zephyr 🚀

A high-performance, Redis-compatible distributed cache system built in Go. zephyr provides horizontal scalability, high availability, and advanced caching features for modern applications.

✨ Features

Core Functionality

• Redis-Compatible Protocol: Drop-in replacement for Redis clients
• High Performance: Sub-millisecond response times with concurrent request handling
• Memory Efficient: Advanced eviction policies (LRU, LFU, TTL-based)
• Thread-Safe: Optimized concurrent access with minimal lock contention

Distributed Systems

• Consistent Hashing: Automatic data distribution across cluster nodes
• High Availability: Master-slave replication with automatic failover
• Horizontal Scaling: Add/remove nodes without downtime
• Data Partitioning: Intelligent key distribution for optimal performance

Advanced Features

• Pub/Sub Messaging: Real-time message broadcasting
• Transactions: ACID transaction support with MULTI/EXEC
• Lua Scripting: Server-side script execution
• Persistence: WAL and snapshot-based durability
• Monitoring: Built-in metrics and health checks

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   zephyr Node  │    │   zephyr Node  │    │   zephyr Node  │
│                 │    │                 │    │                 │
│  ┌───────────┐  │    │  ┌───────────┐  │    │  ┌───────────┐  │
│  │   Cache   │  │◄──►│  │   Cache   │  │◄──►│  │   Cache   │  │
│  │  Engine   │  │    │  │  Engine   │  │    │  │  Engine   │  │
│  └───────────┘  │    │  └───────────┘  │    │  └───────────┘  │
│                 │    │                 │    │                 │
│  ┌───────────┐  │    │  ┌───────────┐  │    │  ┌───────────┐  │
│  │    WAL    │  │    │  │    WAL    │  │    │  │    WAL    │  │
│  └───────────┘  │    │  └───────────┘  │    │  └───────────┘  │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         └───────────────────────┼───────────────────────┘
                                 │
                    ┌─────────────────┐
                    │  Consistent     │
                    │  Hash Ring      │
                    └─────────────────┘

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/yourname/zephyr.git
cd zephyr

# Build the binary
go build -o zephyr cmd/server/main.go

# Or install directly
go install github.com/yourname/zephyr/cmd/server@latest

Docker

# Run single node
docker run -p 6379:6379 zephyr/zephyr:latest

# Run with custom configuration
docker run -p 6379:6379 -v $(pwd)/config.yaml:/etc/zephyr/config.yaml zephyr/zephyr:latest

Basic Usage

# Start a single node
./zephyr --port 6379

# Start a cluster node
./zephyr --port 6379 --cluster --node-id node1 --peers node2:6380,node3:6381

Client Examples

Go Client:

import "github.com/go-redis/redis/v8"

client := redis.NewClient(&redis.Options{
    Addr: "localhost:6379",
})

// Set a key with TTL
client.Set(ctx, "mykey", "myvalue", time.Minute)

// Get a key
val, err := client.Get(ctx, "mykey").Result()

Python Client:

import redis

r = redis.Redis(host='localhost', port=6379)
r.set('mykey', 'myvalue', ex=60)  # 60 second TTL
value = r.get('mykey')

Node.js Client:

const redis = require('redis');
const client = redis.createClient({ host: 'localhost', port: 6379 });

await client.setEx('mykey', 60, 'myvalue');  // 60 second TTL
const value = await client.get('mykey');

⚙️ Configuration

config.yaml

server:
  port: 6379
  bind: "0.0.0.0"
  max_connections: 10000
  tcp_keepalive: true
  timeout: 30s

cluster:
  enabled: true
  node_id: "node1"
  peers:
    - "node2:6380"
    - "node3:6381"
  replication_factor: 2

cache:
  max_memory: "2GB"
  eviction_policy: "allkeys-lru"  # noeviction, allkeys-lru, allkeys-lfu, volatile-lru, volatile-lfu, volatile-ttl
  default_ttl: "1h"

persistence:
  enable_wal: true
  wal_dir: "./data/wal"
  snapshot_enabled: true
  snapshot_interval: "5m"
  snapshot_dir: "./data/snapshots"

monitoring:
  enable_metrics: true
  metrics_port: 8080
  health_check_interval: "10s"
  
logging:
  level: "info"  # debug, info, warn, error
  format: "json"
  file: "./logs/zephyr.log"

