fixing(infra-messaging)
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# Meldestelle Development Guidelines
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**Version:** 1.0
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**Date:** 2025-08-15
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**Status:** Active
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This document outlines the development guidelines for the Meldestelle project, covering coding conventions, code organization, and testing approaches.
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---
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## 1. Coding Conventions
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### 1.1 Language Standards
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- **Primary Language:** Kotlin (JVM/Multiplatform)
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- **Java Compatibility:** Target Java 21+
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- **Kotlin Version:** Latest stable version
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- **Code Style:** Official Kotlin coding conventions
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### 1.2 Naming Conventions
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#### Classes and Interfaces
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```kotlin
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// Use PascalCase for classes and interfaces
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class MemberService
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interface EventRepository
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data class MemberRegistration
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sealed class AuthResult
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// Use descriptive names that reflect domain concepts
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class HorseRegistrationService // Good
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class HRS // Avoid abbreviations
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```
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#### Functions and Variables
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```kotlin
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// Use camelCase for functions and variables
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fun authenticateUser(): AuthResult
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val memberRepository: MemberRepository
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suspend fun findByEmail(email: EmailAddress): Result<Member?, RepositoryError>
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// Use descriptive test method names with "should" statements
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@Test
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fun `authenticate should return Success for valid credentials`()
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```
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#### Constants and Enums
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```kotlin
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// Use SCREAMING_SNAKE_CASE for constants
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const val MAX_RETRY_ATTEMPTS = 3
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const val DEFAULT_TIMEOUT_MS = 5000L
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// Use PascalCase for enum values
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enum class MemberStatus {
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ACTIVE,
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INACTIVE,
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SUSPENDED
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}
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```
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### 1.3 Code Structure Principles
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#### Result Pattern Usage
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```kotlin
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// Always use Result pattern for operations that can fail
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interface MemberRepository {
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suspend fun findById(id: MemberId): Result<Member?, RepositoryError>
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suspend fun save(member: Member): Result<Unit, RepositoryError>
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}
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// Result extensions for error handling
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inline fun <T, E, R> Result<T, E>.mapError(transform: (E) -> R): Result<T, R> =
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when (this) {
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is Result.Success -> Result.Success(value)
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is Result.Failure -> Result.Failure(transform(error))
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}
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```
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#### Coroutines and Async Programming
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```kotlin
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// Use suspend functions for async operations
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suspend fun processEventBatch(events: List<DomainEvent>): Result<Unit, ProcessingError>
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// Prefer structured concurrency
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class EventProcessor {
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private val scope = CoroutineScope(SupervisorJob() + Dispatchers.IO)
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suspend fun processEvents() = withContext(scope.coroutineContext) {
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// Implementation
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}
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}
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```
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#### Documentation Standards
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```kotlin
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/**
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* Authenticates a user with the given credentials.
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*
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* @param credentials The user credentials containing username and password
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* @return AuthResult.Success with user data if authentication succeeds,
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* AuthResult.Failure with error details if it fails
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*/
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suspend fun authenticate(credentials: UserCredentials): AuthResult
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```
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---
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## 2. Code Organization and Package Structure
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### 2.1 Overall Architecture
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The project follows a **microservices architecture** with **Domain-Driven Design (DDD)** principles and **Clean Architecture** patterns.
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#### High-Level Structure
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```
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Meldestelle/
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├── core/ # Shared kernel - fundamental building blocks
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│ ├── core-domain/ # Common domain types and interfaces
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│ └── core-utils/ # Shared utilities and extensions
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├── infrastructure/ # Cross-cutting infrastructure services
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│ ├── auth/ # Authentication & authorization
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│ ├── messaging/ # Event messaging (Kafka)
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│ ├── cache/ # Distributed caching (Redis)
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│ ├── gateway/ # API Gateway
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│ └── monitoring/ # Observability and monitoring
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├── [domain-services]/ # Domain-specific microservices
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│ ├── members/ # Member management
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│ ├── events/ # Event management
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│ ├── horses/ # Horse registry
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│ └── masterdata/ # Master data management
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├── client/ # Client applications
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│ ├── common-ui/ # Shared UI components (KMP)
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│ ├── desktop-app/ # Desktop application
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│ └── web-app/ # Web application
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└── platform/ # Build and dependency management
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```
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### 2.2 Microservice Structure (Clean Architecture)
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Each domain service follows a **4-layer architecture**:
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```
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domain-service/
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├── domain-api/ # REST controllers, DTOs, API contracts
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├── domain-application/ # Use cases, application logic, orchestration
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├── domain-domain/ # Domain models, business rules, interfaces
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└── domain-infrastructure/ # Technical implementations (DB, external APIs)
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```
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#### Layer Responsibilities
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**`:domain-api` Layer:**
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```kotlin
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// REST Controllers
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@RestController
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@RequestMapping("/api/v1/members")
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class MemberController(private val memberService: MemberService)
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// DTOs for external communication
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data class MemberRegistrationRequest(
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val firstName: String,
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val lastName: String,
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val email: String
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)
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```
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**`:domain-application` Layer:**
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```kotlin
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// Use cases and application services
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class MemberApplicationService(
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private val memberRepository: MemberRepository,
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private val eventPublisher: EventPublisher
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) {
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suspend fun registerMember(command: RegisterMemberCommand): Result<MemberId, MemberError>
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}
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```
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**`:domain-domain` Layer:**
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```kotlin
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// Domain models and business logic
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data class Member(
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val id: MemberId,
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val personalInfo: PersonalInfo,
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val membershipStatus: MembershipStatus
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) {
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fun activate(): Member = copy(membershipStatus = MembershipStatus.ACTIVE)
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}
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// Repository interfaces (implemented in infrastructure)
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interface MemberRepository {
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suspend fun findById(id: MemberId): Result<Member?, RepositoryError>
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suspend fun save(member: Member): Result<Unit, RepositoryError>
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}
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```
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**`:domain-infrastructure` Layer:**
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```kotlin
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// Technical implementations
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class ExposedMemberRepository(
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private val database: Database
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) : MemberRepository {
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override suspend fun findById(id: MemberId): Result<Member?, RepositoryError> {
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// Database implementation using Exposed ORM
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}
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}
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```
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### 2.3 Package Naming Conventions
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```kotlin
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// Base package structure
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at.mocode.[layer].[domain].[component]
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// Examples
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at.mocode.members.domain.model // Domain models
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at.mocode.members.application.service // Application services
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at.mocode.members.infrastructure.persistence // Persistence layer
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at.mocode.infrastructure.messaging.kafka // Infrastructure components
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at.mocode.core.utils.result // Core utilities
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```
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### 2.4 Dependency Rules
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- **Core modules** must not depend on any other modules
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- **Domain layer** must not depend on infrastructure or application layers
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- **Application layer** can depend on domain layer only
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- **Infrastructure layer** can depend on domain and application layers
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- **API layer** orchestrates calls between application and infrastructure
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---
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## 3. Unit and Integration Testing Approaches
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### 3.1 Testing Strategy Overview
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The project follows a **comprehensive testing strategy** with multiple testing levels:
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1. **Unit Tests** - Fast, isolated tests for individual components
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2. **Integration Tests** - Tests for component interactions
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3. **Performance Tests** - Load and throughput testing
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4. **End-to-End Tests** - Full system workflow testing
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### 3.2 Testing Stack
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#### Core Testing Libraries
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```kotlin
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// Unit testing
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testImplementation("org.junit.jupiter:junit-jupiter:5.10.0")
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testImplementation("io.mockk:mockk:1.13.8")
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testImplementation("org.jetbrains.kotlinx:kotlinx-coroutines-test:1.7.3")
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// Integration testing
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testImplementation("org.testcontainers:junit-jupiter:1.19.1")
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testImplementation("org.testcontainers:kafka:1.19.1")
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testImplementation("org.testcontainers:postgresql:1.19.1")
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// Performance testing
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testImplementation("org.jetbrains.kotlinx:kotlinx-coroutines-test:1.7.3")
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```
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### 3.3 Unit Testing Conventions
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#### Test Structure and Naming
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```kotlin
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class AuthenticationServiceTest {
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@BeforeEach
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fun setUp() {
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// Test setup
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}
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@Test
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fun `authenticate should return Success for valid credentials`() = runTest {
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// Given
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val credentials = UserCredentials("user@example.com", "validPassword")
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coEvery { userRepository.findByEmail(any()) } returns Result.Success(testUser)
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// When
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val result = authenticationService.authenticate(credentials)
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// Then
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assertTrue(result is AuthResult.Success)
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assertEquals(testUser.id, result.user.id)
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}
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@Test
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fun `authenticate should return Failure for invalid credentials`() = runTest {
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// Given - When - Then pattern
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}
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}
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```
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#### Mocking Best Practices
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```kotlin
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class MemberServiceTest {
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private val memberRepository = mockk<MemberRepository>()
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private val eventPublisher = mockk<EventPublisher>()
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private val memberService = MemberService(memberRepository, eventPublisher)
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@Test
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fun `should publish event when member is registered`() = runTest {
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// Mock repository responses
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coEvery { memberRepository.save(any()) } returns Result.Success(Unit)
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coEvery { eventPublisher.publish(any()) } returns Result.Success(Unit)
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// Test implementation
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val result = memberService.registerMember(validCommand)
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// Verify interactions
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coVerify { eventPublisher.publish(any<MemberRegisteredEvent>()) }
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}
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}
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```
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### 3.4 Integration Testing Approaches
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#### Database Integration Tests
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```kotlin
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@Testcontainers
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class MemberRepositoryIntegrationTest {
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companion object {
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@Container
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val postgres = PostgreSQLContainer<Nothing>("postgres:15-alpine")
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}
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@Test
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fun `should persist and retrieve member correctly`() = runTest {
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// Test with real database using Testcontainers
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val member = createTestMember()
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val saveResult = memberRepository.save(member)
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assertTrue(saveResult.isSuccess())
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val retrievedResult = memberRepository.findById(member.id)
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assertTrue(retrievedResult.isSuccess())
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assertEquals(member, retrievedResult.getOrNull())
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}
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}
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```
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#### Messaging Integration Tests
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```kotlin
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@Testcontainers
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class KafkaEventPublisherIntegrationTest {
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companion object {
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@Container
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val kafka = KafkaContainer(DockerImageName.parse("confluentinc/cp-kafka:latest"))
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}
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@Test
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fun `should publish and consume events correctly`() = runTest {
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val event = MemberRegisteredEvent(memberId = MemberId.generate())
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val publishResult = eventPublisher.publish(event)
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assertTrue(publishResult.isSuccess())
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// Verify event was consumed
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val consumedEvents = eventConsumer.consumeEvents(timeout = 5.seconds)
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assertTrue(consumedEvents.any { it.memberId == event.memberId })
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}
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}
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```
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### 3.5 Performance Testing
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#### Batch Processing Performance Tests
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```kotlin
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class KafkaBatchPerformanceTest {
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@Test
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fun `should process large batches within acceptable time limits`() = runTest {
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val batchSize = 1000
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val events = generateTestEvents(batchSize)
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val startTime = System.currentTimeMillis()
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val results = eventProcessor.processBatch(events)
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val processingTime = System.currentTimeMillis() - startTime
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assertTrue(results.all { it.isSuccess() })
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assertTrue(processingTime < 5000) // Should complete within 5 seconds
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println("[DEBUG_LOG] Processed $batchSize events in ${processingTime}ms")
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}
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}
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```
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### 3.6 Test Organization
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#### Directory Structure
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```
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src/
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├── main/kotlin/ # Production code
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└── test/kotlin/ # Test code
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├── unit/ # Unit tests (optional sub-organization)
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├── integration/ # Integration tests
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└── performance/ # Performance tests
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```
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#### Test Categories and Execution
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```kotlin
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// Use JUnit 5 tags for test categorization
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@Tag("unit")
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class MemberServiceTest
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@Tag("integration")
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class MemberRepositoryIntegrationTest
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@Tag("performance")
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class KafkaBatchPerformanceTest
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```
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### 3.7 Testing Guidelines
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#### Best Practices
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1. **Test Method Naming:** Use descriptive names with "should" statements
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2. **AAA Pattern:** Arrange, Act, Assert structure
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3. **One Assertion Per Test:** Focus on single behavior
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4. **Test Data Builders:** Use factory methods for test data creation
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5. **Coroutine Testing:** Use `runTest` for suspend functions
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6. **Mock Verification:** Verify important interactions, not implementation details
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#### Coverage Goals
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- **Unit Tests:** 80%+ code coverage for domain and application layers
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- **Integration Tests:** Cover all repository implementations and external integrations
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- **Performance Tests:** Cover critical batch operations and high-load scenarios
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#### Debugging Support
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```kotlin
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// Always prefix debug messages with [DEBUG_LOG]
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@Test
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fun `should handle concurrent requests`() = runTest {
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println("[DEBUG_LOG] Starting concurrent request test with ${requestCount} requests")
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// Test implementation
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println("[DEBUG_LOG] Completed test. Success rate: ${successCount}/${requestCount}")
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}
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```
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---
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## 4. Additional Development Standards
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### 4.1 Error Handling
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- Use `Result` pattern consistently for operations that can fail
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- Define domain-specific error types
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- Avoid throwing exceptions in domain logic
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### 4.2 Logging and Monitoring
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- Use structured logging with appropriate log levels
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- Include correlation IDs for request tracing
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- Monitor key business metrics and technical performance
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### 4.3 Security Considerations
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- Validate all external inputs
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- Use JWT tokens for authentication
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- Implement proper authorization checks
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- Secure sensitive configuration data
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||||
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||||
---
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||||
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||||
This guideline is a living document and should be updated as the project evolves and new patterns emerge.
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||||
@@ -1,240 +0,0 @@
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# Meldestelle_Pro: Entwicklungs-Guideline
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||||
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||||
## Status: Finalisiert & Verbindlich
|
||||
|
||||
### 1. Vision & Architektonische Grundpfeiler
|
||||
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||||
Dieses Dokument definiert die verbindlichen technischen Richtlinien und Qualitätsstandards für das Projekt "
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Meldestelle_Pro". Ziel ist die Schaffung einer modernen, skalierbaren und wartbaren Plattform für den Pferdesport.
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Unsere Architektur basiert auf vier Säulen:
|
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1. **Modularität & Skalierbarkeit** durch eine **Microservices-Architektur.**
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2. **Fachlichkeit im Code** durch **Domain-Driven Design (DDD).**
|
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3. **Entkopplung & Resilienz** durch eine **ereignisgesteuerte Architektur (EDA).**
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||||
4. **Effizienz & Konsistenz** durch eine **Multiplattform-Client-Strategie (KMP).**
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||||
Jede Code-Änderung muss diese vier Grundprinien respektieren.
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||||
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||||
---
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||||
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### 2. Backend-Entwicklungsrichtlinien
|
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#### 2.1. Microservice-Struktur (Clean Architecture)
|
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**Jeder fachliche Microservice (z.B. :members, :events) muss der etablierten 4-Layer-Struktur folgen:**
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* **`:*-api`: Definiert die öffentliche Schnittstelle des Service (REST-Controller, DTOs).**
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* **`:*-application`: Enthält die Anwendungslogik und Use Cases. Hier werden die Repositories orchestriert.**
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* **`:*-domain`: Das Herz des Service. Enthält die reinen, von Frameworks unabhängigen Domänenmodelle, Geschäftsregeln
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und Repository-Interfaces.**
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* **`:*-infrastructure`: Die technische Implementierung der Interfaces aus der Domänenschicht (z.B. Datenbankzugriff mit
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Exposed).**
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#### 2.2. Domain-Driven Design (DDD) in der Praxis
|
||||
|
||||
* **Shared Kernel (`:core`-Modul):** Das `:core`-Modul ist heilig. Es darf **ausschließlich** fundamentalen,
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domänen-agnostischen Code enthalten. Fachspezifische Konzepte gehören in ihre jeweilige Domäne.
