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Auction Service

Event-driven microservice for managing auction items with RabbitMQ integration and high-throughput concurrent processing.

Architecture Overview

The auction service consists of two main components:

1. API Service (cmd/api/)

Role: HTTP REST API + Event Publisher

  • Handles item and comment CRUD operations
  • Manages categories and item metadata (attributes, images)
  • Publishes domain events (items, comments) to RabbitMQ
  • Used by external clients and services

Events Published:

  • item.created.v1 → When a new item is created
  • item.updated.v1 → When an item is updated
  • item.deleted.v1 → When an item is deleted
  • item.comment.created.v1 → When a comment is added to an item
  • item.comment.deleted.v1 → When a comment is deleted from an item
  • item.image.uploaded.v1 → When an image is uploaded to an item
  • item.image.deleted.v1 → When an image is deleted from an item
  • item.attribute.created.v1 → When item attributes are created
  • item.attribute.deleted.v1 → When an item attribute is deleted

2. Worker Service (cmd/worker/)

Role: Event Consumer + Item State Manager

  • Consumes events from other services (bid service, payment service, etc.)
  • Updates item state based on external events
  • Runs with 3 replicas (horizontal scaling)
  • 60 concurrent workers (3 replicas × 20 workers each)
  • 45 total DB connections (3 replicas × 15 connections each)

Events Consumed:

  • bid.placed.v1 → Updates item current price
  • bid.won.v1 → Marks item as sold and sets buyer

Project Structure

auction/
├── cmd/
│   ├── api/                    # HTTP API Service (Publisher)
│   │   └── main.go
│   └── worker/                 # Event Worker Service (Consumer)
│       └── main.go
│
├── app/                        # Application layer (HTTP handlers)
│   ├── create_item_handler.go
│   ├── get_items_handler.go
│   ├── get_item_handler.go
│   ├── update_item_handler.go
│   ├── delete_item_handler.go
│   ├── get_categories_handler.go
│   ├── get_category_handler.go
│   ├── get_comments_handler.go
│   ├── create_comment_handler.go
│   ├── delete_comment_handler.go
│   ├── get_item_images_handler.go
│   ├── upload_item_image_handler.go
│   ├── delete_item_image_handler.go
│   ├── get_item_attributes_handlers.go
│   ├── get_item_attribute_handler.go
│   ├── create_item_attributes_handler.go
│   ├── delete_item_attribute_handler.go
│   └── repository.go
│
├── domain/                     # Domain entities
│   ├── item.go
│   ├── category.go
│   ├── item_category.go
│   ├── item_attribute.go
│   ├── item_comment.go
│   └── item_image.go
│
├── internal/
│   ├── middleware/             # HTTP middlewares
│   └── consumers/              # Event consumer handlers
│       └── bid_consumer.go     # Handles bid events
│
├── infra/
│   ├── postgres/               # Database layer
│   │   ├── migrations/
│   │   │   ├── 001_create_items.sql
│   │   │   ├── 002_create_categories.sql
│   │   │   ├── 003_create_item_categories.sql
│   │   │   ├── 004_create_item_attributes.sql
│   │   │   ├── 005_create_item_comments.sql
│   │   │   └── 006_create_item_images.sql
│   │   └── repository.go       # Connection pool tuning
│   └── rabbitmq/               # Message broker
│       ├── publisher.go        # Event publishing
│       └── consumer.go         # Concurrent event consuming
│
├── pkg/
│   ├── config/                 # Configuration management
│   ├── events/                 # Event schemas
│   ├── httperror/              # HTTP error handling
│   └── aws/                    # AWS S3 integration
│
├── docker-compose.yaml         # Multi-service setup with replicas
└── Dockerfile                  # Multi-stage build (api + worker)

