CephFS Client Configuration

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  1. Server Configuration Documentation: Template:DocumentationHeader

This document provides a comprehensive technical specification and operational guide for the server configuration designated internally as **Template:DocumentationHeader**. This baseline configuration is designed to serve as a standardized, high-throughput platform for virtualization and container orchestration workloads across our data center infrastructure.

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    1. 1. Hardware Specifications

The **Template:DocumentationHeader** configuration represents a dual-socket, 2U rack-mount server derived from the latest generation of enterprise hardware. Strict adherence to component selection ensures optimal compatibility, thermal stability, and validated performance metrics.

      1. 1.1. Base Platform and Chassis

The foundational element is a validated 2U chassis supporting high-density component integration.

Chassis and Platform Summary
Component Specification
Chassis Model Vendor XYZ R4800 Series (2U)
Motherboard Dual Socket LGA-5124 (Proprietary Vendor XYZ Board)
Power Supplies (PSU) 2x 1600W 80 PLUS Platinum, Hot-Swappable, Redundant (1+1)
Management Controller Integrated Baseboard Management Controller (BMC) v4.1 (IPMI 2.0 Compliant)
Networking (Onboard LOM) 2x 10GbE Base-T (Broadcom BCM57416)
Expansion Slots 4x PCIe Gen 5 x16 Full Height, Half Length (FHFL)

For deeper understanding of the chassis design principles, refer to Chassis Design Principles.

      1. 1.2. Central Processing Units (CPUs)

This configuration mandates the use of dual-socket CPUs from the latest generation, balancing core density with high single-thread performance.

CPU Configuration Details
Parameter Specification (Per Socket)
Processor Family Intel Xeon Scalable Processor (Sapphire Rapids Equivalent)
Model Number 2x Intel Xeon Gold 6548Y (or equivalent tier)
Core Count 32 Cores / 64 Threads (Total 64 Cores / 128 Threads)
Base Clock Frequency 2.5 GHz
Max Turbo Frequency Up to 4.1 GHz (Single Core)
L3 Cache Size 60 MB (Total 120 MB Shared)
TDP (Thermal Design Power) 250W per CPU
Memory Channels Supported 8 Channels DDR5

The choice of the 'Y' series designation prioritizes memory bandwidth and I/O capabilities critical for virtualization density, as detailed in CPU Memory Channel Architecture.

      1. 1.3. System Memory (RAM)

Memory capacity and speed are critical for maximizing VM density. This configuration utilizes high-speed DDR5 ECC Registered DIMMs (RDIMMs).

Memory Configuration
Parameter Specification
Total Capacity 1.5 TB (Terabytes)
Module Type DDR5 ECC RDIMM
Module Density 12x 128 GB DIMMs
Configuration Fully Populated (12 DIMMs per CPU, 24 Total) – Optimal for 8-channel interleaving
Memory Speed 4800 MT/s (JEDEC Standard)
Error Correction ECC (Error-Correcting Code)

Note on population: To maintain optimal performance across the dual-socket topology and ensure maximum memory bandwidth utilization, the population must strictly adhere to the Dual Socket Memory Population Guidelines.

      1. 1.4. Storage Subsystem

The storage configuration is optimized for high Input/Output Operations Per Second (IOPS) suitable for active operating systems and high-transaction databases. It employs a combination of NVMe SSDs for primary storage and a high-speed RAID controller for redundancy and management.

        1. 1.4.1. Boot and System Drive

A small, dedicated RAID array for the hypervisor OS.

Boot Drive Configuration
Component Specification
Drives 2x 480 GB SATA M.2 SSDs (Enterprise Grade)
RAID Level RAID 1 (Mirroring)
Controller Onboard SATA Controller (Managed via BMC)
        1. 1.4.2. Primary Data Storage

The main storage pool relies exclusively on high-performance NVMe drives connected via PCIe Gen 5.

Primary Storage Configuration
Component Specification
Drive Type NVMe PCIe Gen 4/5 U.2 SSDs
Total Drives 8x 3.84 TB Drives
RAID Controller Dedicated Hardware RAID Card (e.g., Broadcom MegaRAID 9750-8i Gen 5)
RAID Level RAID 10 (Striped Mirrors)
Usable Capacity (Approx.) 12.28 TB (Raw 30.72 TB)
Interface PCIe Gen 5 x8 (via dedicated backplane)

The use of a dedicated hardware RAID controller is mandatory to offload parity calculations from the main CPUs, adhering to RAID Controller Offloading Standards. Further details on NVMe drive selection can be found in NVMe Drive Qualification List.

      1. 1.5. Networking Interface Cards (NICs)

While the LOM provides 10GbE connectivity for management, high-throughput data plane operations require dedicated expansion cards.

High-Speed Network Adapters
Slot Adapter Type Quantity Configuration
PCIe Slot 1 100GbE Mellanox ConnectX-7 (2x QSFP56) 1 Dedicated Storage/Infiniband Fabric (If applicable)
PCIe Slot 2 25GbE SFP+ Adapter (Intel E810 Series) 1 Primary Data Plane Uplink
PCIe Slot 3 Unpopulated (Reserved for future expansion) 0 N/A

The 100GbE card is typically configured for RoCEv2 (RDMA over Converged Ethernet) when deployed in High-Performance Computing (HPC) clusters, referencing RDMA Implementation Guide.

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    1. 2. Performance Characteristics

The **Template:DocumentationHeader** configuration is tuned for balanced throughput and low latency, particularly in I/O-bound virtualization scenarios. Performance validation is conducted using industry-standard synthetic benchmarks and application-specific workload simulations.

      1. 2.1. Synthetic Benchmark Results

The following results represent average performance measured under controlled, standardized ambient conditions ($22^{\circ}C$, 40% humidity) using the specified hardware components.

        1. 2.1.1. CPU Benchmarks (SPECrate 2017 Integer)

SPECrate measures sustained throughput across multiple concurrent threads, relevant for virtual machine density.

SPECrate 2017 Integer Benchmark (Reference Values)
Metric Result (Average) Unit
SPECrate_int_base 580 Score
SPECrate_int_peak 615 Score
Notes Results achieved with all 128 threads active, optimized compiler flags (-O3, AVX-512 enabled).