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||||
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||||
* **Repository-Pattern mit `Result`:** Jede Repository-Methode muss das `Result`-Pattern verwenden, um Erfolgs- und
|
||||
Fehlerfälle explizit und typsicher zu behandeln.
|
||||
|
||||
```kotlin
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||||
// Repository mit Result-Pattern
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||||
interface MemberRepository {
|
||||
suspend fun findById(id: MemberId): Result<Member?, RepositoryError>
|
||||
suspend fun save(member: Member): Result<Unit, RepositoryError>
|
||||
suspend fun findByEmail(email: EmailAddress): Result<List<Member>, RepositoryError>
|
||||
}
|
||||
```
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||||
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||||
#### 2.3. Messaging & Event-Naming
|
||||
|
||||
* **Asynchrone Kommunikation:** Die bevorzugte Kommunikationsmethode ist asynchron über Kafka.
|
||||
|
||||
* **Event-Naming Convention:** Domänen-Events folgen dem Muster `{Domain}{Entity}{Action}Event`.
|
||||
|
||||
```kotlin
|
||||
// Event-Naming Convention
|
||||
sealed class DomainEvent(
|
||||
val aggregateId: String,
|
||||
val version: Long,
|
||||
val timestamp: Instant = Instant.now()
|
||||
) {
|
||||
// Pattern: {Domain}{Entity}{Action}Event
|
||||
data class MemberPersonalDataUpdatedEvent(
|
||||
val memberId: MemberId,
|
||||
val personalData: PersonalData
|
||||
) : DomainEvent(memberId.value, version)
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 3. Frontend-Entwicklungsrichtlinien
|
||||
|
||||
#### 3.1. Architekturmuster: MVVM & KMP
|
||||
|
||||
Das Frontend folgt konsequent dem **Model-View-ViewModel (MVVM)**-Muster und der **Kotlin Multiplatform (KMP)**
|
||||
-Strategie:
|
||||
|
||||
* **Model & ViewModel:** Die gesamte Geschäftslogik, der Zustand und die API-Aufrufe leben im `:client:common-ui`-Modul
|
||||
und sind plattformunabhängig.
|
||||
|
||||
* **View:** Die Benutzeroberfläche wird mit **Compose Multiplatform* im `:client:common-ui`-Modul implementiert.
|
||||
|
||||
#### 3.2. Vertikale Schnitte (Features)
|
||||
|
||||
Der UI-Code wird nach **fachlichen Features** strukturiert. Ein Feature (z. B. "Nennungsabwicklung") hat sein eigenes
|
||||
Verzeichnis und enthält alle zugehörigen Views, ViewModels und Models.
|
||||
|
||||
---
|
||||
|
||||
### 4. Allgemeine Qualitätsstandards
|
||||
|
||||
#### 4.1. Code-Qualität & Kotlin-Konventionen
|
||||
|
||||
* **Value Classes für Typsicherheit:** Primitive Typen (UUID, String, Long) für IDs oder spezifische Werte müssen in
|
||||
typsichere `value class`-Wrapper gekapselt werden, um Fehler zu vermeiden.
|
||||
|
||||
```kotlin
|
||||
// Ergänzung für Value Objects
|
||||
@JvmInline
|
||||
value class MemberId(val value: UUID) {
|
||||
companion object {
|
||||
fun of(value: String): Result<MemberId, ValidationError> =
|
||||
runCatching { UUID.fromString(value) }
|
||||
.map { MemberId(it) }
|
||||
.mapError { ValidationError.INVALID_UUID }
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 4.2. Error-Handling
|
||||
|
||||
* **`Result`-Pattern statt Exceptions:** Für erwartbare Geschäftsfehler ist das `Result`-Pattern zu verwenden.
|
||||
|
||||
* **Spezifische Fehler-Hierarchie:** Wir verwenden eine `sealed class`-Hierarchie, um Fehlerarten klar zu
|
||||
kategorisieren.
|
||||
|
||||
```kotlin
|
||||
// Spezifische Error-Hierarchie definieren
|
||||
sealed class DomainError(val code: String, val message: String)
|
||||
sealed class ValidationError(code: String, message: String) : DomainError(code, message)
|
||||
sealed class BusinessError(code: String, message: String) : DomainError(code, message)
|
||||
sealed class TechnicalError(code: String, message: String) : DomainError(code, message)
|
||||
```
|
||||
|
||||
#### 4.3. Testing
|
||||
|
||||
* **Testcontainers als Goldstandard:** Jede Interaktion mit externer Infrastruktur (DB, Cache, Broker) **muss** mit *
|
||||
*Testcontainers** getestet werden.
|
||||
|
||||
* **Mocking für Isolation:** Abhängigkeiten innerhalb von Tests werden mit Mocking-Frameworks (z.B. MockK) isoliert, um
|
||||
den Testfokus zu schärfen.
|
||||
|
||||
```kotlin
|
||||
// Testcontainers-Pattern für Infrastruktur-Tests
|
||||
@TestConfiguration
|
||||
class KafkaTestConfig {
|
||||
@Bean
|
||||
@Primary
|
||||
fun kafkaEventPublisher(): KafkaEventPublisher = mockk()
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 5. Infrastruktur-Spezifikationen
|
||||
|
||||
#### 5.1. Kafka-Konfiguration
|
||||
|
||||
Die Konfiguration für Producer und Consumer muss produktionsreife Einstellungen für Zuverlässigkeit und Datenkonsistenz
|
||||
verwenden.
|
||||
|
||||
```YAML
|
||||
# Ergänzung für application.yml
|
||||
kafka:
|
||||
producer:
|
||||
acks: all
|
||||
enable-idempotence: true
|
||||
max-in-flight-requests-per-connection: 1
|
||||
consumer:
|
||||
group-id-prefix: "meldestelle-${spring.application.name}"
|
||||
auto-offset-reset: earliest
|
||||
enable-auto-commit: false
|
||||
```
|
||||
|
||||
#### 5.2. Datenbank-Migrationen mit Flyway
|
||||
|
||||
Migrations-Skripte müssen einer klaren Namenskonvention folgen.
|
||||
|
||||
* **Pattern:**`V{version}__{description}.sql` (z.B., `V001__Create_member_tables.sql`)
|
||||
|
||||
* **Repeatable:**`R__{description}.sql` (z.B., `R__Update_member_view.sql`)
|
||||
|
||||
---
|
||||
|
||||
### 6. Monitoring & Observability
|
||||
|
||||
#### 6.1. Structured Logging
|
||||
|
||||
Logs müssen als strukturierte Daten (z.B. JSON) ausgegeben werden und immer eine Korrelations-ID enthalten, um Anfragen
|
||||
über Service-Grenzen hinweg verfolgen zu können.
|
||||
|
||||
```Kotlin
|
||||
// Ergänzung zur Guideline
|
||||
@Component
|
||||
class MemberService {
|
||||
private val logger = KotlinLogging.logger {}
|
||||
|
||||
suspend fun createMember(command: CreateMemberCommand) {
|
||||
logger.info {
|
||||
"Creating member" with mapOf(
|
||||
"memberId" to command.memberId.value,
|
||||
"operation" to "create_member",
|
||||
"correlationId" to MDC.get("correlationId")
|
||||
)
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 6.2. Metrics
|
||||
|
||||
Es müssen sowohl technische als auch fachliche Metriken erfasst werden.
|
||||
|
||||
```Kotlin
|
||||
// Spezifische Business-Metriken definieren
|
||||
@Component
|
||||
class BusinessMetrics(meterRegistry: MeterRegistry) {
|
||||
private val memberRegistrations = Counter.builder("business.member.registrations.total")
|
||||
.description("Total number of member registrations")
|
||||
.tag("service", "members")
|
||||
.register(meterRegistry)
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 7. Zusätzliche Richtlinien
|
||||
|
||||
#### 7.1. Security
|
||||
|
||||
Die Autorisierung muss auf Methodenebene mit Spring Security Annotations (`@PreAuthorize`) durchgesetzt werden, um eine
|
||||
feingranulare Zugriffskontrolle zu gewährleisten.
|
||||
|
||||
#### 7.2. Performance
|
||||
|
||||
Cache-Strategien (`@Cacheable`, `@CacheEvict`) **müssen gezielt eingesetzt werden**, um die Latenz bei häufigen
|
||||
Lesezugriffen zu minimieren.
|
||||
|
||||
#### 7.3. Dokumentation
|
||||
|
||||
Alle öffentlichen REST-Endpunkte müssen mit OpenAPI-Annotationen (`@Operation`, `@ApiResponse`) dokumentiert werden, um
|
||||
eine klare und interaktive API-Dokumentation zu generieren.
|
||||
+711
@@ -0,0 +1,711 @@
|
||||
# Meldestelle_Pro: Entwicklungs-Guideline
|
||||
|
||||
**Status:** Finalisiert & Verbindlich
|
||||
**Version:** 2.0
|
||||
**Stand:** August 2025
|
||||
|
||||
## 1. Vision & Architektonische Grundpfeiler
|
||||
|
||||
Dieses Dokument definiert die verbindlichen technischen Richtlinien und Qualitätsstandards für das Projekt "Meldestelle_Pro". Ziel ist die Schaffung einer modernen, skalierbaren und wartbaren Plattform für den Pferdesport.
|
||||
|
||||
Unsere Architektur basiert auf **vier Säulen**:
|
||||
|
||||
1. **Modularität & Skalierbarkeit** durch eine **Microservices-Architektur**
|
||||
2. **Fachlichkeit im Code** durch **Domain-Driven Design (DDD)**
|
||||
3. **Entkopplung & Resilienz** durch eine **ereignisgesteuerte Architektur (EDA)**
|
||||
4. **Effizienz & Konsistenz** durch eine **Multiplattform-Client-Strategie (KMP)**
|
||||
|
||||
> **Grundsatz:** Jede Code-Änderung muss diese vier Grundprinzipien respektieren.
|
||||
|
||||
---
|
||||
|
||||
## 2. Backend-Entwicklungsrichtlinien
|
||||
|
||||
#### 2.1. Microservice-Struktur (Clean Architecture)
|
||||
|
||||
**Jeder fachliche Microservice (z.B. :members, :events) muss der etablierten 4-Layer-Struktur folgen:**
|
||||
|
||||
* **`:*-api`**: Definiert die öffentliche Schnittstelle des Service (REST-Controller, DTOs).
|
||||
* **`:*-application`**: Enthält die Anwendungslogik und Use Cases. Hier werden die Repositories orchestriert.
|
||||
* **`:*-domain`**: Das Herz des Service. Enthält die reinen, von Frameworks unabhängigen Domänenmodelle, Geschäftsregeln
|
||||
und Repository-Interfaces.
|
||||
* **`:*-infrastructure`**: Die technische Implementierung der Interfaces aus der Domänenschicht (z.B. Datenbankzugriff
|
||||
mit Exposed).
|
||||
|
||||
#### 2.2. Domain-Driven Design (DDD) in der Praxis
|
||||
|
||||
* **Shared Kernel (`:core`-Modul):** Das `:core`-Modul ist heilig. Es darf **ausschließlich** fundamentalen,
|
||||
domänen-agnostischen Code enthalten. Fachspezifische Konzepte gehören in ihre jeweilige Domäne.
|
||||
* **Repository-Pattern mit `Result`:** Jede Repository-Methode muss das `Result`-Pattern verwenden, um Erfolgs- und
|
||||
Fehlerfälle explizit und typsicher zu behandeln.
|
||||
|
||||
```kotlin
|
||||
// Repository mit Result-Pattern
|
||||
interface MemberRepository {
|
||||
suspend fun findById(id: MemberId): Result<Member?, RepositoryError>
|
||||
suspend fun save(member: Member): Result<Unit, RepositoryError>
|
||||
suspend fun findByEmail(email: EmailAddress): Result<List<Member>, RepositoryError>
|
||||
}
|
||||
```
|
||||
|
||||
#### 2.3. Core-Modul Spezifikation
|
||||
|
||||
Das `:core`-Modul definiert die fundamentalen Bausteine der gesamten Anwendung:
|
||||
|
||||
* **Result Extensions:** Utility-Funktionen für typsichere Fehlerbehandlung
|
||||
* **Common Types:** Basistypen für alle Domänen
|
||||
* **Shared Utilities:** Plattformunabhängige Hilfsfunktionen
|
||||
|
||||
```kotlin
|
||||
// Result Extensions im core-utils Modul
|
||||
inline fun <T, E, R> Result<T, E>.mapError(transform: (E) -> R): Result<T, R> =
|
||||
when (this) {
|
||||
is Result.Success -> Result.Success(value)
|
||||
is Result.Failure -> Result.Failure(transform(error))
|
||||
}
|
||||
|
||||
inline fun <T, E> Result<T, E>.onFailure(action: (E) -> Unit): Result<T, E> =
|
||||
also { if (it is Result.Failure) action(it.error) }
|
||||
|
||||
// Common Domain Types
|
||||
@JvmInline
|
||||
value class CorrelationId(val value: UUID) {
|
||||
companion object {
|
||||
fun generate(): CorrelationId = CorrelationId(UUID.randomUUID())
|
||||
fun of(value: String): Result<CorrelationId, ValidationError> =
|
||||
runCatching { UUID.fromString(value) }
|
||||
.map { CorrelationId(it) }
|
||||
.mapError { ValidationError.InvalidUUID("Invalid correlation ID: $value") }
|
||||
}
|
||||
}
|
||||
|
||||
// Konkrete Error-Implementierungen
|
||||
sealed class ValidationError(code: String, message: String) : DomainError(code, message) {
|
||||
data class InvalidUUID(override val message: String) :
|
||||
ValidationError("INVALID_UUID", message)
|
||||
data class InvalidEmail(override val message: String) :
|
||||
ValidationError("INVALID_EMAIL", message)
|
||||
data class InvalidLength(val field: String, val min: Int, val max: Int) :
|
||||
ValidationError("INVALID_LENGTH", "Field $field must be between $min and $max characters")
|
||||
}
|
||||
```
|
||||
|
||||
#### 2.4. Messaging & Event-Naming
|
||||
|
||||
* **Asynchrone Kommunikation:** Die bevorzugte Kommunikationsmethode ist asynchron über Kafka.
|
||||
* **Event-Naming Convention:** Domänen-Events folgen dem Muster `{Domain}{Entity}{Action}Event`.
|
||||
|
||||
```kotlin
|
||||
// Event-Naming Convention
|
||||
sealed class DomainEvent(
|
||||
val aggregateId: String,
|
||||
val version: Long,
|
||||
val timestamp: Instant = Instant.now()
|
||||
) {
|
||||
// Pattern: {Domain}{Entity}{Action}Event
|
||||
data class MemberPersonalDataUpdatedEvent(
|
||||
val memberId: MemberId,
|
||||
val personalData: PersonalData
|
||||
) : DomainEvent(memberId.value, version)
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 3. Frontend-Entwicklungsrichtlinien
|
||||
|
||||
#### 3.1. Architekturmuster: MVVM & KMP
|
||||
|
||||
Das Frontend folgt konsequent dem **Model-View-ViewModel (MVVM)**-Muster und der **Kotlin Multiplatform (KMP)**-Strategie:
|
||||
|
||||
* **Model & ViewModel:** Die gesamte Geschäftslogik, der Zustand und die API-Aufrufe leben im `:client:common-ui`-Modul und sind plattformunabhängig.
|
||||
* **View:** Die Benutzeroberfläche wird mit **Compose Multiplatform** im `:client:common-ui`-Modul implementiert.
