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

The Bulk API is designed to process massive datasets by breaking them into smaller batches that Salesforce processes asynchronously. When a batch fails with the “Max CPU time exceeded” error, it typically indicates that the complexity of the operations triggered by the record—such as Apex triggers, Flows, or complex sharing calculations—exceeds the 10,000ms limit within a single transaction.

Reducing the batch size is the standard architectural remedy because it reduces the number of records processed in a single transaction, thereby lowering the total CPU time consumed by those records. However, the architect must consider the impact on the overall throughput and execution time.

When batch sizes are smaller, the total number of batches required to process the same dataset increases. For instance, moving from a batch size of 2,000 to 200 for a 1-million-record dataset increases the number of batches from 500 to 5,000. Each batch carries its own overhead for initialization and finalization within the Salesforce platform. Consequently, while the individual batches are more likely to succeed, the total time required to complete the entire job will increase.

The architect should also be aware of the daily limit on the total number of batches allowed (typically 15,000 in a 24-hour period). While Option C mentions API request limits, the Bulk API is governed more strictly by its own batch limits. Option B is less likely because "parallel mode" naturally manages concurrency. Thus, the primary trade-off the architect must present to the business is a gain in reliability (successful processing) at the cost of total duration (increased sync time).

When external services are highly volatile (added/removed frequently), the goal is to decouple the Salesforce UI from the underlying service logic. An Integration Architect should propose invoking a middleware service to retrieve the valid shipping methods.

By using middleware (such as an ESB or MuleSoft) as an abstraction layer, Salesforce doesn't need to "know" the details of the 34 different shipping providers. When a sales rep selects a country, Salesforce makes a single callout to the middleware. The middleware then performs the routing logic to identify which shippers are active for that region and returns a standardized list to Salesforce.

Option A is a "maintenance nightmare"; every time a shipping service changes in any of the 34 countries, an admin would need to manually update picklist values and dependencies in Salesforce, which is not scalable. Option C (Platfor31m Events) is an asynchronous pattern unsuitable for a real-time "request-reply" scenario where a rep is waiting for an estimate during a live customer interaction. Utilizing middleware centralizes the logic, simplifies Salesforce configuration, and allows NTO to change shipping providers without any code deployments or metadata updates in the Salesforce org.

Achieving "exactly once" delivery and high reliability in a critical finance integration requires an asynchronous pattern that provides better control and error handling than standard @future methods. Queueable Apex is the architecturally preferred solution for this scenario.

Queueable Apex offers several advantages over @future methods:

Stateful tracking: Unlike @future, Queueable jobs return a Job ID, allowing the system to monitor progress and verify completion.

Chaining: You can chain jobs to process records sequentially, which helps maintain the integrity of order and line item data.

Complex Data Types: Queueables can accept complex objects as parameters, making it easier to pass high-fidelity order data than the primitive types required by @future.

Option A is unreliable because it relies on human intervention for retries, which is prone to error and does not scale. Option C is less desirable because @future methods cannot be monitored as effectively and lack the ability to return a Job ID for subsequent tracking.

To ensure accurate invoicing, the architect should design the Queueable class with a custom error handling process that includes logging failures and a retry mechanism. Additionally, to prevent duplicate invoicing, the finance application should be designed with an Idempotency check (using a unique Order ID from Salesforce) to ensure that if a retry is sent, the system recognizes the duplicate and does not create a second invoice. This combination of Queueable Apex and idempotency provides the highest level of reliability for critical financial transactions.

Prior to implementing Shield Platform Encryption, the most critical step for an Integration Architect is to perform a comprehensive Review of Shield Platform Encryption configurations and their impact on existing platform functionality. Encryption at rest is not a "set-and-forget" feature; it changes how the Salesforce database interacts with various features, and failing to review these limitations beforehand can lead to significant business disruption.

Salesforce documentation emphasizes that encryption affects several core areas:

SOQL/SOSL Limitations: Encrypted fields have restricted capabilities in WHERE, GROUP BY, and ORDER BY clauses.1 For example, if Social Security Numbers (SSNs) are encrypted using Probabilistic Encryption, they cannot be filtered or sorted in a query.2 This could break existing integrations or reports that rely on finding specific records by SSN.

Search Functionality: While Salesforce supports searching for encrypted data, there are specific behaviors to consider regarding how search indexes are built and updated.

AppExchange and Managed Packages: If the SSN field is used by a third-party app or a managed package, encrypting it might cause those external tools to fail if they are not designed to handle encrypted data types.

Field Attributes: Encrypted fields cannot be used as Unique or External IDs if using the probabilistic scheme, which is a vital consideration for data synchronization architectures.3

Therefore, the architect must first conduct a Business Impact Analysis. This includes identifying where the sensitive data (SSNs) is used in Apex code, Flows, validation rules, and reports. By reviewing the configurations and functional limitations first, the architect can decide between Probabilistic (higher security) and Deterministic (allows filtering) encryption strategies.4 Option A is a step taken during or after implementation (Background Encryption), and Option C is an anti-pattern, as encrypting "everything" leads to unnecessary performance overhead and massive functional loss. Only after a thorough review can the architect safely proceed with the technical implementation of Shield.

