Mastering API Composition Pattern in .NET — A Guide to Unified Data for Distributed Systems

Modern enterprise applications increasingly rely on microservices to scale development, deployments, and operations. But splitting business logic into multiple services comes at a cost: data is now distributed across those services.

How do you gather all the data needed to render a single UI screen (like an order summary page) without overloading the client with dozens of calls?

Enter the API Composition Pattern — a design that aggregates data from multiple microservices into a single, unified API call, simplifying both client-side development and improving system performance.

In this blog, we’ll explore:

• What is the API Composition Pattern?

• Why and when should you use it?

• How to implement it in .NET (with code!)

• Best practices for real-world success

What is the API Composition Pattern?

The API Composition Pattern acts as a middle layer (or facade) that:

• Aggregates data from multiple microservices.

• Builds a single, unified response.

• Reduces client-side complexity.

Instead of the client making multiple API calls to different services — Orders, Payments, Shipping — the API Composer orchestrates those calls on the server side and composes the final response.

Why Use API Composition?

✅ Simplified Client Logic — Clients call a single endpoint instead of multiple services.
✅ Better Performance — Server-side calls can be parallelized, reducing overall latency.
✅ Decoupling — Each microservice focuses on its domain; composition logic is centralized.
✅ Optimized Data Shape — Return exactly the data the client needs.

Implementing API Composition in .NET

Let’s walk through a practical example using an e-commerce scenario. Suppose we need to build an Order Summary API that returns:

• Order details from OrderService

• Payment status from PaymentService

• Shipping status from ShippingService

Step 1️⃣ — Define Data Contracts

https://dotnetfullstackdev.medium.com/

public class OrderSummaryDto
{
    public OrderDto Order { get; set; }
    public PaymentDto Payment { get; set; }
    public ShippingDto Shipping { get; set; }
}

public class OrderDto { public int Id; public decimal Total; }
public class PaymentDto { public int OrderId; public string Status; }
public class ShippingDto { public int OrderId; public string TrackingNumber; }

Step 2️⃣ — Create API Composition Service

public class OrderSummaryService
{
    private readonly HttpClient _httpClient;

    public OrderSummaryService(HttpClient httpClient)
    {
        _httpClient = httpClient;
    }

    public async Task<OrderSummaryDto> GetOrderSummaryAsync(int orderId)
    {
        var orderTask = _httpClient.GetFromJsonAsync<OrderDto>($"https://orderservice/api/orders/{orderId}");
        var paymentTask = _httpClient.GetFromJsonAsync<PaymentDto>($"https://paymentservice/api/payments/{orderId}");
        var shippingTask = _httpClient.GetFromJsonAsync<ShippingDto>($"https://shippingservice/api/shipping/{orderId}");

        await Task.WhenAll(orderTask, paymentTask, shippingTask);

        return new OrderSummaryDto
        {
            Order = await orderTask,
            Payment = await paymentTask,
            Shipping = await shippingTask
        };
    }
}

Step 3️⃣ — Expose a Controller Endpoint

[ApiController]
[Route("api/ordersummary")]
public class OrderSummaryController : ControllerBase
{
    private readonly OrderSummaryService _summaryService;

    public OrderSummaryController(OrderSummaryService summaryService)
    {
        _summaryService = summaryService;
    }

    [HttpGet("{orderId}")]
    public async Task<ActionResult<OrderSummaryDto>> Get(int orderId)
    {
        var summary = await _summaryService.GetOrderSummaryAsync(orderId);
        return Ok(summary);
    }
}

How It Works

1️⃣ The client calls GET /api/ordersummary/1234.
2️⃣ The OrderSummaryService concurrently calls all dependent services: Order, Payment, and Shipping.
3️⃣ Once all responses arrive, the service composes a single DTO and returns it to the client.

Challenges and Considerations

🔸 Performance — For high-volume systems, ensure dependencies are fast. Use caching or partial composition if needed.
🔸 Error Handling — What if one service fails? Return partial results? Fail the request?
🔸 Consistency — Data might be slightly stale or inconsistent across services.
🔸 Security and Authorization — Ensure sensitive data is filtered based on user roles.

Best Practices

✅ Use parallel calls (Task.WhenAll) to reduce latency.
✅ Implement circuit breakers (Polly) to handle failing services gracefully.
✅ Use caching for data that doesn’t change often.
✅ Log and monitor calls to detect slow dependencies.
✅ Keep composition logic separate from business logic — for example, using a dedicated API Gateway or BFF (Backend-for-Frontend).

Conclusion

The API Composition Pattern is a powerful strategy for building unified, user-friendly APIs in distributed .NET systems. By aggregating data on the server side, you:

• Reduce client complexity

• Improve performance

• Keep your microservices focused and independent

In .NET, implementing API Composition is straightforward — using HttpClient, DTOs, and a single controller layer. Add resilience with Polly, and you’re ready to build reliable, scalable, and elegant distributed systems.