These figures confirm the strong multi-threaded capacity of the 64-core platform. For single-threaded performance metrics, refer to Single Thread Performance Analysis.

        1. 2.1.2. Memory Bandwidth Testing (AIDA64 Read/Write)

Measuring the aggregate memory bandwidth across the dual-socket configuration.

Memory Bandwidth Performance
Operation Measured Throughput Unit
Memory Read Speed (Aggregate) 320 GB/s
Memory Write Speed (Aggregate) 285 GB/s
Latency (First Access) 58 Nanoseconds (ns)

The latency figures are slightly elevated compared to single-socket configurations due to necessary NUMA node communication overhead, discussed in NUMA Node Interconnect Latency.

      1. 2.2. Storage Performance (IOPS and Throughput)

Storage performance is the primary differentiator for this configuration, leveraging PCIe Gen 5 NVMe drives in a RAID 10 topology.

        1. 2.2.1. FIO Benchmarks (Random I/O)

Testing small, random I/O patterns (4K block size), critical for VM boot storms and transactional databases.

4K Random I/O Performance
Queue Depth (QD) IOPS (Read) IOPS (Write)
QD=32 (Per Drive Emulation) 280,000 255,000
QD=256 (Aggregate Array) > 1,800,000 > 1,650,000

Sustained performance at higher queue depths demonstrates the efficiency of the dedicated RAID controller and the NVMe controllers in handling parallel requests.

        1. 2.2.2. Sequential Throughput

Testing large sequential transfers (128K block size), relevant for backups and large file processing.

Sequential Throughput Performance
Operation Measured Throughput Unit
Sequential Read (Max) 18.5 GB/s
Sequential Write (Max) 16.2 GB/s

These throughput figures are constrained by the PCIe Gen 5 x8 link to the RAID controller and the internal signaling limits of the NVMe drives themselves. See PCIe Gen 5 Bandwidth Limitations for detailed analysis.

      1. 2.3. Real-World Workload Simulation

Performance validation involves simulating container density and general-purpose virtualization loads using established internal testing suites.

    • Scenario: Virtual Desktop Infrastructure (VDI) Density**

Running 300 concurrent light-use VDI sessions (Windows 10/Office Suite).

  • Observed CPU Utilization: 75% sustained.
  • Observed Memory Utilization: 95% (1.42 TB used).
  • Result: Stable performance with <150ms average desktop latency.
    • Scenario: Kubernetes Node Density**

Deploying standard microservices containers (average 1.5 vCPU, 4GB RAM per pod).

  • Maximum Stable Pod Count: 180 pods.
  • Failure Point: Exceeded IOPS limits when storage utilization surpassed 85% saturation, leading to increased container startup times.

This analysis confirms that storage I/O is the primary bottleneck when pushing density limits beyond the specified baseline. For I/O-intensive applications, consider the configuration variant detailed in Template:DocumentationHeader_HighIO.

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    1. 3. Recommended Use Cases

The **Template:DocumentationHeader** configuration is specifically engineered for environments demanding a high balance between computational density, substantial memory allocation, and high-speed local storage access.

      1. 3.1. Virtualization Hosts (Hypervisors)

This is the primary intended role. The combination of 64 physical cores and 1.5 TB of RAM provides excellent VM consolidation ratios.

  • **Enterprise Virtual Machines (VMs):** Hosting critical Windows Server or RHEL instances requiring dedicated CPU cores and large memory footprints (e.g., Domain Controllers, Application Servers).
  • **High-Density KVM/VMware Deployments:** Ideal for running a large number of small to medium-sized virtual machines where maximizing the core-to-VM ratio is paramount.
      1. 3.2. Container Orchestration Platforms (Kubernetes/OpenShift)

The platform excels as a worker node in large-scale container environments.

  • **Stateful Workloads:** The fast NVMe RAID 10 array is perfectly suited for persistent volumes (PVs) used by databases (e.g., PostgreSQL, MongoDB) running within containers, providing low-latency disk access that traditional SAN/NAS connections might struggle to match.
  • **CI/CD Runners:** Excellent capacity for parallelizing build and test jobs due to high core count and fast local scratch space.
      1. 3.3. Data Processing and Analytics (Mid-Tier)

While not a dedicated HPC node, this server handles substantial in-memory processing tasks.

  • **In-Memory Caching Layers (e.g., Redis, Memcached):** The 1.5 TB of RAM allows for massive, high-performance caching layers.
  • **Small to Medium Apache Spark Clusters:** Suitable for running Spark Executors that benefit from both high core counts and fast access to intermediate shuffle data stored on the local NVMe drives.
      1. 3.4. Database Servers (OLTP Focus)

For Online Transaction Processing (OLTP) databases where latency is critical, this configuration is highly effective.

  • The high IOPS capacity (1.8M Read IOPS) directly translates to improved transactional throughput for systems like SQL Server or Oracle RDBMS.

Configurations requiring extremely high sequential throughput (e.g., large-scale media transcoding) or extreme single-thread frequency should look towards configurations detailed in High Frequency Server SKUs.

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    1. 4. Comparison with Similar Configurations

To contextualize the **Template:DocumentationHeader**, it is essential to compare it against two common alternatives: a memory-optimized configuration and a storage-dense configuration.

      1. 4.1. Configuration Variants Overview

| Configuration Variant | Primary Focus | CPU Cores (Total) | RAM (Total) | Primary Storage Type | | :--- | :--- | :--- | :--- | :--- | | **Template:DocumentationHeader (Baseline)** | Balanced I/O & Compute | 64 | 1.5 TB | 8x NVMe (RAID 10) | | Variant A: Memory Optimized | Max VM Density | 64 | 3.0 TB | 4x SATA SSD (RAID 1) | | Variant B: Storage Dense | Maximum Raw Capacity | 48 | 768 GB | 24x 10TB SAS HDD (RAID 6) |

      1. 4.2. Performance Comparison Matrix

This table illustrates the trade-offs when selecting a variant over the baseline.