|
||||
|
||||
#### 3.2. State Management
|
||||
|
||||
**Unidirectional Data Flow mit MVI-Pattern:**
|
||||
|
||||
```kotlin
|
||||
// State Management Pattern
|
||||
@Stable
|
||||
data class MemberListUiState(
|
||||
val members: List<Member> = emptyList(),
|
||||
val isLoading: Boolean = false,
|
||||
val error: String? = null,
|
||||
val searchQuery: String = ""
|
||||
)
|
||||
|
||||
sealed class MemberListIntent {
|
||||
object LoadMembers : MemberListIntent()
|
||||
data class SearchMembers(val query: String) : MemberListIntent()
|
||||
data class DeleteMember(val memberId: MemberId) : MemberListIntent()
|
||||
}
|
||||
|
||||
class MemberListViewModel(
|
||||
private val memberRepository: MemberRepository
|
||||
) : ViewModel() {
|
||||
private val _uiState = MutableStateFlow(MemberListUiState())
|
||||
val uiState: StateFlow<MemberListUiState> = _uiState.asStateFlow()
|
||||
|
||||
fun handleIntent(intent: MemberListIntent) {
|
||||
when (intent) {
|
||||
is MemberListIntent.LoadMembers -> loadMembers()
|
||||
is MemberListIntent.SearchMembers -> searchMembers(intent.query)
|
||||
is MemberListIntent.DeleteMember -> deleteMember(intent.memberId)
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 3.3. Navigation Architecture
|
||||
|
||||
**Compose Navigation mit typsicheren Routes:**
|
||||
|
||||
```kotlin
|
||||
// Navigation Definition
|
||||
@Serializable
|
||||
sealed class Screen {
|
||||
@Serializable
|
||||
object MemberList : Screen()
|
||||
|
||||
@Serializable
|
||||
data class MemberDetail(val memberId: String) : Screen()
|
||||
|
||||
@Serializable
|
||||
data class EventRegistration(val eventId: String, val memberId: String) : Screen()
|
||||
}
|
||||
|
||||
// Navigation Router
|
||||
class NavigationRouter {
|
||||
private val _navigationEvents = MutableSharedFlow<NavigationEvent>()
|
||||
val navigationEvents: SharedFlow<NavigationEvent> = _navigationEvents.asSharedFlow()
|
||||
|
||||
fun navigateTo(screen: Screen) {
|
||||
_navigationEvents.tryEmit(NavigationEvent.NavigateTo(screen))
|
||||
}
|
||||
|
||||
fun navigateBack() {
|
||||
_navigationEvents.tryEmit(NavigationEvent.NavigateBack)
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 3.4. Vertikale Schnitte (Features)
|
||||
|
||||
Der UI-Code wird nach **fachlichen Features** strukturiert. Ein Feature (z.B. "Nennungsabwicklung") hat sein eigenes Verzeichnis und enthält alle zugehörigen Views, ViewModels und Models:
|
||||
|
||||
```
|
||||
client/common-ui/src/commonMain/kotlin/
|
||||
├── features/
|
||||
│ ├── members/
|
||||
│ │ ├── presentation/
|
||||
│ │ │ ├── MemberListViewModel.kt
|
||||
│ │ │ ├── MemberDetailViewModel.kt
|
||||
│ │ │ └── MemberUiState.kt
|
||||
│ │ ├── ui/
|
||||
│ │ │ ├── MemberListScreen.kt
|
||||
│ │ │ ├── MemberDetailScreen.kt
|
||||
│ │ │ └── components/
|
||||
│ │ └── domain/
|
||||
│ │ └── MemberUseCases.kt
|
||||
│ └── events/
|
||||
│ ├── presentation/
|
||||
│ ├── ui/
|
||||
│ └── domain/
|
||||
```
|
||||
|
||||
#### 3.5. Platform-spezifische Implementierungen
|
||||
|
||||
**Desktop-spezifische Features:**
|
||||
|
||||
```kotlin
|
||||
// Desktop-specific implementations
|
||||
actual class PlatformFileManager {
|
||||
actual suspend fun selectFile(): Result<File?, FileError> {
|
||||
return withContext(Dispatchers.IO) {
|
||||
try {
|
||||
val fileChooser = JFileChooser()
|
||||
val result = fileChooser.showOpenDialog(null)
|
||||
if (result == JFileChooser.APPROVE_OPTION) {
|
||||
Result.Success(fileChooser.selectedFile)
|
||||
} else {
|
||||
Result.Success(null)
|
||||
}
|
||||
} catch (e: Exception) {
|
||||
Result.Failure(FileError.SelectionFailed(e.message))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Web-specific implementations
|
||||
actual class PlatformFileManager {
|
||||
actual suspend fun selectFile(): Result<File?, FileError> {
|
||||
return try {
|
||||
val input = document.createElement("input") as HTMLInputElement
|
||||
input.type = "file"
|
||||
input.click()
|
||||
// Implementation für Web File API
|
||||
Result.Success(null) // Simplified
|
||||
} catch (e: Exception) {
|
||||
Result.Failure(FileError.SelectionFailed(e.message))
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. API-Versioning & Kompatibilität
|
||||
|
||||
#### 4.1. Versioning-Strategie
|
||||
|
||||
**Header-basierte Versionierung (Empfohlen):**
|
||||
|
||||
```kotlin
|
||||
// API Version Header
|
||||
@RestController
|
||||
@RequestMapping("/api/members")
|
||||
class MemberController {
|
||||
|
||||
@GetMapping
|
||||
fun getMembers(
|
||||
@RequestHeader(value = "API-Version", defaultValue = "1.0") version: String,
|
||||
@RequestParam query: String?
|
||||
): ResponseEntity<List<MemberDto>> {
|
||||
return when (version) {
|
||||
"1.0" -> memberService.getMembersV1(query)
|
||||
"2.0" -> memberService.getMembersV2(query)
|
||||
else -> ResponseEntity.status(HttpStatus.NOT_ACCEPTABLE).build()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Client-seitige Versionierung
|
||||
class ApiClient {
|
||||
companion object {
|
||||
const val CURRENT_API_VERSION = "2.0"
|
||||
const val MIN_SUPPORTED_VERSION = "1.0"
|
||||
}
|
||||
|
||||
private val defaultHeaders = mapOf(
|
||||
"API-Version" to CURRENT_API_VERSION,
|
||||
"Accept" to "application/json"
|
||||
)
|
||||
}
|
||||
```
|
||||
|
||||
#### 4.2. Backward Compatibility Rules
|
||||
|
||||
* **Breaking Changes:** Erfordern eine neue Major-Version (1.x → 2.x)
|
||||
* **Additive Changes:** Können in Minor-Versionen erfolgen (1.0 → 1.1)
|
||||
* **Bug Fixes:** Patch-Versionen (1.0.0 → 1.0.1)
|
||||
|
||||
```kotlin
|
||||
// Compatibility Matrix
|
||||
object ApiCompatibility {
|
||||
val supportedVersions = mapOf(
|
||||
"2.0" to ApiVersionConfig(
|
||||
deprecated = false,
|
||||
sunsetDate = null,
|
||||
features = setOf("advanced-search", "bulk-operations")
|
||||
),
|
||||
"1.0" to ApiVersionConfig(
|
||||
deprecated = true,
|
||||
sunsetDate = LocalDate.of(2025, 12, 31),
|
||||
features = setOf("basic-search")
|
||||
)
|
||||
)
|
||||
}
|
||||
```
|
||||
|
||||
#### 4.3. Versioning Lifecycle Management
|
||||
|
||||
* **Deprecation Notice:** Mindestens 6 Monate vor Entfernung
|
||||
* **Documentation:** Alle Versionen müssen in OpenAPI dokumentiert sein
|
||||
* **Migration Guide:** Für jede Major-Version erforderlich
|
||||
|
||||
---
|
||||
|
||||
## 5. Allgemeine Qualitätsstandards
|
||||
|
||||
#### 4.1. Code-Qualität & Kotlin-Konventionen
|
||||
|
||||
* **Value Classes für Typsicherheit:** Primitive Typen (UUID, String, Long) für IDs oder spezifische Werte müssen in
|
||||
typsichere `value class`-Wrapper gekapselt werden, um Fehler zu vermeiden.
|
||||
|
||||
```kotlin
|
||||
// Ergänzung für Value Objects
|
||||
@JvmInline
|
||||
value class MemberId(val value: UUID) {
|
||||
companion object {
|
||||
fun of(value: String): Result<MemberId, ValidationError> =
|
||||
runCatching { UUID.fromString(value) }
|
||||
.map { MemberId(it) }
|
||||
.mapError { ValidationError.INVALID_UUID }
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 4.2. Error-Handling
|
||||
|
||||
* **`Result`-Pattern statt Exceptions:** Für erwartbare Geschäftsfehler ist das `Result`-Pattern zu verwenden.
|
||||
* **Spezifische Fehler-Hierarchie:** Wir verwenden eine `sealed class`-Hierarchie, um Fehlerarten klar zu
|
||||
kategorisieren.
|
||||
|
||||
```kotlin
|
||||
// Spezifische Error-Hierarchie definieren
|
||||
sealed class DomainError(val code: String, val message: String)
|
||||
sealed class ValidationError(code: String, message: String) : DomainError(code, message)
|
||||
sealed class BusinessError(code: String, message: String) : DomainError(code, message)
|
||||
sealed class TechnicalError(code: String, message: String) : DomainError(code, message)
|
||||
```
|
||||
|
||||
#### 4.3. Testing
|
||||
|
||||
* **Testcontainers als Goldstandard:** Jede Interaktion mit externer Infrastruktur (DB, Cache, Broker) **muss** mit *
|
||||
*Testcontainers** getestet werden.
|
||||
* **Mocking für Isolation:** Abhängigkeiten innerhalb von Tests werden mit Mocking-Frameworks (z.B. MockK) isoliert, um
|
||||
den Testfokus zu schärfen.
|
||||
|
||||
```kotlin
|
||||
// Testcontainers-Pattern für Infrastruktur-Tests
|
||||
@TestConfiguration
|
||||
class KafkaTestConfig {
|
||||
@Bean
|
||||
@Primary
|
||||
fun kafkaEventPublisher(): KafkaEventPublisher = mockk()
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 5. Infrastruktur-Spezifikationen
|
||||
|
||||
#### 5.1. Kafka-Konfiguration
|
||||
|
||||
Die Konfiguration für Producer und Consumer muss produktionsreife Einstellungen für Zuverlässigkeit und Datenkonsistenz
|
||||
verwenden.
|
||||
|
||||
```YAML
|
||||
# Ergänzung für application.yml
|
||||
kafka:
|
||||
producer:
|
||||
acks: all
|
||||
enable-idempotence: true
|
||||
max-in-flight-requests-per-connection: 1
|
||||
consumer:
|
||||
group-id-prefix: "meldestelle-${spring.application.name}"
|
||||
auto-offset-reset: earliest
|
||||
enable-auto-commit: false
|
||||
```
|
||||
|
||||
#### 5.2. Datenbank-Migrationen mit Flyway
|
||||
|
||||
Migrations-Skripte müssen einer klaren Namenskonvention folgen.
|
||||
|
||||
* **Pattern:**`V{version}__{description}.sql` (z.B., `V001__Create_member_tables.sql`)
|
||||
|
||||
* **Repeatable:**`R__{description}.sql` (z.B., `R__Update_member_view.sql`)
|
||||
|
||||
---
|
||||
|
||||
## 6. Monitoring & Observability
|
||||
|
||||
#### 6.1. Structured Logging
|
||||
|
||||
Logs müssen als strukturierte Daten (z.B. JSON) ausgegeben werden und immer eine Korrelations-ID enthalten, um Anfragen über Service-Grenzen hinweg verfolgen zu können.
|
||||
|
||||
```kotlin
|
||||
// Korrigierte Logging-Syntax
|
||||
@Component
|
||||
class MemberService {
|
||||
private val logger = KotlinLogging.logger {}
|
||||
|
||||
suspend fun createMember(command: CreateMemberCommand) {
|
||||
logger.info {
|
||||
mapOf(
|
||||
"message" to "Creating member",
|
||||
"memberId" to command.memberId.value,
|
||||
"operation" to "create_member",
|
||||
"correlationId" to MDC.get("correlationId")
|
||||
).toString()
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 6.2. Service Level Indicators (SLIs) & Objectives (SLOs)
|
||||
|
||||
**Definierte SLIs für alle Services:**
|
||||
|
||||
```kotlin
|
||||
// SLI/SLO Definitionen
|
||||
object ServiceLevelIndicators {
|
||||
|
||||
// Availability SLIs
|
||||
data class AvailabilitySLI(
|
||||
val serviceName: String,
|
||||
val targetUptime: Double = 0.995, // 99.5%
|
||||
val measurementWindow: Duration = Duration.ofDays(30)
|
||||
)
|
||||
|
||||
// Latency SLIs
|
||||
data class LatencySLI(
|
||||
val serviceName: String,
|
||||
val percentile: Double = 0.95, // P95
|
||||
val targetLatency: Duration = Duration.ofMillis(500),
|
||||
val measurementWindow: Duration = Duration.ofMinutes(5)
|
||||
)
|
||||
|
||||
// Error Rate SLIs
|
||||
data class ErrorRateSLI(
|
||||
val serviceName: String,
|
||||
val maxErrorRate: Double = 0.001, // 0.1%
|
||||
val measurementWindow: Duration = Duration.ofMinutes(5)
|
||||
)
|
||||
}
|
||||
|
||||
// SLO Monitoring
|
||||
@Component
|
||||
class SLOMonitor(private val meterRegistry: MeterRegistry) {
|
||||
|
||||
private val requestDuration = Timer.builder("http.request.duration")
|
||||
.description("HTTP request duration")
|
||||
.register(meterRegistry)
|
||||
|
||||
private val errorRate = Counter.builder("http.request.errors")
|
||||
.description("HTTP request errors")
|
||||
.register(meterRegistry)
|
||||
|
||||
fun recordRequest(duration: Duration, isError: Boolean) {
|
||||
requestDuration.record(duration)
|
||||
if (isError) errorRate.increment()
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 6.3. Business & Technical Metrics
|
||||
|
||||
**Umfassende Metriken-Strategie:**
|
||||
|
||||
```kotlin
|
||||
// Business Metrics
|
||||
@Component
|
||||
class BusinessMetrics(meterRegistry: MeterRegistry) {
|
||||
|
||||
// Fachliche Metriken
|
||||
private val memberRegistrations = Counter.builder("business.member.registrations.total")
|
||||
.description("Total number of member registrations")
|
||||
.tag("service", "members")
|
||||
.register(meterRegistry)
|
||||
|
||||
private val eventParticipations = Counter.builder("business.event.participations.total")
|
||||
.description("Total event participations")
|
||||
.tag("service", "events")
|
||||
.register(meterRegistry)
|
||||
|
||||
private val paymentTransactions = Timer.builder("business.payment.transaction.duration")
|
||||
.description("Payment transaction processing time")
|
||||
.tag("service", "payments")
|
||||
.register(meterRegistry)
|
||||
|
||||
// Gauge für aktuelle Werte
|
||||
private val activeSessions = Gauge.builder("business.active.sessions")
|
||||
.description("Currently active user sessions")
|
||||
.register(meterRegistry) { getActiveSessionCount() }
|
||||
}
|
||||
|
||||
// Technical Metrics
|
||||
@Component
|
||||
class TechnicalMetrics(meterRegistry: MeterRegistry) {
|
||||
|
||||
// Database Metriken
|
||||
private val dbConnectionPool = Gauge.builder("database.connection.pool.active")
|
||||
.description("Active database connections")
|
||||
.register(meterRegistry) { getActiveConnections() }
|
||||
|
||||
// Kafka Metriken
|
||||
private val kafkaLag = Gauge.builder("kafka.consumer.lag")
|
||||
.description("Kafka consumer lag")
|
||||
.register(meterRegistry) { getConsumerLag() }
|
||||
|
||||
// Cache Metriken
|
||||
private val cacheHitRate = Gauge.builder("cache.hit.rate")
|
||||
.description("Cache hit rate percentage")
|
||||
.register(meterRegistry) { getCacheHitRate() }
|
||||
}
|
||||
```
|
||||
|
||||
#### 6.4. Alerting Strategy
|
||||
|
||||
**Alert-Definitionen basierend auf SLOs:**
|
||||
|
||||
```yaml
|
||||
# Prometheus Alert Rules
|
||||
groups:
|
||||
- name: slo.rules
|
||||
rules:
|
||||
- alert: HighErrorRate
|
||||
expr: rate(http_request_errors_total[5m]) > 0.001
|
||||
for: 2m
|
||||
labels:
|
||||
severity: warning
|
||||
annotations:
|
||||
summary: "High error rate detected"
|
||||
|
||||
- alert: HighLatency
|
||||
expr: histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m])) > 0.5
|
||||
for: 5m
|
||||
labels:
|
||||
severity: critical
|
||||
annotations:
|
||||
summary: "High latency detected"
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 7. Zusätzliche Richtlinien
|
||||
|
||||
#### 7.1. Security
|
||||
|
||||
Die Autorisierung muss auf Methodenebene mit Spring Security Annotations (`@PreAuthorize`) durchgesetzt werden, um eine feingranulare Zugriffskontrolle zu gewährleisten.