Event Flow Diagram

┌───────────────────────────────────────────────────────────┐
│                    Auction Service                        │
├───────────────────────────────────────────────────────────┤
│                                                           │
│  ┌─────────────┐                  ┌─────────────┐         │
│  │ API Service │                  │   Worker    │         │
│  │ (Publisher) │                  │  (Consumer) │         │
│  │             │                  │  x3 replicas│         │
│  │             │                  │  60 workers │         │
│  └──────┬──────┘                  └──────▲──────┘         │
│         │                                │                │
│         │ Publishes item.*               │ Consumes       │
│         │                                │ bid.*          │
└─────────┼────────────────────────────────┼────────────────┘
          │                                │
          ▼                                │
    ┌─────────────┐                        │
    │  RabbitMQ   │                        │
    ├─────────────┤                        │
    │ Exchange:   │                        │
    │ auction.item│──────┐                 │
    │             │      │                 │
    │ Exchange:   │      │                 │
    │ auction.bid │──────┼─────────────────┘
    └─────────────┘      │
                         │
         ┌───────────────┼────────────────┐
         │               │                │
         ▼               ▼                ▼
    ┌─────────┐   ┌─────────────┐   ┌──────────┐
    │ Payment │   │Notification │   │PostgreSQL│
    │ Service │   │  Service    │   │   DB     │
    └─────────┘   └─────────────┘   └──────────┘
                                     45/100 conns

Performance & Scalability

Worker Concurrency Configuration

The worker service is optimized for high-throughput event processing:

// Per replica configuration (cmd/worker/main.go)
ConsumerConfig{
    PrefetchCount:  10,  // Prefetch 10 messages from RabbitMQ
    WorkerPoolSize: 20,  // Process up to 20 messages concurrently
}

// Docker deployment (docker-compose.yaml)
deploy:
    replicas: 3          // 3 worker instances

// Total capacity
// - 60 concurrent workers (3 × 20)
// - 30 messages prefetched (3 × 10)

Database Connection Pool

Tuned for concurrent access (infra/postgres/repository.go):

db.SetMaxOpenConns(15)                    // Max 15 connections per replica
db.SetMaxIdleConns(8)                     // Keep 8 idle in pool
db.SetConnMaxLifetime(5 * time.Minute)    // Recycle every 5 min
db.SetConnMaxIdleTime(2 * time.Minute)    // Close idle after 2 min

// Total DB connections: 3 replicas × 15 = 45 connections
// Safe margin below PostgreSQL default max_connections=100

Monitoring

Connection pool stats are logged every 30 seconds:

INFO  Connection pool stats
  max_open=15
  open=8
  in_use=5
  idle=3
  wait_count=0        ← Should stay 0 (workers never block)
  wait_duration_ms=0

Alert if:

  • wait_count > 0 → Workers are waiting for DB connections, increase MaxOpenConns
  • in_use / max_open > 0.8 → Pool is >80% full, potential bottleneck

Running the Service

Prerequisites

  • Go 1.25+
  • Docker & Docker Compose
  • PostgreSQL
  • RabbitMQ

Development Mode

# Start all services (API + 3 Worker replicas + Postgres)
docker-compose --profile dev up

# Or start individually
docker-compose --profile dev up auction-api-dev
docker-compose --profile dev up auction-worker-dev

# Check running workers
docker-compose ps | grep worker

Production Mode

# Build and start all services
docker-compose up -d

# Services:
# - auction-api: http://localhost:8081
# - auction-worker: 3 replicas (background workers)
# - auction-postgres: localhost:5433

# View worker logs
docker-compose logs -f auction-worker

# Monitor connection pool
docker-compose logs -f auction-worker | grep "pool stats"

Local Development (Without Docker)

1. Start dependencies

docker-compose up auction-postgres

2. Run API service

POSTGRES_HOST=localhost \
POSTGRES_PORT=5433 \
POSTGRES_DATABASE=auction \
POSTGRES_USERNAME=postgres \
POSTGRES_PASSWORD=postgres \
RABBITMQ_URL=amqp://guest:guest@localhost:5672/ \
SERVICE_NAME=auction \
PORT=8080 \
go run cmd/api/main.go

3. Run Worker service

POSTGRES_HOST=localhost \
POSTGRES_PORT=5433 \
POSTGRES_DATABASE=auction \
POSTGRES_USERNAME=postgres \
POSTGRES_PASSWORD=postgres \
RABBITMQ_URL=amqp://guest:guest@localhost:5672/ \
SERVICE_NAME=auction \
go run cmd/worker/main.go