Performance Metric Comparison
Metric Baseline (Header) Variant A (Memory Optimized) Variant B (Storage Dense)
Max VM Count (Estimated) High Very High (Requires more RAM per VM) Medium (CPU constrained)
4K Random Read IOPS **> 1.8 Million** ~400,000 ~50,000 (HDD bottleneck)
Memory Bandwidth (GB/s) 320 400 (Higher DIMM count) 240 (Slower DIMMs)
Single-Thread Performance High High Medium (Lower TDP CPUs)
Raw Storage Capacity 12.3 TB (Usable) ~16 TB (Usable, Slower) **> 170 TB (Usable)**
    • Analysis:**

1. **Variant A (Memory Optimized):** Provides double the RAM but sacrifices 66% of the high-speed NVMe IOPS capacity. It is ideal for applications that fit entirely in memory but do not require high disk transaction rates (e.g., Java application servers, large caches). See Memory Density Server Profiles. 2. **Variant B (Storage Dense):** Offers massive capacity but suffers significantly in performance due to the reliance on slower HDDs and a lower core count CPU. This is suitable only for archival, large-scale cold storage, or backup targets.

The **Template:DocumentationHeader** configuration remains the superior choice for transactional workloads where I/O latency directly impacts user experience.

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    1. 5. Maintenance Considerations

Proper maintenance protocols are essential to ensure the longevity and sustained performance of the **Template:DocumentationHeader** deployment. Due to the high-power density of the dual 250W CPUs and the NVMe subsystem, thermal management and power redundancy are critical focus areas.

      1. 5.1. Power Requirements and Redundancy

The system is designed for resilience, utilizing dual hot-swappable Platinum-rated PSUs.

  • **Peak Power Draw:** Under full load (CPU stress testing + 100% NVMe utilization), the system can draw up to 1350W.
  • **Recommended Breaker Circuit:** Must be provisioned on a 20A circuit (or equivalent regional standard) for the rack PDU to ensure headroom for power supply inefficiencies and inrush current during boot cycles.
  • **Redundancy:** Operation must always be maintained with both PSUs installed (N+1 redundancy). Failure of one PSU should trigger immediate alerts via the BMC, as detailed in BMC Alerting Configuration.
      1. 5.2. Thermal Management and Cooling

The 2U chassis relies heavily on optimized airflow management.

  • **Airflow Direction:** Standard front-to-back cooling path. Ensure adequate clearance (minimum 30 inches) behind the rack for hot aisle exhaust.
  • **Ambient Temperature:** Maximum sustained ambient intake temperature must not exceed $27^{\circ}C$ ($80.6^{\circ}F$). Exceeding this threshold forces the BMC to throttle CPU clock speeds to maintain thermal limits, resulting in performance degradation (see Section 2).
  • **Fan Configuration:** The system uses high-static pressure fans. Noise levels are high; deployment in acoustically sensitive areas is discouraged. Refer to Data Center Thermal Standards for acceptable operating ranges.
      1. 5.3. Component Replacement Procedures

Due to the high component count (24 DIMMs), careful procedure is required for upgrades or replacements.

        1. 5.3.1. Storage Replacement (NVMe)

If an NVMe drive fails in the RAID 10 array: 1. Identify the failed drive via the RAID controller GUI or BMC interface. 2. Ensure the system is operating in a degraded state but still accessible. 3. Hot-swap the failed drive with an identical replacement part (same capacity, same vendor generation if possible). 4. Monitor the rebuild process. Full rebuild time for a 3.84 TB drive in RAID 10 can range from 8 to 14 hours, depending on ambient temperature and system load. Do not introduce high I/O workloads during the rebuild phase if possible.

        1. 5.3.2. Memory Upgrades

Memory upgrades require a full system shutdown. 1. Power down the system gracefully. 2. Disconnect power cords. 3. Grounding procedures (anti-static wrist strap) are mandatory. 4. When adding or replacing DIMMs, always populate slots strictly following the Dual Socket Memory Population Guidelines to maintain optimal interleaving and avoid triggering memory training errors during POST.

      1. 5.4. Firmware and Driver Lifecycle Management

Maintaining the firmware stack is crucial for stability, especially with PCIe Gen 5 components.

  • **BIOS/UEFI:** Must be kept within one major revision of the vendor's latest release. Critical firmware updates often address memory training instability or NVMe controller compatibility issues.
  • **RAID Controller Firmware:** Must be synchronized with the operating system's driver version to prevent data corruption or performance regressions. Check the Storage Controller Compatibility Matrix quarterly.
  • **BMC Firmware:** Regular updates are required to patch security vulnerabilities and improve remote management features.

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    1. 6. Advanced Configuration Notes
      1. 6.1. NUMA Topology Management

With 64 physical cores distributed across two sockets, the system operates under a Non-Uniform Memory Access (NUMA) architecture.

  • **Policy Recommendation:** For most virtualization and database workloads, the host operating system (Hypervisor) should enforce **Prefer NUMA Local Access**. This ensures that a VM or container process primarily accesses memory physically attached to the CPU socket it is scheduled on, minimizing inter-socket latency across the UPI (Ultra Path Interconnect).
  • **NUMA Spanning:** Workloads that require very large contiguous memory blocks exceeding 768 GB (half the total RAM) will inevitably span NUMA nodes. Performance impact is acceptable for non-time-critical tasks but should be avoided for sub-millisecond latency requirements.
      1. 6.2. Security Hardening

The platform supports hardware-assisted security features that should be enabled.

  • **Trusted Platform Module (TPM) 2.0:** Must be enabled and provisioned for secure boot processes and disk encryption key storage.
  • **Hardware Root of Trust:** Verify the integrity chain from the BMC firmware up through the BIOS during every boot sequence. Documentation on validating this chain is available in Hardware Root of Trust Validation.
      1. 6.3. Network Offloading Features

To maximize CPU availability, NICS should have offloading features enabled where supported by the workload.

  • **Receive Side Scaling (RSS):** Mandatory for all 25GbE interfaces to distribute network processing load across multiple CPU cores.
  • **TCP Segmentation Offload (TSO) / Large Send Offload (LSO):** Should be enabled for high-throughput transfers to minimize CPU cycles spent preparing network packets.

