Service Upload Performance Comparison

Project Overview

This project is a comprehensive performance benchmark of file upload and processing services implemented in three different programming languages: Go, Rust, and Python.

Objective

The primary goal is to compare and analyze the performance characteristics of each language implementation for a common file upload and processing task.

Service Workflow

1. File Upload Endpoint

   • Expose a REST API endpoint for file uploads
   • Accept ZIP files containing JSON data

2. File Handling

   • Receive uploaded file
   • Save file to a temporary directory
   • Unzip the uploaded file
   • Extract and process JSON files

Implementation Languages

1. Go (Golang)

• Web Framework: Gin
• Performance-oriented implementation
• Concurrent processing
• Structured logging

2. Rust

• Web Framework: Actix Web
• Zero-cost abstractions
• High performance and memory safety
• Efficient JSON processing

3. Python

• Web Framework: FastAPI
• Async processing
• Type hints and validation
• Modern Python async capabilities

Performance Metrics

Each implementation will be evaluated on:

• Request Throughput
• Memory Usage
• CPU Utilization
• Latency
• Concurrency Handling

Benchmarking Methodology

• Consistent test dataset
• Identical hardware/environment
• Multiple test runs
• Metrics collected using:
  • Profiling tools
  • System monitoring
  • Detailed logging

Running Benchmarks

Prerequisites

• Docker
• Docker Compose
• Performance monitoring tools

Benchmark Steps

1. Prepare test data
2. Run each service
3. Execute load tests
4. Collect and analyze performance data

Example Benchmark Command

docker-compose up -d
./run-benchmarks.sh