Redis Cluster & Valkey Support

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📋 Overview

Add comprehensive support for Redis Cluster and Valkey to enable high-availability, horizontal scaling, and Redis-compatible alternatives in DBX.

🎯 Goals

• Redis Cluster Support: Enable horizontal scaling with automatic sharding and failover
• Valkey Support: Provide Redis-compatible alternative with enhanced performance
• Backward Compatibility: Maintain existing single-node Redis functionality
• Performance: Optimize for distributed operations and high throughput
• Developer Experience: Seamless migration path and enhanced SDK support

🔍 Current State Analysis

Existing Architecture

• Single Redis connection via redis-rs crate (v0.23)
• Connection pooling with RedisPool
• HTTP/WebSocket APIs that proxy to Redis
• TypeScript SDK with native bindings
• Basic configuration via DBX_DATABASE_URL

Limitations

• No cluster-aware routing
• Single point of failure
• No horizontal scaling capability
• Limited to single Redis instance
• No support for Redis-compatible alternatives

🏗️ Proposed Architecture

1. Enhanced Connection Management

pub enum RedisConnectionType {
    Single(RedisPool),
    Cluster(RedisClusterPool),
    Valkey(RedisPool), // Valkey uses same protocol as Redis
}

pub struct RedisClusterPool {
    nodes: Vec<String>,
    cluster_client: Arc<redis::cluster::ClusterClient>,
    pool_size: u32,
    read_from_replicas: bool,
}

2. Configuration Extensions

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Config {
    pub database_url: String,
    pub database_type: DatabaseType,
    pub cluster_config: Option<ClusterConfig>,
    pub host: String,
    pub port: u16,
    pub pool_size: u32,
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ClusterConfig {
    pub nodes: Vec<String>,
    pub read_from_replicas: bool,
    pub max_retries: u32,
    pub retry_delay_ms: u64,
    pub enable_cross_slot_operations: bool,
}

3. Key Distribution Strategy

pub trait KeyDistributor {
    fn get_target_node(&self, key: &str) -> String;
    fn get_all_nodes(&self) -> Vec<String>;
    fn handle_key_redistribution(&self, key: &str) -> Result<()>;
}

pub struct ConsistentHashDistributor {
    ring: Vec<(u32, String)>, // hash -> node
    virtual_nodes: u32,
}

📋 Implementation Plan

Phase 1: Foundation (Week 1-2)

1.1 Configuration System Enhancement

• Extend DatabaseType enum to include RedisCluster and Valkey
• Add ClusterConfig struct for cluster-specific settings
• Update environment variable parsing
• Add configuration validation

Environment Variables:

# Single Redis (existing)
DBX_DATABASE_URL=redis://localhost:6379

# Redis Cluster
DBX_DATABASE_TYPE=redis-cluster
DBX_CLUSTER_NODES=node1:6379,node2:6379,node3:6379
DBX_CLUSTER_READ_FROM_REPLICAS=true
DBX_CLUSTER_MAX_RETRIES=3
DBX_CLUSTER_RETRY_DELAY_MS=100

# Valkey
DBX_DATABASE_TYPE=valkey
DBX_DATABASE_URL=valkey://localhost:6379

1.2 Connection Factory Implementation

• Create ConnectionFactory trait and implementation
• Implement connection creation for different database types
• Add connection health checking
• Implement connection pooling per node for clusters

1.3 Error Handling Framework

• Define cluster-specific error types
• Implement retry logic with exponential backoff
• Add failover handling
• Create error reporting and monitoring

Phase 2: Cluster Implementation (Week 3-4)

2.1 Cluster Client Wrapper

• Implement RedisClusterPool struct
• Add cluster node discovery and management
• Implement connection pooling per cluster node
• Add cluster topology monitoring

2.2 Key Routing Logic

• Implement KeyDistributor trait
• Create ConsistentHashDistributor for even key distribution
• Add cross-slot operation handling
• Implement key redistribution on cluster changes

2.3 Cluster Operations

• Add cluster-specific admin operations
• Implement cluster info and node management
• Add cluster health monitoring
• Implement cluster failover detection

Phase 3: API Layer Updates (Week 5-6)

3.1 Route Handler Updates

• Update existing route handlers to be cluster-aware
• Add cluster-specific endpoints under /cluster/ prefix
• Implement cross-node operation handling
• Add cluster metrics and monitoring endpoints

3.2 WebSocket Support

• Extend WebSocket connections for cluster support
• Implement multi-node WebSocket management
• Add cluster-aware real-time operations
• Handle WebSocket failover scenarios

3.3 Performance Optimization

• Implement command pipelining across cluster nodes
• Add connection pooling optimization
• Implement smart routing to minimize cross-node operations
• Add batch operation support for clusters

Phase 4: SDK Updates (Week 7-8)

4.1 TypeScript SDK Enhancements

• Add DbxRedisClusterClient class
• Implement cluster-aware operations
• Add automatic retry and failover logic
• Update type definitions for cluster operations

4.2 WebSocket SDK Updates

• Extend WebSocket client for cluster support
• Add multi-node WebSocket connections
• Implement cluster-aware real-time features
• Add connection failover handling

4.3 Documentation and Examples

• Update SDK documentation for cluster operations
• Add cluster migration guides
• Create performance comparison examples
• Add troubleshooting guides