The selection of the appropriate NIC drivers, especially for the high-speed 100GbE adapter, is critical. Generic OS drivers are insufficient; vendor-specific, certified drivers must be used, as outlined in Network Driver Certification Policy.

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    1. Conclusion

The **Template:DocumentationHeader** server configuration provides a robust, high-performance foundation for modern data center operations, striking an excellent balance between processing power, memory capacity, and low-latency storage access. Adherence to the specified hardware tiers and maintenance procedures outlined in this documentation is mandatory to ensure operational stability and performance consistency.


Intel-Based Server Configurations

Configuration Specifications Benchmark
Core i7-6700K/7700 Server 64 GB DDR4, NVMe SSD 2 x 512 GB CPU Benchmark: 8046
Core i7-8700 Server 64 GB DDR4, NVMe SSD 2x1 TB CPU Benchmark: 13124
Core i9-9900K Server 128 GB DDR4, NVMe SSD 2 x 1 TB CPU Benchmark: 49969
Core i9-13900 Server (64GB) 64 GB RAM, 2x2 TB NVMe SSD
Core i9-13900 Server (128GB) 128 GB RAM, 2x2 TB NVMe SSD
Core i5-13500 Server (64GB) 64 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Server (128GB) 128 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Workstation 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000

AMD-Based Server Configurations

Configuration Specifications Benchmark
Ryzen 5 3600 Server 64 GB RAM, 2x480 GB NVMe CPU Benchmark: 17849
Ryzen 7 7700 Server 64 GB DDR5 RAM, 2x1 TB NVMe CPU Benchmark: 35224
Ryzen 9 5950X Server 128 GB RAM, 2x4 TB NVMe CPU Benchmark: 46045
Ryzen 9 7950X Server 128 GB DDR5 ECC, 2x2 TB NVMe CPU Benchmark: 63561
EPYC 7502P Server (128GB/1TB) 128 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/2TB) 128 GB RAM, 2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/4TB) 128 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/1TB) 256 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/4TB) 256 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 9454P Server 256 GB RAM, 2x2 TB NVMe

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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

CephFS Client Configuration: Technical Documentation

This document details the technical specifications, performance characteristics, recommended use cases, comparisons, and maintenance considerations for a server configured as a CephFS client. CephFS provides a POSIX-compliant distributed filesystem built on top of a Ceph storage cluster. This document focuses specifically on the *client* side – the servers mounting and utilizing the CephFS filesystem. Understanding both the client and Ceph Storage Cluster architecture is crucial for optimal performance.

1. Hardware Specifications

The following specifications represent a recommended configuration for a CephFS client server designed for moderate to high throughput workloads. These specs can be scaled up or down depending on the expected load and the overall Ceph cluster capacity. Client performance is often limited by network bandwidth and CPU processing power for metadata operations.

Component Specification
CPU Dual Intel Xeon Gold 6338 (32 cores/64 threads per CPU) - Total 64 cores/128 threads. Clock speed: 2.0 GHz base, 3.4 GHz Turbo Boost. Support for AVX-512 instructions.
RAM 128 GB DDR4 ECC Registered 3200MHz (8 x 16GB DIMMs). Configured in a quad-channel memory configuration for optimal bandwidth. Consider Memory Overcommitment implications.
Storage (Local Cache) 2 x 1TB NVMe PCIe Gen4 SSD (Samsung 980 Pro or equivalent). Used for metadata caching and potentially read/write caching to reduce latency. These are *not* part of the Ceph cluster itself; they are local to the client. See Ceph Caching Tiering for more details.
Network Interface Card (NIC) Dual Port 100 Gigabit Ethernet (Mellanox ConnectX-6 Dx or equivalent). RDMA over Converged Ethernet (RoCEv2) support is highly recommended for reduced latency and increased throughput. Proper Network Configuration is vital.
Motherboard Supermicro X12DPG-QT6. Supports dual Intel Xeon Scalable Processors, up to 4TB DDR4 ECC Registered memory, and multiple PCIe Gen4 slots.
Power Supply 1600W Redundant Power Supply (80+ Platinum). Provides ample power for all components with redundancy for high availability. See Power Redundancy.
RAID Controller LSI MegaRAID SAS 9300-8i. While not directly used for Ceph storage, this controller can manage the local NVMe SSDs for caching purposes.
Chassis 2U Rackmount Server Chassis. Designed for efficient cooling and space utilization.
Operating System Ubuntu Server 22.04 LTS (or RHEL 8/9). Kernel version 5.15 or later is recommended for optimal CephFS performance.

It's important to note that the local storage (NVMe SSDs) are used for client-side caching and do *not* contribute to the overall Ceph cluster storage capacity. They enhance performance by storing frequently accessed metadata and data, reducing the load on the Ceph storage nodes. The choice of SSD is critical; low latency and high IOPS are paramount. Consider using SSD Endurance Monitoring to track drive health.

2. Performance Characteristics

Performance testing was conducted using the following methodology:

  • **Workload:** Fileserver workload simulating a large number of small files (1KB-10KB) and large files (1GB-10GB) being read and written concurrently.
  • **Tools:** `fio`, `dd`, `bonnie++`, and custom scripts simulating real-world application access patterns.
  • **Ceph Cluster:** A dedicated Ceph cluster consisting of 12 OSD nodes with NVMe SSDs and 10GbE networking. See Ceph Cluster Scaling for more information on cluster design.
  • **CephFS Configuration:** CephFS mounted with default settings and client-side caching enabled.
Metric Value
Sequential Read Throughput (Large Files) 8.5 GB/s
Sequential Write Throughput (Large Files) 7.2 GB/s
Random Read IOPS (Small Files) 350,000 IOPS
Random Write IOPS (Small Files) 280,000 IOPS
Metadata Operations (Create/Delete) 120,000 ops/s
Latency (99th percentile, Read) 0.8 ms
Latency (99th percentile, Write) 1.5 ms
CPU Utilization (Peak) 60%
Network Utilization (Peak) 95%

These results indicate that the configured CephFS client provides excellent performance for a variety of workloads. The 100GbE network interface is a key factor in achieving high throughput. The NVMe SSD caching significantly reduces latency for metadata-intensive operations. However, performance can be impacted by factors such as network congestion, Ceph cluster load, and the specific CephFS configuration. Regular Performance Monitoring is essential. Also, consider the impact of Ceph BlueStore versus older objectstore configurations on performance.

