ecom-log-generator - A lightweight Docker image that generates random eCommerce-style logs for testing logging tools. Simulates operations like signups, orders, logins, and cart actions with realistic JSON-formatted output. Perfect for validating log collection, parsing, and monitoring setups in containerized environments.

Note: This is only for testing purposes. Do not use it for long periods to avoid unnecessary log storage costs.

The Docker image is available at: quay.io/prateekjain/ecom-log-generator. You can pull and run it directly without building locally, unless you want to modify the code.

Overview

This repository contains a Dockerized application that generates random eCommerce-style logs, designed for testing and validating logging tools. It simulates common eCommerce operations such as user signups, order processing, logins, and cart actions, producing JSON-formatted logs with realistic data. The image is lightweight and intended for general-purpose use in testing log collection, parsing, and monitoring pipelines.

Features

• Generates random logs for:
  • User signups
  • Order processing (success/failure with error messages)
  • Login attempts
  • Cart operations (add/remove/update)
• JSON-formatted output with timestamps, request IDs, and operation details
• Logs written to both stdout (for tools like CloudWatch) and a file (/var/log/ecom_logs.log)
• Configurable via environment variables
• Runs indefinitely, simulating continuous application activity

Use Case

This Docker image is built for testing logging tools and setups. Whether you're validating a log aggregator, testing a monitoring dashboard, or debugging a log ingestion pipeline, this generator provides a steady stream of realistic eCommerce logs. It's particularly useful for:

• Verifying log collection and ingestion
• Testing log parsing rules in tools like ELK, Splunk, or Datadog
• Simulating application behavior for load testing logging infrastructure

Prerequisites

• Docker installed locally
• A logging tool/system to test (e.g., CloudWatch, ELK, etc.)

Getting Started

Pull the Image from Quay.io

Run the container directly from the registry:

docker run -v /path/to/local/logs:/var/log quay.io/prateekjain/ecom-log-generator

Building the Image (only if you want to modify it)

1. Clone this repository:

   git clone https://github.com/prateekjaindev/ecom-log-generator.git
   cd ecom-log-generator

2. Build the Docker image:

   docker build -t ecom-log-generator .

Running Locally

Run the container to start generating logs:

docker run -v /path/to/local/logs:/var/log ecom-log-generator

Logs will be printed to stdout and written to /var/log/ecom_logs.log in the mounted volume.

Use Ctrl+C to stop the container.

Sample Log Output

{
  "timestamp": "2025-03-30T10:15:23.456789",
  "request_id": "550e8400-e29b-41d4-a716-446655440000",
  "user_id": "user_42",
  "service": "ecom-api",
  "operation": "order",
  "status": "success",
  "duration_ms": 845,
  "order_id": "123e4567-e89b-12d3-a456-426614174000",
  "items": [
    {
      "product": "Laptop",
      "quantity": 1,
      "price": 129.99
    }
  ],
  "total": 129.99
}

Testing with a Logging Tool

Local Testing

Pipe the output to your logging tool or monitor the log file:

docker run quay.io/prateekjain/ecom-log-generator | your-logging-tool --input stdin

Remote Deployment

Tag and push the image to your own container registry (if needed):

docker tag quay.io/prateekjain/ecom-log-generator:latest [your-registry]/ecom-log-generator:latest
docker push [your-registry]/ecom-log-generator:latest

Deploy in any container orchestration environment with appropriate logging configuration to collect and process the logs.

Configuration

You can customize the log output by setting environment variables:

• LOG_FILE: Path to the log file inside the container (default: /var/log/ecom_logs.log)

Example with custom log file:

docker run -e LOG_FILE=/var/log/custom.log -v /path/to/local/logs:/var/log quay.io/prateekjain/ecom-log-generator

Notes

• The generator runs indefinitely until stopped, making it suitable for long-running tests.
• Log frequency is randomized (0.1-2 seconds between events) to mimic real application behavior.
• Mount a volume to persist logs if needed for analysis.

License

MIT License (LICENSE) - feel free to use and modify for your testing needs!