Production Environment Hardware Configuration Guide
RustFS is a high-performance distributed object storage system developed in Rust, suitable for massive unstructured data storage scenarios. This document provides comprehensive hardware selection and configuration guidance for production environment deployment.
Deployment Planning Factor Analysis
Before formally deploying RustFS, it's recommended to conduct 2-3 weeks of business research, focusing on evaluating the following dimensions:
- Data Scale Analysis
- Initial Data Volume: Accurately calculate effective data volume at production startup (recommended in TiB units), considering hot/cold data ratios
- Growth Trend Prediction: Estimate data increments for the next 24 months based on business development plans (recommended quarterly growth rate model)
- Object Scale: Calculate total object count based on average object size (recommended 128 KB-1 MB range), note special optimization needed when exceeding 100 million objects
- Business Characteristic Assessment
- Access Patterns: Distinguish read-intensive (such as content distribution) from write-intensive (such as log collection) scenarios
- Compliance Requirements: Data retention cycles must comply with industry regulatory requirements (e.g., financial industry must retain for at least 5 years)
- Multi-site Deployment: Cross-regional deployment requires network latency assessment (recommended controlled within 50ms) and bandwidth cost evaluation
- Storage Architecture Design
- Bucket Planning: Divide storage buckets by business units, single cluster recommended not exceeding 500 active buckets
- Disaster Recovery Strategy: Choose dual-active architecture (recommended) or asynchronous replication based on data importance
Hardware Configuration Matrix
Baseline configuration solutions based on stress test results:
| Component | Basic Environment | Production Standard Configuration | High-Performance Configuration |
|---|---|---|---|
| Node Count | 4 nodes | 8 nodes | 16+ nodes |
| Storage Media | 4× NVMe SSD | 8×NVMe SSD | 12×NVMe SSD |
| Network Architecture | Dual 25GbE (link aggregation) | Dual 100GbE | 200GbE |
| CPU | 2×Intel Silver 4310 (16 cores) | 2×AMD EPYC 7313 (32 cores) | 2×Intel Platinum 8461Y (48 cores) |
| Memory | 64 GB DDR4-3200 ECC | 256 GB DDR5-4800 ECC | 512 GB DDR5-5600 ECC |
| Storage Controller | HBA 9500-8i | HBA 9600-16i | Dual controller redundant architecture |
Important Deployment Principles:
- Adopt "server farm" mode, ensuring all nodes use identical hardware batches and firmware versions
- Network architecture must meet: leaf-spine topology + physically isolated storage network + dual uplink paths
- Recommend using 2U server models, single node recommended configuration of 12+ disk bays (based on actual hard disk count)
Performance Critical Path Optimization
Network Topology Optimization (Highest Priority)
- Bandwidth Calculation: Reserve 0.5 Gbps bandwidth per TB of effective data (e.g., 100 TB data needs 50 Gbps dedicated bandwidth)
- Latency Requirements:
- Inter-node P99 latency ≤ 2ms
- Cross-rack latency ≤ 5ms
Storage Subsystem Tuning
- Controller Configuration:
- Enable read-ahead cache (recommended 256 MB+)
- Disable all RAID functions, use pass-through mode
- Regularly check BBU battery health status
- SSD Parameters:
- Reserve 20% OP space to improve durability
- Enable atomic write features (requires hardware support)
Memory Management Strategy
- Allocation Ratios:
- Metadata cache: 60% of total memory
- Read/write buffers: 30%
- System reserve: 10%
Network Design Reference Model
Bandwidth and Disk Ratio Relationship
| Network Type | Theoretical Throughput | Suitable Disk Types | Maximum Disk Support |
|---|---|---|---|
| 10GbE | 1.25 GB/s | 7.2K HDD (180 MB/s) | 8 disks |
| 25GbE | 3.125 GB/s | SATA SSD (550 MB/s) | 6 disks |
| 100GbE | 12.5 GB/s | NVMe Gen4 (7 GB/s) | 2 disks full-speed read/write |
Best Practice Case: A video platform uses 16-node cluster, each node configured with:
- 8×7.68 TB NVMe SSD
- Dual 100GbE CX5 network cards
- Achieves aggregate throughput of 38 GB/s
Memory Configuration Calculator
Dynamic algorithm based on disk capacity and business characteristics:
# Memory calculation formula (unit: GB)
def calc_memory(data_tb, access_pattern):
base = 32 # Base memory
if access_pattern == "read_heavy":
return base + data_tb * 0.8
elif access_pattern == "write_heavy":
return base + data_tb * 1.2
else: # mixed
return base + data_tb * 1.0Reference Configuration Table:
| Data Scale | Read-Intensive | Write-Intensive | Mixed |
|---|---|---|---|
| 10 TB | 40 GB | 44 GB | 42 GB |
| 100 TB | 112 GB | 152 GB | 132 GB |
| 500 TB | 432 GB | 632 GB | 532 GB |
Storage Deployment Standards
Media Selection Criteria
| Metric | HDD Suitable Scenarios | SSD Suitable Scenarios | NVMe Mandatory Scenarios |
|---|---|---|---|
| Latency Requirements | >50ms | 1 to 10ms | < 1ms |
| Throughput Requirements | < 500 MB/s | 500 MB-3 GB/s | > 3 GB/s |
| Typical Use Cases | Archive storage | Hot data cache | Real-time analysis |
File System Configuration
# XFS formatting example
mkfs.xfs -f -L rustfs_disk1 -d su=256k,sw=10 /dev/sdb
# Recommended mount parameters
UUID=xxxx /mnt/disk1 xfs defaults,noatime,nodiratime,logbsize=256k 0 0High Availability Assurance Measures
- Power Supply:
- Adopt dual power supply architecture
- Each PDU connects to different substations
- Equip UPS (at least 30 minutes runtime)
- Cooling Requirements:
- Cabinet power density ≤ 15kW/cabinet
- Inlet/outlet temperature difference controlled within 8℃
- Firmware Management:
- Establish hardware compatibility matrix
- Use unified firmware versions
Implementation Recommendations: Recommend conducting 72-hour stress testing before formal deployment, simulating the following scenarios:
- Node failover testing
- Network partition drills
- Burst write pressure testing (recommended reaching 120% of theoretical value)
This guide is based on the latest RustFS development version. For actual deployment, please combine with specific hardware vendor white papers for parameter fine-tuning. Or contact RustFS official recommendations for quarterly hardware health assessments to ensure continuous stable operation of storage clusters.