detailed Answers <<
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NEW QUESTION # 117
Customer is evaluating Platform Events solution and would like help in comparing/contrasting it with Outbound Message for a real-time / near-real time needs. They expect 3,000 consumers of messages from Salesforce.
Which three considerations should be evaluated and highlighted when deciding between the solutions?
Choose 3 answers
Answer: A,C,D
Explanation:
Explanation
Both Platform Events and Outbound Message offer declarative means for asynchronous near-real time needs.
They aren't best suited for real-time integrations (A). In both Platform Events and Outbound Messages, the event messages are retried by and delivered in sequence, and only once. Salesforce ensures there is no duplicate message delivery (B). Message sequence is possible in Outbound Message but not guaranteed with Platform Events. Both offer very high reliability. Fault handling and recovery are fully handled by Salesforce Number of concurrent subscribers to Platform Events is capped at 2,000. An Outbound Message configuration can pass only 100 notifications in a single message to a SOAP end point (D). Both Platform Events and Outbound Message are highly scalable. However, unlike Outbound Message, only Platform Events have Event Delivery and Event Publishing limits to be considered (E). Reference: Salesforce Integration Architecture Designer Resource Guide, page 23
NEW QUESTION # 118
An enterprise customer is implementing Salesforce for Case Management. Based on the landscape (Email, Order Management, Data Warehouse, Case Management), what should the integration architect evaluate?
Answer: A
Explanation:
The evaluation of an integration landscape is a process of rationalization. The goal is to identify which legacy systems Salesforce will replace (System Retirement) and which systems it must coexist with (Integration).
In this scenario, Salesforce is being implemented for Case Management. Salesforce Service Cloud is the industry leader for this specific function. Therefore, the legacy Case Management System should be retired.
Any architecture that suggests "integrating" Salesforce with the legacy Case Management system (Options A and B) is creating a redundant and complex "dual-master" scenario that increases technical debt.
To provide a successful support experience, Salesforce needs to be the central "Engagement Layer," which requires integration with the remaining ecosystem:
* Email Management System: To support "Email-to-Case" and ensure all customer communications are captured within the Salesforce Case record.
* Order Management System (OMS): Support agents often need to verify purchase history or shipping status to resolve a case. A "Data Virtualization" or "Request-Reply" integration with the OMS is vital.
* Data Warehouse: For long-term historical reporting and cross-functional analytics, Salesforce must push case data to the enterprise Data Warehouse.
By evaluating the integration with the Data Warehouse, Order Management, and Email Management systems, the architect ensures that Salesforce is enriched with the context it needs to resolve cases while simultaneously retiring the redundant legacy support system.
NEW QUESTION # 119
Northern Trail Outfitters (NTO) uses different shipping services for each of the 34 countries it serves.
Services are added and removed frequently to optimize shipping times and costs. Sales representatives need to select between valid service(s) for the customer's country and request shipping estimates from that service.
Which solution should an architect propose?
Answer: B
Explanation:
When an organization must interact with multiple external services (34 different shipping providers) that change frequently, the primary architectural goal is to decouple Salesforce from the specific endpoints and protocols of those services.11 The architect should propose us12ing middleware to abstract the call. By introducing a middleware layer (such as an ESB or iPaaS), Salesforce makes a single, standardized call to the middleware, passing the country and order details. The middleware then handles the "Process Orchestration":
* Service Routing: Determining which shipping service is valid for the specified country.
* Protocol Mediation: Translating the standard Salesforce request into the specific format (REST, SOAP, XML, etc.) required by each individual shipping provider.
* Maintenance: When a shipper is added or removed, the change is made in the middleware without requiring any code or metadata updates in Salesforce.
Option A (Picklists) creates a high administrative burden and does not solve the underlying technical complexity of making callouts to dozens of different APIs. Option B (Platform Events) is asynchronous and would introduce unnecessary latency for a sales rep who needs an estimate "on the spot" to complete an order.
Middleware abstraction provides a scalable, maintainable, and agile architecture that allows NTO to optimize its shipping operations without disrupting the CRM user experience.
