Cloud-Native Microservices Platform: Design Document

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1. Overview

This project builds a cloud-native microservices platform with three loosely coupled services—User, Order, Notification—demonstrating event-driven architecture, infrastructure as code, and full observability. The platform uses Kotlin (Spring Boot) or Go (Gin) for services, PostgreSQL for persistence, and Kafka (MSK) for asynchronous events. Deployment targets AWS via Terraform for reproducibility. Monitoring/alerting is provided via Prometheus and Grafana.

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2. Goals and Objectives

End-to-end microservices lifecycle: Develop, test, deploy, monitor, and maintain microservices using best industry practices.
Event-driven workflows: Showcase decoupling and asynchronous communication using Kafka.
Infrastructure-as-Code: Apply modular Terraform to manage all AWS infrastructure.
Observability: Instrument all services, collect metrics, and visualize in Grafana.
Security & Compliance: Enforce least-privilege, encryption, and secure inter-service comms.

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Scope

Microservices:
- user-service
- order-service
- notification-service
Infrastructure Modules:
- VPC, RDS (PostgreSQL), MSK (Kafka), ECS/EKS, IAM, ALB/API Gateway
Observability:
- Prometheus scraping each service, Grafana dashboards
Documentation:
- README, architecture diagrams, example workflows

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4. Architecture & Components

4.1 High-Level Diagram

[Client] 
   │
   ▼
[API Gateway (ALB)]
   │
 ┌─┼─────────┬────────────┐
 │           │            │
▼           ▼            ▼
[User Svc] [Order Svc] [Notif Svc]
   │           │            │
   ▼           ▼            ▼
[Postgres] [Postgres]    (Stateless)
   │           │
   └─►[Kafka (MSK)]◄──────┘
        │        │
   ┌────┴────┐   │
   ▼         ▼   ▼
(Order, User events)

API Gateway (ALB): Routes external traffic.
ECS Fargate: Deploys stateless services.
Kafka (MSK): Core event bus.
RDS PostgreSQL: Service DBs.
Prometheus: Scrapes /metrics.
Grafana: Visualization/alerts.

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5. Data Flow

User Service:
- Receives REST call, writes to Postgres
- Emits user.created to Kafka
Order Service:
- Consumes user.created, processes orders
- Writes order to Postgres, emits order.processed
Notification Service:
- Consumes events, sends emails/notifications
Prometheus:
- Each service exposes /metrics endpoint
- Prometheus scrapes all, Grafana dashboards visualize metrics

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6. Technology Stack

Backend: Kotlin (Spring Boot) or Go (Gin)
Messaging: Kafka (AWS MSK)
Database: PostgreSQL (RDS)
Container Runtime: ECS Fargate or EKS (Kubernetes)
Networking: VPC, ALB
Infrastructure: Terraform 1.x, AWS CLI
Observability: Prometheus, Grafana

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7. Infrastructure as Code

Terraform Modules

Root infra/
- modules/vpc/
- modules/rds/
- modules/msk/
- modules/ecs/ or modules/eks/
- modules/iam/
- modules/alb/
  - environments/dev/, staging/, prod/
State management: S3 backend + DynamoDB lock
CI: Plan/apply via pipeline; validate on PR

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8. Non-Functional Requirements

Availability: ≥ 99.5% (multi-AZ, health checks, auto-recovery)
Latency: < 200ms avg (API/DB/queue performance tuning)
Idempotency: Terraform applies and service APIs
Security: TLS for Kafka, IAM for service accounts, encryption at rest (RDS, MSK)

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9. Deployment and Release

GitOps: All changes via PR/merge in infra/ repo; pipeline triggers terraform plan/apply
Blue/green deploy: ECS task set swaps or k8s rolling update
Service rollout: Health checks, automatic rollback on failure

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10. Testing & Resilience

Service-level: Unit/integration tests (JUnit/Go test)
E2E: Docker Compose for local integration, then ECS/EKS
Infra: terraform validate and plan checks in CI
Chaos testing: Randomly terminate tasks/pods to ensure resilience, use AWS Fault Injection Simulator if available

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11. Observability & Monitoring

Prometheus Exporters: Spring Boot actuator/Go promhttp on /metrics
Prometheus Server: Runs on EC2 or ECS/EKS
Grafana Dashboards: Pre-built, with alerts for high error rates, latency, saturation
Drift detection: Monthly terraform plan diff vs. applied state

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12. Security

Kafka (MSK): TLS, IAM authentication
PostgreSQL: Encrypted storage, restricted security group access
ECS/EKS: Task roles with least privilege, separate network for backend
ALB: HTTPS only, WAF (optional)
Secret Management: AWS Secrets Manager for DB/Kafka creds