API Endpoints

Public Endpoints (No Authentication Required)

Items:

  • GET /api/v1/items - List all items with pagination and filtering
  • GET /api/v1/items/:id - Get item details by ID
  • GET /api/v1/items/:id/comments - Get all comments for an item
  • GET /api/v1/items/:id/images - Get all images for an item
  • GET /api/v1/items/:itemId/attributes - Get all attributes for an item
  • GET /api/v1/items/:itemId/attributes/:attributeId - Get a specific attribute

Categories:

  • GET /api/v1/categories - List all categories
  • GET /api/v1/categories/:id - Get category details by ID

Private Endpoints (Require X-User-ID header)

Items:

  • POST /api/v1/items - Create new auction item
  • PUT /api/v1/items/:id - Update item details
  • DELETE /api/v1/items/:id - Delete item

Comments:

  • POST /api/v1/items/:id/comments - Add comment to an item
  • DELETE /api/v1/items/:itemId/comments/:commentId - Delete a comment

Images:

  • POST /api/v1/items/:id/images - Upload image to an item (multipart/form-data)
  • DELETE /api/v1/items/:itemId/images/:imageId - Delete an image from an item

Attributes:

  • POST /api/v1/items/:itemId/attributes - Create attributes for an item (bulk)
  • DELETE /api/v1/items/:itemId/attributes/:attributeId - Delete a specific attribute

API Examples

Create Item

curl -X POST http://localhost:8081/api/v1/items \
  -H "Content-Type: application/json" \
  -H "X-User-ID: user-123" \
  -d '{
    "name": "Vintage Camera",
    "description": "Rare 1960s camera",
    "currencyCode": "USD",
    "startPrice": "100.00",
    "bidIncrement": "5.00",
    "startDate": "2024-01-15T10:00:00Z",
    "endDate": "2024-01-20T10:00:00Z",
    "status": "active"
  }'

Get Items with Filtering

# List all active items
curl -X GET "http://localhost:8081/api/v1/items?status=active"

# Get items with pagination
curl -X GET "http://localhost:8081/api/v1/items?page=1&limit=20"

Add Comment to Item

curl -X POST http://localhost:8081/api/v1/items/item-uuid/comments \
  -H "Content-Type: application/json" \
  -H "X-User-ID: user-123" \
  -d '{
    "content": "Is this item still available?"
  }'

Get Categories

curl -X GET http://localhost:8081/api/v1/categories

Upload Item Image

curl -X POST http://localhost:8081/api/v1/items/item-uuid/images \
  -H "X-User-ID: user-123" \
  -F "image=@/path/to/image.jpg"

Delete Item Image

curl -X DELETE http://localhost:8081/api/v1/items/item-uuid/images/image-uuid \
  -H "X-User-ID: user-123"

Create Item Attributes

curl -X POST http://localhost:8081/api/v1/items/item-uuid/attributes \
  -H "Content-Type: application/json" \
  -H "X-User-ID: user-123" \
  -d '{
    "attributes": [
      {
        "key": "brand",
        "value": "Canon"
      },
      {
        "key": "condition",
        "value": "excellent"
      },
      {
        "key": "year",
        "value": "1965"
      }
    ]
  }'

Get Item Attributes

# Get all attributes for an item
curl -X GET http://localhost:8081/api/v1/items/item-uuid/attributes

# Get a specific attribute
curl -X GET http://localhost:8081/api/v1/items/item-uuid/attributes/attribute-uuid

Delete Item Attribute

curl -X DELETE http://localhost:8081/api/v1/items/item-uuid/attributes/attribute-uuid \
  -H "X-User-ID: user-123"

Event Integration

Publishing Events (API Service)

When items and comments are created/updated/deleted, the API service automatically publishes events:

Item Events

// Publishes to: auction.item exchange
// Routing key: item.created.v1
{
  "event": "item.created",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "item-uuid",
    "name": "Vintage Camera",
    "sellerId": "user-123",
    "startPrice": "100.00",
    "currentPrice": "100.00",
    "currencyCode": "USD"
  }
}