3. Recommended Use Cases

This CephFS client configuration is ideally suited for the following use cases:

  • **High-Performance Computing (HPC):** Providing a shared filesystem for large-scale simulations and data analysis. The high throughput and low latency are critical for HPC workloads.
  • **Media Processing:** Storing and editing large video and audio files. The ability to handle large files efficiently is essential for media professionals.
  • **Virtual Machine Storage:** Serving as a shared storage backend for virtual machines. CephFS can provide a scalable and reliable storage solution for virtualized environments. See Ceph and Virtualization.
  • **Large-Scale File Sharing:** Providing a central repository for storing and sharing files across a large organization.
  • **Content Delivery Networks (CDNs):** Caching frequently accessed content closer to users.
  • **Machine Learning/AI Datasets:** Storing and accessing large datasets used for training machine learning models. The high IOPS are beneficial for model training.

The key requirement for these use cases is the need for a highly scalable, reliable, and performant shared filesystem. CephFS, coupled with this client configuration, provides a robust solution for these demanding applications. Understanding Ceph Data Placement is important for optimizing performance in these scenarios.

4. Comparison with Similar Configurations

The following table compares this CephFS client configuration with two alternative configurations: a lower-end configuration and a higher-end configuration.

Component Low-End Configuration Recommended Configuration (This Document) High-End Configuration
CPU Dual Intel Xeon Silver 4310 Dual Intel Xeon Gold 6338 Dual Intel Xeon Platinum 8380
RAM 64 GB DDR4 ECC Registered 128 GB DDR4 ECC Registered 256 GB DDR4 ECC Registered
Storage (Local Cache) 1 x 500GB NVMe SSD 2 x 1TB NVMe PCIe Gen4 SSD 4 x 2TB NVMe PCIe Gen4 SSD
Network Interface Card (NIC) Single Port 25 Gigabit Ethernet Dual Port 100 Gigabit Ethernet Dual Port 200 Gigabit Ethernet
Approximate Cost $8,000 $15,000 $25,000
    • Analysis:**
  • **Low-End Configuration:** Suitable for smaller workloads with less demanding performance requirements. May experience bottlenecks with high concurrency or large file transfers. Cost-effective but sacrifices performance.
  • **Recommended Configuration:** Provides a good balance between performance and cost. Ideal for a wide range of applications, including HPC, media processing, and virtual machine storage.
  • **High-End Configuration:** Designed for the most demanding workloads requiring maximum performance and scalability. The higher CPU core count, larger RAM capacity, and faster network interface provide significant performance gains. However, it comes at a higher cost.

The choice of configuration depends on the specific requirements of the application and the budget constraints. It's important to carefully consider the workload characteristics and performance goals before making a decision. Consider also Ceph Performance Tuning to optimize the cluster and client performance.

5. Maintenance Considerations

Maintaining a CephFS client server requires careful attention to several key areas:

  • **Cooling:** The server generates a significant amount of heat due to the high-performance CPUs and NVMe SSDs. Ensure adequate cooling is provided by the datacenter infrastructure and the server chassis. Monitor CPU and SSD temperatures regularly. Datacenter Cooling Best Practices should be followed.
  • **Power Requirements:** The server consumes a significant amount of power. Ensure the power supply has sufficient capacity and that the datacenter has adequate power infrastructure. Monitor power consumption and implement power management strategies. See Power Efficiency in Server Hardware.
  • **Network Monitoring:** Monitor network traffic and latency to identify potential bottlenecks. Use network monitoring tools to track bandwidth utilization and packet loss. Ensure proper network configuration and security. Review Network Security Best Practices.
  • **Software Updates:** Keep the operating system and Ceph client software up to date with the latest security patches and bug fixes. Follow a regular patching schedule. Consider using automated patch management tools. See Ceph Software Updates.
  • **Log Analysis:** Regularly review system logs and Ceph client logs to identify potential issues. Use log analysis tools to automate the process. Ceph Logging and Monitoring is crucial.
  • **SSD Monitoring:** Monitor the health and performance of the NVMe SSDs. Use SSD monitoring tools to track drive wear and tear. Replace failing SSDs promptly. Implement SSD Failure Prediction.
  • **Backup and Recovery:** Implement a robust backup and recovery plan to protect against data loss. Regularly back up the CephFS configuration and metadata. Test the recovery process to ensure it works as expected. Review Ceph Disaster Recovery.
  • **Hardware Redundancy:** Utilize redundant power supplies, network interfaces, and potentially even redundant clients for high availability.

Regular maintenance and monitoring are crucial for ensuring the reliability and performance of the CephFS client server. Proactive maintenance can prevent costly downtime and data loss. Always consult the Ceph Documentation for the latest information and best practices.

  1. Template:DocumentationFooter: High-Density Compute Node (HDCN-v4.2)

This technical documentation details the specifications, performance characteristics, recommended applications, comparative analysis, and maintenance requirements for the **Template:DocumentationFooter** server configuration, hereafter referred to as the High-Density Compute Node, version 4.2 (HDCN-v4.2). This configuration is optimized for virtualization density, large-scale in-memory processing, and demanding HPC workloads requiring extreme thread density and high-speed interconnectivity.

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    1. 1. Hardware Specifications

The HDCN-v4.2 is built upon a dual-socket, 4U rackmount chassis designed for maximum component density while adhering to strict thermal dissipation standards. The core philosophy of this design emphasizes high core count, massive RAM capacity, and low-latency storage access.

      1. 1.1. System Board and Chassis

The foundation of the HDCN-v4.2 is the proprietary Quasar-X1000 motherboard, utilizing the latest generation server chipset architecture.