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13. Maintenance Plan

Monthly: Drift detection, patching base images, review IAM policies
On-call: PagerDuty/SNS alerts for Grafana triggers

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14. Timeline & Milestones

Week	Milestone
1	Scaffold services (local Docker Compose)
2	Terraform infra MVP (VPC, RDS, MSK, ECS)
3	Kafka integration, end-to-end event flows
4	Observability, dashboards, documentation

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Local Development Setup

To run the microservices locally, follow these steps:

Build the services:

./gradlew build

Start all services with Docker Compose

docker-compose -f docker-compose-local.yml up

The services will be available at:

User Service: http://localhost:8081
Order Service: http://localhost:8082
Notification Service: http://localhost:8083
PostgreSQL: localhost:5432
Kafka: localhost:9092

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15. Future Enhancements (Out of Scope but Recommended)

Service mesh (Istio/App Mesh) for advanced traffic management
Canary deployments and autoscaling
Secrets rotation automation
Full SRE runbook for on-call

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Appendix

Example Kafka Event (user.created)

{
  "event_type": "user.created",
  "user_id": "123456",
  "email": "user@domain.com",
  "created_at": "2024-05-23T19:00:00Z"
}

Sample Prometheus Metrics (user-service)


http_requests_total{method="POST",endpoint="/users"} 1234
service_errors_total{service="user-service"} 3

Sample Grafana Dashboard

{
  "title": "User Service Dashboard",
  "panels": [
    {
      "title": "HTTP Requests",
      "type": "graph",
      "datasource": "Prometheus",
      "targets": [
        {
          "expr": "http_requests_total{method=\"POST\",endpoint=\"/users\"}",
          "refId": "A"
        }
      ]
    }
  ]
}

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Diagrams, Prototypes, and Examples

I can provide architecture diagrams (UML, draw.io, or PlantUML format), sample Terraform modules, or boilerplate for Spring Boot/Gin microservices, as well as Prometheus/Grafana configs—just ask for the specifics you want next!

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Stretch Goals:

A specific architecture diagram (SVG, PlantUML, Markdown)
Terraform skeleton for one of the modules
Spring Boot or Go service boilerplate
Example Kafka producer/consumer code
Prometheus/Grafana YAMLs
End-to-end test scenarios

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1. High-Level UML Component Diagram (PlantUML)

Paste this into PlantUML Online Editor for a visual diagram.

    @startuml
    !define RECTANGLE class

    rectangle "API Gateway (ALB)" as alb

    rectangle "User Service\n(Spring Boot)" as user
    rectangle "Order Service\n(Spring Boot)" as order
    rectangle "Notification Service\n(Spring Boot)" as notif

    database "RDS PostgreSQL" as db
    cloud "Kafka (MSK)" as kafka

    rectangle "Prometheus" as prometheus
    rectangle "Grafana" as grafana

    alb --> user : REST
    alb --> order : REST
    alb --> notif : REST

    user --> db : JDBC
    order --> db : JDBC

    user --> kafka : "user.created"
    order --> kafka : "order.processed"
    notif --> kafka : "notification events"

    kafka --> order : "user.created"
    kafka --> notif : "order.processed"

    user --> prometheus : "/metrics"
    order --> prometheus : "/metrics"
    notif --> prometheus : "/metrics"
    prometheus --> grafana : "metrics"

    @enduml

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2. Terraform Skeleton (infra/ Directory Structure)

Directory Layout:

infra/
├── main.tf
├── variables.tf
├── outputs.tf
├── provider.tf
├── modules/
│   ├── vpc/
│   │   └── (vpc.tf, variables.tf, outputs.tf)
│   ├── rds/
│   │   └── (rds.tf, variables.tf, outputs.tf)
│   ├── msk/
│   │   └── (msk.tf, variables.tf, outputs.tf)
│   ├── ecs/
│   │   └── (ecs.tf, variables.tf, outputs.tf)
│   ├── alb/
│   │   └── (alb.tf, variables.tf, outputs.tf)
│   ├── iam/
│   │   └── (iam.tf, variables.tf, outputs.tf)
│   └── observability/
│       └── (prometheus.tf, grafana.tf)
└── environments/
    ├── dev/
    │   └── (main.tf, variables.tf)
    ├── staging/
    └── prod/

Example: Top-level main.tf

module "vpc" {
  source = "./modules/vpc"
  ...
}

module "rds" {
  source = "./modules/rds"
  vpc_id = module.vpc.vpc_id
  ...
}

module "msk" {
  source = "./modules/msk"
  vpc_id = module.vpc.vpc_id
  ...
}

module "ecs" {
  source = "./modules/ecs"
  vpc_id = module.vpc.vpc_id
  ...
}

module "alb" {
  source = "./modules/alb"
  vpc_id = module.vpc.vpc_id
  ...
}

module "iam" {
  source = "./modules/iam"
  ...
}

module "observability" {
  source = "./modules/observability"
  ...
}

Each module directory (modules/vpc, modules/rds, etc.) will have its own *.tf files. Let me know if you want a sample for a specific module (e.g., full VPC or RDS).

