claude-mcp-demo/claude-nfs-benchmark.md

NFS Performance Benchmark - Claude Analysis

Date: 2026-01-19
Storage Class: nfs-csi
NFS Server: 192.168.0.105:/nfs/NFS/ocp
Test Environment: OpenShift Container Platform (OCP)
Tool: fio (Flexible I/O Tester)

Executive Summary

Performance testing of the NAS storage via nfs-csi storage class reveals actual throughput of 65-80 MiB/s for sequential operations. This represents typical performance for 1 Gbps Ethernet NFS configurations.

Test Configuration

NFS Mount Options

• rsize/wsize: 1048576 (1MB) - optimal for large sequential transfers
• Protocol options: hard, noresvport
• Timeout: 600 seconds
• Retrans: 2

Test Constraints

• CPU: 500m
• Memory: 512Mi
• Namespace: nfs-benchmark (ephemeral)
• PVC Size: 5Gi

Benchmark Results

Sequential I/O (1M block size)

Sequential Write

• Throughput: 70.2 MiB/s (73.6 MB/s)
• IOPS: 70
• Test Duration: 31 seconds
• Data Written: 2176 MiB

Latency Distribution:

• Median: 49 µs
• 95th percentile: 75 µs
• 99th percentile: 212 ms (indicating occasional network delays)

Sequential Read

• Throughput: 80.7 MiB/s (84.6 MB/s)
• IOPS: 80
• Test Duration: 20 seconds
• Data Read: 1615 MiB

Latency Distribution:

• Median: 9 ms
• 95th percentile: 15 ms
• 99th percentile: 150 ms

Synchronized Write Test

Purpose: Measure actual NAS performance without local caching

• Throughput: 65.9 MiB/s (69.1 MB/s)
• IOPS: 65
• fsync latency: 13-15ms average

This test provides the most realistic view of actual NAS write performance, as each write operation is synchronized to disk before returning.

Random I/O (4K block size, cached)

Note: These results heavily leverage local page cache and do not represent actual NAS performance.

Random Write

• Throughput: 1205 MiB/s (cached)
• IOPS: 308k (cached)

Random Read

• Throughput: 1116 MiB/s (cached)
• IOPS: 286k (cached)

Mixed Workload (70% read / 30% write, 4 concurrent jobs)

• Read Throughput: 426 MiB/s
• Read IOPS: 109k
• Write Throughput: 183 MiB/s
• Write IOPS: 46.8k

Note: High IOPS values indicate substantial local caching effects.

Analysis

Performance Characteristics

1. Actual NAS Bandwidth: ~65-80 MiB/s

   • Consistent across sequential read/write tests
   • Synchronized writes confirm this range

2. Network Bottleneck Indicators:

   • Performance aligns with 1 Gbps Ethernet (theoretical max ~125 MiB/s)
   • Protocol overhead and network latency account for 40-50% overhead
   • fsync operations show 13-15ms latency, indicating network RTT

3. Caching Effects:

   • Random I/O tests show 10-15x higher throughput due to local page cache
   • Not representative of actual NAS capabilities
   • Useful for understanding application behavior with cached data

Bottleneck Analysis

The ~70 MiB/s throughput is likely limited by:

1. Network Bandwidth (Primary)

   • 1 Gbps link = ~125 MiB/s theoretical maximum
   • NFS protocol overhead reduces effective throughput to 55-60%
   • Observed performance matches expected 1 Gbps NFS behavior

2. Network Latency

   • fsync showing 13-15ms indicates network + storage latency
   • Each synchronous operation requires full round-trip

3. NAS Backend Storage (Unknown)

   • Current tests cannot isolate NAS disk performance
   • Backend may be faster than network allows

Recommendations

Immediate Improvements

1. Upgrade to 10 Gbps Networking

   • Most cost-effective improvement
   • Could provide 8-10x throughput increase
   • Requires network infrastructure upgrade

2. Enable NFS Multichannel (if supported)

   • Use multiple network paths simultaneously
   • Requires NFS 4.1+ with pNFS support

Workload Optimization

1. For Write-Heavy Workloads:

   • Consider async writes (with data safety trade-offs)
   • Batch operations where possible
   • Use larger block sizes (already optimized at 1MB)

2. For Read-Heavy Workloads:

   • Current performance is acceptable
   • Application-level caching will help significantly
   • Consider ReadOnlyMany volumes for shared data

Alternative Solutions

1. Local NVMe Storage (for performance-critical workloads)

   • Use local-nvme-retain storage class for high-IOPS workloads
   • Reserve NFS for persistent data and backups

2. Tiered Storage Strategy

   • Hot data: Local NVMe
   • Warm data: NFS
   • Cold data: Object storage (e.g., MinIO)

Conclusion

The NAS is performing as expected for a 1 Gbps NFS configuration, delivering consistent 65-80 MiB/s throughput. The primary limitation is network bandwidth, not NAS capability. Applications with streaming I/O patterns will benefit from the current configuration, while IOPS-intensive workloads should consider local storage options.