Comment Events

// Publishes to: auction.item exchange
// Routing key: item.comment.created.v1
{
  "event": "item.comment.created",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "comment-uuid",
    "itemId": "item-uuid",
    "authorId": "user-123",
    "content": "Is this item still available?",
    "createdAt": "2024-01-15T10:00:00Z"
  }
}

Image Events

// Publishes to: auction.item exchange
// Routing key: item.image.uploaded.v1
{
  "event": "item.image.uploaded",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "image-uuid",
    "itemId": "item-uuid",
    "imageUrl": "https://s3.amazonaws.com/bucket/items/item-uuid/image-uuid.jpg",
    "createdAt": "2024-01-15T10:00:00Z"
  }
}

// Routing key: item.image.deleted.v1
{
  "event": "item.image.deleted",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "image-uuid",
    "itemId": "item-uuid",
    "imageUrl": "https://s3.amazonaws.com/bucket/items/item-uuid/image-uuid.jpg",
    "deletedAt": "2024-01-15T10:00:00Z"
  }
}

Attribute Events

// Publishes to: auction.item exchange
// Routing key: item.attribute.created.v1
{
  "event": "item.attribute.created",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "attribute-uuid",
    "itemId": "item-uuid",
    "key": "brand",
    "value": "Canon",
    "createdAt": "2024-01-15T10:00:00Z"
  }
}

// Routing key: item.attribute.deleted.v1
{
  "event": "item.attribute.deleted",
  "version": "v1",
  "timestamp": "2024-01-15T10:00:00Z",
  "traceId": "trace-uuid",
  "correlationId": "correlation-uuid",
  "payload": {
    "id": "attribute-uuid",
    "itemId": "item-uuid",
    "deletedAt": "2024-01-15T10:00:00Z"
  }
}

Consuming Events (Worker Service)

The worker service listens for events from other services:

// Consumes from: auction.bid exchange
// Routing keys: bid.*.v1 (all bid events)

// Example: bid.placed.v1
{
  "event": "bid.placed",
  "version": "v1",
  "payload": {
    "bidId": "bid-uuid",
    "itemId": "item-uuid",
    "userId": "user-uuid",
    "amount": "150.00",
    "currencyCode": "USD"
  }
}

Event Use Cases

Item Events are consumed by:

  • Payment Service → Process payments when items are sold
  • Notification Service → Notify users about item updates
  • Analytics Service → Track item creation and sales metrics

Comment Events are consumed by:

  • Notification Service → Notify item sellers when new questions are asked
  • Moderation Service → Review comments for inappropriate content
  • Analytics Service → Track user engagement and activity

Image Events are consumed by:

  • CDN Service → Cache and optimize images for delivery
  • Image Processing Service → Generate thumbnails and resize images
  • Moderation Service → Scan images for inappropriate content
  • Analytics Service → Track media uploads and storage metrics

Attribute Events are consumed by:

  • Search Service → Index item attributes for faceted search (filter by brand, condition, etc.)
  • Recommendation Service → Use attributes to find similar items
  • Analytics Service → Track which attributes are most commonly used
  • Data Quality Service → Validate and normalize attribute values

Domain Model

The auction service supports a rich domain model for marketplace items:

Core Entities

Item - The main auction item with pricing and timing information

  • Basic info: name, description, seller ID
  • Pricing: start price, current price, bid increment, currency
  • Timing: start date, end date
  • Status: active, sold, expired, cancelled
  • Buyer info: set when item is sold

Category - Hierarchical classification system for items

  • Supports nested categories (parent-child relationships)
  • Items can belong to multiple categories

ItemAttribute - Custom key-value metadata for items

  • Flexible schema for item-specific properties
  • Examples: brand, condition, size, color, year

ItemComment - User discussions and questions about items

  • User-generated content
  • Timestamped for chronological ordering
  • Supports moderation via deletion

ItemImage - Photo gallery for items

  • Multiple images per item
  • Display order support
  • Image URLs for external storage (AWS S3 / MinIO)
  • Supports PNG and JPEG/JPG formats
  • Maximum file size: 5MB per image

Relationships

Item (1) ←→ (N) ItemCategory ←→ (1) Category
Item (1) ←→ (N) ItemAttribute
Item (1) ←→ (N) ItemComment
Item (1) ←→ (N) ItemImage

Database Migrations

Migrations are automatically applied on startup via Docker docker-entrypoint-initdb.d.

