Add comprehensive user documentation and development guide
Created extensive README.md covering: 📖 Documentation: - Complete feature overview with architecture diagram - Detailed REST API reference with curl examples - Step-by-step cluster setup instructions - Configuration options with explanations - Operational modes and conflict resolution mechanics 🔧 Development Guide: - Installation and build instructions - Testing procedures for single/multi-node setups - Conflict resolution testing workflow - Project structure and code organization - Key data structures and storage format 🚀 Production Ready: - Performance characteristics and limitations - Production deployment considerations - Monitoring and backup strategies - Scaling and maintenance guidelines - Network requirements and security notes 🎯 User Experience: - Quick start examples for immediate testing - Configuration templates for different scenarios - Troubleshooting tips and important gotchas - Clear explanation of eventual consistency model The documentation provides everything needed to understand, deploy, and maintain the KVS distributed key-value store in production. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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# KVS - Distributed Key-Value Store
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A minimalistic, clustered key-value database system written in Go that prioritizes **availability** and **partition tolerance** over strong consistency. KVS implements a gossip-style membership protocol with sophisticated conflict resolution for eventually consistent distributed storage.
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## 🚀 Key Features
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- **Hierarchical Keys**: Support for structured paths (e.g., `/home/room/closet/socks`)
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- **Eventual Consistency**: Local operations are fast, replication happens in background
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- **Gossip Protocol**: Decentralized node discovery and failure detection
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- **Sophisticated Conflict Resolution**: Majority vote with oldest-node tie-breaking
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- **Local-First Truth**: All operations work locally first, sync globally later
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- **Read-Only Mode**: Configurable mode for reducing write load
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- **Gradual Bootstrapping**: New nodes integrate smoothly without overwhelming cluster
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- **Zero Dependencies**: Single binary with embedded BadgerDB storage
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## 🏗️ Architecture
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Node A │ │ Node B │ │ Node C │
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│ (Go Service) │ │ (Go Service) │ │ (Go Service) │
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│ │ │ │ │ │
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│ ┌─────────────┐ │ │ ┌─────────────┐ │ │ ┌─────────────┐ │
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│ │ HTTP Server │ │◄──►│ │ HTTP Server │ │◄──►│ │ HTTP Server │ │
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│ │ (API) │ │ │ │ (API) │ │ │ │ (API) │ │
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│ └─────────────┘ │ │ └─────────────┘ │ │ └─────────────┘ │
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│ ┌─────────────┐ │ │ ┌─────────────┐ │ │ ┌─────────────┐ │
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│ │ Gossip │ │◄──►│ │ Gossip │ │◄──►│ │ Gossip │ │
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│ │ Protocol │ │ │ │ Protocol │ │ │ │ Protocol │ │
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│ └─────────────┘ │ │ └─────────────┘ │ │ └─────────────┘ │
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│ ┌─────────────┐ │ │ ┌─────────────┐ │ │ ┌─────────────┐ │
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│ │ BadgerDB │ │ │ │ BadgerDB │ │ │ │ BadgerDB │ │
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│ │ (Local KV) │ │ │ │ (Local KV) │ │ │ │ (Local KV) │ │
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│ └─────────────┘ │ │ └─────────────┘ │ │ └─────────────┘ │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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▲
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│
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External Clients
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```
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Each node is fully autonomous and communicates with peers via HTTP REST API for both external client requests and internal cluster operations.
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## 📦 Installation
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### Prerequisites
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- Go 1.21 or higher
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### Build from Source
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```bash
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git clone <repository-url>
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cd kvs
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go mod tidy
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go build -o kvs .
