The Complete Salesforce API Landscape

Interview Quick-Revision Guide

The Complete Salesforce API Landscape

Categorized architecture, strict use cases, and rapid-recall patterns for technical interviews.

To ace a Salesforce Architect or Developer interview, you must look past basic API definitions. You need to know why you would choose one API over another based on data volumes, transaction boundaries, and system constraints. Here is your quick-revision blueprint.

API Landscape At-A-Glance

  • Core Data APIs: For standard CRUD operations on CRM records (REST, SOAP, Bulk 2.0, Pub/Sub, Composite).
  • Custom Development APIs: For exposing custom Apex backend logic (Apex REST, Apex SOAP).
  • Metadata & Tooling APIs: For modifying platform structures, configurations, and CI/CD operations.
  • Specialized UI & Sub-System APIs: Tailored for frontend frameworks, UI data bundles, and specific clouds (GraphQL, UI API, Connect REST).

Category 01

Core Data APIs

REST API (Synchronous)

Lightweight HTTP-based framework interacting with individual rows via JSON or XML payloads.

Use Case:Real-time, lightweight web or mobile application integrations.
Benefits:Easy to test, natively handles JSON, stateless, highly scalable for small transactional loads.
Interview Scenario: "A customer fills out a lead capture form on your corporate website. The website triggers an immediate REST POST request to instantly instantiate that Lead record inside Salesforce."

SOAP API (Synchronous)

Rigid, strongly typed, contract-based framework utilizing strictly XML payloads and WSDL files.

Use Case:Legacy system integrations or high-security financial middleware tracks.
Benefits:Strict type safety via WSDL mapping prevents runtime data schema format mismatches.
Interview Scenario: "An on-premise banking ledger system needs to push accounting logs into Salesforce. The middleware uses the enterprise WSDL contract to strictly enforce data parameters before dispatching."

Bulk API 2.0 (Asynchronous)

High-throughput background loading framework designed to digest raw CSV text streams.

Use Case:Data warehouse syncs, initial system migrations, large data backups.
Benefits:Bypasses standard transaction limits, automatically fragments files up to 150 million rows daily.
Interview Scenario: "Your company acquires a competitor and you must bring 3 million historical Account rows into your system without hitting execution timeout caps."

Pub/Sub API (Event-Driven / gRPC)

Bi-directional, event-driven architecture streaming Platform Events and CDC via HTTP/2 channels.

Use Case:Real-time replication pipelines or loosely coupled messaging middleware setups.
Benefits:High performance via binary Apache Avro formats; eliminates heavy custom REST polling loops.
Interview Scenario: "An external inventory system must spin up an order packaging line the exact millisecond an Opportunity is marked Close-Won inside Salesforce."

Composite API (Synchronous)

Orchestration engine packing up to 25 separate execution threads inside a single HTTP roundtrip.

Use Case:Deep hierarchical inserts (Parent-Child-Grandchild operations) in one transaction.
Benefits:Saves API limits drastically by passing outputs from step A dynamically into step B as inputs.
Interview Scenario: "An external billing system wants to instantiate a new customer Account, attach an active Contact, and log an onboarding Task simultaneously in a single transaction call."
Category 02

Custom Development APIs

Apex REST & Apex SOAP APIs

Custom exposed web services crafted using @RestResource or webservice global modifiers in Apex code.

Use Case:Exposing custom server-side validation or combining multi-object actions that standard endpoints can't handle.
Benefits:Enforces complex, customized server-side logic and validation before any record changes are applied.
Interview Scenario: "An external platform needs to verify inventory allocation before creating an order line. A custom Apex REST endpoint checks inventory, queries related fields, and creates the record in one clean block."
Category 03

Metadata & Tooling APIs

Metadata API vs. Tooling API

Structural control endpoints interacting with environment configuration schemas, layouts, and system customization files.

Use Case:Metadata: Core deployments / DevOps pipelines.
Tooling: IDE development, code editors, granular log retrievals.
Benefits:Automates deployment management; Tooling API provides fine-grained, fast access to smaller configuration slices.
Interview Scenario: "A CI/CD tool uses the Metadata API to deploy new fields from a Git branch into a Sandbox environment, while a code editor uses the Tooling API to fetch debug logs on the fly."
Category 04

Specialized UI & Sub-System APIs

GraphQL API & UI API

Client-side UI engines built to fetch data alongside context layout rules simultaneously.

Use Case:Powering Lightning Web Components (LWC), custom web portals, and performance-optimized mobile layouts.
Benefits:GraphQL avoids over-fetching data by returning exactly the fields requested in a single call. UI API matches user permissions automatically.
Interview Scenario: "A custom LWC component needs to show an Account name, related Contact details, and active user profile layout settings all in one network request to maximize page load speeds."

Connect REST API

Specialized programmatic layer mapping back to cloud features like Chatter feeds, Experience sites, and Commerce features.

Use Case:Building customized social networking layers, B2B commerce shopping experiences, or custom frontends for CMS.
Benefits:Returns responses pre-formatted for human reading (e.g., parses Chatter text links automatically).
Interview Scenario: "An external mobile shopping app wants to showcase active products directly from B2B Commerce Cloud and push localized activity post updates right into the user's account dashboard."

⏱️ Pre-Interview Flash Recap

  1. Use Bulk API 2.0 when data exceeds 50,000 records.
  2. Use Composite API instead of looping standard REST API calls to avoid hitting request rate limits.
  3. Choose GraphQL API for mobile applications to reduce data usage and network payloads.
  4. Remember that Metadata API operates on structural configurations, while the Tooling API runs faster on smaller metadata subsets.

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