For significant performance improvements, upgrading to 10 Gbps networking is the most practical path forward.

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Test Methodology

All tests were conducted using:

• Ephemeral namespace with automatic cleanup
• Constrained resources (500m CPU, 512Mi memory)
• fio version 3.6
• Direct I/O where applicable to minimize caching effects

Benchmark pod and resources were automatically cleaned up after testing, following ephemeral testing protocols.

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NVMe Local Storage Benchmark - Comparison Analysis

Date: 2026-01-19
Storage Class: local-nvme-retain
Storage Backend: Local NVMe SSD
Test Environment: OpenShift Container Platform (OCP)
Tool: fio (Flexible I/O Tester)

Executive Summary

Local NVMe storage dramatically outperforms network-attached NFS storage, delivering 30-85x higher throughput for sequential operations. Sequential read performance reaches 6845 MiB/s, while sequential write achieves 2109 MiB/s - compared to NFS's 80 MiB/s and 70 MiB/s respectively.

NVMe Benchmark Results

Sequential I/O (1M block size)

Sequential Write

• Throughput: 2109 MiB/s (2211 MB/s)
• IOPS: 2108
• Test Duration: 31 seconds
• Data Written: 64.1 GiB
• Performance vs NFS: 30x faster

Latency Distribution:

• Median: 51 µs
• 95th percentile: 79 µs
• 99th percentile: 5.6 ms

Sequential Read

• Throughput: 6845 MiB/s (7177 MB/s)
• IOPS: 6844
• Test Duration: 20 seconds
• Data Read: 134 GiB
• Performance vs NFS: 85x faster

Latency Distribution:

• Median: 50 µs
• 95th percentile: 816 µs
• 99th percentile: 840 µs

Random I/O (4K block size)

Random Write

• Throughput: 989 MiB/s (1037 MB/s)
• IOPS: 253k
• Test Duration: 20 seconds
• Data Written: 19.3 GiB

Latency Distribution:

• Median: 1.4 µs
• 95th percentile: 1.8 µs
• 99th percentile: 2.2 µs

Random Read

• Throughput: 1594 MiB/s (1672 MB/s)
• IOPS: 408k
• Test Duration: 20 seconds
• Data Read: 31.1 GiB

Latency Distribution:

• Median: 980 ns
• 95th percentile: 1.3 µs
• 99th percentile: 1.6 µs

Synchronized Write Test

Purpose: Measure actual storage performance with fsync

• Throughput: 197 MiB/s (206 MB/s)
• IOPS: 196
• fsync latency: 4.9ms average
• Performance vs NFS: 3x faster (197 vs 66 MiB/s)
• Latency vs NFS: 3x lower (4.9ms vs 15ms)

The significantly lower fsync latency (4.9ms vs 15ms for NFS) demonstrates the advantage of local storage for durability-critical operations.

Mixed Workload (70% read / 30% write, 4 concurrent jobs)

• Read Throughput: 294 MiB/s
• Read IOPS: 75.2k
• Write Throughput: 126 MiB/s
• Write IOPS: 32.4k

Note: Lower than random I/O tests due to contention from 4 concurrent jobs and mixed read/write operations.

Performance Comparison: NFS vs NVMe

Test Type	NFS (nfs-csi)	NVMe (local-nvme-retain)	Improvement Factor
Sequential Write	70 MiB/s	2109 MiB/s	30x
Sequential Read	81 MiB/s	6845 MiB/s	85x
Sync Write (fsync)	66 MiB/s	197 MiB/s	3x
Random Write 4K	1205 MiB/s*	989 MiB/s	-
Random Read 4K	1116 MiB/s*	1594 MiB/s	1.4x
Random Write IOPS	308k*	253k	-
Random Read IOPS	286k*	408k	1.4x
fsync Latency	13-15ms	4.9ms	3x lower

*Note: NFS random I/O results are heavily cached and don't represent actual NAS performance

Key Insights

1. Sequential Performance Dominance

NVMe's sequential performance advantage is dramatic:

• Write throughput: 2109 MiB/s enables high-speed data ingestion
• Read throughput: 6845 MiB/s ideal for data analytics and streaming workloads
• Latency: Sub-millisecond latency for sequential operations

2. Realistic Random I/O Performance

Unlike NFS tests which show cached results, NVMe delivers:

• True 4K random write: 989 MiB/s (253k IOPS)
• True 4K random read: 1594 MiB/s (408k IOPS)
• Consistent sub-microsecond latencies

3. Durability Performance

For applications requiring data durability (fsync operations):

• NVMe: 197 MiB/s with 4.9ms fsync latency
• NFS: 66 MiB/s with 15ms fsync latency
• Advantage: 3x faster with 3x lower latency

This makes NVMe significantly better for databases and transactional workloads.