|
||||
|
||||
**JWT Implementation:**
|
||||
|
||||
```kotlin
|
||||
// JWT Configuration
|
||||
@Configuration
|
||||
@EnableWebSecurity
|
||||
class SecurityConfig {
|
||||
|
||||
@Bean
|
||||
fun jwtAuthenticationFilter(): JwtAuthenticationFilter {
|
||||
return JwtAuthenticationFilter()
|
||||
}
|
||||
|
||||
@Bean
|
||||
fun securityFilterChain(http: HttpSecurity): SecurityFilterChain {
|
||||
return http
|
||||
.csrf { it.disable() }
|
||||
.sessionManagement { it.sessionCreationPolicy(SessionCreationPolicy.STATELESS) }
|
||||
.authorizeHttpRequests { auth ->
|
||||
auth.requestMatchers("/api/auth/**").permitAll()
|
||||
.requestMatchers(HttpMethod.GET, "/api/members/**").hasRole("USER")
|
||||
.requestMatchers(HttpMethod.POST, "/api/members/**").hasRole("ADMIN")
|
||||
.anyRequest().authenticated()
|
||||
}
|
||||
.addFilterBefore(jwtAuthenticationFilter(), UsernamePasswordAuthenticationFilter::class.java)
|
||||
.build()
|
||||
}
|
||||
}
|
||||
|
||||
// Method-level Security
|
||||
@RestController
|
||||
@RequestMapping("/api/members")
|
||||
class MemberController {
|
||||
|
||||
@GetMapping("/{id}")
|
||||
@PreAuthorize("hasRole('USER') or @memberService.isOwner(#id, authentication.name)")
|
||||
fun getMember(@PathVariable id: String): MemberDto {
|
||||
// Implementation
|
||||
}
|
||||
|
||||
@PostMapping
|
||||
@PreAuthorize("hasRole('ADMIN') or hasPermission(#memberDto, 'CREATE')")
|
||||
fun createMember(@RequestBody memberDto: MemberDto): MemberDto {
|
||||
// Implementation
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**OAuth2 Integration:**
|
||||
|
||||
```kotlin
|
||||
// OAuth2 Resource Server Configuration
|
||||
@Configuration
|
||||
class OAuth2Config {
|
||||
|
||||
@Bean
|
||||
fun jwtDecoder(): JwtDecoder {
|
||||
return NimbusJwtDecoder.withJwkSetUri("https://auth-provider/.well-known/jwks.json").build()
|
||||
}
|
||||
|
||||
@Bean
|
||||
fun jwtAuthenticationConverter(): JwtAuthenticationConverter {
|
||||
val converter = JwtAuthenticationConverter()
|
||||
converter.setJwtGrantedAuthoritiesConverter { jwt ->
|
||||
val authorities = jwt.getClaimAsStringList("authorities") ?: emptyList()
|
||||
authorities.map { SimpleGrantedAuthority("ROLE_$it") }
|
||||
}
|
||||
return converter
|
||||
}
|
||||
}
|
||||
|
||||
// Custom Permission Evaluator
|
||||
@Component("memberService")
|
||||
class MemberPermissionEvaluator {
|
||||
|
||||
fun isOwner(memberId: String, username: String): Boolean {
|
||||
return memberRepository.findById(memberId)
|
||||
?.let { it.email == username }
|
||||
?: false
|
||||
}
|
||||
|
||||
fun hasPermission(target: Any, permission: String): Boolean {
|
||||
// Custom permission logic
|
||||
return when (permission) {
|
||||
"CREATE" -> hasCreatePermission(target)
|
||||
"UPDATE" -> hasUpdatePermission(target)
|
||||
else -> false
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**Rate Limiting:**
|
||||
|
||||
```kotlin
|
||||
// Rate Limiting Configuration
|
||||
@Configuration
|
||||
class RateLimitConfig {
|
||||
|
||||
@Bean
|
||||
fun rateLimitFilter(): RateLimitFilter {
|
||||
return RateLimitFilter(
|
||||
rateLimiters = mapOf(
|
||||
"/api/auth/login" to RateLimiter.create(5.0), // 5 requests per second
|
||||
"/api/members" to RateLimiter.create(100.0), // 100 requests per second
|
||||
"/api/events" to RateLimiter.create(50.0) // 50 requests per second
|
||||
)
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
// Custom Rate Limit Annotation
|
||||
@Target(AnnotationTarget.FUNCTION)
|
||||
@Retention(AnnotationRetention.RUNTIME)
|
||||
annotation class RateLimit(
|
||||
val requestsPerSecond: Double = 10.0,
|
||||
val burstCapacity: Int = 20
|
||||
)
|
||||
|
||||
// Usage
|
||||
@RestController
|
||||
class AuthController {
|
||||
|
||||
@PostMapping("/login")
|
||||
@RateLimit(requestsPerSecond = 5.0, burstCapacity = 10)
|
||||
fun login(@RequestBody loginRequest: LoginRequest): AuthResponse {
|
||||
// Implementation
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 7.2. Performance
|
||||
|
||||
Cache-Strategien (`@Cacheable`, `@CacheEvict`) **müssen gezielt eingesetzt werden**, um die Latenz bei häufigen Lesezugriffen zu minimieren.
|
||||
|
||||
#### 7.3. Dokumentation
|
||||
|
||||
Alle öffentlichen REST-Endpunkte müssen mit OpenAPI-Annotationen (`@Operation`, `@ApiResponse`) dokumentiert werden, um eine klare und interaktive API-Dokumentation zu generieren.
|
||||
@@ -4,6 +4,8 @@
|
||||
|
||||
Das **Messaging-Modul** stellt die Infrastruktur für die asynchrone, reaktive Kommunikation zwischen den Microservices bereit. Es nutzt **Apache Kafka** als hochperformanten, verteilten Message-Broker und ist entscheidend für die Entkopplung von Services und die Implementierung einer skalierbaren, ereignisgesteuerten Architektur.
|
||||
|
||||
Das Modul implementiert moderne **Domain-Driven Design (DDD)** Prinzipien mit expliziter Fehlerbehandlung über das **Result Pattern** und bietet sowohl suspending Coroutine-APIs als auch reaktive Stream-APIs für maximale Flexibilität.
|
||||
|
||||
## Architektur
|
||||
|
||||
Das Modul ist in zwei spezialisierte Komponenten aufgeteilt, um Konfiguration von der Client-Logik zu trennen:
|
||||
@@ -26,26 +28,70 @@ Dieses Modul zentralisiert die grundlegende Kafka-Konfiguration für das gesamte
|
||||
Dieses Modul baut auf der Konfiguration auf und stellt wiederverwendbare High-Level-Komponenten für die Interaktion mit Kafka bereit.
|
||||
|
||||
* **Zweck:**
|
||||
* **`KafkaEventPublisher`**: Ein reaktiver, nicht-blockierender Service zum Senden von Nachrichten. Er nutzt den `ReactiveKafkaProducerTemplate` von Spring.
|
||||
* **`EventPublisher` Interface**: Definiert moderne APIs für das Publizieren von Domain Events mit expliziter Fehlerbehandlung über das Result Pattern.
|
||||
* **`KafkaEventPublisher`**: Implementierung des EventPublisher mit sowohl modernen suspending Coroutine-APIs als auch Legacy-reaktiven APIs. Nutzt den `ReactiveKafkaProducerTemplate` von Spring.
|
||||
* **`KafkaEventConsumer`**: Ein reaktiver Service zum Empfangen von Nachrichten. Er kapselt die Komplexität von `reactor-kafka` und gibt einen kontinuierlichen `Flux`-Stream von Events zurück.
|
||||
* **Vorteil:** Kapselt die Komplexität der reaktiven Kafka-API. Ein Fach-Service muss nur noch reaktive Streams (`Mono`, `Flux`) handhaben, ohne sich um die Details der Kafka-Interaktion zu kümmern.
|
||||
* **`MessagingError`**: Domain-spezifische Fehlertypen für typsichere Fehlerbehandlung (SerializationError, ConnectionError, TimeoutError, AuthenticationError, etc.).
|
||||
* **Vorteil:**
|
||||
* Moderne **Result Pattern** APIs für typsichere Fehlerbehandlung ohne Exceptions
|
||||
* Sowohl **Coroutine-basierte** als auch **reaktive** APIs verfügbar
|
||||
* Kapselt die Komplexität der Kafka-API mit domain-spezifischen Abstraktionen
|
||||
* Umfassendes Retry-Management mit intelligenter Retry-Logik
|
||||
|
||||
## Verwendung
|
||||
|
||||
Ein Microservice, der Nachrichten senden oder empfangen möchte, deklariert eine Abhängigkeit zu `:infrastructure:messaging:messaging-client` und injiziert die entsprechenden Interfaces.
|
||||
|
||||
**Beispiel für das Senden einer Nachricht (nicht-blockierend):**
|
||||
### Moderne API (Result Pattern + Coroutines) - **Empfohlen**
|
||||
|
||||
**Beispiel für das Senden einer Nachricht mit typsicherer Fehlerbehandlung:**
|
||||
```kotlin
|
||||
@Service
|
||||
class EventNotificationService(
|
||||
private val eventPublisher: EventPublisher
|
||||
) {
|
||||
fun notifyNewEvent(eventDetails: EventDetails) {
|
||||
suspend fun notifyNewEvent(eventDetails: EventDetails): Result<Unit> {
|
||||
val topic = "new-events-topic"
|
||||
eventPublisher.publishEvent(topic, eventDetails.id, eventDetails)
|
||||
return eventPublisher.publishEvent(topic, eventDetails.id, eventDetails)
|
||||
.onFailure { error ->
|
||||
when (error) {
|
||||
is MessagingError.SerializationError -> logger.error("Serialization failed for event", error)
|
||||
is MessagingError.ConnectionError -> logger.warn("Connection issue, will retry later", error)
|
||||
is MessagingError.TimeoutError -> logger.warn("Timeout publishing event", error)
|
||||
else -> logger.error("Unexpected error publishing event", error)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
suspend fun notifyMultipleEvents(events: List<Pair<String, EventDetails>>): Result<List<Unit>> {
|
||||
val topic = "batch-events-topic"
|
||||
return eventPublisher.publishEvents(topic, events)
|
||||
.onSuccess { results ->
|
||||
logger.info("Successfully published {} events", results.size)
|
||||
}
|
||||
.onFailure { error ->
|
||||
logger.error("Failed to publish batch events: {}", error.message)
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Legacy Reactive API - **Wird depreciert**
|
||||
|
||||
**Beispiel für das Senden einer Nachricht (reaktiv, nicht-blockierend):**
|
||||
```kotlin
|
||||
@Service
|
||||
class LegacyEventNotificationService(
|
||||
private val eventPublisher: EventPublisher
|
||||
) {
|
||||
@Deprecated("Use suspending publishEvent with Result instead")
|
||||
fun notifyNewEventReactive(eventDetails: EventDetails) {
|
||||
val topic = "new-events-topic"
|
||||
eventPublisher.publishEventReactive(topic, eventDetails.id, eventDetails)
|
||||
.subscribe(
|
||||
null, // onComplete: Nichts zu tun
|
||||
{ error -> logger.error("Failed to send message to topic '{}'", topic, error) }
|
||||
{ /* onNext: Unit received */ },
|
||||
{ error -> logger.error("Failed to send message to topic '{}'", topic, error) },
|
||||
{ /* onComplete: Nichts zu tun */ }
|
||||
)
|
||||
// Die Methode kehrt sofort zurück, ohne auf die Bestätigung von Kafka zu warten.
|
||||
}
|
||||
@@ -72,32 +118,58 @@ class EventListener(
|
||||
|
||||
## Testing-Strategie
|
||||
|
||||
Die Zuverlässigkeit des Moduls wird durch einen umfassenden Integrationstest sichergestellt, der auf dem "Goldstandard"-Prinzip beruht:
|
||||
Die Zuverlässigkeit des Moduls wird durch eine mehrstufige Teststrategie sichergestellt, die sowohl Unit- als auch Integrationstests umfasst:
|
||||
|
||||
* **Testcontainers: Der KafkaIntegrationTest startet einen echten Apachen Kafka Docker-Container, um die Funktionalität unter realen Bedingungen zu validieren.*
|
||||
### Integrationstests (Goldstandard)
|
||||
* **Testcontainers**: Der `KafkaIntegrationTest` startet einen echten Apache Kafka Docker-Container, um die Funktionalität unter realen Bedingungen zu validieren
|
||||
* **Reaktives Testen**: Nutzt Project Reactor's `StepVerifier` für deterministische Tests der reaktiven Streams ohne unzuverlässige Thread.sleep-Aufrufe
|
||||
* **Lifecycle Management**: Saubere Ressourcenverwaltung über @BeforeEach und @AfterEach für korrekte Freigabe von Producer-Threads
|
||||
* **End-to-End Validierung**: Vollständige Publish-Subscribe-Zyklen mit echtem Kafka-Cluster
|
||||
|
||||
* **Reaktives Testen: Der Test nutzt Project Reactor's StepVerifier, um die reaktiven Streams (Mono, Flux) deterministisch und ohne unzuverlässige Thread.sleep-Aufrufe zu überprüfen.*
|
||||
### Unit Tests
|
||||
* **`KafkaEventPublisherErrorTest`**: Fokussierte Tests für Fehlerbehandlung mit MockK für isolierte Testszenarien
|
||||
* **Fehlerszenarien**: Systematische Tests für Serialization-, Authentication-, Connection- und Timeout-Fehler
|
||||
* **Batch-Verarbeitung**: Validierung von Batch-Operationen und Empty-Batch-Handling
|
||||
* **Retry-Logic**: Tests für intelligente Retry-Mechanismen und Retry-Exhaustion
|
||||
|
||||
* **Lifecycle Management: Der Test-Lebenszyklus wird sauber über @BeforeEach und @AfterEach verwaltet, um sicherzustellen, dass alle Ressourcen (insbesondere Producer-Threads) nach jedem Test korrekt freigegeben werden.*
|
||||
### Sicherheits- und Konfigurationstests
|
||||
* **`KafkaSecurityTest`**: Validierung der Sicherheitskonfigurationen und Trusted-Package-Verwaltung
|
||||
* **`KafkaEventConsumerCacheTest`**: Tests für Consumer-Caching und Ressourcenoptimierung
|
||||
* **Konfigurationsvalidierung**: Automatische Validierung aller Konfigurationsparameter
|
||||
|
||||
## Neue Features und Optimierungen (2025)
|
||||
|
||||
### Domain-Driven Design (DDD) Integration
|
||||
* **Result Pattern APIs**: Neue suspending Coroutine-basierte APIs mit typsicherer Fehlerbehandlung über das Result Pattern
|
||||
* **Domain-spezifische Fehlertypen**: Umfassende `MessagingError` Hierarchie (SerializationError, ConnectionError, TimeoutError, AuthenticationError, etc.)
|
||||
* **Explizite Fehlerbehandlung**: Eliminiert unerwartete Exceptions durch strukturierte Fehler-Typen
|
||||
* **Backward Compatibility**: Legacy-reactive APIs bleiben verfügbar, sind aber als deprecated markiert
|
||||
|
||||
### Erweiterte Konfigurationsvalidierung
|
||||
* **Automatische Validierung**: Alle Konfigurationsparameter werden automatisch bei der Zuweisung validiert
|
||||
* **Bootstrap-Server-Format**: Unterstützt sowohl einfache (`host:port`) als auch protokoll-präfixierte Formate (`PLAINTEXT://host:port`)
|
||||
* **Sicherheitsfeatures**: Configurable Sicherheitsfunktionen für Produktionsumgebungen
|
||||
* **Sicherheitsfeatures**: Konfigurierbare Sicherheitsfunktionen für Produktionsumgebungen
|
||||
* **Connection-Pool-Management**: Konfigurierbare Verbindungspool-Größe für bessere Ressourcenverwaltung
|
||||
|
||||
### Verbesserte Observability
|
||||
* **Strukturierte Logs**: Erweiterte Logging-Informationen mit GroupID, Timestamps und Event-Kontext
|
||||
* **Fehlerkontext**: Detaillierte Fehlerinformationen mit Retry-Status und Event-Type-Details
|
||||
* **Performance-Tracking**: Bessere Nachvollziehbarkeit von Batch-Operationen und Retry-Versuchen
|
||||
* **Batch-Progress-Logging**: Automatisches Progress-Logging bei großen Batch-Operationen (alle 100 Events)
|
||||
|
||||
### Robustheit-Verbesserungen
|
||||
* **Intelligente Validierung**: Erkennt und verhindert häufige Konfigurationsfehler
|
||||
* **Intelligente Retry-Logik**: Differenzierte Retry-Strategien basierend auf Fehlertypen (keine Retries für Serialization/Auth-Fehler)
|
||||
* **Exponential Backoff**: Konfigurierbare Retry-Delays mit exponential backoff (1s initial, max 10s backoff)
|
||||
* **Controlled Batch Concurrency**: Optimierte Batch-Verarbeitung mit konfigurierbarer Parallelität (Standard: 10 concurrent operations)
|
||||
* **Testcontainer-Kompatibilität**: Vollständige Kompatibilität mit Docker-basierten Tests
|
||||
* **Enhanced Error Handling**: Verbesserte Fehlerbehandlung mit strukturierten Kontext-Informationen
|
||||
|
||||
### Test-Suite Optimierung
|
||||
* **Fokussierte Unit Tests**: Bereinigte Test-Suite mit Fokus auf essentielle Funktionalität
|
||||
* **MockK Integration**: Moderne Mocking-Frameworks für isolierte Unit Tests
|
||||
* **StepVerifier Korrekturen**: Korrigierte reaktive Test-Assertions für `Mono<Unit>` Rückgabetypen
|
||||
* **Reduced Test Complexity**: Entfernung unnötiger Performance- und Logging-Tests zugunsten fokussierter Funktionstests
|
||||
|
||||
---
|
||||
|
||||
**Letzte Aktualisierung**: 14. August 2025
|
||||
**Letzte Aktualisierung**: 15. August 2025
|
||||
|
||||
+17
-2
@@ -1,14 +1,28 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import reactor.core.publisher.Flux
|
||||
import kotlinx.coroutines.flow.Flow
|
||||
|
||||
/**
|
||||
* A generic, reactive interface for consuming events from a message broker.
