Option 3 is correct because flows provide fault paths where you can log or notify failures, allowing robust error handling. Option 1 is invalid because payloads don‘t support logic. Option 2 may amplify the problem. Option 4 is not technically possible.

Option 3 is correct because paginating the response minimizes memory use and prevents timeout issues, while supporting scalable client consumption. Option 1 is irrelevant here. Option 2 is incorrect because full datasets can cause performance issues. Option 4 is about timing, not technical optimization.

Option 4 is correct because CDC provides real-time updates with guaranteed delivery to subscribers, making it ideal for inbound updates. Option 1 introduces delays. Option 2 is good for publishing, not always guaranteed delivery. Option 3 is for internal processing.

Option 2 is correct because Named Credentials centralize authentication securely, avoiding exposure of credentials in code. Option 1 is insecure. Option 3 is unrelated. Option 4 refers to data access control, not integration.

Option 3 is correct because OAuth and FLS enforce proper access controls, reducing the risk of exposing sensitive data. Option 1 is unsafe. Option 2 increases the surface for data leaks. Option 4 hides important debug information.

Option 3 is correct because the external system pushing updates directly to the REST API allows real-time communication. Option 1 is for outbound-only. Option 2 adds delays. Option 4 is not real-time and requires polling.

Option 2 is correct because a secure JWT via Named Credentials ensures both authentication and integrity when calling AWS Lambda. Option 1 and 4 lack security. Option 3 adds control but isn’t sufficient for authentication.

Option 2 is correct because caching prevents unnecessary duplicate API calls, optimizing usage limits. Option 1 worsens the problem. Option 3 adds response time stress. Option 4 improves reliability but not volume.

Option 2 is correct because using middleware lets you centralize logs, manage retries, and store them securely. Option 1 sounds correct but logs only failures. Option 3 misses successful transaction records. Option 4 lacks logging capabilities.

Option 1 is correct because caching and batching reduce the number of API calls, improving performance and ensuring scalability. Option 2 causes performance bottlenecks and is prone to timeout issues. Option 3 affects user experience and is not scalable. Option 4 dismisses middleware, which often improves scalability.

Option 2 is correct because using message queues like Kafka decouples systems, allowing each to scale independently. Option 1 affects logging but not scalability. Option 3 is not suitable for real-time needs. Option 4 introduces tight coupling and poor scalability.

Option 3 is correct because Platform Events allow asynchronous communication, enabling systems to work independently and scale efficiently. Option 1 is unrelated. Option 2 is incorrect; retries can be configured. Option 4 is unrealistic as REST APIs are still widely needed.

Option 3 is correct because the Bulk API allows large datasets to be processed efficiently and supports parallel processing for performance. Option 1 is limited by timeout constraints. Option 2 is slow and inefficient. Option 4 is a logging practice, not a data ingestion strategy.

Option 2 is correct because events allow a publish-subscribe model where multiple systems can receive updates independently, improving scalability. Option 1 causes delays and failures. Option 3 mixes concerns and limits performance. Option 4 is insecure and not scalable.

Option 2 is correct because logging and reprocessing errors allow the rest of the transaction to complete, supporting better reliability. Option 1 hides important errors. Option 3 reduces throughput and is inefficient. Option 4 leads to unpredictable failures.

Option 2 is correct because sending a unique identifier allows the external system to detect and ignore duplicates, ensuring idempotency. Option 1 is runtime-only and doesn‘t persist across calls. Option 3 is risky without tracking. Option 4 is for config, not transaction management.

Option 2 is correct because exponential backoff reduces pressure on external systems while maintaining retry attempts. Option 1 creates performance risks. Option 3 doesn‘t help with retries. Option 4 prevents recovery from temporary failures.

Option 2 is correct because queuing and retrying ensures delivery while allowing investigation and resolution. Option 1 leads to data loss. Option 3 alone lacks tracking. Option 4 causes data integrity issues.

Option 2 is correct because retrying after short waits helps bypass temporary locks without impacting user experience. Option 1 affects usability. Option 3 might work but lacks recovery. Option 4 compromises security.

Option 2 is correct because event-driven architecture enables producers and consumers to function independently, improving system scalability and flexibility. Option 1 is unrelated. Option 3 is incorrect; error handling is still needed. Option 4 overstates the case.

Option 2 is correct because processing records in bulk reduces the cost of API/DML per record and makes the process more efficient. Option 1 is a side effect, not the main benefit. Option 3 is inefficient. Option 4 is a minor benefit, not the main goal.

