Key-Value Cache Service

A high-performance in-memory key-value cache service with HTTP API, implemented in Go and containerized with Docker.

Overview

This project implements an in-memory Key-Value Cache service that handles basic operations:

• PUT: Insert or update a key-value pair
• GET: Retrieve a value for a given key

The service is optimized for performance under high load and is designed to run within resource constraints (2 core, 2 GB RAM).

Features

• Fast in-memory storage with O(1) access time
• LRU (Least Recently Used) cache eviction strategy
• Thread-safe concurrent operations
• RESTful HTTP API interface
• Containerized with Docker for easy deployment
• Memory-efficient design to prevent Out-of-Memory errors

API Endpoints

PUT Operation

• HTTP Method: POST
• Endpoint: /put
• Request Format:

  {
    "key": "string (max 256 characters)",
    "value": "string (max 256 characters)"
  }

• Response Format:

  {
    "status": "OK",
    "message": "Key inserted/updated successfully."
  }

GET Operation

• HTTP Method: GET
• Endpoint: /get
• Query Parameter: key
• Example: /get?key=exampleKey
• Response Format (success):

  {
    "status": "OK",
    "key": "exampleKey",
    "value": "the corresponding value"
  }

• Response Format (key not found):

  {
    "status": "ERROR",
    "message": "Key not found."
  }

Technical Design

Architecture

The project follows a clean architecture approach with the following components:

• Cache: Core in-memory storage with LRU eviction
• API: HTTP server with request validation and response formatting
• Docker: Containerization for consistent deployments

Getting Started

Prerequisites

• Docker

Running the Service

The service is available as a Docker image on Docker Hub:

# Pull the image
docker pull charanbhatia/key-value-cache:latest

# Run the container
docker run -d -p 7171:7171 charanbhatia/key-value-cache:latest

The service will be available at http://localhost:7171

Building from Source

# Clone the repository
git clone https://github.com/charanbhatia/key-value-redis-cache.git
cd key-value-redis-cache

# Build Docker image
docker build -t key-value-cache .

# Run container
docker run -d -p 7171:7171 key-value-cache

Testing the Service

# Test PUT operation
curl -X POST http://localhost:7171/put \
  -H "Content-Type: application/json" \
  -d '{"key":"test-key","value":"test-value"}'

# Test GET operation
curl http://localhost:7171/get?key=test-key

Vercel live link: https://key-value-redis-cache-1i57.vercel.app/home

Performance Considerations

• The service is optimized for a balanced mix of GET and PUT operations
• LRU eviction ensures optimal memory usage under high load
• The service maintains low-latency responses even at high request volumes
• Designed to handle thousands of concurrent connections