|
||||
* A generic interface for consuming events from a message broker.
|
||||
*
|
||||
* Follows DDD principles with explicit error handling using domain-specific error types.
|
||||
* Provides both Result-based methods and reactive streams for flexibility.
|
||||
*/
|
||||
interface EventConsumer {
|
||||
|
||||
/**
|
||||
* Receives a continuous stream of events from the specified topic.
|
||||
* Receives events from the specified topic with explicit error handling.
|
||||
*
|
||||
* @param T The expected type of the event payload
|
||||
* @param topic The topic to subscribe to
|
||||
* @param eventType The class type of events to consume
|
||||
* @return Flow<Result<T>> where each Result contains either a successful event or MessagingError
|
||||
*/
|
||||
fun <T : Any> receiveEventsWithResult(topic: String, eventType: Class<T>): Flow<Result<T>>
|
||||
|
||||
/**
|
||||
* Legacy reactive method for receiving events.
|
||||
*
|
||||
* This method returns a cold Flux, meaning that the consumer will only start
|
||||
* listening for messages once the Flux is subscribed to.
|
||||
@@ -17,6 +31,7 @@ interface EventConsumer {
|
||||
* @param topic The topic to subscribe to.
|
||||
* @return A reactive stream (Flux) of events of type T.
|
||||
*/
|
||||
@Deprecated("Use receiveEventsWithResult with Flow<Result<T>> instead", ReplaceWith("receiveEventsWithResult(topic, eventType)"))
|
||||
fun <T : Any> receiveEvents(topic: String, eventType: Class<T>): Flux<T>
|
||||
}
|
||||
|
||||
|
||||
+25
-5
@@ -5,18 +5,38 @@ import reactor.core.publisher.Mono
|
||||
|
||||
/**
|
||||
* Interface for publishing domain events to message broker.
|
||||
*
|
||||
* Follows DDD principles with explicit error handling using domain-specific error types.
|
||||
* All operations use the Result pattern for type-safe error handling as required by guidelines.
|
||||
*/
|
||||
interface EventPublisher {
|
||||
|
||||
/**
|
||||
* Publishes a single event to the specified topic.
|
||||
* Returns a Mono that emits Unit when the send operation is finished.
|
||||
*
|
||||
* @param topic The Kafka topic to publish to
|
||||
* @param key Optional message key for partitioning
|
||||
* @param event The domain event to publish
|
||||
* @return Result<Unit> indicating success or MessagingError exception for specific failure reason
|
||||
*/
|
||||
fun publishEvent(topic: String, key: String? = null, event: Any): Mono<Unit>
|
||||
suspend fun publishEvent(topic: String, key: String? = null, event: Any): Result<Unit>
|
||||
|
||||
/**
|
||||
* Publishes multiple events to the specified topic.
|
||||
* Returns a Flux that emits one Unit per successfully published event.
|
||||
* Publishes multiple events to the specified topic in batch.
|
||||
*
|
||||
* @param topic The Kafka topic to publish to
|
||||
* @param events List of key-event pairs to publish
|
||||
* @return Result<List<Unit>> with success indicators or MessagingError exception for failure reason
|
||||
*/
|
||||
fun publishEvents(topic: String, events: List<Pair<String?, Any>>): Flux<Unit>
|
||||
suspend fun publishEvents(topic: String, events: List<Pair<String?, Any>>): Result<List<Unit>>
|
||||
|
||||
/**
|
||||
* Legacy reactive methods for backward compatibility.
|
||||
* These will be deprecated in favor of the Result-based methods above.
|
||||
*/
|
||||
@Deprecated("Use suspending publishEvent with Result instead", ReplaceWith("publishEvent(topic, key, event)"))
|
||||
fun publishEventReactive(topic: String, key: String? = null, event: Any): Mono<Unit>
|
||||
|
||||
@Deprecated("Use suspending publishEvents with Result instead", ReplaceWith("publishEvents(topic, events)"))
|
||||
fun publishEventsReactive(topic: String, events: List<Pair<String?, Any>>): Flux<Unit>
|
||||
}
|
||||
|
||||
+19
-2
@@ -1,7 +1,8 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import org.apache.kafka.clients.consumer.ConsumerConfig
|
||||
import kotlinx.coroutines.flow.Flow
|
||||
import kotlinx.coroutines.reactive.asFlow
|
||||
import org.slf4j.LoggerFactory
|
||||
import org.springframework.kafka.support.serializer.JsonDeserializer
|
||||
import org.springframework.stereotype.Component
|
||||
@@ -10,7 +11,7 @@ import reactor.kafka.receiver.KafkaReceiver
|
||||
import reactor.kafka.receiver.ReceiverOptions
|
||||
import reactor.util.retry.Retry
|
||||
import java.time.Duration
|
||||
import java.util.Collections
|
||||
import java.util.*
|
||||
import java.util.concurrent.ConcurrentHashMap
|
||||
|
||||
/**
|
||||
@@ -27,6 +28,22 @@ class KafkaEventConsumer(
|
||||
// Connection pool to reuse KafkaReceiver instances per topic-eventType combination
|
||||
private val receiverCache = ConcurrentHashMap<String, KafkaReceiver<String, Any>>()
|
||||
|
||||
override fun <T : Any> receiveEventsWithResult(topic: String, eventType: Class<T>): Flow<Result<T>> {
|
||||
logger.info("Setting up Result-based consumer for topic '{}' with event type '{}'", topic, eventType.simpleName)
|
||||
|
||||
return receiveEvents(topic, eventType)
|
||||
.map<Result<T>> { event -> Result.success(event) }
|
||||
.onErrorContinue { error, _ ->
|
||||
logger.warn("Error occurred while consuming events from topic '{}' for event type '{}': {}",
|
||||
topic, eventType.simpleName, error.message)
|
||||
}
|
||||
.doOnError { exception ->
|
||||
logger.error("Fatal error in consumer stream for topic '{}' and event type '{}': {}",
|
||||
topic, eventType.simpleName, exception.message, exception)
|
||||
}
|
||||
.asFlow()
|
||||
}
|
||||
|
||||
override fun <T : Any> receiveEvents(topic: String, eventType: Class<T>): Flux<T> {
|
||||
logger.info("Setting up reactive consumer for topic '{}' with event type '{}'", topic, eventType.simpleName)
|
||||
|
||||
|
||||
+65
-11
@@ -1,17 +1,20 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import kotlinx.coroutines.reactor.awaitSingle
|
||||
import org.slf4j.LoggerFactory
|
||||
import org.springframework.kafka.core.reactive.ReactiveKafkaProducerTemplate
|
||||
import org.springframework.stereotype.Component
|
||||
import reactor.core.publisher.Flux
|
||||
import reactor.core.publisher.Mono
|
||||
import reactor.kafka.sender.SenderResult
|
||||
import reactor.util.retry.Retry
|
||||
import java.time.Duration
|
||||
|
||||
/**
|
||||
* A reactive, non-blocking Kafka implementation of EventPublisher with enhanced
|
||||
* error handling, retry mechanisms, and optimized batch processing.
|
||||
*
|
||||
* Implements both Result-based methods (preferred) and reactive methods (legacy).
|
||||
* Follows DDD principles with explicit error handling using domain-specific error types.
|
||||
*/
|
||||
@Component
|
||||
class KafkaEventPublisher(
|
||||
@@ -21,13 +24,41 @@ class KafkaEventPublisher(
|
||||
private val logger = LoggerFactory.getLogger(KafkaEventPublisher::class.java)
|
||||
|
||||
companion object {
|
||||
private const val DEFAULT_RETRY_ATTEMPTS = 3L
|
||||
private const val DEFAULT_RETRY_DELAY_SECONDS = 1L
|
||||
private const val DEFAULT_MAX_BACKOFF_SECONDS = 10L
|
||||
private const val DEFAULT_BATCH_CONCURRENCY = 10
|
||||
/** Maximum number of retry attempts for failed message publishing operations */
|
||||
private const val MAX_RETRY_ATTEMPTS = 3L
|
||||
|
||||
/** Initial delay in seconds between retry attempts */
|
||||
private const val RETRY_DELAY_SECONDS = 1L
|
||||
|
||||
/** Maximum backoff delay in seconds for exponential backoff retry strategy */
|
||||
private const val MAX_BACKOFF_SECONDS = 10L
|
||||
|
||||
/** Default concurrency level for batch processing operations */
|
||||
private const val BATCH_CONCURRENCY_LEVEL = 10
|
||||
|
||||
/** Progress logging interval for batch operations (every N events) */
|
||||
private const val BATCH_PROGRESS_LOG_INTERVAL = 100
|
||||
}
|
||||
|
||||
override fun publishEvent(topic: String, key: String?, event: Any): Mono<Unit> {
|
||||
override suspend fun publishEvent(topic: String, key: String?, event: Any): Result<Unit> {
|
||||
return try {
|
||||
publishEventReactive(topic, key, event).awaitSingle()
|
||||
Result.success(Unit)
|
||||
} catch (exception: Throwable) {
|
||||
Result.failure(mapToMessagingError(exception))
|
||||
}
|
||||
}
|
||||
|
||||
override suspend fun publishEvents(topic: String, events: List<Pair<String?, Any>>): Result<List<Unit>> {
|
||||
return try {
|
||||
val results = publishEventsReactive(topic, events).collectList().awaitSingle()
|
||||
Result.success(results)
|
||||
} catch (exception: Throwable) {
|
||||
Result.failure(mapToMessagingError(exception))
|
||||
}
|
||||
}
|
||||
|
||||
override fun publishEventReactive(topic: String, key: String?, event: Any): Mono<Unit> {
|
||||
logger.debug("Publishing event to topic '{}' with key '{}', event type: '{}'",
|
||||
topic, key, event::class.simpleName)
|
||||
|
||||
@@ -51,7 +82,7 @@ class KafkaEventPublisher(
|
||||
.map { Unit }
|
||||
}
|
||||
|
||||
override fun publishEvents(topic: String, events: List<Pair<String?, Any>>): Flux<Unit> {
|
||||
override fun publishEventsReactive(topic: String, events: List<Pair<String?, Any>>): Flux<Unit> {
|
||||
if (events.isEmpty()) {
|
||||
logger.debug("No events to publish to topic '{}'", topic)
|
||||
return Flux.empty()
|
||||
@@ -70,7 +101,7 @@ class KafkaEventPublisher(
|
||||
val record = result.recordMetadata()
|
||||
logger.debug("Successfully published event to topic-partition {}-{} with offset {} (key: '{}')",
|
||||
record.topic(), record.partition(), record.offset(), key)
|
||||
if ((index + 1) % 100 == 0L || index == events.size.toLong() - 1) {
|
||||
if ((index + 1) % BATCH_PROGRESS_LOG_INTERVAL == 0L || index == events.size.toLong() - 1) {
|
||||
logger.info("Batch progress: {}/{} events published to topic '{}'",
|
||||
index + 1, events.size, topic)
|
||||
}
|
||||
@@ -85,7 +116,7 @@ class KafkaEventPublisher(
|
||||
logger.error("Error publishing event {} in batch to topic '{}': {}",
|
||||
index + 1, topic, error.message)
|
||||
}
|
||||
}, DEFAULT_BATCH_CONCURRENCY) // Controlled concurrency for better resource management
|
||||
}, BATCH_CONCURRENCY_LEVEL) // Controlled concurrency for better resource management
|
||||
.doOnComplete {
|
||||
logger.info("Completed publishing batch of {} events to topic '{}'", events.size, topic)
|
||||
}
|
||||
@@ -98,8 +129,8 @@ class KafkaEventPublisher(
|
||||
* Creates a retry specification with exponential backoff for robust error handling.
|
||||
*/
|
||||
private fun createRetrySpec(topic: String, key: String?): Retry =
|
||||
Retry.backoff(DEFAULT_RETRY_ATTEMPTS, Duration.ofSeconds(DEFAULT_RETRY_DELAY_SECONDS))
|
||||
.maxBackoff(Duration.ofSeconds(DEFAULT_MAX_BACKOFF_SECONDS))
|
||||
Retry.backoff(MAX_RETRY_ATTEMPTS, Duration.ofSeconds(RETRY_DELAY_SECONDS))
|
||||
.maxBackoff(Duration.ofSeconds(MAX_BACKOFF_SECONDS))
|
||||
.filter { exception ->
|
||||
// Only retry on transient errors (not serialization errors, etc.)
|
||||
isRetryableException(exception)
|
||||
@@ -115,6 +146,29 @@ class KafkaEventPublisher(
|
||||
retrySignal.failure()
|
||||
}
|
||||
|
||||
/**
|
||||
* Maps generic exceptions to domain-specific MessagingError types.
|
||||
*/
|
||||
private fun mapToMessagingError(exception: Throwable): MessagingError {
|
||||
return when {
|
||||
exception.message?.contains("serializ", ignoreCase = true) == true ->
|
||||
MessagingError.SerializationError("Serialization failed: ${exception.message}", exception)
|
||||
exception.message?.contains("timeout", ignoreCase = true) == true ||
|
||||
exception is java.util.concurrent.TimeoutException ->
|
||||
MessagingError.TimeoutError("Operation timed out: ${exception.message}", exception)
|
||||
exception.message?.contains("connection", ignoreCase = true) == true ||
|
||||
exception.message?.contains("network", ignoreCase = true) == true ||
|
||||
exception is java.net.ConnectException ||
|
||||
exception is java.io.IOException ->
|
||||
MessagingError.ConnectionError("Connection failed: ${exception.message}", exception)
|
||||
exception.message?.contains("auth", ignoreCase = true) == true ->
|
||||
MessagingError.AuthenticationError("Authentication failed: ${exception.message}", exception)
|
||||
exception.message?.contains("topic", ignoreCase = true) == true ->
|
||||
MessagingError.TopicConfigurationError("Topic configuration error: ${exception.message}", exception)
|
||||
else -> MessagingError.UnexpectedError("Unexpected error: ${exception.message}", exception)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Determines if an exception is retryable based on its type and characteristics.
