Reducing Try-Catch in Dynamics 365 Plugins Using DTO Validation Classes

Dynamics 365 plugins run inside an event-driven execution pipeline where business rules and data validation must be enforced before database operations complete. As systems evolve, plugin code often degrades into heavy defensive programming filled with null checks, type casting, and nested exception handling.

Over time, exception handling begins to overshadow the actual business logic.

This article introduces a DTO + Validation Layer pattern that restructures plugin design into a clean, testable, and scalable architecture.

What Is “Try-Catch Hell” in Plugins?

Typical Causes

• a. Direct access to raw Entity attributes
• b. Runtime casting (Money, OptionSetValue, EntityReference)
• c. Constant checks for missing attributes
• d. Validation logic mixed with business logic

Symptoms

Result:
Plugins behave like procedural error-handling scripts instead of structured business components.

Architectural Shift: Entity-Centric → DTO-Centric

Traditional plugins manipulate the CRM Entity directly.

Problem:
The Entity object is:

• Loosely typed
• Attribute dictionary–based
• Runtime dependent

This makes failures more likely.

Proposed Flow

CRM Entity → Mapper → DTO → Validator → Business Logic

This separates:

• a. Data extraction
• b. Validation
• c. Processing

DTO: A Strongly-Typed Contract

DTOs act as a safe bridge between CRM data and business logic.

public class InvoiceDTO
{
    public decimal Amount { get; set; }
    public string CustomerName { get; set; }
    public DateTime InvoiceDate { get; set; }
}

Mapping Layer: Controlled Data Extraction

All CRM attribute handling is isolated in one place.

public static class InvoiceMapper
{
    public static InvoiceDTO Map(Entity entity)
    {
        return new InvoiceDTO
        {
            Amount = entity.GetAttributeValue<Money>("new_amount")?.Value ?? 0,
            CustomerName = entity.GetAttributeValue<string>("new_customer"),
            InvoiceDate = entity.GetAttributeValue<DateTime>("new_invoicedate")
        };
    }
}

Benefits

• a. Centralized attribute names
• b. No repetitive null checks
• c. Easier schema updates

Validation Layer: Centralized Rule Logic

public class InvoiceValidator
{
    public void Validate(InvoiceDTO invoice)
    {
        if (invoice.Amount <= 0)
            throw new InvalidPluginExecutionException("Invoice amount must be greater than zero.");

        if (string.IsNullOrWhiteSpace(invoice.CustomerName))
            throw new InvalidPluginExecutionException("Customer is required.");

        if (invoice.InvoiceDate > DateTime.UtcNow)
            throw new InvalidPluginExecutionException("Invoice date cannot be in the future.");
    }
}

The Clean Plugin Pattern

public void Execute(IServiceProvider serviceProvider)
{
    var context = (IPluginExecutionContext)serviceProvider.GetService(typeof(IPluginExecutionContext));
    var entity = (Entity)context.InputParameters["Target"];

    var dto = InvoiceMapper.Map(entity);

    var validator = new InvoiceValidator();
    validator.Validate(dto);

    ProcessInvoice(dto);
}

Now the plugin:

• a. Does not perform attribute-level checks
• b. Contains no nested try-catch blocks
• c. Focuses only on orchestration

Reduction of Exception Noise

Before: Exceptions for missing fields, null references, casting issues, and validation errors.

After: Only meaningful business validation exceptions remain.

The architecture shifts from reactive error handling to structured validation.

Generative Design Advantages

Testability Improvement

[TestMethod]
public void Should_Fail_When_Amount_Is_Negative()
{
    var dto = new InvoiceDTO { Amount = -10, CustomerName = "ABC" };
    var validator = new InvoiceValidator();

    Assert.ThrowsException<InvalidPluginExecutionException>(() => validator.Validate(dto));
}

No CRM context required.

Performance Considerations

• a. DTO mapping is lightweight
• b. Early validation reduces pipeline rollbacks
• c. Clear logic improves maintainability

To conclude, the DTO + Validation pattern is not just a coding improvement- it changes the way plugins are built.

In many Dynamics 365 projects, plugins slowly become difficult to read because developers keep adding null checks, type conversions, and try-catch blocks. Over time, the actual business logic gets lost inside error handling.

Using DTOs and a Validation layer fixes this problem in a structured way.

Instead of working directly with the CRM Entity object everywhere, we first convert data into a clean, strongly typed DTO. This removes repeated attribute checks and reduces runtime errors. The code becomes clearer because we work with proper properties instead of dictionary-style field access.

Then, all business rules are moved into a Validator class. This means:

• a. Validation is written once
• b. Rules stay consistent
• c. Plugins stay small and readable

Now the plugin only performs four simple steps:

Get data → Convert to DTO → Validate → Run business logic

Because of this:

• a. The code is easier to read
• b. Future changes are easier
• c. Errors are easier to trace
• d. Logic can be reused in other plugins

Developers can understand the purpose of the plugin faster, instead of trying to follow complex nested try-catch blocks.

If your Dynamics 365 environment is evolving in complexity, reach out to CloudFronts, transform@cloudfronts.com, specialists regularly design and implement structured plugin architectures that improve performance, maintainability, and long-term scalability.