Location: infra/postgres/migrations/

Current migrations:

  • 001_create_items.sql - Creates items table with triggers and indexes
  • 002_create_categories.sql - Creates categories table for item classification
  • 003_create_item_categories.sql - Creates many-to-many relationship between items and categories
  • 004_create_item_attributes.sql - Creates item attributes table for custom metadata
  • 005_create_item_comments.sql - Creates comments table for user discussions
  • 006_create_item_images.sql - Creates images table for item photos

Image Storage (AWS S3 / MinIO)

The auction service supports uploading and managing item images using AWS S3 or MinIO (S3-compatible storage).

Features

  • Multipart Form Upload: Upload images via multipart/form-data with field name image
  • File Validation:
    • Supported formats: PNG, JPEG, JPG
    • Maximum file size: 5MB
    • Content-Type validation
  • Authorization: Only item sellers can upload/delete images for their items
  • Event-Driven: Publishes item.image.uploaded.v1 and item.image.deleted.v1 events
  • URL Construction: Automatic image URL generation for both AWS S3 and MinIO

Storage Structure

Images are stored in the following S3 key pattern:

items/{itemId}/{uuid}.{extension}

Example:
items/abc123-def456/78910-xyz123.jpg

Using MinIO (Development)

MinIO is an S3-compatible object storage server ideal for local development:

# Start MinIO with Docker
docker run -d \
  --name minio \
  -p 9000:9000 \
  -p 9001:9001 \
  -e MINIO_ROOT_USER=minioadmin \
  -e MINIO_ROOT_PASSWORD=minioadmin \
  minio/minio server /data --console-address ":9001"

# Access MinIO Console: http://localhost:9001
# Credentials: minioadmin / minioadmin

Environment configuration for MinIO:

AWS_ENDPOINT=http://localhost:9000
AWS_ACCESS_KEY=minioadmin
AWS_SECRET_KEY=minioadmin
AWS_BUCKET=auction-images

Using AWS S3 (Production)

For production deployment with AWS S3:

  1. Create an S3 bucket (e.g., auction-images-prod)
  2. Configure bucket policy for public read access (optional)
  3. Create IAM user with S3 permissions (s3:PutObject, s3:GetObject, s3:DeleteObject)
  4. Set environment variables:
AWS_ENDPOINT=                              # Leave empty for AWS S3
AWS_ACCESS_KEY=AKIA...                     # IAM access key
AWS_SECRET_KEY=wJal...                     # IAM secret key
AWS_DEFAULT_REGION=eu-central-1            # Your AWS region
AWS_BUCKET=auction-images-prod             # Your bucket name

Image URL Format

MinIO/Custom Endpoint:

http(s)://{AWS_ENDPOINT}/{AWS_BUCKET}/{key}
Example: http://localhost:9000/auction-images/items/abc123/image.jpg

AWS S3:

https://{bucket}.s3.{region}.amazonaws.com/{key}
Example: https://auction-images.s3.eu-central-1.amazonaws.com/items/abc123/image.jpg

Error Handling

The image upload handler includes comprehensive error handling:

  • Missing file: Returns 400 Bad Request if image field is missing
  • File too large: Returns 400 Bad Request if file exceeds 5MB
  • Invalid format: Returns 400 Bad Request if not PNG/JPEG/JPG
  • Unauthorized: Returns 403 Forbidden if user is not the item seller
  • Storage failure: Returns 500 Internal Server Error if S3 upload fails
  • Rollback: Automatically deletes S3 object if database save fails

Configuration

Environment variables (.env):

# Server
PORT=8080
HOST_PORT=8081

# Database
POSTGRES_HOST=auction-postgres
POSTGRES_PORT=5432
POSTGRES_DATABASE=auction
POSTGRES_USERNAME=postgres
POSTGRES_PASSWORD=postgres