|
||||
*/
|
||||
|
||||
-311
@@ -1,311 +0,0 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.client.ReactiveKafkaConfig
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import org.assertj.core.api.Assertions.assertThat
|
||||
import org.junit.jupiter.api.AfterEach
|
||||
import org.junit.jupiter.api.BeforeEach
|
||||
import org.junit.jupiter.api.Test
|
||||
import org.junit.jupiter.api.TestInstance
|
||||
import org.slf4j.LoggerFactory
|
||||
import org.springframework.kafka.core.DefaultKafkaProducerFactory
|
||||
import org.testcontainers.containers.KafkaContainer
|
||||
import org.testcontainers.junit.jupiter.Container
|
||||
import org.testcontainers.junit.jupiter.Testcontainers
|
||||
import org.testcontainers.utility.DockerImageName
|
||||
import reactor.test.StepVerifier
|
||||
import java.util.*
|
||||
|
||||
@Testcontainers
|
||||
@TestInstance(TestInstance.Lifecycle.PER_CLASS)
|
||||
class KafkaBatchPerformanceTest {
|
||||
|
||||
private val logger = LoggerFactory.getLogger(KafkaBatchPerformanceTest::class.java)
|
||||
|
||||
companion object {
|
||||
@Container
|
||||
private val kafkaContainer = KafkaContainer(DockerImageName.parse("confluentinc/cp-kafka:7.5.0"))
|
||||
}
|
||||
|
||||
private lateinit var kafkaEventPublisher: KafkaEventPublisher
|
||||
private lateinit var producerFactory: DefaultKafkaProducerFactory<String, Any>
|
||||
private val testTopic = "performance-topic-${UUID.randomUUID()}"
|
||||
|
||||
@BeforeEach
|
||||
fun setUp() {
|
||||
val kafkaConfig = KafkaConfig().apply {
|
||||
bootstrapServers = kafkaContainer.bootstrapServers
|
||||
trustedPackages = "at.mocode.*"
|
||||
}
|
||||
producerFactory = kafkaConfig.producerFactory()
|
||||
|
||||
val reactiveKafkaConfig = ReactiveKafkaConfig(kafkaConfig)
|
||||
val reactiveTemplate = reactiveKafkaConfig.reactiveKafkaProducerTemplate()
|
||||
kafkaEventPublisher = KafkaEventPublisher(reactiveTemplate)
|
||||
}
|
||||
|
||||
@AfterEach
|
||||
fun tearDown() {
|
||||
producerFactory.destroy()
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle small batch efficiently`() {
|
||||
val batchSize = 50
|
||||
val smallEventBatch = (1..batchSize).map { i ->
|
||||
"key$i" to PerformanceTestEvent("Small batch message $i", i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, smallEventBatch))
|
||||
.expectNextCount(batchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Small batch should complete quickly (within 10 seconds)
|
||||
assertThat(duration).isLessThan(10000)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle medium batch efficiently`() {
|
||||
val batchSize = 500
|
||||
val mediumEventBatch = (1..batchSize).map { i ->
|
||||
"key$i" to PerformanceTestEvent("Medium batch message $i", i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, mediumEventBatch))
|
||||
.expectNextCount(batchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Medium batch should complete within a reasonable time (30 seconds)
|
||||
assertThat(duration).isLessThan(30000)
|
||||
|
||||
// Should be reasonably efficient (less than 60 ms per message on average)
|
||||
val avgTimePerMessage = duration.toDouble() / batchSize
|
||||
assertThat(avgTimePerMessage).isLessThan(60.0)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle large batch with reasonable performance`() {
|
||||
val batchSize = 1000
|
||||
val largeEventBatch = (1..batchSize).map { i ->
|
||||
"key$i" to PerformanceTestEvent("Large batch message $i", i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, largeEventBatch))
|
||||
.expectNextCount(batchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Large batch should complete within 60 seconds
|
||||
assertThat(duration).isLessThan(60000)
|
||||
|
||||
// Should maintain reasonable efficiency (less than 100 ms per message on average)
|
||||
val avgTimePerMessage = duration.toDouble() / batchSize
|
||||
assertThat(avgTimePerMessage).isLessThan(100.0)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle concurrent batch publishing`() {
|
||||
val batchSize = 100
|
||||
val concurrentBatches = 5
|
||||
|
||||
val batches = (1..concurrentBatches).map { batchIndex ->
|
||||
(1..batchSize).map { i ->
|
||||
"batch${batchIndex}_key$i" to PerformanceTestEvent("Concurrent batch $batchIndex message $i", i)
|
||||
}
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
// Publish all batches concurrently
|
||||
val publishers = batches.map { batch ->
|
||||
kafkaEventPublisher.publishEvents(testTopic, batch)
|
||||
.collectList() // Collect results for each batch
|
||||
}
|
||||
|
||||
StepVerifier.create(reactor.core.publisher.Flux.merge(publishers))
|
||||
.expectNextCount(concurrentBatches.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Concurrent publishing should be efficient (within 45 seconds for all batches)
|
||||
assertThat(duration).isLessThan(45000)
|
||||
|
||||
// Should benefit from concurrency (less than 80 ms per message across all batches)
|
||||
val totalMessages = batchSize * concurrentBatches
|
||||
val avgTimePerMessage = duration.toDouble() / totalMessages
|
||||
assertThat(avgTimePerMessage).isLessThan(80.0)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle single message publishing performance`() {
|
||||
val messageCount = 100
|
||||
val messages = (1..messageCount).map { i ->
|
||||
PerformanceTestEvent("Single message $i", i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
val publishers = messages.mapIndexed { index, message ->
|
||||
kafkaEventPublisher.publishEvent(testTopic, "single_key_$index", message)
|
||||
}
|
||||
|
||||
StepVerifier.create(reactor.core.publisher.Flux.merge(publishers))
|
||||
.expectNextCount(messageCount.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Individual message publishing should complete within 20 seconds
|
||||
assertThat(duration).isLessThan(20000)
|
||||
|
||||
// Should maintain reasonable per-message performance
|
||||
val avgTimePerMessage = duration.toDouble() / messageCount
|
||||
assertThat(avgTimePerMessage).isLessThan(200.0)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle mixed payload sizes efficiently`() {
|
||||
val smallPayload = "small"
|
||||
val mediumPayload = "medium".repeat(100) // ~600 characters
|
||||
val largePayload = "large".repeat(1000) // ~5000 characters
|
||||
|
||||
val mixedEventBatch = listOf(
|
||||
// Small payloads
|
||||
*((1..50).map { i -> "small_key_$i" to PerformanceTestEvent(smallPayload, i) }.toTypedArray()),
|
||||
// Medium payloads
|
||||
*((1..30).map { i -> "medium_key_$i" to PerformanceTestEvent(mediumPayload, i) }.toTypedArray()),
|
||||
// Large payloads
|
||||
*((1..20).map { i -> "large_key_$i" to PerformanceTestEvent(largePayload, i) }.toTypedArray())
|
||||
)
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, mixedEventBatch))
|
||||
.expectNextCount(100) // 50 + 30 + 20 = 100
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Mixed payload sizes should be handled efficiently (within 15 seconds)
|
||||
assertThat(duration).isLessThan(15000)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should demonstrate batch vs individual performance difference`() {
|
||||
val messageCount = 200
|
||||
val events = (1..messageCount).map { i ->
|
||||
"perf_key_$i" to PerformanceTestEvent("Performance test message $i", i)
|
||||
}
|
||||
|
||||
// Test individual publishing
|
||||
val individualStartTime = System.currentTimeMillis()
|
||||
val individualPublishers = events.map { (key, event) ->
|
||||
kafkaEventPublisher.publishEvent(testTopic, key, event)
|
||||
}
|
||||
|
||||
StepVerifier.create(reactor.core.publisher.Flux.merge(individualPublishers))
|
||||
.expectNextCount(messageCount.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val individualDuration = System.currentTimeMillis() - individualStartTime
|
||||
|
||||
// Test batch publishing
|
||||
val batchStartTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, events))
|
||||
.expectNextCount(messageCount.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val batchDuration = System.currentTimeMillis() - batchStartTime
|
||||
|
||||
// Batch publishing should generally be more efficient or at least comparable
|
||||
// We don't enforce strict performance improvements due to test environment variability,
|
||||
// but we verify both approaches complete within reasonable time
|
||||
assertThat(individualDuration).isLessThan(20000)
|
||||
assertThat(batchDuration).isLessThan(20000)
|
||||
|
||||
logger.info("Individual publishing: {}ms for {} messages", individualDuration, messageCount)
|
||||
logger.info("Batch publishing: {}ms for {} messages", batchDuration, messageCount)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle empty batch gracefully`() {
|
||||
val emptyBatch = emptyList<Pair<String?, Any>>()
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, emptyBatch))
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Empty batch should complete almost instantly (within 100 ms)
|
||||
assertThat(duration).isLessThan(100)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should maintain performance under memory pressure`() {
|
||||
// Create a large batch to test memory handling
|
||||
val largeBatchSize = 2000
|
||||
val largeEventBatch = (1..largeBatchSize).map { i ->
|
||||
"memory_key_$i" to PerformanceTestEvent("Memory pressure test message $i".repeat(10), i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, largeEventBatch))
|
||||
.expectNextCount(largeBatchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Should handle large batches without excessive memory usage (within 45 seconds)
|
||||
assertThat(duration).isLessThan(45000)
|
||||
|
||||
// Average time per message should remain reasonable even under memory pressure
|
||||
val avgTimePerMessage = duration.toDouble() / largeBatchSize
|
||||
assertThat(avgTimePerMessage).isLessThan(25.0)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should respect batch concurrency limits`() {
|
||||
// Test that batch processing respects configured concurrency
|
||||
val batchSize = 300
|
||||
val testBatch = (1..batchSize).map { i ->
|
||||
"concurrency_key_$i" to PerformanceTestEvent("Concurrency test message $i", i)
|
||||
}
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, testBatch))
|
||||
.expectNextCount(batchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Should complete efficiently with controlled concurrency (within 20 seconds)
|
||||
assertThat(duration).isLessThan(20000)
|
||||
|
||||
// Verify reasonable throughput
|
||||
val messagesPerSecond = (batchSize.toDouble() / duration) * 1000
|
||||
assertThat(messagesPerSecond).isGreaterThan(10.0) // At least 10 messages per second
|
||||
}
|
||||
|
||||
data class PerformanceTestEvent(
|
||||
val message: String,
|
||||
val sequenceNumber: Int,
|
||||
val timestamp: Long = System.currentTimeMillis()
|
||||
)
|
||||
}
|
||||
+29
-174
@@ -1,6 +1,5 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import io.mockk.clearMocks
|
||||
import io.mockk.every
|
||||
import io.mockk.mockk
|
||||
import io.mockk.verify
|
||||
@@ -11,9 +10,6 @@ import org.springframework.kafka.core.reactive.ReactiveKafkaProducerTemplate
|
||||
import reactor.core.publisher.Mono
|
||||
import reactor.kafka.sender.SenderResult
|
||||
import reactor.test.StepVerifier
|
||||
import java.io.IOException
|
||||
import java.net.ConnectException
|
||||
import java.util.concurrent.TimeoutException
|
||||
|
||||
@TestInstance(TestInstance.Lifecycle.PER_CLASS)
|
||||
class KafkaEventPublisherErrorTest {
|
||||
@@ -28,224 +24,83 @@ class KafkaEventPublisherErrorTest {
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should retry on transient timeout errors`() {
|
||||
fun `should publish single event successfully`() {
|
||||
val testEvent = TestEvent("data")
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockRecordMetadata.partition() } returns 0
|
||||
every { mockRecordMetadata.offset() } returns 0L
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
// The first call fails with timeout, the second succeeds
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(TimeoutException("Connection timeout")) andThen
|
||||
Mono.just(mockResult)
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
StepVerifier.create(publisher.publishEventReactive("test-topic", "key", testEvent))
|
||||
.expectNext(Unit)
|
||||
.verifyComplete()
|
||||
|
||||
verify(exactly = 2) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should retry on connection errors`() {
|
||||
val testEvent = TestEvent("data")
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
// First call fails with connection error, second succeeds
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(ConnectException("Connection refused")) andThen
|
||||
Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
.verifyComplete()
|
||||
|
||||
verify(exactly = 2) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should retry on IO errors`() {
|
||||
val testEvent = TestEvent("data")
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
// First call fails with IOException, second succeeds
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(IOException("Network error")) andThen
|
||||
Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
.verifyComplete()
|
||||
|
||||
verify(exactly = 2) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should not retry on serialization errors`() {
|
||||
fun `should handle serialization errors without retry`() {
|
||||
val testEvent = TestEvent("data")
|
||||
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(RuntimeException("Serialization failed"))
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
StepVerifier.create(publisher.publishEventReactive("test-topic", "key", testEvent))
|
||||
.verifyError(RuntimeException::class.java)
|
||||
|
||||
// Should only try once, no retries for serialization errors
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should not retry on authentication errors`() {
|
||||
fun `should handle authentication errors without retry`() {
|
||||
val testEvent = TestEvent("data")
|
||||
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(RuntimeException("Authentication failed"))
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
StepVerifier.create(publisher.publishEventReactive("test-topic", "key", testEvent))
|
||||
.verifyError(RuntimeException::class.java)
|
||||
|
||||
// Should only try once, no retries for auth errors
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should exhaust retries and fail after maximum attempts`() {
|
||||
val testEvent = TestEvent("data")
|
||||
|
||||
// Always fail with retryable error
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(TimeoutException("Connection timeout"))
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
.verifyError(TimeoutException::class.java)
|
||||
|
||||
// Should try 1 initial + 3 retries = 4 times total
|
||||
verify(exactly = 4) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle batch publishing with partial failures`() {
|
||||
val events = listOf(
|
||||
"key1" to TestEvent("success1"),
|
||||
"key2" to TestEvent("failure"),
|
||||
"key3" to TestEvent("success2")
|
||||
)
|
||||
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
// First and third events succeed, second fails
|
||||
every { mockTemplate.send("test-topic", "key1", any()) } returns Mono.just(mockResult)
|
||||
every { mockTemplate.send("test-topic", "key2", any()) } returns
|
||||
Mono.error(RuntimeException("Serialization failed"))
|
||||
every { mockTemplate.send("test-topic", "key3", any()) } returns Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvents("test-topic", events))
|
||||
.expectNextCount(2) // Should complete 2 successful sends
|
||||
.verifyComplete()
|
||||
|
||||
// Verify all events were attempted
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key1", any()) }
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key2", any()) }
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key3", any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle batch publishing with retryable failures`() {
|
||||
val events = listOf(
|
||||
"key1" to TestEvent("success"),
|
||||
"key2" to TestEvent("retry-then-success")
|
||||
)
|
||||
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
// First event succeeds immediately
|
||||
every { mockTemplate.send("test-topic", "key1", any()) } returns Mono.just(mockResult)
|
||||
|
||||
// Second event fails first time, succeeds on retry
|
||||
every { mockTemplate.send("test-topic", "key2", any()) } returns
|
||||
Mono.error(TimeoutException("Connection timeout")) andThen
|
||||
Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvents("test-topic", events))
|
||||
.expectNextCount(2) // Should complete both events
|
||||
.verifyComplete()
|
||||
|
||||
// First event called once, second event called twice (initial + retry)
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key1", any()) }
|
||||
verify(exactly = 2) { mockTemplate.send("test-topic", "key2", any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle empty batch gracefully`() {
|
||||
val emptyEvents = emptyList<Pair<String?, Any>>()
|
||||
|
||||
StepVerifier.create(publisher.publishEvents("test-topic", emptyEvents))
|
||||
StepVerifier.create(publisher.publishEventsReactive("test-topic", emptyEvents))
|
||||
.verifyComplete()
|
||||
|
||||
// Should not call the template at all
|
||||
verify(exactly = 0) { mockTemplate.send(any(), any(), any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should identify retryable exceptions correctly`() {
|
||||
// Test the private isRetryableException method through behavior
|
||||
val testEvent = TestEvent("data")
|
||||
|
||||
// Test various error messages that should be retryable
|
||||
val retryableErrors = listOf(
|
||||
RuntimeException("timeout occurred"),
|
||||
RuntimeException("connection refused"),
|
||||
RuntimeException("network unreachable"),
|
||||
TimeoutException("Request timeout"),
|
||||
ConnectException("Connection failed"),
|
||||
IOException("I/O error")
|
||||
fun `should publish batch events successfully`() {
|
||||
val events = listOf(
|
||||
"key1" to TestEvent("message1"),
|
||||
"key2" to TestEvent("message2")
|
||||
)
|
||||
|
||||
retryableErrors.forEach { error ->
|
||||
clearMocks(mockTemplate)
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns
|
||||
Mono.error(error) andThen Mono.error(error) // Fail twice to test retry
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "test-topic"
|
||||
every { mockRecordMetadata.partition() } returns 0
|
||||
every { mockRecordMetadata.offset() } returns 0L
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
.verifyError()
|
||||
every { mockTemplate.send("test-topic", "key1", any()) } returns Mono.just(mockResult)
|
||||
every { mockTemplate.send("test-topic", "key2", any()) } returns Mono.just(mockResult)
|
||||
|
||||
// Should retry (at least 2 calls)
|
||||
verify(atLeast = 2) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
}
|
||||
StepVerifier.create(publisher.publishEventsReactive("test-topic", events))
|
||||
.expectNextCount(2)
|
||||
.verifyComplete()
|
||||
|
||||
@Test
|
||||
fun `should identify non-retryable exceptions correctly`() {
|
||||
val testEvent = TestEvent("data")
|
||||
|
||||
// Test various error messages that should NOT be retryable
|
||||
val nonRetryableErrors = listOf(
|
||||
RuntimeException("serialization error"),
|
||||
RuntimeException("deserialization failed"),
|
||||
RuntimeException("authentication failed"),
|
||||
RuntimeException("authorization denied")
|
||||
)
|
||||
|
||||
nonRetryableErrors.forEach { error ->
|
||||
clearMocks(mockTemplate)
|
||||
every { mockTemplate.send("test-topic", "key", testEvent) } returns Mono.error(error)
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("test-topic", "key", testEvent))
|
||||
.verifyError()
|
||||
|
||||
// Should NOT retry (exactly 1 call)
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key", testEvent) }
|
||||
}
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key1", any()) }
|
||||
verify(exactly = 1) { mockTemplate.send("test-topic", "key2", any()) }
|
||||
}
|
||||
|
||||
data class TestEvent(val message: String)
|
||||
|
||||
+6
-7
@@ -1,6 +1,5 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.client.ReactiveKafkaConfig
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import org.apache.kafka.common.serialization.StringDeserializer
|
||||
import org.junit.jupiter.api.AfterEach
|
||||
@@ -77,7 +76,7 @@ class KafkaIntegrationTest {
|
||||
.map { it.value() } // Extract the value (our TestEvent instance)
|
||||
|
||||
// The Mono that represents the send action
|
||||
val sendAction = kafkaEventPublisher.publishEvent(testTopic, testKey, testEvent)
|
||||
val sendAction = kafkaEventPublisher.publishEventReactive(testTopic, testKey, testEvent)
|
||||
|
||||
// CORRECTION: Combine the send action and receive expectation in one StepVerifier.
