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Northern Trail Outfitters needs to make synchronous callouts ''available-to-promise'' services to query product availability and reserve inventory during the customer checkout process. What should an integration architect consider when building a scalable integration solution?
Answer : B
In a Synchronous Request-Reply pattern, the user's experience is directly tied to the performance of the external service. For a mission-critical 'Available-to-Promise' (ATP) service during checkout, the most vital scalability consideration is the typical and worst-case historical response times of the target system.
Salesforce imposes strict Governor Limits on synchronous callouts to protect platform health. Specifically, if an ATP callout takes longer than 120 seconds, the transaction will time out. More importantly, Salesforce limits the number of long-running requests (those lasting longer than 5 seconds). If multiple users are checking out simultaneously and the external inventory system begins to respond slowly (worst-case), those requests can quickly occupy all available slots in the concurrent request queue, leading to 'Concurrent Request Limit Exceeded' errors for all users in the org.
By analyzing historical response times, the architect can determine if the service is reliable enough for a synchronous callout. If the worst-case response time frequently exceeds 5 seconds, the architect should consider a more resilient pattern, such as the Continuation pattern or an asynchronous approach, to prevent blocking the UI thread and hitting platform limits. Options A and C are irrelevant to synchronous checkout performance; query cursors relate to database state, and batch jobs are asynchronous background processes that do not impact real-time user checkout latency.
Northern Trail Outfitters (NTO) is planning to create a native employee-facing mobile app with the look and feel of Salesforce Lighting Experience. The mobile app needs to integrate with NTO's Salesforce org. Which Salesforce API should be used to implement this integration?
Answer : C
When building custom mobile or web applications that aim to replicate the look and feel of Salesforce Lightning Experience, the User Interface (UI) API is the architecturally recommended choice.
The UI API is specifically designed to provide the metadata and data needed to build high-fidelity user interfaces. Unlike the standard REST API (Option B), which returns raw record data, the UI API returns both data and metadata in a single response. This includes information about page layouts, field-level security, picklist values, and localized labels. By using the UI API, the mobile app can dynamically render fields according to the user's permissions and the organization's layout configurations, ensuring that the custom app stays in sync with changes made in Salesforce Setup without requiring code updates in the mobile app.
Connect REST API (Option A) is primarily used for Chatter, Communities (Experience Cloud), and CMS content, and while it is useful for those specific social features, it does not provide the layout and record-level metadata required for a full CRM interface. The UI API is the same underlying technology that powers the Salesforce mobile app and Lightning Experience itself. Therefore, utilizing this API allows NTO's developers to build a native app that perfectly mimics the Lightning Experience while reducing the amount of custom logic needed to handle complex Salesforce UI requirements.
A customer imports data from an external system into Salesforce using Bulk API. These jobs have batch sizes of 2,000 and are run in parallel mode. The batches fail frequently with the error ''Max CPU time exceeded''. A smaller batch size will fix this error. What should be considered when using a smaller batch size?
Answer : A
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).
A security assessment noted vulnerabilities on unmanaged packages; notably, secrets like usernames, passwords, and OAuth tokens are stored in plain text. Which persistence mechanisms should an integration architect require to ensure that secrets are protected from deliberate or inadvertent exposure?
Answer : A
A customer is migrating from an old legacy system to Salesforce. As part of the modernization effort, the customer would like to integrate all existing systems that currently work with its legacy application with Salesforce. Which constraint/pain-point should an integration architect consider when choosing the integration pattern/mechanism?
Answer : A
When migrating from a legacy landscape to a modern platform like Salesforce, the most immediate technical hurdle is the diversity of system types and communication protocols used by the existing systems.
In a legacy environment, integrations are often not standardized. An architect may encounter systems that communicate via modern REST/SOAP APIs, but they will also likely find older systems that rely on Flat File exchanges (FTP/SFTP), Email-based triggers, or direct Database connections. These 'System Types' are a fundamental constraint because they dictate the choice of integration middleware. For example, Salesforce cannot natively poll a file system or read an on-premise database; therefore, an architect must identify these constraints to justify the need for an ETL or ESB tool that can bridge these legacy protocols with Salesforce's API-centric architecture.
While reporting (Option B) and multi-currency (Option C) are important functional requirements for the Salesforce implementation, they do not dictate the integration pattern (e.g., Request-Reply vs. Batch) as much as the technical interface of the source/target systems does. By evaluating the APIs, file systems, and email capabilities of the legacy landscape first, the architect ensures that the chosen integration mechanism---whether it be the Streaming API, Bulk API, or middleware orchestration---is technically capable of actually communicating with the legacy debt.
