Distributed Deployment

RustFS provides enterprise-grade distributed object storage capabilities, supporting multi-node clusters for high availability and scalability.

Architecture Overview

RustFS uses a distributed architecture without single points of failure. Each node in the cluster can serve both read and write requests, providing:

• High Availability: Automatic failover and recovery
• Linear Scalability: Add nodes to increase capacity and performance
• Data Durability: Configurable erasure coding for data protection
• Load Distribution: Automatic load balancing across nodes

Deployment Modes

Multi-Node Multi-Drive (MNMD)

The recommended production deployment mode:

# 4 nodes, 4 drives each (16 drives total)
rustfs server http://node{1...4}.example.com/data{1...4} \
  --console-address ":9001"

Benefits:

• Maximum fault tolerance
• Best performance scaling
• Optimal for large-scale deployments

Multi-Node Single-Drive (MNSD)

Suitable for environments with external storage:

# 4 nodes, 1 drive each
rustfs server http://node{1...4}.example.com/data \
  --console-address ":9001"

Use Cases:

• Cloud deployments with attached storage
• Containerized environments
• Testing and development

Cluster Configuration

Node Requirements

Minimum Configuration:

• 4 nodes for basic redundancy
• 8GB RAM per node
• Gigabit network connectivity

Recommended Configuration:

• 8+ nodes for production
• 16GB+ RAM per node
• 10Gb network connectivity

Erasure Coding

RustFS automatically selects optimal erasure coding based on cluster size:

Nodes	EC Configuration	Fault Tolerance
4	EC:2+2	2 node failures
8	EC:4+4	4 node failures
12	EC:6+6	6 node failures
16+	EC:8+8	8 node failures

High Availability Features

Automatic Failover

• Immediate detection of node failures
• Automatic request routing to healthy nodes
• No manual intervention required

Data Healing

• Continuous background healing process
• Automatic reconstruction of lost data
• Proactive replacement of degraded objects

Rolling Updates

• Zero-downtime software updates
• Gradual node updates with health checks
• Automatic rollback on failure

Performance Optimization

Network Optimization

1. Dedicated Network

   # Use dedicated network interfaces for cluster traffic
   rustfs server http://node{1...4}.internal:9000/data{1...4}

2. Load Balancing

   • Deploy load balancer in front of cluster
   • Use health checks for automatic failover
   • Distribute client connections evenly

Storage Optimization

1. Drive Selection

   • Use consistent drive types across nodes
   • Consider NVMe for high-performance workloads
   • Plan for drive replacement cycles

2. Capacity Planning

   • Monitor storage utilization trends
   • Plan expansion before reaching 80% capacity
   • Consider seasonal usage patterns

Monitoring and Alerting

Key Metrics

• Node Health: CPU, memory, disk usage
• Network: Bandwidth, latency, packet loss
• Storage: Capacity, IOPS, healing status
• Cluster: Object count, data distribution

Alert Configuration

# Example Prometheus alerts
- alert: NodeDown
  expr: up{job="rustfs"} == 0
  for: 1m

- alert: HighDiskUsage
  expr: disk_usage_percent > 80
  for: 5m

Disaster Recovery

Multi-Site Deployment

• Deploy clusters across multiple data centers
• Configure cross-site replication
• Implement disaster recovery procedures

Backup Strategies

• Regular data exports to external storage
• Point-in-time recovery capabilities
• Automated backup verification

Security

Cluster Security

• TLS encryption for inter-node communication
• Certificate-based node authentication
• Network segmentation for cluster traffic

Access Control

• Role-based access control (RBAC)
• Integration with external identity providers
• Audit logging for all operations

Troubleshooting

Common Issues

1. Split-Brain Prevention

   • Ensure odd number of nodes when possible
   • Configure proper quorum settings
   • Monitor network connectivity

2. Performance Degradation

   • Check for failing drives
   • Monitor network utilization
   • Analyze access patterns

3. Capacity Issues

   • Monitor storage growth trends
   • Plan expansion proactively
   • Implement lifecycle policies