�� Testing Strategy

Unit Tests

• Connection factory tests
• Key distribution algorithm tests
• Cluster operation tests
• Error handling and retry logic tests

Integration Tests

• Redis Cluster setup with Docker Compose
• Valkey instance testing
• Failover scenario testing
• Cross-node operation testing

Performance Tests

• Load testing with cluster vs single-node
• Latency comparison across different topologies
• Throughput testing with various key distributions
• Memory usage and connection pool efficiency tests

End-to-End Tests

• Full cluster deployment testing
• SDK integration testing
• WebSocket cluster testing
• Migration scenario testing

📊 Success Metrics

Performance Metrics

• Latency: < 5ms increase for cluster operations vs single-node
• Throughput: > 90% of single-node throughput in cluster mode
• Availability: 99.9% uptime with automatic failover
• Memory Usage: < 20% increase in memory footprint

Developer Experience Metrics

• Migration Time: < 1 hour for existing applications
• API Compatibility: 100% backward compatibility
• Documentation Coverage: 100% of new features documented
• Error Handling: Clear error messages for all failure scenarios

🔧 Technical Requirements

Dependencies

• redis-rs cluster features enabled
• tokio for async operations
• serde for configuration serialization
• tracing for distributed tracing

Infrastructure

• Docker Compose for cluster testing
• Kubernetes manifests for production deployment
• Monitoring and alerting setup
• Backup and recovery procedures

Security Considerations

• TLS support for cluster communications
• Authentication for cluster nodes
• Network security for cross-node operations
• Audit logging for cluster operations

🚨 Risk Assessment

High Risk

• Data Consistency: Cross-slot operations in cluster mode
• Performance Degradation: Network overhead in distributed setup
• Complexity: Increased operational complexity

Medium Risk

• Migration Complexity: Existing application migration
• Monitoring: Distributed system monitoring challenges
• Debugging: Harder to debug issues in cluster mode

Low Risk

• Backward Compatibility: Well-defined migration path
• Documentation: Comprehensive documentation available
• Testing: Extensive testing strategy in place

📚 Documentation Requirements

Technical Documentation

• Architecture design document
• API reference for cluster operations
• Configuration guide
• Performance tuning guide

User Documentation

• Migration guide from single-node to cluster
• SDK usage examples
• Troubleshooting guide
• Best practices document

Operational Documentation

• Deployment guide
• Monitoring and alerting setup
• Backup and recovery procedures
• Disaster recovery plan

🎯 Acceptance Criteria

Functional Requirements

• Support for Redis Cluster with automatic sharding
• Support for Valkey with Redis compatibility
• Automatic failover and recovery
• Cross-slot operation handling
• Backward compatibility with existing APIs

Non-Functional Requirements

• Performance within 5% of single-node Redis
• 99.9% availability with automatic failover
• Comprehensive error handling and retry logic
• Full SDK support for cluster operations
• Complete documentation and examples

Operational Requirements

• Monitoring and alerting for cluster health
• Backup and recovery procedures
• Deployment automation
• Performance benchmarking tools

🔄 Migration Path

Phase 1: Preparation

1. Update configuration to support cluster mode
2. Add cluster-specific environment variables
3. Implement connection factory
4. Add basic cluster operations

Phase 2: Implementation

1. Implement cluster client wrapper
2. Add key distribution logic
3. Update API layer for cluster support
4. Extend SDK with cluster capabilities

Phase 3: Testing

1. Comprehensive testing with Redis Cluster
2. Performance benchmarking
3. Failover scenario testing
4. SDK integration testing

Phase 4: Deployment

1. Production deployment with monitoring
2. Gradual migration of existing applications
3. Performance monitoring and optimization
4. Documentation and training

👥 Team Requirements

Core Team

• Backend Developer: Rust implementation and cluster logic
• Frontend Developer: SDK updates and documentation
• DevOps Engineer: Infrastructure and deployment
• QA Engineer: Testing and validation

Skills Required

• Rust programming (advanced)
• Redis Cluster administration
• Distributed systems knowledge
• Performance optimization
• Monitoring and observability

�� Timeline

• Week 1-2: Foundation and configuration
• Week 3-4: Cluster implementation
• Week 5-6: API layer updates
• Week 7-8: SDK updates and testing
• Week 9-10: Documentation and deployment
• Week 11-12: Performance optimization and monitoring

🏷️ Labels

• enhancement
• cluster
• valkey
• scalability
• high-availability
• breaking-change
• documentation
• testing

🔗 Related Issues

• #XXX - Redis List Operations
• #XXX - Redis Sorted Set Operations
• #XXX - Performance Optimization
• #XXX - Monitoring and Observability

💬 Discussion Points

1. Key Distribution Strategy: Should we use consistent hashing or Redis's built-in hash slots?
2. Cross-Slot Operations: How should we handle operations that span multiple hash slots?
3. Failover Strategy: What's the optimal failover strategy for different use cases?
4. Performance Trade-offs: How do we balance consistency vs performance in cluster mode?
5. Monitoring Strategy: What metrics are most important for cluster health monitoring?

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Priority: High
Effort: Large (8-12 weeks)
Impact: High (enables horizontal scaling and high availability)