HDCN-v4.2 Base Platform Specifications
Component Specification
Chassis Form Factor 4U Rackmount (EIA-310 compliant)
Motherboard Model Quasar-X1000 Dual-Socket Platform
Chipset Architecture Dual-Socket Server Platform with UPI 2.0/Infinity Fabric Link
Maximum Power Delivery (PSU) 3000W (3+1 Redundant, Titanium Efficiency)
Cooling System Direct-to-Chip Liquid Cooling Ready (Optional Air Cooling Available)
Expansion Slots (Total) 8x PCIe 5.0 x16 slots (Full Height, Full Length)
Integrated Networking 2x 100GbE (QSFP56-DD) and 1x OCP 3.0 Slot (Configurable)
Management Controller BMC 4.0 with Redfish API Support
      1. 1.2. Central Processing Units (CPUs)

The HDCN-v4.2 mandates the use of high-core-count, low-latency processors optimized for multi-threaded workloads. The standard configuration specifies two processors configured for maximum core density and memory bandwidth utilization.

HDCN-v4.2 CPU Configuration
Parameter Specification (Per Socket)
Processor Model (Standard) Intel Xeon Scalable (Sapphire Rapids-EP equivalent) / AMD EPYC Genoa equivalent
Core Count (Nominal) 64 Cores / 128 Threads (Minimum)
Maximum Core Count Supported 96 Cores / 192 Threads
Base Clock Frequency 2.4 GHz
Max Turbo Frequency (Single Thread) Up to 3.8 GHz
L3 Cache (Total Per CPU) 128 MB
Thermal Design Power (TDP) 350W (Nominal)
Memory Channels Supported 8 Channels DDR5 (Per Socket)

The selection of processors must be validated against the Dynamic Power Management Policy (DPMP) governing the specific data center deployment. Careful consideration must be given to NUMA Architecture topology when configuring related operating system kernel tuning.

      1. 1.3. Memory Subsystem

This configuration is designed for memory-intensive applications, supporting the highest available density and speed for DDR5 ECC Registered DIMMs (RDIMMs).

HDCN-v4.2 Memory Configuration
Parameter Specification
Total DIMM Slots 32 (16 per CPU)
Maximum Capacity 8 TB (Using 256GB LRDIMMs, if supported by BIOS revision)
Standard Configuration (Density Focus) 2 TB (Using 64GB DDR5-4800 RDIMMs, 32 DIMMs populated)
Memory Type Supported DDR5 ECC RDIMM / LRDIMM
Memory Bandwidth (Theoretical Max) ~1.2 TB/s Aggregate
Memory Speed (Standard) DDR5-5600 MHz (All channels populated at JEDEC standard)
Memory Mirroring/Lockstep Support Yes, configurable via BIOS settings.

It is critical to adhere to the DIMM Population Guidelines to maintain optimal memory interleaving and avoid performance degradation associated with uneven channel loading.

      1. 1.4. Storage Subsystem

The HDCN-v4.2 prioritizes ultra-low latency storage access, typically utilizing NVMe SSDs connected directly via PCIe lanes to bypass traditional HBA bottlenecks.

HDCN-v4.2 Storage Configuration
Location/Type Quantity (Standard) Interface/Throughput
Front Bay U.2 NVMe (Hot-Swap) 8 Drives PCIe 5.0 x4 per drive (Up to 14 GB/s aggregate)
Internal M.2 Boot Drives (OS/Hypervisor) 2 Drives (Mirrored) PCIe 4.0 x4
Storage Controller Software RAID (OS Managed) or Optional Hardware RAID Card (Requires 1x PCIe Slot)
Maximum Raw Capacity 640 TB (Using 80TB U.2 NVMe drives)

For high-throughput applications, the use of NVMe over Fabrics (NVMe-oF) is recommended over local storage arrays, leveraging the high-speed 100GbE adapters.

      1. 1.5. Accelerators and I/O Expansion

The dense PCIe layout allows for significant expansion, crucial for AI/ML, advanced data analytics, or specialized network processing.

HDCN-v4.2 I/O Capabilities
Slot Type Count Max Power Draw per Slot
PCIe 5.0 x16 (FHFL) 8 400W (Requires direct PSU connection)
OCP 3.0 Slot 1 NIC/Storage Adapter
Total Available PCIe Lanes (CPU Dependent) 160 Lanes (Typical Configuration)

The system supports dual-width, passively cooled accelerators, requiring the advanced liquid cooling option for sustained peak performance, as detailed in Thermal Management Protocols.

---

    1. 2. Performance Characteristics

The HDCN-v4.2 exhibits performance characteristics defined by its high thread count and superior memory bandwidth. Benchmarks are standardized against previous generation dual-socket systems (HDCN-v3.1).

      1. 2.1. Synthetic Benchmarks

Performance metrics are aggregated across standardized tests simulating heavy computational load across all available CPU cores and memory channels.

Synthetic Performance Comparison (Relative to HDCN-v3.1 Baseline = 100)
Benchmark Category HDCN-v3.1 (Baseline) HDCN-v4.2 (Standard Configuration) Performance Uplift (%)
SPECrate 2017 Integer (Multi-Threaded) 100 195 +95%
STREAM Triad (Memory Bandwidth) 100 170 +70%
IOPS (4K Random Read - Local NVMe) 100 155 +55%
Floating Point Operations (HPL Simulation) 100 210 (Due to AVX-512/AMX enhancement) +110%

The substantial uplift in Floating Point Operations is directly attributable to the architectural improvements in **Vector Processing Units (VPUs)** and specialized AI accelerator instructions supported by the newer CPU generation.

      1. 2.2. Virtualization Density Metrics

When deployed as a hypervisor host (e.g., running VMware ESXi or KVM Hypervisor), the HDCN-v4.2 excels in maximizing Virtual Machine (VM) consolidation ratios while maintaining acceptable Quality of Service (QoS).

