Integration-Architect Exam Dumps - Salesforce Integration Architecture Designer Questions and Answers

To translate abstract business needs into a functional Integration Architecture, an architect must move beyond "what" the business wants to "how" the data will technically flow. The details in Option B represent the fundamental building blocks of any integration design.

Source and Target Systems: Determining which systems are involved dictates the available APIs (REST, SOAP, Bulk) and required security protocols (OAuth, Mutual SSL).

Directionality: Knowing if the update is unidirectional or bidirectional is critical for record mastering, identifying the "System of Record," and preventing infinite data loops.

Data Volume: This is a primary driver for selecting the Integration Pattern. High volumes (millions of records) require the Bulk API, while low-volume, real-time updates are better suited for Streaming or REST APIs.

Transformation Complexity: If data must be heavily massaged or merged from multiple sources, it justifies the need for Middleware (ESB/iPaaS).

Option A focuses on user interface and licensing, which are implementation details rather than architectural integration requirements. Option C deals with project management and resource allocation. While these are important for the project's success, they do not help the architect decide between a Request-Reply or Fire-and-Forget pattern. By focusing on systems, data direction, and volume, the architect ensures that the proposed solution is technically viable, scalable, and adheres to Salesforce platform governor limits.

In a contract-first integration approach using RAML, the specification acts as the single source of truth for request and response structures. Since Salesforce unit tests are prohibited from performing actual network callouts, the HttpCalloutMock interface must be used to simulate external API behavior.

To ensure unit tests truly confirm adherence to the RAML contract, the architect must mandate that the mock implementation specifically returns responses formatted per the RAML specification. This means the mock's JSON or XML body, headers, and HTTP status codes (e.g., 200 OK, 400 Bad Request) must exactly match the "interface contract" defined in the RAML file.

By strictly aligning the mock with the RAML spec, developers ensure that the Apex client's parsing logic (e.g., JSON.deserialize()) is tested against the agreed-upon data model. If the external service later changes its schema in a way that deviates from the RAML, the unit tests—which are based on that contract—will help identify where the Apex code might fail. Options B and C are technically incorrect: the client does not "call" or "implement" the mock; rather, the test runtime provides the mock instance to the client via Test.setMock().

Achieving "exactly once" delivery for critical financial data requires a resilient asynchronous pattern that supports complex state management and error handling. Queueable Apex is the architecturally preferred mechanism for this requirement.

Queueable Apex provides several advantages over standard @future methods (Option C):

State Tracking: Queueable jobs return a unique Job ID, allowing the architect to track the status of the request and build automated monitoring dashboards.

Job Chaining: Multiple Queueable jobs can be chained together, which is essential if an order and its multiple line items must be processed in a specific sequence to ensure data integrity at the finance application.

Complex Data Types: Unlike @future methods, which only accept primitive types, Queueable Apex can handle complex sObjects and collections, making it easier to pass complete Order and Line Item data in a single transaction.

To fulfill the "exactly once" requirement, the architect must also implement an Idempotency strategy. The custom error handling process should include a unique "Integration ID" (such as the Salesforce Order ID) in the API payload. If a Queueable job fails due to a transient error and retries the call, the finance application can use this ID to recognize that it has already received the order, thus preventing duplicate invoicing. Option A is unreliable as it depends on human intervention for retries, and Option C lacks the robust monitoring and object-passing capabilities required for sophisticated financial integrations.

To provide near real-time notifications to a client that already supports CometD, an Integration Architect should leverage the Streaming API. While Platform Events are a modern alternative, PushTopic Events are specifically designed to stream changes to Salesforce records based on a defined SOQL query.

A PushTopic event is triggered when a record is created, updated, deleted, or undeleted. By creating a PushTopic on the Opportunity object, NTO defines the criteria (fields and record states) that should trigger a message to the 1subscriber. The affiliate’s CometD client can then subscribe to this topic's channel (e.g., /topic/OpportunityUpdates) to receive the data payload instantly.

Option A is incorrect because "Accept CometD API Requests" is not a standard checkbox or configuration within a Connected App; authentication is handled via standard OAuth flows, but the streaming channel must still be defined. Option C describes a Polling mechanism, which is the architectural opposite of the requested "immediate notification" and would unnecessarily consume SOAP API limits while introducing latency. By using a PushTopic, NTO ensures a decoupled, event-driven architecture that scales effectively for notification-only use cases while respecting the technical capabilities of the affiliate’s existing CometD-compatible infrastructure.

Governance and maintenance are critical when using event-driven architectures. Unlike standard objects, which can often be retrieved from the Recycle Bin, Platform Event definitions are handled with high permanence. Once an event definition is deleted, it is permanently removed. This deletion also immediately destroys any associated triggers, subscriptions, and any events currently stored in the event bus. Architects must highlight this risk to ensure proper metadata backup and change management processes are in place. Options A and B refer to specific security and monitoring features that are secondary to the fundamental architectural risk of permanent metadata loss.

