Custom APIs in Dataverse: Choosing Between Internal and External Strategies

When designing Custom APIs in Dataverse, deciding between an internal or external strategy depends on your solution’s architecture, performance needs, and integration boundaries. Internal Custom APIs run entirely within Dataverse and are ideal when the business logic relies on CRM data, must follow Dataverse security rules, or benefits from unified auditing, plug-in execution, and transactional consistency. These are best suited for validations, entity operations, or orchestrations that must remain inside the platform. In contrast, external Custom APIs involve hosting logic outside Dataverse—such as Azure Functions, Web APIs, or cloud-based microservices—and are appropriate when the logic requires advanced computation, integrates heavily with external systems, or must scale beyond Dataverse’s plug-in limits. External APIs offer greater flexibility, but require secure authentication, lifecycle management, and monitoring. Ultimately, choosing between internal and external strategies depends on where the logic can execute most efficiently, the level of control needed, and how tightly the operation is coupled with Dataverse data and processes.

When designing enterprise-grade solutions on Microsoft Dataverse, Custom APIs play a critical role in structuring business logic, enabling integration, and providing reusable operations across apps and services. A key architectural decision is whether to implement your Custom API internally (inside Dataverse) or externally (outside Dataverse, e.g., Azure Functions or Web APIs).

Each strategy comes with technical and operational implications that affect performance, scalability, security, and maintainability.

Internal Custom APIs (Within Dataverse)

Internal Custom APIs are implemented directly inside Dataverse, with logic written in C# plugins that run within the Dataverse server pipeline.

What They Are

• Custom operations defined in Dataverse
• Executed via a plugin handler (C# class)
• Invoked from Power Apps, Power Automate, JavaScript, or external clients

When to Use Internal Custom APIs

Use internal Custom APIs when:

• Logic is tightly coupled with Dataverse data
• Pre/Post validations
• Entity updates, lookups, cascading logic
• Transactional consistency is required
• All steps must succeed or fail together
• Uses Dataverse’s native transaction scope
• You need Dataverse-level security enforcement
• Row security
• Field-level security
• Business unit hierarchies
• Performance needs are moderate and operations are synchronous
• The API is called frequently within the platform (model-driven apps, plugins, flows)

Benefits of Internal APIs

• Runs within the Dataverse pipeline (high consistency)
• Full access to entity images, execution context, pre/post operations
• No external hosting, deployment, or maintenance
• Better security due to Dataverse authentication and RBAC
• Can trigger business rules, workflows, and plugin steps automatically
• Lower latency for Dataverse-to-Dataverse calls

Limitations

• Execution time limits (2 minutes for sync, 10 minutes for async)
• Plugin throttling under heavy load
• Complex logic can become slow or expensive to maintain
• Not ideal for heavy computation or large datasets

External Custom APIs (Hosted Outside Dataverse)

External Custom APIs run outside Dataverse, commonly in:

• Azure Functions
• Azure App Service / Web APIs
• Azure Logic Apps
• Microservices

They integrate with Dataverse using:

• Dataverse Web API
• Custom connectors
• Power Automate HTTP actions

When to Use External APIs

Use external Custom APIs when:

• Advanced or heavy processing is involved
• Machine learning
• Large data merges
• PDF generation/reporting
• Complex decision engines
• Integration with external systems is the primary focus
• SAP
• Oracle systems
• Payment gateways
• Compliance engines
• Logic must be scalable, asynchronous, and run independently
• You need:
• Multithreading
• Custom logging
• Dependency injection
• Long-running workflows
• You want deployment flexibility (DevOps pipelines)

Benefits of External APIs

• Scalable and high-performance
• Can run long tasks without Dataverse timeouts
• Platform-agnostic (can be updated independently)
• Easier to test and debug
• Ideal for microservices architecture
• Supports reusable endpoints shared across systems

Limitations

• Requires additional infrastructure (Azure resources)
• More complex security implementation
• Data consistency must be managed manually
• Cannot participate in Dataverse transactions
• Needs monitoring and error handling frameworks

Key Architectural Decision Criteria

Here is a practical way to decide between internal and external strategies:

A. Is the logic domain-specific or platform-specific?

• Depends on Dataverse fields/records → Internal
• Independent of Dataverse → External

B. Are performance and scalability critical?

• High volume or intensive processing → External
• Light, transactional logic → Internal

C. Which security model do you need?

• Need Dataverse role-based control → Internal
• Need API-key, OAuth, or client app-level control → External

D. Does it need to run in the same transaction as a Dataverse operation?

• Yes → Internal
• No → External

E. What type of user or system consumes it?

• Dataverse UI components or Flows → Both possible
• External systems → External

Comparison Table: Internal vs External Custom APIs

When a Hybrid Approach Is Best

Some solutions need both internal and external APIs.

Examples:

Example 1: Blacklist Processing (Your Case)

• Internal API → create processing records, validate fields
• External API → run heavy matching logic or AI checks

Example 2: Document Generation

• Internal → gather data from Dataverse
• External → Create PDF, watermark, signatures

Example 3: Real-Time UI Actions

• Internal → Validate record
• External → Call SAP / banking system