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3. Spring Boot Service Boilerplate (User Service)

UserServiceApplication.kt

@SpringBootApplication
class UserServiceApplication

fun main(args: Array<String>) {
    runApplication<UserServiceApplication>(*args)
}

UserController.kt

@RestController
@RequestMapping("/users")
class UserController(
    private val userService: UserService
) {
    @PostMapping
    fun createUser(@RequestBody req: CreateUserRequest): ResponseEntity<User> =
        ResponseEntity.ok(userService.createUser(req))
}

data class CreateUserRequest(val email: String, val name: String)

UserService.kt

@Service
class UserService(
    private val userRepository: UserRepository,
    private val kafkaTemplate: KafkaTemplate<String, UserCreatedEvent>
) {
    fun createUser(req: CreateUserRequest): User {
        val user = userRepository.save(User(email = req.email, name = req.name))
        kafkaTemplate.send("user.created", user.id.toString(), UserCreatedEvent(user.id, user.email, user.name))
        return user
    }
}

data class UserCreatedEvent(val id: Long, val email: String, val name: String)

User.kt (JPA Entity)

@Entity
data class User(
    @Id @GeneratedValue val id: Long = 0,
    val email: String,
    val name: String
)

UserRepository.kt

interface UserRepository : JpaRepository<User, Long>

application.yml

spring:
  datasource:
    url: jdbc:postgresql://localhost:5432/userdb
    username: user
    password: pass
  kafka:
    bootstrap-servers: localhost:9092

management:
  endpoints:
    web:
      exposure:
        include: health,info,prometheus

KafkaConfig.kt

@Configuration
class KafkaConfig {
    @Bean
    fun kafkaTemplate(producerFactory: ProducerFactory<String, UserCreatedEvent>): KafkaTemplate<String, UserCreatedEvent> =
        KafkaTemplate(producerFactory)
}

Prometheus Actuator

Add dependency:

implementation("io.micrometer:micrometer-registry-prometheus")

and /actuator/prometheus will expose metrics.

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4. Complete Kafka Producer/Consumer Code (Kotlin/Spring Boot Example)

Producer (User Service)

// Inside UserService, see above
kafkaTemplate.send("user.created", user.id.toString(), UserCreatedEvent(user.id, user.email, user.name))

Consumer (Order Service)

@Component
class UserEventListener {
    @KafkaListener(topics = ["user.created"], groupId = "order-service")
    fun handleUserCreated(event: String) {
        val userEvent = ObjectMapper().readValue(event, UserCreatedEvent::class.java)
        // process userEvent
    }
}

Producer (Order Service)

kafkaTemplate.send("order.processed", order.id.toString(), OrderProcessedEvent(...))

Consumer (Notification Service)

@Component
class OrderEventListener {
    @KafkaListener(topics = ["order.processed"], groupId = "notification-service")
    fun handleOrderProcessed(event: String) {
        val orderEvent = ObjectMapper().readValue(event, OrderProcessedEvent::class.java)
        // send notification
    }
}

Kafka Config Example

@Configuration
class KafkaConfig {
    @Bean
    fun consumerFactory(): ConsumerFactory<String, String> {
        val props = HashMap<String, Any>()
        props[ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG] = "localhost:9092"
        props[ConsumerConfig.GROUP_ID_CONFIG] = "order-service"
        props[ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG] = StringDeserializer::class.java
        props[ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG] = StringDeserializer::class.java
        return DefaultKafkaConsumerFactory(props)
    }
    @Bean
    fun kafkaListenerContainerFactory(): ConcurrentKafkaListenerContainerFactory<String, String> {
        val factory = ConcurrentKafkaListenerContainerFactory<String, String>()
        factory.consumerFactory = consumerFactory()
        return factory
    }
}

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5. Fully Featured Prometheus/Grafana Setup