# Message Broker
RABBITMQ_URL=amqp://guest:guest@rabbitmq:5672/
SERVICE_NAME=auction

# AWS S3 / MinIO (for image storage)
AWS_ENDPOINT=http://localhost:9000          # MinIO endpoint (leave empty for AWS S3)
AWS_ACCESS_KEY=minioadmin                   # S3 access key
AWS_SECRET_KEY=minioadmin                   # S3 secret key
AWS_DEFAULT_REGION=eu-central-1             # AWS region
AWS_BUCKET=auction-images                   # Bucket name

Monitoring

RabbitMQ Management UI

Health Checks

  • Postgres: docker-compose ps (should show healthy)
  • API: curl http://localhost:8081/api/v1/items
  • Worker: Check logs for "Worker service started successfully"

Connection Pool Monitoring

# Watch pool stats in real-time
docker-compose logs -f auction-worker | grep "pool stats"

# Check PostgreSQL active connections
docker exec -it auction-auction-auction-postgres-1 \
  psql -U postgres -d auction \
  -c "SELECT count(*) FROM pg_stat_activity WHERE datname='auction';"

Production Considerations

Scalability

  • API Service: Scale horizontally (multiple instances behind load balancer)
  • Worker Service: Currently 3 replicas with 20 workers each = 60 concurrent processors
    • Scale up: Increase WorkerPoolSize (more workers per replica)
    • Scale out: Increase replicas (more instances)
  • Database: Connection pool tuned for 45 concurrent connections
    • If scaling workers, adjust MaxOpenConns proportionally
  • RabbitMQ: Cluster for high availability

Reliability

  • Dead Letter Queues: Automatically created for failed event processing
  • Idempotency: Event handlers should be idempotent
  • Graceful Shutdown: Both services handle SIGTERM properly
  • Message Acknowledgment: Manual ACK after successful processing
  • Retry Logic: RabbitMQ handles redelivery of unacknowledged messages

Observability

  • Tracing: All events include traceId and correlationId
  • Logging: Structured logging with Zap
  • Metrics: Connection pool stats, consumer lag monitoring
  • Health: Connection pool wait_count indicates bottlenecks

Concurrency Pattern

The worker uses a semaphore pattern for controlled concurrency:

// infra/rabbitmq/consumer.go
semaphore := make(chan struct{}, workerPoolSize)  // Buffer = pool size

// Acquire slot (blocks if pool full)
semaphore <- struct{}{}

// Process in goroutine
go func(msg amqp.Delivery) {
    defer func() { <-semaphore }()  // Release slot when done
    processMessage(msg)
}(msg)

Benefits:

  • Controlled parallelism: Never exceed workerPoolSize concurrent goroutines
  • Memory safety: Prevents unbounded goroutine creation
  • Backpressure: Blocks RabbitMQ consumption when pool is full

Performance Tuning Guide

Increasing Throughput

If you need to process more events per second:

  1. Increase WorkerPoolSize (more concurrency per replica):

    // cmd/worker/main.go
WorkerPoolSize: 50  // From 20 to 50
    • Also increase MaxOpenConns to at least WorkerPoolSize

  2. Increase Replicas (more instances):

    # docker-compose.yaml
deploy:
  replicas: 5  # From 3 to 5
    • Total workers: 5 × 50 = 250 concurrent processors
    • Total DB conns: 5 × 50 = 250 (may need to increase PostgreSQL max_connections)

  3. Increase PrefetchCount (larger buffer):

    PrefetchCount: 50  // From 10 to 50
    • Only helps if message processing is fast (< 100ms)

Connection Pool Tuning

Formula:

MaxOpenConns ≥ WorkerPoolSize
Total DB Connections = Replicas × MaxOpenConns
Total DB Connections < PostgreSQL max_connections

Example scaling:

5 replicas × 50 workers × 15 conns = 750 potential connections
→ Need to set PostgreSQL max_connections ≥ 800

Note: This documentation was generated and maintained with assistance from Claude Code AI.

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