When building a distributable package (likely a Managed Package) that must securely communicate back to a central "Hub" org, the architect must use a framework that supports OAuth 2.0 flows. Storing plain-text or even encrypted passwords (Option B) is a security violation and is brittle across different environments.

The architecturally sound solution is to leverage the Authentication Provider and Named Credentials framework. In the central org, a Connected App is created to act as the OAuth endpoint. In the package, an Authentication Provider is configured using the Consumer Key and Consumer Secret from that Connected App. This setup allows the administrator in the "Subscriber" org (the org where the package is installed) to initiate an OAuth flow.

When the security team "authorizes" the integration after installation, they are essentially completing the OAuth handshake. This grants the subscriber org an Access Token and a Refresh Token associated with the specific integration user in the central org. This mechanism ensures:

Credential Security: No passwords are ever stored in the code or metadata.

Centralized Control: The security team in the central org can revoke the Refresh Token at any time to kill the integration.

Scalability: The same package can be distributed to hundreds of orgs, each with its own unique, secure connection to the central Hub.

By using an Authentication Provider combined with a Named Credential, the Apex code in the package can simply call the endpoint by its developer name, and Salesforce handles the entire authentication header injection automatically, ensuring a robust and secure cross-org integration.

For large-scale data migrations, the Bulk API is the primary architectural tool for high-performance loading. To maximize throughput and "optimize performance," the architect should recommend processing jobs in parallel mode.

In parallel mode, Salesforce processes multiple batches of a job simultaneously, taking advantage of the multi-tenant platform's concurrent processing capabilities. This significantly reduces the total time required for a massive data migration compared to serial mode (Option B), which processes batches one by one.

However, the architect must warn the team about potential lock contention. If multiple parallel batches attempt to update the same parent record or participate in complex sharing calculations at the same time, "Unable to lock row" errors may occur. To mitigate this while maintaining parallel speed, the data should be sorted by Parent ID to ensure that batches do not overlap on the same records. Option A is rarely necessary for standard migrations unless the volume exceeds extreme thresholds. Parallel Bulk API is the standard "best practice" for ensuring the migration completes within the allotted cutover window.

In the discovery and translation phase of a Salesforce project, an Integration Architect must move beyond high-level business goals to define the technical "DNA" of the data exchange. While organizational readiness and user experience are vital to project success, they do not dictate the architectural patterns required to move data between systems.

The most critical details for designing an integration architecture are the Timing and Volume requirements. Identifying whether a business process is Synchronous or Asynchronous is the primary decision point. For example, if a Salesforce user requires an immediate validation from an external system before they can save a record, a synchronous "Request-Reply" pattern using an Apex Callout is required. If the data update can happen in the background without blocking the user, an asynchronous "Fire-and-Forget" pattern is preferred to improve system performance and user experience.

Furthermore, understanding the Update Frequency (e.g., real-time, hourly, or nightly) and the Data Volume (e.g., 100 records vs. 1 million records) allows the architect to select the appropriate Salesforce API. High-volume, low-frequency updates are best handled by the Bulk API to minimize API limit consumption, while low-volume, high-frequency updates are better suited for the REST API or Streaming API. By specifically seeking out these timing and frequency aspects, the architect ensures that the chosen solution is scalable, stays within platform governor limits, and meets the business's Service Level Agreements (SLAs). Without these details, the architect risks designing a solution that is either too slow for the business needs or too taxing on system resources.

When migrating from a legacy environment to a multi-tenant cloud platform like Salesforce, Data volume and processing volume represent the most critical technical constraints. Legacy systems often operate without the strict governor limits found in Salesforce, meaning they may push large datasets or high-frequency updates that could easily overwhelm standard Salesforce APIs.

An integration architect must evaluate these volumes to determine the appropriate integration pattern:

Pattern Selection: If the daily volume involves millions of records, the architect must recommend the Bulk API rather than standard REST or SOAP APIs to avoid hitting daily API limits.

Synchronous vs. Asynchronous: High processing volumes often necessitate asynchronous patterns (such as Fire-and-Forget or Batch) to prevent user-interface lag and "Concurrent Request Limit" errors.

Data Virtualization: If the legacy data volume is massive but only needs to be viewed occasionally, the architect might consider Salesforce Connect to avoid consuming expensive internal data storage.

While reporting (Option A) and multi-currency (Option C) are important functional requirements, they do not fundamentally dictate the technical "plumbing" or scalability of the integration architecture. By prioritizing the analysis of volume and processing needs, the architect ensures the new modernization effort is stable, performant, and capable of scaling as the business grows within the bounds of the Salesforce platform.