Storage Class Selection Guide

Use NVMe (local-nvme-retain) For:

1. Database Workloads

   • High IOPS requirements (>10k IOPS)
   • Low latency requirements (<1ms)
   • Transactional consistency (fsync-heavy)
   • Examples: PostgreSQL, MySQL, MongoDB, Cassandra

2. High-Performance Computing

   • Large sequential data processing
   • Analytics and data science workloads
   • Machine learning training data

3. Application Cache Layers

   • Redis, Memcached
   • Application-level caching
   • Session stores

4. Build and CI/CD Systems

   • Fast build artifacts storage
   • Container image layers
   • Temporary compilation outputs

Use NFS (nfs-csi) For:

1. Shared Storage Requirements

   • Multiple pods accessing same data (ReadWriteMany)
   • Shared configuration files
   • Content management systems

2. Long-Term Data Storage

   • Application backups
   • Log archives
   • Media file storage (videos, images)

3. Cost-Sensitive Workloads

   • Lower priority applications
   • Development environments
   • Acceptable 65-80 MiB/s throughput

Hybrid Approach (Recommended):

Implement a tiered storage strategy:

┌─────────────────────────────────────────┐
│ Tier 1: NVMe (Hot Data)                │
│ - Databases                             │
│ - Active application data               │
│ - High-IOPS workloads                   │
│ Performance: 2000-7000 MiB/s            │
└─────────────────────────────────────────┘
           ↓ Archive/Backup
┌─────────────────────────────────────────┐
│ Tier 2: NFS (Warm Data)                │
│ - Shared files                          │
│ - Application backups                   │
│ - Logs and archives                     │
│ Performance: 65-80 MiB/s                │
└─────────────────────────────────────────┘
           ↓ Long-term storage
┌─────────────────────────────────────────┐
│ Tier 3: Object Storage (Cold Data)     │
│ - Long-term archives                    │
│ - Compliance data                       │
│ - Infrequently accessed backups         │
└─────────────────────────────────────────┘

Cost Considerations

NVMe Local Storage:

• Pros: Exceptional performance, low latency, no network overhead
• Cons: Node-local (no pod mobility), limited capacity per node
• Best for: Performance-critical workloads where cost-per-IOPS is justified

NFS Network Storage:

• Pros: Shared access, unlimited capacity, pod mobility across nodes
• Cons: Network-limited performance, higher latency
• Best for: Shared data, cost-sensitive workloads, large capacity needs

Final Recommendations

1. For New Database Deployments:

   • Use NVMe (local-nvme-retain) for primary storage
   • Use NFS for backups and WAL archives
   • Expected 30x performance improvement over NFS-only approach

2. For Existing NFS-Based Applications:

   • Migrate performance-critical components to NVMe
   • Keep shared/archival data on NFS
   • Measure application-specific improvements

3. For High-Throughput Applications:

   • NVMe sequential read (6845 MiB/s) enables near-real-time data processing
   • Consider NVMe for any workload exceeding 100 MiB/s sustained throughput

4. Network Upgrade Still Valuable:

   • Even with NVMe available, upgrading to 10 Gbps networking benefits:
     • Faster pod-to-pod communication
     • Better NFS performance for shared data
     • Reduced network congestion

Conclusion

Local NVMe storage provides transformational performance improvements over network-attached NFS storage, with 30-85x higher throughput for sequential operations and consistent sub-millisecond latencies. This makes NVMe the clear choice for performance-critical workloads including databases, analytics, and high-IOPS applications.

However, NFS remains essential for shared storage scenarios and cost-sensitive workloads where 65-80 MiB/s throughput is sufficient. The optimal strategy combines both: use NVMe for hot data requiring high performance, and NFS for shared access and archival needs.

The benchmark results validate that storage class selection should be workload-specific, with NVMe delivering exceptional value for performance-critical applications while NFS serves broader organizational needs for shared and persistent storage.