In this architectural scenario, the Integration Architect must navigate two critical technical "bottlenecks": the 9-second API Gateway timeout and the 90-second backend processing time. Since the backend takes significantly longer than the gateway allows for a synchronous connection, a standard Request-Reply pattern will fail. Furthermore, having 3,000 concurrent agents perform synchronous callouts would risk hitting Salesforce's concurrent long-running request limits.

The most scalable and user-friendly solution is to implement an Asynchronous Request-Reply pattern using Platform Events and the empAPI.

When an agent clicks "Check Eligibility," Salesforce sends an initial asynchronous request to the ESB (MuleSoft). The ESB immediately acknowledges receipt with a 202 Accepted status, freeing up the Salesforce UI thread and avoiding the API Gateway’s 9-second timeout. Once the backend eligibility system completes its 90-second process, MuleSoft acts as a client to Salesforce, performing a Remote Call-In to publish a specific Platform Event containing the result and the original Request ID.

On the frontend, the Lightning UI uses the empAPI (Enterprise Messaging Platform API) to subscribe to the streaming channel for that Platform Event. Because the empAPI uses CometD technology to maintain a single long-lived connection, it can efficiently push the response to the agent's screen the moment it arrives, without requiring the agent to manually refresh or click a "Check Update" button (as suggested in Option B). This provides a "real-time" feel despite the long backend latency.

Option A is non-viable because synchronous polling would exacerbate the load on the API Gateway and likely lead to governance limit issues within Salesforce. By using Platform Events and empAPI, the architect ensures the solution remains within Salesforce's execution limits while providing a seamless, automated experience for a high-volume call center environment.

Salesforce is a highly capable CRM platform, but it is not a dedicated messaging or orchestration engine. When requirements include complex message queuing, process choreography, and guaranteed quality of service (QoS), the Integration Architect must recommend a middleware solution (ESB or iPaaS).

"True message queuing" involves holding messages in a persistent state until the target system is ready to receive them, handling sophisticated retry logic (such as exponential backoff), and providing dead-letter queues for failed messages. While Salesforce has basic asynchronous tools like Outbound Messaging or Platform Events, they lack the granular control over queuing and orchestration that enterprise middleware provides.

Option A is incorrect because performing heavy transformation and protocol translation (like XML to JSON or SOAP to REST) within Salesforce consumes excessive Apex CPU time and is better handled by middleware designed for that purpose. Option B is conceptually backward; usually, architects move away from synchronous Request-Reply toward asynchronous Fire-and-Forget to improve scalability. By recommending a middleware solution to handle these infrastructure-level concerns, the architect ensures that Salesforce remains performant for its users while the middleware manages the technical complexities of reliably connecting the enterprise.

To achieve a "Customer 360" view where sales and service associates have the context needed for daily interactions, Salesforce is the logical System of Record (SoR) for customer and prospect engagement.

While the ERP remains the master for financial transactions (invoices) and the Marketing tool masters campaign analytics, Salesforce should house the core "Golden Record" of the customer. This is achieved by integrating relevant data from the ERP (order status, invoice history) and Marketing (lead source, email engagement) into Salesforce. This strategy (Option A) empowers associates to log interactions and view history in one place, fulfilling the primary goal of the CRM implementation while avoiding the complexity of a new custom database (Option B) or trying to force prospect-level engagement data into a rigid ERP (Option C).

In the world of Salesforce SOAP APIs, the choice of WSDL depends on the nature of the application being built. When an architect needs to build an integration that is org-agnostic—meaning it can work across multiple different Salesforce organizations with varying custom objects and fields—the Partner WSDL is the correct choice.

The Partner WSDL is loosely-typed. It does not contain information about an org's specific custom metadata; instead, it uses a generic sObject structure. This allows a single client application (like a third-party integration tool or a mobile app) to connect to any Salesforce org and dynamically discover its schema at runtime. Because it is not tied to a specific org's metadata, it does not need to be regenerated every time a custom field is added to one of the target orgs.

In contrast, Option A (Enterprise WSDL) is strongly-typed. It is generated specifically for one org and contains hard-coded references to that org's custom objects and fields. While this provides better compile-time safety for internal, single-org integrations, it is unsuitable for an application intended for "more than one Salesforce org" because the WSDL would be invalid for any org that doesn't have the exact same metadata. Option C is a general term; the actual choices provided by Salesforce for integration are the Partner or Enterprise WSDLs. Therefore, for maximum flexibility and reusability across a multi-org landscape, the Partner WSDL is the industry standard.

Securing outbound integrations from Salesforce requires protection at both the authentication and transport layers. Named Credentials and Two-way SSL (Mutual Authentication) together provide a robust security posture for reading external data via HTTP.

Named Credentials serve as a secure management tool for callout endpoints. They abstract the endpoint URL and the necessary authentication parameters (such as Basic Auth or OAuth tokens) away from the Apex code. This separation ensures that sensitive credentials are not hardcoded and can be easily updated in one central location if the endpoint or credentials change.

Two-way SSL (Mutual TLS) provides transport-layer security by requiring both the client (Salesforce) and the external server to authenticate each other using digital certificates. While standard SSL verifies the server to the client, Two-way SSL ensures that the external system only accepts requests from a verified Salesforce org. This "Mutual TLS" setup is highly recommended for enterprise-level integrations where proof of the caller's identity is as critical as the encryption of the data in transit. By combining these two methods, the architect ensures that the integration is secured against both credential theft and unauthorized server access.