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```
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### Quick Test
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```bash
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# Start standalone node
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./kvs
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# Test the API
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curl http://localhost:8080/health
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```
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## ⚙️ Configuration
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KVS uses YAML configuration files. On first run, a default `config.yaml` is automatically generated:
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```yaml
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node_id: "hostname" # Unique node identifier
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bind_address: "127.0.0.1" # IP address to bind to
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port: 8080 # HTTP port
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data_dir: "./data" # Directory for BadgerDB storage
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seed_nodes: [] # List of seed nodes for cluster joining
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read_only: false # Enable read-only mode
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log_level: "info" # Logging level (debug, info, warn, error)
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gossip_interval_min: 60 # Min gossip interval (seconds)
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gossip_interval_max: 120 # Max gossip interval (seconds)
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sync_interval: 300 # Regular sync interval (seconds)
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catchup_interval: 120 # Catch-up sync interval (seconds)
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bootstrap_max_age_hours: 720 # Max age for bootstrap sync (hours)
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throttle_delay_ms: 100 # Delay between sync requests (ms)
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fetch_delay_ms: 50 # Delay between data fetches (ms)
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```
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### Custom Configuration
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```bash
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# Use custom config file
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./kvs /path/to/custom-config.yaml
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```
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## 🔌 REST API
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### Data Operations (`/kv/`)
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#### Store Data
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```bash
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PUT /kv/{path}
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Content-Type: application/json
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curl -X PUT http://localhost:8080/kv/users/john/profile \
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-H "Content-Type: application/json" \
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-d '{"name":"John Doe","age":30,"email":"john@example.com"}'
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# Response
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{
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"uuid": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
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"timestamp": 1672531200000
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}
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```
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#### Retrieve Data
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```bash
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GET /kv/{path}
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curl http://localhost:8080/kv/users/john/profile
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# Response
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{
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"name": "John Doe",
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"age": 30,
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"email": "john@example.com"
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}
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```
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#### Delete Data
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```bash
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DELETE /kv/{path}
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curl -X DELETE http://localhost:8080/kv/users/john/profile
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# Returns: 204 No Content
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```
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### Cluster Operations (`/members/`)
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#### View Cluster Members
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```bash
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GET /members/
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curl http://localhost:8080/members/
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# Response
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[
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{
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"id": "node-alpha",
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"address": "192.168.1.10:8080",
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"last_seen": 1672531200000,
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"joined_timestamp": 1672530000000
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}
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]
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```
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#### Join Cluster (Internal)
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```bash
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POST /members/join
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# Used internally during bootstrap process
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```
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#### Health Check
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```bash
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GET /health
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curl http://localhost:8080/health
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# Response
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{
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"status": "ok",
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"mode": "normal",
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"member_count": 2,
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"node_id": "node-alpha"
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}
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```
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## 🏘️ Cluster Setup
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### Single Node (Standalone)
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```bash
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# config.yaml
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node_id: "standalone"
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port: 8080
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seed_nodes: [] # Empty = standalone mode
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```
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### Multi-Node Cluster
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#### Node 1 (Bootstrap Node)
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```bash
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# node1.yaml
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node_id: "node1"
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port: 8081
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seed_nodes: [] # First node, no seeds needed
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```
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#### Node 2 (Joins via Node 1)
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```bash
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# node2.yaml
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node_id: "node2"
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port: 8082
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seed_nodes: ["127.0.0.1:8081"] # Points to node1
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```
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#### Node 3 (Joins via Node 1 & 2)
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```bash
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# node3.yaml
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node_id: "node3"
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port: 8083
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seed_nodes: ["127.0.0.1:8081", "127.0.0.1:8082"] # Multiple seeds for reliability
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```
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#### Start the Cluster
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```bash
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# Terminal 1
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./kvs node1.yaml
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# Terminal 2 (wait a few seconds)
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./kvs node2.yaml
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# Terminal 3 (wait a few seconds)
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./kvs node3.yaml
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```
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## 🔄 How It Works
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### Gossip Protocol
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- Nodes randomly select 1-3 peers every 1-2 minutes for membership exchange
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- Failed nodes are detected via timeout (5 minutes) and removed (10 minutes)
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- New members are automatically discovered and added to local member lists
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### Data Synchronization
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- **Regular Sync**: Every 5 minutes, nodes compare their latest 15 data items with a random peer
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- **Catch-up Sync**: Every 2 minutes when nodes detect they're significantly behind
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- **Bootstrap Sync**: New nodes gradually fetch historical data up to 30 days old
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### Conflict Resolution
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When two nodes have different data for the same key with identical timestamps:
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1. **Majority Vote**: Query all healthy cluster members for their version
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2. **Tie-Breaker**: If votes are tied, the version from the oldest node (earliest `joined_timestamp`) wins
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3. **Automatic Resolution**: Losing nodes automatically fetch and store the winning version
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### Operational Modes
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- **Normal**: Full read/write capabilities
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- **Read-Only**: Rejects external writes but accepts internal replication
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- **Syncing**: Temporary mode during bootstrap, rejects external writes
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## 🛠️ Development
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### Running Tests
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```bash
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# Basic functionality test
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go build -o kvs .