Option 2 is correct because logging and isolating errors allows partial success, improving throughput. Option 1 is not supported. Option 3 stops overall execution. Option 4 wastes resources.

Option 1 is correct because adding retries with backoff gives the external system time to recover without overloading it. Option 2 is dangerous. Option 3 floods the system. Option 4 breaks authentication.

Option 2 is correct because fallback endpoints allow integration to proceed if the primary system fails, improving uptime. Option 1 is bad practice. Option 3 risks stalled processes. Option 4 allows data errors.

Option 1 is correct because try/catch with proper logging or alerting allows developers to monitor and debug failures effectively. Option 2 limits flexibility. Option 3 is not persistent. Option 4 leads to unhandled exceptions.

Option 1 is correct because stateless processing using unique identifiers ensures idempotency and prevents duplicates on retries. Option 2 is unreliable. Option 3 lacks action. Option 4 risks flooding the system.

Option 1 is correct because Platform Events with durable subscribers support retry logic and asynchronous communication, making them robust and scalable. Option 2 lacks retries. Option 3 is user-bound. Option 4 is inefficient.

Option 1 is correct because asynchronous callouts allow Salesforce to continue processing independently while waiting for external responses. Option 2 causes timeouts. Option 3 is unsupported. Option 4 leads to poor UX.

Option 2 is correct because unhandled exceptions cause transaction failure, and without logging, teams lose visibility into what failed and why. Option 1 is incorrect unless specifically built. Option 3 is a false assumption. Option 4 is unrelated.

Option 2 is correct because Mutual TLS ensures both the client and server verify each other’s identity via certificates, providing a strong layer of security. Option 2 is unrelated to protocol choice. Option 3 is outdated and lacks secure encryption. Option 4 may apply in niche cases but is less secure than certificate-based authentication.

Option 2 is correct because Tooling API provides access to code coverage, Apex test results, and other developer-related metadata necessary for building custom dev tools. REST API is not designed for this use case. Streaming API is for event notification. Metadata API is better for deployments than analysis.

Option 3 is correct because Tooling API is specifically built for developer tools, offering access to Apex classes, triggers, and compilation info. Metadata API is more suited for deployments. Apex SOAP lacks developer tool focus. Chatter is not relevant here.

Option 1 is correct because OAuth 2.0 with JWT provides a secure, scalable method for authenticating external systems using certificates and token-based flows. Option 2 is insecure and deprecated. Option 3 lacks token-based security context. Option 4 is not a best practice for sensitive authentication because API keys in metadata can be exposed.

Option 2 is correct because Salesforce Private Connect routes traffic over AWS PrivateLink, ensuring communication stays within a secure private network — ideal for government or regulated clients. Option 1 refers to CDN edge delivery, which doesn‘t meet private network requirements. Option 3 helps with authentication but not network routing. Option 4 is not applicable for routing constraints.

Option 3 is correct because the Connected App configured with Refresh Token flow enables persistent, secure access without embedding static credentials. Option 1 still requires certificate handling and is more advanced. Option 2 involves storing usernames/passwords, which is less secure. Option 4 is risky and not recommended for security.

Option 1 is correct because TLS 1.2 is the industry standard for encrypting HTTPS communications, and Salesforce requires it for secure data exchange. Option 2 is outdated and less secure. Option 3 refers to network configuration, not message encryption. Option 4 is not a security standard, but an architectural design choice.

Option 1 is correct because Named Credentials securely manage authentication and token storage within Salesforce, avoiding hardcoding sensitive data. Option 2 offers limited protection and lacks token lifecycle management. Option 3 introduces major security risks. Option 4 is highly insecure and not recommended.

Option 1 is correct because login IP ranges on profiles enforce strict IP-level access control, ensuring only approved networks can make authenticated API calls. Option 2 restricts actions, not IP addresses. Option 3 allows access without control. Option 4 relates to browser-based calls and doesn‘t apply to APIs.

Option 2 is correct because Describe calls can programmatically enforce Field-Level Security (FLS) during integration, preventing access to restricted fields. Option 1 controls record visibility, not field access. Option 3 is a security gap. Option 4 relates to ownership and record visibility only.

Option 1 is correct because Named Credentials can be configured for two-way SSL, allowing both parties to validate each other via certificates for enhanced security. Option 2 only filters access but doesn‘t establish secure identity. Option 3 poses security risks. Option 4 is outdated and unsupported.