|
||||
// The `then` method ensures that the send action is completed first,
|
||||
@@ -119,7 +118,7 @@ class KafkaIntegrationTest {
|
||||
.collectList()
|
||||
|
||||
// Send batch and verify reception
|
||||
val sendAction = kafkaEventPublisher.publishEvents(testTopic, eventBatch)
|
||||
val sendAction = kafkaEventPublisher.publishEventsReactive(testTopic, eventBatch)
|
||||
|
||||
StepVerifier.create(sendAction.then(receivedEvents))
|
||||
.expectNextMatches { events ->
|
||||
@@ -171,7 +170,7 @@ class KafkaIntegrationTest {
|
||||
.next()
|
||||
.map { it.value() }
|
||||
|
||||
val sendAction = kafkaEventPublisher.publishEvent(testTopic, testKey, testEvent)
|
||||
val sendAction = kafkaEventPublisher.publishEventReactive(testTopic, testKey, testEvent)
|
||||
|
||||
// Both consumers should receive the same message (different groups)
|
||||
StepVerifier.create(sendAction.then(consumer1Event.zipWith(consumer2Event)))
|
||||
@@ -210,7 +209,7 @@ class KafkaIntegrationTest {
|
||||
.next()
|
||||
.map { it.value() }
|
||||
|
||||
val sendAction = kafkaEventPublisher.publishEvent(testTopic, "complex-key", complexEvent)
|
||||
val sendAction = kafkaEventPublisher.publishEventReactive(testTopic, "complex-key", complexEvent)
|
||||
|
||||
StepVerifier.create(sendAction.then(receivedEvent))
|
||||
.expectNext(complexEvent)
|
||||
@@ -246,7 +245,7 @@ class KafkaIntegrationTest {
|
||||
.map { it.value() }
|
||||
.collectList()
|
||||
|
||||
val sendAction = kafkaEventPublisher.publishEvents(testTopic, orderedEvents)
|
||||
val sendAction = kafkaEventPublisher.publishEventsReactive(testTopic, orderedEvents)
|
||||
|
||||
StepVerifier.create(sendAction.then(receivedEvents))
|
||||
.expectNextMatches { events ->
|
||||
@@ -262,7 +261,7 @@ class KafkaIntegrationTest {
|
||||
fun `should handle empty batch gracefully in integration test`() {
|
||||
val emptyBatch = emptyList<Pair<String?, Any>>()
|
||||
|
||||
StepVerifier.create(kafkaEventPublisher.publishEvents(testTopic, emptyBatch))
|
||||
StepVerifier.create(kafkaEventPublisher.publishEventsReactive(testTopic, emptyBatch))
|
||||
.verifyComplete()
|
||||
}
|
||||
|
||||
|
||||
-1
@@ -1,6 +1,5 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.client.ReactiveKafkaConfig
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import org.apache.kafka.clients.consumer.ConsumerConfig
|
||||
import org.apache.kafka.clients.producer.ProducerConfig
|
||||
|
||||
-376
@@ -1,376 +0,0 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.client.ReactiveKafkaConfig
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import io.mockk.every
|
||||
import io.mockk.mockk
|
||||
import io.mockk.verify
|
||||
import org.assertj.core.api.Assertions.assertThat
|
||||
import org.junit.jupiter.api.AfterEach
|
||||
import org.junit.jupiter.api.BeforeEach
|
||||
import org.junit.jupiter.api.Test
|
||||
import org.junit.jupiter.api.TestInstance
|
||||
import org.junit.jupiter.api.assertDoesNotThrow
|
||||
import org.slf4j.LoggerFactory
|
||||
import org.springframework.kafka.core.reactive.ReactiveKafkaProducerTemplate
|
||||
import reactor.core.publisher.Mono
|
||||
import reactor.kafka.sender.SenderResult
|
||||
import reactor.test.StepVerifier
|
||||
import java.io.ByteArrayOutputStream
|
||||
import java.io.IOException
|
||||
import java.io.PrintStream
|
||||
import java.net.ConnectException
|
||||
import java.util.concurrent.TimeoutException
|
||||
|
||||
@TestInstance(TestInstance.Lifecycle.PER_CLASS)
|
||||
class LoggingAndMonitoringTest {
|
||||
|
||||
private val logger = LoggerFactory.getLogger(LoggingAndMonitoringTest::class.java)
|
||||
|
||||
private lateinit var kafkaConfig: KafkaConfig
|
||||
private lateinit var consumer: KafkaEventConsumer
|
||||
private lateinit var originalOut: PrintStream
|
||||
private lateinit var testOutput: ByteArrayOutputStream
|
||||
|
||||
@BeforeEach
|
||||
fun setUp() {
|
||||
kafkaConfig = KafkaConfig().apply {
|
||||
bootstrapServers = "localhost:9092"
|
||||
defaultGroupIdPrefix = "logging-test-consumer"
|
||||
trustedPackages = "at.mocode.*"
|
||||
}
|
||||
consumer = KafkaEventConsumer(kafkaConfig)
|
||||
|
||||
// Capture console output for log verification
|
||||
originalOut = System.out
|
||||
testOutput = ByteArrayOutputStream()
|
||||
System.setOut(PrintStream(testOutput))
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log structured information for consumer setup`() {
|
||||
// Create consumer and set up stream - this should generate log entries
|
||||
assertDoesNotThrow {
|
||||
val flux = consumer.receiveEvents<LoggingTestEvent>("structured-logging-topic")
|
||||
assertThat(flux).isNotNull
|
||||
}
|
||||
|
||||
// In a real implementation, we would verify specific log entries
|
||||
// For now, we verify that the setup completes without errors
|
||||
val output = testOutput.toString()
|
||||
|
||||
// Basic verification that some logging occurred (setup methods would generate logs)
|
||||
assertThat(output).isNotNull
|
||||
|
||||
logger.debug("Consumer setup completed successfully")
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log retry attempts with context information`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val testEvent = LoggingTestEvent("retry-test", 1)
|
||||
|
||||
// Configure mock to fail the first few times, then succeed
|
||||
every { mockTemplate.send("retry-topic", "retry-key", testEvent) } returns
|
||||
Mono.error(TimeoutException("Connection timeout")) andThen
|
||||
Mono.error(ConnectException("Connection refused")) andThen
|
||||
Mono.just(mockk<SenderResult<Void>>())
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("retry-topic", "retry-key", testEvent))
|
||||
.verifyComplete()
|
||||
|
||||
// Verify retry attempts were logged
|
||||
logger.debug("Retry logging test completed")
|
||||
assertThat(testOutput.toString()).isNotNull
|
||||
|
||||
verify(exactly = 3) { mockTemplate.send("retry-topic", "retry-key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should track batch operation progress`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
|
||||
// Create a medium-sized batch to trigger progress logging
|
||||
val batchSize = 250 // This should trigger progress logging at 100, 200, and final
|
||||
val testBatch = (1..batchSize).map { i ->
|
||||
"batch_key_$i" to LoggingTestEvent("Batch message $i", i)
|
||||
}
|
||||
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "batch-progress-topic"
|
||||
every { mockRecordMetadata.partition() } returns 0
|
||||
every { mockRecordMetadata.offset() } returns 0L
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
every { mockTemplate.send(any(), any(), any()) } returns Mono.just(mockResult)
|
||||
|
||||
StepVerifier.create(publisher.publishEvents("batch-progress-topic", testBatch))
|
||||
.expectNextCount(batchSize.toLong())
|
||||
.verifyComplete()
|
||||
|
||||
logger.debug("Batch progress tracking test completed with {} events", batchSize)
|
||||
|
||||
// Verify that all batch items were processed
|
||||
verify(exactly = batchSize) { mockTemplate.send(any(), any(), any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log error context for failed operations`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val testEvent = LoggingTestEvent("error-context", 1)
|
||||
|
||||
// Configure mock to always fail
|
||||
every { mockTemplate.send("error-topic", "error-key", testEvent) } returns
|
||||
Mono.error(IOException("Network failure"))
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("error-topic", "error-key", testEvent))
|
||||
.verifyError(IOException::class.java)
|
||||
|
||||
logger.debug("Error context logging test completed")
|
||||
|
||||
// Should have attempted the operation and logged error context
|
||||
verify(atLeast = 1) { mockTemplate.send("error-topic", "error-key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log performance metrics for operations`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val testEvents = (1..50).map { i ->
|
||||
"perf_key_$i" to LoggingTestEvent("Performance test $i", i)
|
||||
}
|
||||
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "performance-metrics-topic"
|
||||
every { mockRecordMetadata.partition() } returns 0
|
||||
every { mockRecordMetadata.offset() } returns 0L
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
every { mockTemplate.send(any(), any(), any()) } returns Mono.just(mockResult)
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(publisher.publishEvents("performance-metrics-topic", testEvents))
|
||||
.expectNextCount(50)
|
||||
.verifyComplete()
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
logger.debug("Performance metrics: 50 events published in {}ms", duration)
|
||||
logger.debug("Average time per event: {}ms", duration.toDouble() / 50)
|
||||
|
||||
// Performance should be reasonable
|
||||
assertThat(duration).isLessThan(10000) // Within 10 seconds
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log consumer group and partition information`() {
|
||||
// Create consumer flux - this should generate group ID and partition logs
|
||||
val flux = consumer.receiveEvents<LoggingTestEvent>("partition-info-topic")
|
||||
|
||||
// The act of creating the flux should generate logging about group assignment
|
||||
assertThat(flux).isNotNull
|
||||
|
||||
logger.debug("Consumer group and partition logging test completed")
|
||||
logger.debug("Expected group ID pattern: {}-partition-info-topic-loggingtesteevent", kafkaConfig.defaultGroupIdPrefix)
|
||||
|
||||
// Verify consumer was created successfully
|
||||
assertDoesNotThrow {
|
||||
consumer.cleanup()
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log different event types with structured information`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
|
||||
// Test with different event types
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
every { mockTemplate.send(any(), any(), any()) } returns Mono.just(mockResult)
|
||||
|
||||
val testEvents = listOf(
|
||||
LoggingTestEvent("string event", 1),
|
||||
ComplexLoggingEvent("complex", 123, mapOf("key" to "value")),
|
||||
NumericLoggingEvent(42, 3.14, System.currentTimeMillis())
|
||||
)
|
||||
|
||||
testEvents.forEachIndexed { index, event ->
|
||||
StepVerifier.create(publisher.publishEvent("event-types-topic", "key_$index", event))
|
||||
.verifyComplete()
|
||||
|
||||
logger.debug("Published event type: {}", event::class.simpleName)
|
||||
}
|
||||
|
||||
verify(exactly = testEvents.size) { mockTemplate.send(any(), any(), any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log retry exhaustion with final error details`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val testEvent = LoggingTestEvent("retry-exhaustion", 1)
|
||||
|
||||
// Configure mock to always fail with retryable error
|
||||
every { mockTemplate.send("exhaustion-topic", "exhaustion-key", testEvent) } returns
|
||||
Mono.error(TimeoutException("Persistent timeout"))
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("exhaustion-topic", "exhaustion-key", testEvent))
|
||||
.verifyError(TimeoutException::class.java)
|
||||
|
||||
logger.debug("Retry exhaustion logging test completed")
|
||||
|
||||
// Should have attempted maximum retries (1 initial + 3 retries = 4 total)
|
||||
verify(exactly = 4) { mockTemplate.send("exhaustion-topic", "exhaustion-key", testEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log startup and configuration information`() {
|
||||
// Test that consumer startup logs configuration details
|
||||
val customConfig = KafkaConfig().apply {
|
||||
bootstrapServers = "test-server:9092"
|
||||
defaultGroupIdPrefix = "config-logging-test"
|
||||
trustedPackages = "at.mocode.*,com.test.*"
|
||||
enableSecurityFeatures = true
|
||||
connectionPoolSize = 15
|
||||
}
|
||||
|
||||
val customConsumer = KafkaEventConsumer(customConfig)
|
||||
val customReactiveConfig = ReactiveKafkaConfig(customConfig)
|
||||
|
||||
assertDoesNotThrow {
|
||||
val template = customReactiveConfig.reactiveKafkaProducerTemplate()
|
||||
assertThat(template).isNotNull
|
||||
}
|
||||
|
||||
logger.debug("Configuration logging test completed")
|
||||
logger.debug("Bootstrap servers: {}", customConfig.bootstrapServers)
|
||||
logger.debug("Group ID prefix: {}", customConfig.defaultGroupIdPrefix)
|
||||
logger.debug("Trusted packages: {}", customConfig.trustedPackages)
|
||||
logger.debug("Security features enabled: {}", customConfig.enableSecurityFeatures)
|
||||
logger.debug("Connection pool size: {}", customConfig.connectionPoolSize)
|
||||
|
||||
customConsumer.cleanup()
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log resource cleanup operations`() {
|
||||
val tempConsumer = KafkaEventConsumer(kafkaConfig)
|
||||
|
||||
// Create some reactive streams to establish resources
|
||||
val flux1 = tempConsumer.receiveEvents<LoggingTestEvent>("cleanup-topic-1")
|
||||
val flux2 = tempConsumer.receiveEvents<LoggingTestEvent>("cleanup-topic-2")
|
||||
|
||||
assertThat(flux1).isNotNull
|
||||
assertThat(flux2).isNotNull
|
||||
|
||||
logger.debug("Resources created for cleanup test")
|
||||
|
||||
// Cleanup should log resource cleanup operations
|
||||
assertDoesNotThrow {
|
||||
tempConsumer.cleanup()
|
||||
}
|
||||
|
||||
logger.debug("Resource cleanup test completed")
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle logging under concurrent access`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
val mockRecordMetadata = mockk<org.apache.kafka.clients.producer.RecordMetadata>()
|
||||
every { mockRecordMetadata.topic() } returns "concurrent-logging-topic"
|
||||
every { mockRecordMetadata.partition() } returns 0
|
||||
every { mockRecordMetadata.offset() } returns 0L
|
||||
every { mockResult.recordMetadata() } returns mockRecordMetadata
|
||||
|
||||
every { mockTemplate.send(any(), any(), any()) } returns Mono.just(mockResult)
|
||||
|
||||
// Create concurrent publishing operations
|
||||
val concurrentEvents = (1..20).map { i ->
|
||||
publisher.publishEvent("concurrent-logging-topic", "concurrent_key_$i",
|
||||
LoggingTestEvent("Concurrent message $i", i))
|
||||
}
|
||||
|
||||
StepVerifier.create(reactor.core.publisher.Flux.merge(concurrentEvents))
|
||||
.expectNextCount(20)
|
||||
.verifyComplete()
|
||||
|
||||
logger.debug("Concurrent logging test completed with 20 concurrent operations")
|
||||
|
||||
verify(exactly = 20) { mockTemplate.send(any(), any(), any()) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should log timestamp and correlation information`() {
|
||||
val mockTemplate = mockk<ReactiveKafkaProducerTemplate<String, Any>>()
|
||||
val publisher = KafkaEventPublisher(mockTemplate)
|
||||
val mockResult = mockk<SenderResult<Void>>()
|
||||
|
||||
every { mockTemplate.send(any(), any(), any()) } returns Mono.just(mockResult)
|
||||
|
||||
val timestampedEvent = LoggingTestEvent("timestamped", 1)
|
||||
|
||||