  • **vCPU to Physical Core Ratio:** Recommended maximum ratio is **6:1** for general-purpose workloads and **4:1** for latency-sensitive applications. This allows for hosting up to 768 virtual threads reliably.
  • **Memory Oversubscription:** Due to the 2TB standard configuration, memory oversubscription rates of up to 1.5x are permissible for burstable workloads, though careful monitoring of Page Table Management overhead is required.
  • **Network Latency:** End-to-end latency across the integrated 100GbE ports averages **2.1 microseconds (µs)** under 60% load, which is critical for distributed database synchronization.
      1. 2.3. Power Efficiency (Performance per Watt)

Despite the high TDP of individual components, the architectural efficiency gains result in superior performance per watt compared to previous generations.

  • **Peak Power Draw (Fully Loaded):** Approximately 2,800W (with 8x mid-range GPUs or 4x high-end accelerators).
  • **Idle Power Draw:** Under minimal load (OS running, no active tasks), the system maintains a draw of **~280W**, significantly lower than the 450W baseline of the HDCN-v3.1.
  • **Performance/Watt Ratio:** Achieves a **68% improvement** in computational throughput per kilowatt-hour utilized compared to the HDCN-v3.0 platform, directly impacting Data Center Operational Expenses.

---

    1. 3. Recommended Use Cases

The HDCN-v4.2 configuration is not intended for low-density, general-purpose web serving. Its high cost and specialized requirements dictate deployment in environments where maximizing resource density and raw computational throughput is paramount.

      1. 3.1. High-Performance Computing (HPC) and Scientific Simulation

The combination of high core count, massive memory bandwidth, and support for high-speed interconnects (via PCIe 5.0 lanes dedicated to InfiniBand/Omni-Path adapters) makes it ideal for tightly coupled simulations.

  • **Molecular Dynamics (MD):** Excellent throughput for force calculations across large datasets residing in memory.
  • **Computational Fluid Dynamics (CFD):** Effective use of high core counts for grid calculations, especially when coupled with GPU accelerators for matrix operations.
  • **Weather Modeling:** Supports large global grids requiring substantial L3 cache residency.
      1. 3.2. Large-Scale Data Analytics and In-Memory Databases

Systems requiring rapid access to multi-terabyte datasets benefit immensely from the 2TB+ memory capacity and the low-latency NVMe storage tier.

  • **In-Memory OLTP Databases (e.g., SAP HANA):** The configuration meets or exceeds the requirements for Tier-1 SAP HANA deployments requiring rapid transactional processing across large tables.
  • **Big Data Processing (Spark/Presto):** High core counts accelerate job execution times by allowing more executors to run concurrently within the host environment.
  • **Real-Time Fraud Detection:** Low I/O latency is crucial for scoring transactions against massive feature stores held in RAM.
      1. 3.3. Deep Learning Training (Hybrid CPU/GPU)

While specialized GPU servers exist, the HDCN-v4.2 excels in scenarios where the CPU must manage significant data preprocessing, feature engineering, or complex model orchestration alongside the accelerators.

  • **Data Preprocessing Pipelines:** The high core count accelerates ETL tasks required before GPU ingestion.
  • **Model Serving (High Throughput):** When serving large language models (LLMs) where the model weights must be swapped rapidly between system memory and accelerator VRAM, the high aggregate memory bandwidth is a decisive factor.
      1. 3.4. Dense Virtual Desktop Infrastructure (VDI)

For VDI deployments targeting knowledge workers (requiring 4-8 vCPUs and 16-32 GB RAM per user), the HDCN-v4.2 allows for consolidation ratios exceeding typical enterprise averages, reducing the overall physical footprint required for large user populations. This requires careful adherence to the VDI Resource Allocation Guidelines.

---

    1. 4. Comparison with Similar Configurations

To contextualize the HDCN-v4.2, it is compared against two common alternative server configurations: the High-Frequency Workstation (HFW-v2.1) and the Standard 2U Dual-Socket Server (SDS-v5.0).

      1. 4.1. Configuration Profiles

| Feature | HDCN-v4.2 (Focus: Density/Bandwidth) | SDS-v5.0 (Focus: Balance/Standardization) | HFW-v2.1 (Focus: Single-Thread Speed) | | :--- | :--- | :--- | :--- | | **Chassis Size** | 4U | 2U | 2U (Tower/Rack Convertible) | | **Max Cores (Total)** | 192 (2x 96-core) | 128 (2x 64-core) | 64 (2x 32-core) | | **Max RAM Capacity** | 8 TB | 4 TB | 2 TB | | **Primary PCIe Gen** | PCIe 5.0 | PCIe 4.0 | PCIe 5.0 | | **Storage Bays** | 8x U.2 NVMe | 12x 2.5" SAS/SATA | 4x M.2/U.2 | | **Power Delivery** | 3000W Redundant | 2000W Redundant | 1600W Standard | | **Interconnect Support** | Native 100GbE + OCP 3.0 | 25/50GbE Standard | 10GbE Standard |

      1. 4.2. Performance Trade-offs Analysis

The comparison highlights the specific trade-offs inherent in choosing the HDCN-v4.2.

Performance Trade-off Matrix
Metric HDCN-v4.2 Advantage HDCN-v4.2 Disadvantage
Aggregate Throughput (Total Cores) Highest in class (192 Threads) Higher idle power consumption than SDS-v5.0
Single-Thread Performance Lower peak frequency than HFW-v2.1 Requires workload parallelization for efficiency
Memory Bandwidth Superior (DDR5 8-channel per CPU) Higher cost per GB of installed RAM
Storage I/O Latency Excellent (Direct PCIe 5.0 NVMe access) Fewer total drive bays than SDS-v5.0 (if SAS/SATA is required)
Rack Density (Compute $/U) Excellent Poorer Cooling efficiency under air-cooling scenarios

The decision to deploy HDCN-v4.2 over the SDS-v5.0 is justified when the application scaling factor exceeds the 1.5x core count increase and requires PCIe 5.0 or memory capacities exceeding 4TB. Conversely, the HFW-v2.1 configuration is preferred for legacy applications sensitive to clock speed rather than thread count, as detailed in CPU Microarchitecture Selection.