Option 1 is correct because the JWT Bearer Flow allows trusted server-to-server authentication without user interaction, ideal for backend integrations. Option 2 and 3 involve user browser interaction. Option 4 stores credentials insecurely and is deprecated.

Option 1 is correct because the REST API provides lightweight, stateless access that suits mobile applications needing CRUD operations with low overhead. Option 2 is used for metadata deployments, not data operations. Option 3 is optimized for large volume batch jobs. Option 4 is push-only and doesn‘t support CRUD.

Option 2 is correct because Bulk API is designed specifically for massive data loads, supporting asynchronous processing and chunked uploads. REST API is limited by payload size. Tooling API is for developer tools. Streaming API doesn‘t support data loading.

Option 3 is correct because the Streaming API allows subscription to data change events, which can push notifications to external systems when changes occur. Bulk and REST APIs are pull-based. Metadata API handles configuration changes, not data change events.

Option 3 is correct because the Metadata API is intended for deploying Salesforce configuration changes, such as fields, layouts, and custom objects. Tooling API is used primarily for IDE integrations. Chatter API is not used for configuration. REST API is for data manipulation, not configuration deployment.

Option 4 is correct because Remote Process Invocation allows for real-time request/response communication and orchestration across systems. REST handles single transactions but not orchestration. Metadata is not for runtime logic. Streaming API is outbound only.

Option 1 is correct because REST API is ideal for small, synchronous data sets due to its lower overhead and speed. Bulk API is overkill for small jobs. Metadata API does not handle data. Streaming API is not for CRUD operations.

Option 1 is correct because Metadata API is designed for deploying metadata such as object definitions, validation rules, and layouts between environments. REST and Bulk APIs deal with data. Tooling API is primarily for IDE development and analysis.

Option 3 is correct because Streaming API enables Change Data Capture subscriptions that notify external systems when records change. REST and Bulk APIs require polling. Tooling API is not for real-time record change tracking.

Option 4 is correct because synchronous Apex callouts are subject to governor limits and if the callout fails, the transaction cannot be rolled back gracefully. Option 1 applies to batch processing, not callouts. Option 2 matters but doesn‘t influence rollback. Option 3 is unrelated to Apex callouts.

Option 3 is correct because Queueable Apex supports asynchronous processing, making it suitable for long-running outbound integrations without blocking the main thread. Option 1 can cause timeout issues. Option 2 is event-driven and not used for initiating calls. Option 4 is for receiving, not making, calls.

Option 2 is correct because outbound messages require minimal coding and are well-suited for admin-configured, simple integrations. Option 1 requires custom code. Option 3 isn‘t supported by outbound messages. Option 4 is not possible, as outbound messages don‘t handle JSON.

Option 4 is correct because outbound messaging cannot handle complex logic or response transformation — it simply sends XML to an endpoint. Option 1 is incorrect as outbound messages use SOAP. Option 2 is unrelated. Option 3 is incorrect — outbound messages retry delivery if not acknowledged.

Option 3 is correct because callouts cannot be made directly in triggers and must be handled in asynchronous context using @future or Queueable. Option 1 is unnecessary and can lead to data inconsistencies. Option 2 violates best practices. Option 4 is only suitable for scheduled tasks.

Option 2 is correct because Named Credentials can securely manage OAuth tokens and are the recommended way to authenticate against external services. Option 1 is insecure. Option 3 is discouraged for storing secrets. Option 4 is not valid for external integrations.

Option 1 is correct because REST APIs must enforce object- and field-level security (FLS) and minimize payload sizes to optimize performance and prevent data leaks. Option 2 is incorrect since Streaming is for events. Option 3 poses security risks. Option 4 is not applicable.

Option 2 is correct because External Services allow you to declaratively register Swagger/OpenAPI definitions and invoke them via Flow without code. Option 1 requires Apex. Option 3 is not necessary. Option 4 defeats the declarative advantage.

Option 3 is correct because Platform Events support high-volume messaging and are optimized for receiving near-real-time updates from external sources. Option 1 is not scalable. Option 2 could exceed limits. Option 4 is inefficient and not real-time.

Option 1 is correct because versioning endpoints like /services/apexrest/v1/resource ensures backward compatibility and supports iterative changes. Option 2 is not reliable. Option 3 is unrelated. Option 4 is not sustainable in production environments.

Option 4 is correct because Apex callouts from LWC can deliver near real-time user-facing interactions directly from the UI. Option 1 is better for event-driven updates but not user-initiated actions. Option 2 introduces delays. Option 3 has flow limitations and lacks UI responsiveness.