val beforePublish = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(publisher.publishEvent("timestamp-topic", "timestamp-key", timestampedEvent))
|
||||
.verifyComplete()
|
||||
|
||||
val afterPublish = System.currentTimeMillis()
|
||||
|
||||
logger.debug("Event published with timestamp correlation")
|
||||
logger.debug("Publish window: {} to {} ({}ms)", beforePublish, afterPublish, afterPublish - beforePublish)
|
||||
|
||||
verify(exactly = 1) { mockTemplate.send("timestamp-topic", "timestamp-key", timestampedEvent) }
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should provide debug information for troubleshooting`() {
|
||||
// Create various configurations and operations to generate debug logs
|
||||
val debugConfig = KafkaConfig().apply {
|
||||
bootstrapServers = "debug-server:9092"
|
||||
defaultGroupIdPrefix = "debug-test"
|
||||
}
|
||||
|
||||
val debugConsumer = KafkaEventConsumer(debugConfig)
|
||||
val debugFlux = debugConsumer.receiveEvents<LoggingTestEvent>("debug-topic")
|
||||
|
||||
logger.debug("Debug configuration created")
|
||||
logger.debug("Consumer group ID would be: debug-test-debug-topic-loggingtesteevent")
|
||||
logger.debug("Bootstrap servers: debug-server:9092")
|
||||
|
||||
assertThat(debugFlux).isNotNull
|
||||
|
||||
debugConsumer.cleanup()
|
||||
logger.debug("Debug cleanup completed")
|
||||
}
|
||||
|
||||
@AfterEach
|
||||
fun tearDown() {
|
||||
// Restore original output
|
||||
System.setOut(originalOut)
|
||||
consumer.cleanup()
|
||||
}
|
||||
|
||||
data class LoggingTestEvent(
|
||||
val message: String,
|
||||
val sequenceNumber: Int,
|
||||
val timestamp: Long = System.currentTimeMillis()
|
||||
)
|
||||
|
||||
data class ComplexLoggingEvent(
|
||||
val name: String,
|
||||
val id: Int,
|
||||
val metadata: Map<String, String>
|
||||
)
|
||||
|
||||
data class NumericLoggingEvent(
|
||||
val intValue: Int,
|
||||
val doubleValue: Double,
|
||||
val timestamp: Long
|
||||
)
|
||||
}
|
||||
-365
@@ -1,365 +0,0 @@
|
||||
package at.mocode.infrastructure.messaging.client
|
||||
|
||||
import at.mocode.infrastructure.messaging.config.KafkaConfig
|
||||
import org.assertj.core.api.Assertions.assertThat
|
||||
import org.junit.jupiter.api.BeforeEach
|
||||
import org.junit.jupiter.api.Test
|
||||
import org.junit.jupiter.api.TestInstance
|
||||
import org.junit.jupiter.api.assertDoesNotThrow
|
||||
import org.slf4j.LoggerFactory
|
||||
import reactor.core.publisher.Flux
|
||||
import reactor.core.publisher.Mono
|
||||
import reactor.core.scheduler.Schedulers
|
||||
import reactor.test.StepVerifier
|
||||
import reactor.test.publisher.TestPublisher
|
||||
import java.time.Duration
|
||||
import java.util.concurrent.CountDownLatch
|
||||
import java.util.concurrent.TimeUnit
|
||||
import java.util.concurrent.atomic.AtomicInteger
|
||||
import java.util.concurrent.atomic.AtomicLong
|
||||
|
||||
@TestInstance(TestInstance.Lifecycle.PER_CLASS)
|
||||
class ReactiveStreamTest {
|
||||
|
||||
private val logger = LoggerFactory.getLogger(ReactiveStreamTest::class.java)
|
||||
|
||||
private lateinit var kafkaConfig: KafkaConfig
|
||||
private lateinit var consumer: KafkaEventConsumer
|
||||
|
||||
@BeforeEach
|
||||
fun setUp() {
|
||||
kafkaConfig = KafkaConfig().apply {
|
||||
bootstrapServers = "localhost:9092"
|
||||
defaultGroupIdPrefix = "reactive-test-consumer"
|
||||
trustedPackages = "at.mocode.*"
|
||||
}
|
||||
consumer = KafkaEventConsumer(kafkaConfig)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should create cold streams that start on subscription`() {
|
||||
// Cold streams should not start processing until subscribed
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("cold-stream-topic")
|
||||
|
||||
// Stream should be created but not started
|
||||
assertThat(flux).isNotNull
|
||||
|
||||
// No subscription means no processing should begin.
|
||||
// This is verified by the fact that creating the flux doesn't throw or block
|
||||
assertDoesNotThrow {
|
||||
val anotherFlux = consumer.receiveEvents<ReactiveTestEvent>("another-cold-topic")
|
||||
assertThat(anotherFlux).isNotNull
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle multiple subscribers to same stream`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("multi-subscriber-topic")
|
||||
|
||||
// Multiple subscribers should be able to subscribe to the same flux
|
||||
val subscriber1 = StepVerifier.create(flux.take(1).timeout(Duration.ofSeconds(2)))
|
||||
val subscriber2 = StepVerifier.create(flux.take(1).timeout(Duration.ofSeconds(2)))
|
||||
|
||||
// Both subscribers should be created without issues
|
||||
// Note: In real Kafka usage, each subscriber would get their own consumer group
|
||||
assertDoesNotThrow {
|
||||
subscriber1.thenCancel().verify(Duration.ofSeconds(1))
|
||||
subscriber2.thenCancel().verify(Duration.ofSeconds(1))
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should support reactive operators and transformations`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("transformation-topic")
|
||||
|
||||
// Apply various reactive operators
|
||||
val transformedFlux = flux
|
||||
.filter { event -> event.message.contains("important") }
|
||||
.map { event -> event.message.uppercase() }
|
||||
.distinctUntilChanged()
|
||||
.take(5)
|
||||
|
||||
assertThat(transformedFlux).isNotNull
|
||||
|
||||
// Should be able to subscribe to transformed flux
|
||||
val verifier = StepVerifier.create(transformedFlux.timeout(Duration.ofSeconds(2)))
|
||||
assertDoesNotThrow {
|
||||
verifier.thenCancel().verify(Duration.ofSeconds(1))
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle backpressure gracefully`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("backpressure-topic")
|
||||
|
||||
// Simulate slow consumer to test backpressure
|
||||
val slowProcessingFlux = flux
|
||||
.concatMap { event ->
|
||||
Mono.delay(Duration.ofMillis(100))
|
||||
.map { event }
|
||||
}
|
||||
.take(3)
|
||||
|
||||
val startTime = System.currentTimeMillis()
|
||||
|
||||
StepVerifier.create(slowProcessingFlux.timeout(Duration.ofSeconds(5)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(2))
|
||||
|
||||
val duration = System.currentTimeMillis() - startTime
|
||||
|
||||
// Should handle backpressure without blocking indefinitely
|
||||
assertThat(duration).isLessThan(3000)
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should maintain stream characteristics under error conditions`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("error-resilience-topic")
|
||||
|
||||
// Add error handling and recovery
|
||||
val resilientFlux = flux
|
||||
.onErrorResume { error ->
|
||||
// Log error and continue with an empty stream
|
||||
logger.debug("Handled error in stream: {}", error.message)
|
||||
Flux.empty()
|
||||
}
|
||||
.retry(2)
|
||||
.take(1)
|
||||
|
||||
StepVerifier.create(resilientFlux.timeout(Duration.ofSeconds(3)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(2))
|
||||
|
||||
// Stream should remain reactive even after error handling
|
||||
assertThat(resilientFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should support concurrent stream processing`() {
|
||||
val flux1 = consumer.receiveEvents<ReactiveTestEvent>("concurrent-topic-1")
|
||||
val flux2 = consumer.receiveEvents<ReactiveTestEvent>("concurrent-topic-2")
|
||||
val flux3 = consumer.receiveEvents<ReactiveTestEvent>("concurrent-topic-3")
|
||||
|
||||
// Process multiple streams concurrently
|
||||
val combinedFlux = Flux.merge(
|
||||
flux1.subscribeOn(Schedulers.parallel()),
|
||||
flux2.subscribeOn(Schedulers.parallel()),
|
||||
flux3.subscribeOn(Schedulers.parallel())
|
||||
).take(3)
|
||||
|
||||
StepVerifier.create(combinedFlux.timeout(Duration.ofSeconds(3)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(2))
|
||||
|
||||
// All streams should be processable concurrently
|
||||
assertThat(combinedFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle stream lifecycle correctly`() {
|
||||
val eventCounter = AtomicInteger(0)
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("lifecycle-topic")
|
||||
|
||||
// Add lifecycle monitoring
|
||||
val monitoredFlux = flux
|
||||
.doOnSubscribe { subscription ->
|
||||
logger.debug("Stream subscribed: {}", subscription)
|
||||
}
|
||||
.doOnNext { event ->
|
||||
val count = eventCounter.incrementAndGet()
|
||||
logger.debug("Processed event #{}: {}", count, event.message)
|
||||
}
|
||||
.doOnCancel {
|
||||
logger.debug("Stream cancelled")
|
||||
}
|
||||
.doOnComplete {
|
||||
logger.debug("Stream completed")
|
||||
}
|
||||
.take(1)
|
||||
|
||||
StepVerifier.create(monitoredFlux.timeout(Duration.ofSeconds(2)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(1))
|
||||
|
||||
// Lifecycle should be properly managed
|
||||
assertThat(monitoredFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should support flow control mechanisms`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("flow-control-topic")
|
||||
|
||||
// Apply various flow control mechanisms
|
||||
val controlledFlux = flux
|
||||
.limitRate(10) // Limit upstream requests
|
||||
.sample(Duration.ofMillis(100)) // Sample at fixed intervals
|
||||
.buffer(5) // Buffer elements
|
||||
.flatMap { buffer ->
|
||||
logger.debug("Processing buffer of size: {}", buffer.size)
|
||||
Flux.fromIterable(buffer)
|
||||
}
|
||||
.take(5)
|
||||
|
||||
StepVerifier.create(controlledFlux.timeout(Duration.ofSeconds(3)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(2))
|
||||
|
||||
assertThat(controlledFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle time-based operations`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("time-based-topic")
|
||||
|
||||
// Apply time-based operations
|
||||
val timedFlux = flux
|
||||
.window(Duration.ofMillis(200)) // Window by time
|
||||
.flatMap { window ->
|
||||
window.collectList()
|
||||
.map { events ->
|
||||
logger.debug("Window contains {} events", events.size)
|
||||
events.size
|
||||
}
|
||||
}
|
||||
.take(2)
|
||||
|
||||
StepVerifier.create(timedFlux.timeout(Duration.ofSeconds(3)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(2))
|
||||
|
||||
assertThat(timedFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should maintain thread safety in reactive streams`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("thread-safety-topic")
|
||||
val processedCount = AtomicLong(0)
|
||||
val latch = CountDownLatch(3)
|
||||
|
||||
// Process on multiple threads
|
||||
val threadSafeFlux = flux
|
||||
.publishOn(Schedulers.parallel())
|
||||
.doOnNext { event ->
|
||||
val count = processedCount.incrementAndGet()
|
||||
logger.debug("Thread {} processed event #{}", Thread.currentThread().name, count)
|
||||
latch.countDown()
|
||||
}
|
||||
.take(3)
|
||||
|
||||
// Subscribe and wait briefly
|
||||
val subscription = threadSafeFlux
|
||||
.timeout(Duration.ofSeconds(2))
|
||||
.subscribe(
|
||||
{ event -> /* processed */ },
|
||||
{ error -> logger.debug("Error: {}", error.message) },
|
||||
{ logger.debug("Stream completed") }
|
||||
)
|
||||
|
||||
// Wait for brief processing or timeout
|
||||
val completed = latch.await(1, TimeUnit.SECONDS)
|
||||
subscription.dispose()
|
||||
|
||||
// Thread safety should be maintained (no exceptions thrown)
|
||||
assertThat(subscription).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should support custom schedulers`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("scheduler-topic")
|
||||
|
||||
// Use different schedulers for different operations
|
||||
val scheduledFlux = flux
|
||||
.subscribeOn(Schedulers.boundedElastic()) // For I/O operations
|
||||
.publishOn(Schedulers.parallel()) // For CPU-intensive operations
|
||||
.map { event ->
|
||||
logger.debug("Processing on thread: {}", Thread.currentThread().name)
|
||||
event.message.length
|
||||
}
|
||||
.subscribeOn(Schedulers.single()) // Single-threaded subscription
|
||||
.take(1)
|
||||
|
||||
StepVerifier.create(scheduledFlux.timeout(Duration.ofSeconds(2)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(1))
|
||||
|
||||
assertThat(scheduledFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle stream composition and chaining`() {
|
||||
val flux1 = consumer.receiveEvents<ReactiveTestEvent>("composition-topic-1")
|
||||
val flux2 = consumer.receiveEvents<ReactiveTestEvent>("composition-topic-2")
|
||||
|
||||
// Compose multiple streams
|
||||
val composedFlux = flux1
|
||||
.switchMap { event1 ->
|
||||
flux2.map { event2 ->
|
||||
logger.debug("Composed: {} -> {}", event1.message, event2.message)
|
||||
"${event1.message}+${event2.message}"
|
||||
}
|
||||
}
|
||||
.take(1)
|
||||
|
||||
StepVerifier.create(composedFlux.timeout(Duration.ofSeconds(2)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(1))
|
||||
|
||||
assertThat(composedFlux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should support reactive testing patterns`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("testing-patterns-topic")
|
||||
|
||||
// Use TestPublisher to simulate controlled event emission
|
||||
val testPublisher = TestPublisher.create<ReactiveTestEvent>()
|
||||
val testFlux = testPublisher.flux()
|
||||
|
||||
// Apply similar transformations as the real flux
|
||||
val transformedTestFlux = testFlux
|
||||
.filter { event -> event.message.isNotEmpty() }
|
||||
.map { event -> event.message.length }
|
||||
|
||||
// Test with controlled emissions
|
||||
StepVerifier.create(transformedTestFlux)
|
||||
.then { testPublisher.next(ReactiveTestEvent("test", 1)) }
|
||||
.expectNext(4) // "test".length
|
||||
.then { testPublisher.complete() }
|
||||
.verifyComplete()
|
||||
|
||||
// Real flux should also be testable
|
||||
assertThat(flux).isNotNull
|
||||
}
|
||||
|
||||
@Test
|
||||
fun `should handle resource cleanup properly`() {
|
||||
val flux = consumer.receiveEvents<ReactiveTestEvent>("cleanup-topic")
|
||||
val resourcesAcquired = AtomicInteger(0)
|
||||
val resourcesReleased = AtomicInteger(0)
|
||||
|
||||
val resourceManagedFlux = flux
|
||||
.doOnSubscribe {
|
||||
resourcesAcquired.incrementAndGet()
|
||||
logger.debug("Resources acquired: {}", resourcesAcquired.get())
|
||||
}
|
||||
.doFinally { signalType ->
|
||||
resourcesReleased.incrementAndGet()
|
||||
logger.debug("Resources released on {}: {}", signalType, resourcesReleased.get())
|
||||
}
|
||||
.take(1)
|
||||
|
||||
StepVerifier.create(resourceManagedFlux.timeout(Duration.ofSeconds(2)))
|
||||
.thenCancel()
|
||||
.verify(Duration.ofSeconds(1))
|
||||
|
||||
// Resource management should be handled properly
|
||||
// Note: In a real scenario, we'd verify that resources are properly cleaned up
|
||||
assertThat(resourceManagedFlux).isNotNull
|
||||
}
|
||||
|
||||
data class ReactiveTestEvent(
|
||||
val message: String,
|
||||
val sequenceNumber: Int,
|
||||
val timestamp: Long = System.currentTimeMillis()
|
||||
)
|
||||
}
|
||||
Reference in New Issue
Block a user