Environment Variables

zephyr_PORT=6379
zephyr_MAX_MEMORY=2GB
zephyr_CLUSTER_ENABLED=true
zephyr_NODE_ID=node1
zephyr_PEERS=node2:6380,node3:6381

🛠️ Supported Commands

String Operations

• GET key - Get value
• SET key value [EX seconds] - Set value with optional TTL
• DEL key [key ...] - Delete keys
• EXISTS key [key ...] - Check if keys exist
• EXPIRE key seconds - Set TTL
• TTL key - Get TTL
• INCR key - Increment integer value
• DECR key - Decrement integer value

Hash Operations

• HSET key field value - Set hash field
• HGET key field - Get hash field
• HDEL key field [field ...] - Delete hash fields
• HGETALL key - Get all hash fields

List Operations

• LPUSH key value [value ...] - Push to head
• RPUSH key value [value ...] - Push to tail
• LPOP key - Pop from head
• RPOP key - Pop from tail
• LLEN key - Get list length

Set Operations

• SADD key member [member ...] - Add to set
• SREM key member [member ...] - Remove from set
• SMEMBERS key - Get all members
• SISMEMBER key member - Check membership

Pub/Sub

• PUBLISH channel message - Publish message
• SUBSCRIBE channel [channel ...] - Subscribe to channels
• UNSUBSCRIBE [channel ...] - Unsubscribe

Transactions

• MULTI - Start transaction
• EXEC - Execute transaction
• DISCARD - Discard transaction
• WATCH key [key ...] - Watch keys for changes

Server Commands

• PING [message] - Ping server
• INFO [section] - Get server info
• FLUSHDB - Clear current database
• FLUSHALL - Clear all databases

📊 Performance

Benchmarks

Single Node Performance (Intel i7-10700K, 32GB RAM):

SET: 180,000 ops/sec
GET: 220,000 ops/sec
Mixed (50/50): 200,000 ops/sec

Cluster Performance (3 nodes):

SET: 450,000 ops/sec
GET: 580,000 ops/sec
Mixed (50/50): 520,000 ops/sec

Memory Usage:

• ~40 bytes overhead per key-value pair
• Efficient memory pooling reduces GC pressure
• Configurable eviction policies prevent OOM

Scaling Characteristics

Nodes	Throughput	Latency (p99)
1	200K ops/s	0.8ms
3	520K ops/s	1.2ms
5	780K ops/s	1.8ms
10	1.2M ops/s	2.5ms

🧪 Testing

Running Tests

# Unit tests
go test ./...

# Integration tests
go test -tags=integration ./...

# Benchmark tests
go test -bench=. ./...

# Coverage report
go test -coverprofile=coverage.out ./...
go tool cover -html=coverage.out

Load Testing

# Install redis-benchmark
apt-get install redis-tools

# Basic load test
redis-benchmark -h localhost -p 6379 -c 100 -n 100000

# Mixed workload test
redis-benchmark -h localhost -p 6379 -c 100 -n 100000 -t set,get --ratio 1:3

🔧 Development

Project Structure

.
├── cmd/
│   └── server/          # Server entry point
├── internal/
│   ├── cache/           # Core cache engine
│   ├── cluster/         # Clustering logic
│   ├── config/          # Configuration management
│   ├── consistent/      # Consistent hashing
│   ├── persistence/     # WAL and snapshots
│   ├── protocol/        # RESP protocol
│   ├── pubsub/          # Pub/Sub system
│   ├── replication/     # Replication logic
│   └── server/          # HTTP/TCP servers
├── pkg/
│   └── client/          # Go client library
├── deployments/
│   ├── docker/          # Docker files
│   └── k8s/             # Kubernetes manifests
├── docs/                # Documentation
├── scripts/             # Build and deployment scripts
└── tests/               # Integration tests

Building from Source

# Development build
make build

# Production build with optimizations
make build-prod

# Cross-compile for multiple platforms
make build-all

# Run linting
make lint

# Run all tests
make test

# Generate documentation
make docs

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Run the test suite (make test)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

Please read CONTRIBUTING.md for detailed guidelines.