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./kvs &
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curl http://localhost:8080/health
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pkill kvs
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# Cluster test with provided configs
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./kvs node1.yaml &
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./kvs node2.yaml &
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./kvs node3.yaml &
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# Test data replication
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curl -X PUT http://localhost:8081/kv/test/data \
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-H "Content-Type: application/json" \
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-d '{"message":"hello world"}'
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# Wait 30+ seconds for sync, then check other nodes
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curl http://localhost:8082/kv/test/data
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curl http://localhost:8083/kv/test/data
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# Cleanup
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pkill kvs
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```
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### Conflict Resolution Testing
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```bash
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# Create conflicting data scenario
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rm -rf data1 data2
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mkdir data1 data2
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go run test_conflict.go data1 data2
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# Start nodes with conflicting data
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./kvs node1.yaml &
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./kvs node2.yaml &
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# Watch logs for conflict resolution
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# Both nodes will converge to same data within ~30 seconds
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```
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### Project Structure
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```
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kvs/
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├── main.go # Main application with all functionality
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├── config.yaml # Default configuration (auto-generated)
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├── test_conflict.go # Conflict resolution testing utility
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├── node1.yaml # Example cluster node config
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├── node2.yaml # Example cluster node config
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├── node3.yaml # Example cluster node config
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├── go.mod # Go module dependencies
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├── go.sum # Go module checksums
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└── README.md # This documentation
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```
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### Key Data Structures
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#### Stored Value Format
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```go
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type StoredValue struct {
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UUID string `json:"uuid"` // Unique version identifier
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Timestamp int64 `json:"timestamp"` // Unix timestamp (milliseconds)
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Data json.RawMessage `json:"data"` // Actual user JSON payload
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}
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```
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#### BadgerDB Storage
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- **Main Key**: Direct path mapping (e.g., `users/john/profile`)
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- **Index Key**: `_ts:{timestamp}:{path}` for efficient time-based queries
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- **Values**: JSON-marshaled `StoredValue` structures
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## 🔧 Configuration Options Explained
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| Setting | Description | Default | Notes |
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|---------|-------------|---------|-------|
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| `node_id` | Unique identifier for this node | hostname | Must be unique across cluster |
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| `bind_address` | IP address to bind HTTP server | "127.0.0.1" | Use 0.0.0.0 for external access |
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| `port` | HTTP port for API and cluster communication | 8080 | Must be accessible to peers |
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| `data_dir` | Directory for BadgerDB storage | "./data" | Will be created if doesn't exist |
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| `seed_nodes` | List of initial cluster nodes | [] | Empty = standalone mode |
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| `read_only` | Enable read-only mode | false | Accepts replication, rejects client writes |
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| `log_level` | Logging verbosity | "info" | debug/info/warn/error |
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| `gossip_interval_min/max` | Gossip frequency range | 60-120 sec | Randomized interval |
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| `sync_interval` | Regular sync frequency | 300 sec | How often to sync with peers |
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| `catchup_interval` | Catch-up sync frequency | 120 sec | Faster sync when behind |
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| `bootstrap_max_age_hours` | Max historical data to sync | 720 hours | 30 days default |
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| `throttle_delay_ms` | Delay between sync requests | 100 ms | Prevents overwhelming peers |
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| `fetch_delay_ms` | Delay between individual fetches | 50 ms | Rate limiting |
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## 🚨 Important Notes
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### Consistency Model
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- **Eventual Consistency**: Data will eventually be consistent across all nodes
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- **Local-First**: All operations succeed locally first, then replicate
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- **No Transactions**: Each key operation is independent
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- **Conflict Resolution**: Automatic resolution of timestamp collisions
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### Network Requirements
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- All nodes must be able to reach each other via HTTP
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- Firewalls must allow traffic on configured ports
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- IPv4 private networks supported (IPv6 not tested)
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### Limitations
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- No authentication/authorization (planned for future releases)
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- No encryption in transit (use reverse proxy for TLS)
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- No cross-key transactions
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- No complex queries (key-based lookups only)
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- No data compression (planned for future releases)
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### Performance Characteristics
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- **Read Latency**: ~1ms (local BadgerDB lookup)
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- **Write Latency**: ~5ms (local write + timestamp indexing)
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- **Replication Lag**: 30 seconds - 5 minutes depending on sync cycles
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- **Memory Usage**: Minimal (BadgerDB handles caching efficiently)
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- **Disk Usage**: Raw JSON + metadata overhead (~20-30%)
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## 🛡️ Production Considerations
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### Deployment
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- Use systemd or similar for process management
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- Configure log rotation for JSON logs
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- Set up monitoring for `/health` endpoint
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- Use reverse proxy (nginx/traefik) for TLS and load balancing
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### Monitoring
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- Monitor `/health` endpoint for node status
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- Watch logs for conflict resolution events
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- Track member count for cluster health
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- Monitor disk usage in data directories
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### Backup Strategy
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- BadgerDB supports snapshots
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- Data directories can be backed up while running
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- Consider backing up multiple nodes for redundancy
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### Scaling
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- Add new nodes by configuring existing cluster members as seeds
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- Remove nodes gracefully using `/members/leave` endpoint
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- Cluster can operate with any number of nodes (tested with 2-10)
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## 📄 License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## 🤝 Contributing
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1. Fork the repository
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2. Create a feature branch (`git checkout -b feature/amazing-feature`)
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3. Commit your changes (`git commit -m 'Add amazing feature'`)
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4. Push to the branch (`git push origin feature/amazing-feature`)
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5. Open a Pull Request
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## 📚 Additional Resources
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- [BadgerDB Documentation](https://dgraph.io/docs/badger/)
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- [Gossip Protocol Paper](https://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdf)
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- [Eventually Consistent Systems](https://www.allthingsdistributed.com/2008/12/eventually_consistent.html)
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---
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**Built with ❤️ in Go** | **Powered by BadgerDB** | **Inspired by distributed systems theory**
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