NEW QUESTION # 120
An integration architect has built a Salesforce application that integrates multiple systems and keeps them synchronized via Platform Events. What is taking place if events are only being published?
Answer: C
Explanation:
The timing of Platform Event publishing is a critical detail for an Integration Architect, as it affects data consistency and transaction integrity. In Salesforce, the default and most common behavior for publishing Platform Events from Apex is "Publish After Commit." When an architect chooses the "Publish After Commit" setting (defined at the event level), the events are held in a buffer and are only released to the event bus after the Apex transaction completes successfully. This ensures that if the database transaction fails and rolls back, the event-which might trigger external actions- is never sent. This prevents "ghost" events where an external system is told to process data that was never actually saved to the Salesforce database.
The question implies a standard scenario where events are being "published" into the bus. In this state, the events have passed the transaction boundary. If the events were only "being published from Apex" (Option C), it doesn't describe the state of the delivery or the transaction. Option B is technically incorrect for standard event publishing logic, as Salesforce explicitly separates the event bus from the database commit to maintain atomicity.
Understanding this "After Commit" behavior is vital when designing synchronization patterns. If the architect requires the event to be sent regardless of whether the transaction succeeds (e.g., for logging a failure), they would need to configure the event as "Publish Immediately." However, in a standard synchronization use case where events are "only being published," it signifies that the source transaction has finalized, and the messages are now available for subscribers (like middleware or other Salesforce orgs) to consume.
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NEW QUESTION # 121
Northern Trail Outfitters' (NTO) Salesforce org usually goes through 8k-10k batches a day to synch data from external sources. NTO's Integration Architect has received requirements for a new custom object, FooBarc, for which 90M records will need to be loaded into the org. Once complete, 20GB (about 30M records) needs to be extracted to an external auditing system.
What should the architect recommend using to meet these requirements in a day?
Answer: A
Explanation:
Answer D is valid because using Bulk API 2.0 for both inserting and querying data can meet the requirements of loading and extracting large volumes of data in a day. Bulk API 2.0 is a RESTful API that allows creating, updating, deleting, or querying millions of records asynchronously by uploading or downloading CSV or JSON files. Bulk API 2.0 has several advantages over Bulk API 1.0, such as:
It does not count against the daily limit of 5,000 batches per rolling 24-hour period.
It supports PK Chunking for queries, which automatically splits large data sets into manageable chunks based on the primary key.
It simplifies the job lifecycle and reduces the number of API calls needed to perform a bulk operation.
Answer A is not valid because using Bulk API 2.0 for inserting data and REST API for querying data is not an optimal solution for handling large volumes of data in a day. REST API is a synchronous API that allows creating, updating, deleting, or querying individual records or small batches of records using HTTP methods. REST API has several limitations and drawbacks for this use case, such as:
It counts against the daily limit of 15,000 API requests per 24-hour period.
It does not support PK Chunking for queries, which means that large data sets may exceed the query timeout or heap size limits.
It requires more API calls and processing time to perform a bulk operation than Bulk API 2.0.
Answer B is not valid because using Bulk API 1.0 for both inserting and querying data is not a feasible solution for handling large volumes of data in a day. Bulk API 1.0 is a SOAP-based API that allows creating, updating, deleting, or querying millions of records asynchronously by uploading or downloading XML or CSV files. Bulk API 1.0 has several limitations and drawbacks compared to Bulk API 2.0, such as:
It counts against the daily limit of 5,000 batches per rolling 24-hour period, which may not be enough to load and extract 90M and 30M records respectively.
It does not support JSON format for data files, which may not be compatible with some external systems or applications.
It requires more API calls and complexity to manage the job lifecycle and handle errors or retries than Bulk API 2.0.
Answer C is not valid because using Bulk API 1.0 for inserting data and REST API for querying data is not a suitable or reliable solution for handling large volumes of data in a day. As explained above, both Bulk API 1.0 and REST API have limitations and drawbacks that may affect the performance, efficiency, and scalability of the integration.
NEW QUESTION # 122
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