📈 Monitoring

Metrics Endpoint

zephyr exposes Prometheus-compatible metrics at /metrics:

curl http://localhost:8080/metrics

Key Metrics:

• zephyr_ops_total - Total operations by type
• zephyr_ops_duration_seconds - Operation latency histograms
• zephyr_memory_usage_bytes - Memory usage by component
• zephyr_connections_active - Active client connections
• zephyr_cluster_nodes_up - Number of healthy cluster nodes
• zephyr_replication_lag_seconds - Replication lag

Health Checks

# Basic health check
curl http://localhost:8080/health

# Detailed status
curl http://localhost:8080/status

Grafana Dashboard

Import the provided Grafana dashboard for comprehensive monitoring.

🐳 Deployment

Docker Compose

version: '3.8'
services:
  zephyr-1:
    image: zephyr/zephyr:latest
    ports:
      - "6379:6379"
      - "8080:8080"
    environment:
      - zephyr_NODE_ID=node1
      - zephyr_CLUSTER_ENABLED=true
      - zephyr_PEERS=zephyr-2:6379,zephyr-3:6379
    volumes:
      - ./data/node1:/data

  zephyr-2:
    image: zephyr/zephyr:latest
    ports:
      - "6380:6379"
      - "8081:8080"
    environment:
      - zephyr_NODE_ID=node2
      - zephyr_CLUSTER_ENABLED=true
      - zephyr_PEERS=zephyr-1:6379,zephyr-3:6379
    volumes:
      - ./data/node2:/data

  zephyr-3:
    image: zephyr/zephyr:latest
    ports:
      - "6381:6379"
      - "8082:8080"
    environment:
      - zephyr_NODE_ID=node3
      - zephyr_CLUSTER_ENABLED=true
      - zephyr_PEERS=zephyr-1:6379,zephyr-2:6379
    volumes:
      - ./data/node3:/data

Kubernetes

# Deploy to Kubernetes
kubectl apply -f deployments/k8s/

# Scale the cluster
kubectl scale statefulset zephyr --replicas=5

# Check status
kubectl get pods -l app=zephyr

Helm Chart

# Add repository
helm repo add zephyr https://charts.zephyr.io

# Install
helm install my-cache zephyr/zephyr \
  --set cluster.enabled=true \
  --set cluster.replicas=3 \
  --set resources.memory=2Gi

🔒 Security

• TLS Encryption: Enable TLS for client connections and inter-node communication
• Authentication: Support for password-based and certificate-based auth
• Network Security: Configurable bind addresses and firewall rules
• Data Encryption: Optional encryption at rest for persistent data

security:
  tls:
    enabled: true
    cert_file: "/etc/ssl/certs/zephyr.crt"
    key_file: "/etc/ssl/private/zephyr.key"
  auth:
    enabled: true
    password: "your-secure-password"
  encryption:
    at_rest: true
    algorithm: "AES-256-GCM"

🐛 Troubleshooting

Common Issues

High Memory Usage:

• Check eviction policy configuration
• Monitor key distribution across nodes
• Verify TTL settings are appropriate

Connection Issues:

• Verify firewall rules allow traffic on configured ports
• Check cluster peer connectivity
• Review network latency between nodes

Performance Degradation:

• Monitor GC pressure with GOGC tuning
• Check disk I/O for persistence operations
• Review client connection pooling

Debug Mode

# Enable debug logging
./zephyr --log-level debug

# Enable profiling
./zephyr --pprof --pprof-port 6060

# View profiles
go tool pprof http://localhost:6060/debug/pprof/profile

📚 Documentation

• Architecture Guide
• Configuration Reference
• API Documentation
• Cluster Setup Guide
• Performance Tuning
• Migration Guide

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Community

• Discord: Join our Discord server
• GitHub Discussions: Community discussions
• Stack Overflow: Tag your questions with zephyr
• Twitter: @zephyr_db

🙏 Acknowledgments

• Redis team for the excellent protocol design
• Go community for amazing concurrent programming primitives
• All contributors who helped make this project better

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zephyr - Built with ❤️ in Go