Prometheus Configuration (prometheus.yml)

global:
  scrape_interval: 15s
scrape_configs:
  - job_name: 'user-service'
    metrics_path: '/actuator/prometheus'
    static_configs:
      - targets: ['user-service:8080']
  - job_name: 'order-service'
    metrics_path: '/actuator/prometheus'
    static_configs:
      - targets: ['order-service:8080']
  - job_name: 'notification-service'
    metrics_path: '/actuator/prometheus'
    static_configs:
      - targets: ['notification-service:8080']

Grafana Setup

Add Prometheus as a data source (URL: http://prometheus:9090)
Import Dashboards: Use Spring Boot Micrometer dashboards or build custom ones for:
- Request rate, latency, error rates per service
- JVM memory/cpu stats (for Kotlin services)
- Kafka consumer lag (dashboard example)

Docker Compose for local stack

version: "3"
services:
  prometheus:
    image: prom/prometheus
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"
  grafana:
    image: grafana/grafana
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin

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6. End-to-End Test Suite (Example with Testcontainers for Integration)

Add dependencies

testImplementation("org.springframework.boot:spring-boot-starter-test")
testImplementation("org.testcontainers:junit-jupiter")
testImplementation("org.testcontainers:kafka")
testImplementation("org.testcontainers:postgresql")

Example E2E Test

@SpringBootTest
@AutoConfigureMockMvc
@Testcontainers
class UserOrderE2ETest {
    companion object {
        @Container
        val postgres = PostgreSQLContainer("postgres:13")
        @Container
        val kafka = KafkaContainer("5.5.1")
    }
    @Autowired lateinit var mockMvc: MockMvc

    @Test
    fun `end-to-end user creation emits event and triggers order service`() {
        // 1. Create user via REST
        val userJson = """{"email":"test@acme.com","name":"Jane"}"""
        mockMvc.perform(
            post("/users").contentType(MediaType.APPLICATION_JSON).content(userJson)
        ).andExpect(status().isOk)

        // 2. Assert that a 'user.created' event was published to Kafka
        // (Implement a Kafka consumer to listen and verify the event)

        // 3. Mock or spin up order service to consume and process event

        // 4. Verify order processed event and notification sent (simulate downstream)
    }
}

You can expand this to include

Full integration with real Kafka and Postgres
Test notification flow via a mock SMTP server (e.g. GreenMail)
Chaos tests: Randomly kill service containers during tests and assert recovery

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What Next?

Architecture Diagram: Use PlantUML code above for high-level architecture.
Terraform: Copy-paste skeleton; ask for any module in detail.
Spring Boot: Use code as template; let me know if you want the Order/Notification variants.
Kafka: Producer/Consumer code included.
Prometheus/Grafana: Configs and dashboards ready; expand as needed.
End-to-End Tests: Copy pattern above for each microservice pair.

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
.vscode		.vscode
gradle/wrapper		gradle/wrapper
services		services
src		src
.gitignore		.gitignore
Dockerfile		Dockerfile
README.md		README.md
build.gradle.kts		build.gradle.kts
docker-compose-local.yml		docker-compose-local.yml
docker-compose.yml		docker-compose.yml
gradlew		gradlew
gradlew.bat		gradlew.bat
settings.gradle.kts		settings.gradle.kts

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Latest commit

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Cloud-Native Microservices Platform: Design Document

1. Overview

2. Goals and Objectives

4. Architecture & Components

4.1 High-Level Diagram

5. Data Flow

6. Technology Stack

7. Infrastructure as Code

8. Non-Functional Requirements

9. Deployment and Release

10. Testing & Resilience

11. Observability & Monitoring

12. Security

13. Maintenance Plan

14. Timeline & Milestones

Local Development Setup

15. Future Enhancements (Out of Scope but Recommended)

Appendix

Example Kafka Event (user.created)

Sample Prometheus Metrics (user-service)

Sample Grafana Dashboard

Diagrams, Prototypes, and Examples

1. High-Level UML Component Diagram (PlantUML)

2. Terraform Skeleton (infra/ Directory Structure)

Example: Top-level main.tf

3. Spring Boot Service Boilerplate (User Service)

UserServiceApplication.kt

UserController.kt

UserService.kt

User.kt (JPA Entity)

UserRepository.kt

application.yml

KafkaConfig.kt

Prometheus Actuator

4. Complete Kafka Producer/Consumer Code (Kotlin/Spring Boot Example)

Producer (User Service)

Consumer (Order Service)

Producer (Order Service)

Consumer (Notification Service)

Kafka Config Example

5. Fully Featured Prometheus/Grafana Setup

Prometheus Configuration (prometheus.yml)

Grafana Setup

Docker Compose for local stack

6. End-to-End Test Suite (Example with Testcontainers for Integration)

Add dependencies

Example E2E Test

You can expand this to include

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