Salesforce Plat-Arch-204 Exam Dumps

For developer-centric tools that need to access fine-grained technical data like code coverage and test results, the Tooling API is the correct architectural choice.

While the Metadata API (Option B) is used to deploy or retrieve code, it does not provide real-time query access to the underlying metrics of a test run. The Tooling API, however, exposes specialized objects such as ApexCodeCoverage, ApexCodeCoverageAggregate, and ApexTestResult. These objects allow the Java application to query exactly which lines of code were executed during a test and the overall percentage of coverage for the organization.

The Analytics REST API (Option A) is designed for querying and interacting with Einstein Analytics (CRM Analytics) datasets and dashboards, which is irrelevant to software development lifecycle (SDLC) metrics. By using the Tooling API, the Java application can perform RESTful queries to gather comprehensive data on test successes, failures, and coverage gaps. This allows NTO to integrate Salesforce into its existing enterprise-wide quality dashboard, ensuring a unified view of code health across all platforms.

When dealing with a 'big surge' or high-volume influx of requests, a synchronous pattern like Request and Reply (Option A) can lead to significant performance bottlenecks. In a synchronous model, each Salesforce user thread must wait for the external scheduling system to respond, which could lead to 'Concurrent Request Limit' errors during peak times.

The Remote Process Invocation---Fire and Forget pattern is the architecturally sound choice for managing surges. In this pattern, Salesforce captures the registration intent and immediately hands it off to an asynchronous process or a middleware queue. Salesforce does not wait for the external system to process the room capacity logic; instead, it receives a simple acknowledgment that the message was received.23

This pattern decouples the front-end user experience from the back-end processing limits. Middleware can then 'drip-feed' these registration4s into the scheduling system at a rate it can handl5e. If the scheduling system becomes overwhelmed or goes offline, the messages remain safely in the queue. Option C (Batch) is unsuitable because users expect near real-time feedback on their registration attempt, even if the final confirmation is sent a few minutes later. By utilizing Fire and Forget, NTO ensures a responsive Community Experience during the critical launch window while maintaining system stability.

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.

When comparing Platform Events and Outbound Messaging for a near-real-time architecture, a Salesforce Platform Integration Architect must evaluate fundamental differences in their delivery models and governance. While both provide declarative, asynchronous 'Fire-and-Forget' capabilities, their technical constraints differ significantly, particularly regarding scalability and platform limits.

The key architectural highlight in this scenario is that Platform Events operate on a specialized event bus with specific Event Publishing and Event Delivery limits. Unlike Outbound Messaging, which is governed by more general daily outbound call limits (often tied to user licenses), Platform Events have a dedicated allocation for the number of events that can be published per hour and delivered in a 24-hour period to external clients via the Pub/Sub API or CometD. For example, the number of concurrent subscribers to a Platform Event channel is typically capped at 2,000 for standard configurations. Since the customer expects 3,000 customers to view these messages, this limit is a critical evaluation point; the architecture would need to account for this gap, perhaps by using middleware to fan out messages to the larger audience.

In contrast, Outbound Messaging does not have an 'Event Delivery' limit in the same sense. It is a point-to-point SOAP-based push mechanism where Salesforce manages retries for up to 24 hours if the receiving endpoint is unavailable. However, it is less flexible for multi-consumer scenarios because it requires a separate configuration for every unique destination.

Regarding the other options: Option A is incorrect because neither system strictly guarantees 'exactly-once' delivery without the possibility of duplicates; in fact, Outbound Messaging may deliver a message more than once if it doesn't receive a timely acknowledgment. Option B is incorrect because Platform Events do not have built-in 'fault recovery' handled by Salesforce in the same way as Outbound Messaging's automatic retry queue; with Platform Events, it is the subscriber's responsibility to use a Replay ID to retrieve missed events within the 72-hour retention window. Therefore, highlighting the unique delivery and publishing limits is the most vital step for the architect.

Implementing Shield Platform Encryption is a significant architectural change that requires careful planning before activation. The architect's first priority must be to Review Shield Platform Encryption configurations and understand the platform's functional limitations.

Encryption at rest affects how data interacts with other platform features. For example, encrypting a field can impact the ability to use that field in SOQL WHERE clauses, report filters, list views, or as a unique/external ID. Before encrypting Social Security Numbers, the architect must audit all existing integrations, Apex code, and reports that reference that field to ensure they will still function correctly.

Option A is incorrect because unnecessarily encrypting all data can negatively impact system performance and break standard functionality. Encryption should be applied selectively to sensitive fields based on a clear data classification policy. Option B is factually wrong; Shield is a data protection tool, not an authentication or authorization mechanism like OAuth or SSO. By reviewing the configurations first, the architect can identify potential 'blockers'---such as a field being used in a formula or a criteria-based sharing rule---and address them before the encryption keys are generated and applied.