Role Definition

The solution architect is responsible for the design of the software solution.

In this role, the solution architect is responsible not only for coding the solution, but also for the following topics:

Microservices and API Design

Microservice architecture is one of the most popular architectural patterns for building scalable and maintainable software solutions.

Microservices are a set of small, independent services that can be developed, deployed, and scaled independently. Along with API Design, they form the backbone of modern software architectures.

On the other hand, API Design is the design of the API that will be used to communicate between the services.

Data Strategy and Data Management

Data Strategy is the strategy for the data management of the software solution.

Phase 1: Architectural Patterns & Design

Goal: Prove you can design scalable, decoupled systems.

Microservices vs. Monolith

Be ready to explain when not to use microservices. The distributed monolith is a common failure mode interviewers look for.

Domain-Driven Design (DDD)

Question: How do you identify bounded contexts in a legacy monolith?

Ready Answer: Analyze business capabilities, identify natural seams in the codebase, and look for areas with distinct data models or workflows.

Question: What define the equality operator for Identity vs Value Object?

Ready Answer: Identity objects are compared by their unique identifier (ID), while Value Objects are compared based on their attributes or properties.

Design Patterns

Resilience Patterns

Phase 2: The .NET Core Ecosystem

Goal: Show deep expertise in the primary technology stack.

Communication Protocols

.NET Specifics

API Gateways

Question: When would you use gRPC over REST?

Ready Answer: Use gRPC for high-performance, low-latency communication between internal microservices, especially when you need strong typing and support for streaming. REST is better suited for public APIs where human readability and broad client support are priorities.

Question: What is the difference between Scoped and Transient services in .NET Dependency Injection?

Ready Answer:

- Scoped services are created once per client request (or scope), meaning they are shared within that request but not across requests.

- Transient services are created each time they are requested, so a new instance is provided every time they are injected.

- Singleton services are

Question: What is a .NET Generics?

Ready Answer: Generics in .NET allow you to define classes, interfaces, and methods with a placeholder for the data type. This enables code reusability and type safety, as you can create data structures and algorithms that work with any data type without sacrificing performance or safety.

Phase 3: Data Strategy (SQL Server)

Goal: Address the hardest part of distributed systems — state.

Phase 4: DevOps & Containerization

Goal: Demonstrate you understand the “Path to Production”.

Phase 5: Observability

Goal: How do you know it’s broken before the customer calls?

The Three Pillars of Observability

  1. Logging: Structured logging (Serilog) sent to ELK/Seq/AppInsights. Logging is used to track application behavior and to troubleshoot issues.

Example of structured logging:

  {
    "timestamp": "2025-01-01T00:00:00.000Z",
    "level": "INFO",
    "message": "User logged in",
    "userId": "1234567890"
  }

Example of error logging with context:

  {
    "timestamp": "2025-01-01T00:00:00.000Z",
    "level": "ERROR",
    "message": "Failed to process order",
    "orderId": "ORD-12345",
    "userId": "1234567890",
    "exception": "System.InvalidOperationException",
    "stackTrace": "..."
  }

Example of performance logging:

  {
    "timestamp": "2025-01-01T00:00:00.000Z",
    "level": "INFO",
    "message": "API request completed",
    "endpoint": "/api/orders",
    "method": "POST",
    "duration": 250,
    "statusCode": 201
  }

  1. Metrics : CPU, Memory, Request Latency (Prometheus/Grafana). Metrics are used to track application performance and to troubleshoot issues.

    Example of metrics:

    {
  "timestamp": "2025-01-01T00:00:00.000Z",
  "cpu": 50,
  "memory": 100,
  "requestLatency": 100
}

  2. Tracing: OpenTelemetry (standard in .NET now). Visualizing a request as it hops between 5 different microservices (Correlation IDs). Tracing is used to track application behavior and to troubleshoot issues.

    Example of tracing:

    {
  "traceId": "1234567890",
  "spanId": "1234567890",
  "parentSpanId": "1234567890",
  "operationName": "GetUser",
  "startTime": "2025-01-01T00:00:00.000Z",
  "endTime": "2025-01-01T00:00:00.000Z",
  "duration": 100
}

Top 5 Interview Questions to Expect

  1. How do you handle a transaction that spans two different microservices (e.g., Order and Inventory)?

    • Answer Guide: Do not suggest a distributed transaction (MSDTC). Propose the Saga Pattern (Order Created -> Reserve Inventory -> If Fail -> Compensating Transaction to Cancel Order).

  2. We have a slow SQL query in a monolithic stored procedure. How do we migrate this to microservices?

    • Answer Guide: Identify the bounded context. Extract the logic to code (EF Core/Dapper). Implement caching (Redis). If read-heavy, suggest CQRS with a read-optimized replica.

  3. How do you prevent one microservice from taking down the whole system if it creates a loop of requests?

    • Answer Guide: Discuss Circuit Breakers (stop calling the failing service) and Rate Limiting.

  4. REST vs. Message Queues: How do you decide which to use?

    • Answer Guide: Use REST/gRPC when the client needs an immediate answer (Query). Use Messaging (Queues) for state changes (Commands) to decouple systems and handle load spikes.

  5. How do you manage configuration across Dev, QA, and Prod environments in Kubernetes?

    • Answer Guide: Helm Charts, Kustomize, or external configuration stores (Azure App Config) injected as environment variables or volume mounts.

    Helm Charts are the best way to manage configuration across Dev, QA, and Prod environments in Kubernetes.

Phase 6: Testing

Goal: Show deep expertise in testing.

Testing Pyramid

The testing pyramid is a model that suggests the different types of tests should be in a specific ratio. It is a way to balance the different types of tests and to ensure that the tests are comprehensive and effective.

Testing pyramid diagram showing five levels of testing from bottom to top: Unit Tests (largest red base), Component Tests (orange), Integration Tests (yellow), API Tests (teal), and UI Tests (blue triangle at top). Manual Tests appear as a blue cloud above the pyramid. Left side shows arrow labeled More Isolation to More Integration. Right side shows arrow labeled Faster to Slower. Gray boxes on right contain icons representing End to End testing, integration workflows, component testing, and unit testing respectively. The pyramid illustrates that unit tests should form the foundation with fewer higher-level tests as you move up the hierarchy.

Test coverage should be:

Unit Tests:        100%
Integration Tests:  80%
E2E Tests:          50%

Testing Types

3A Principles

The 3A principles are a way to test the code. They are:

Test Libraries

Unit Tests

Unit tests are used to test the smallest units of code. They are typically fast to run and can be run independently.

Integration Tests

Integration tests are used to test the integration of the different units of code. They are typically slower to run and can be run independently.

BDD Tests

Behavior Driven Development (BDD) tests are used to test the behavior of the different units of code. They are typically slower to run and can be run independently.

Contract Tests

Contract tests are used to test the contracts of the different units of code. They are typically slower to run and can be run independently.

Component Tests

Component tests are used to test the components of the different units of code. They are typically slower to run and can be run independently. A well known framework is Testcontainers. It allows to test the components of the different units of code in a containerized environment.