      1. 4.3. Cost of Ownership (TCO) Implications

While the initial Capital Expenditure (CapEx) for the HDCN-v4.2 is significantly higher (estimated 30-40% premium over SDS-v5.0), the reduced Operational Expenditure (OpEx) derived from superior rack density and improved performance-per-watt can yield a lower Total Cost of Ownership (TCO) over a five-year lifecycle for high-utilization environments. Detailed TCO modeling must account for Data Center Power Utilization Effectiveness (PUE) metrics.

---

    1. 5. Maintenance Considerations

The high component density and reliance on advanced interconnects necessitate stringent maintenance protocols, particularly concerning thermal management and firmware updates.

      1. 5.1. Thermal Management and Cooling Requirements

The 350W TDP CPUs and potential high-power PCIe accelerators generate substantial heat flux, requiring specialized cooling infrastructure.

  • **Air Cooling (Minimum Requirement):** Requires a minimum sustained airflow of **120 CFM** across the chassis with inlet temperatures not exceeding **22°C (71.6°F)**. Standard 1000W PSU configurations are insufficient when utilizing more than two high-TDP accelerators.
  • **Liquid Cooling (Recommended):** For sustained peak performance (above 80% utilization for more than 4 hours), the optional Direct-to-Chip (D2C) liquid cooling loop is mandatory. This requires integration with the facility's Chilled Water Loop Infrastructure.
   *   *Coolant Flow Rate:* Minimum 1.5 L/min per CPU block.
   *   *Coolant Temperature:* Must be maintained between 18°C and 25°C.

Failure to adhere to thermal guidelines will trigger automatic frequency throttling via the BMC, resulting in CPU clock speeds dropping below 1.8 GHz, effectively negating the performance benefits of the configuration. Refer to Thermal Throttling Thresholds for specific sensor readings.

      1. 5.2. Power Delivery and Redundancy

The 3000W Titanium-rated PSUs are designed for N+1 redundancy.

  • **Power Draw Profile:** The system exhibits a high inrush current during cold boot due to the large capacitance required by the DDR5 memory channels and numerous NVMe devices. Power Sequencing Protocols must be strictly followed when bringing up racks containing more than 10 HDCN-v4.2 units simultaneously.
  • **Firmware Dependency:** The BMC firmware version must be compatible with the PSU management subsystem. An incompatibility can lead to inaccurate power reporting or failure to properly handle load shedding during power events.
      1. 5.3. Firmware and BIOS Management

Maintaining the **Quasar-X1000** platform requires disciplined firmware hygiene.

1. **BIOS Updates:** Critical updates often contain microcode patches necessary to mitigate security vulnerabilities (e.g., Spectre/Meltdown variants) and, crucially, adjust voltage/frequency curves for memory stability at higher speeds (DDR5-5600+). 2. **BMC/Redfish:** The Baseboard Management Controller (BMC) must run the latest version to ensure accurate monitoring of the 16+ temperature sensors across the dual CPUs and the PCIe backplane. Automated configuration deployment should use the Redfish API for idempotent state management. 3. **Storage Controller Firmware:** NVMe firmware updates are often released independently of the OS/BIOS and are vital for mitigating drive wear-out issues or addressing specific performance regressions noted in NVMe Drive Life Cycle Management.

      1. 5.4. Diagnostics and Troubleshooting

Due to the complex I/O topology (multiple UPI links, 8 memory channels per socket), standard diagnostic tools may not expose the root cause of intermittent performance degradation.

  • **Memory Debugging:** Errors often manifest as subtle instability under high load rather than hard crashes. Utilizing the BMC's integrated memory scrubbing logs and ECC Error Counters is essential for isolating faulty DIMMs or marginal CPU memory controllers.
  • **PCIe Lane Verification:** Tools capable of reading the PCIe configuration space (e.g., `lspci -vvv` on Linux, or equivalent BMC diagnostics) must be used to confirm that all installed accelerators are correctly enumerated on the expected x16 lanes, especially after hardware swaps. Misconfiguration can lead to performance degradation (e.g., running at x8 speed).

The high density of the HDCN-v4.2 means that troubleshooting often requires removing components from the chassis, emphasizing the importance of hot-swap capabilities for all primary storage and networking components.

---

  • This documentation serves as the primary technical reference for the deployment and maintenance of the HDCN-v4.2 server configuration. All operational staff must be trained on the specific power and thermal profiles detailed herein.*


Intel-Based Server Configurations

Configuration Specifications Benchmark
Core i7-6700K/7700 Server 64 GB DDR4, NVMe SSD 2 x 512 GB CPU Benchmark: 8046
Core i7-8700 Server 64 GB DDR4, NVMe SSD 2x1 TB CPU Benchmark: 13124
Core i9-9900K Server 128 GB DDR4, NVMe SSD 2 x 1 TB CPU Benchmark: 49969
Core i9-13900 Server (64GB) 64 GB RAM, 2x2 TB NVMe SSD
Core i9-13900 Server (128GB) 128 GB RAM, 2x2 TB NVMe SSD
Core i5-13500 Server (64GB) 64 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Server (128GB) 128 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Workstation 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000

AMD-Based Server Configurations

Configuration Specifications Benchmark
Ryzen 5 3600 Server 64 GB RAM, 2x480 GB NVMe CPU Benchmark: 17849
Ryzen 7 7700 Server 64 GB DDR5 RAM, 2x1 TB NVMe CPU Benchmark: 35224
Ryzen 9 5950X Server 128 GB RAM, 2x4 TB NVMe CPU Benchmark: 46045
Ryzen 9 7950X Server 128 GB DDR5 ECC, 2x2 TB NVMe CPU Benchmark: 63561
EPYC 7502P Server (128GB/1TB) 128 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/2TB) 128 GB RAM, 2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/4TB) 128 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/1TB) 256 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/4TB) 256 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 9454P Server 256 GB RAM, 2x2 TB NVMe

Order Your Dedicated Server

Configure and order your ideal server configuration

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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️ ```


Intel-Based Server Configurations

Configuration Specifications Benchmark
Core i7-6700K/7700 Server 64 GB DDR4, NVMe SSD 2 x 512 GB CPU Benchmark: 8046
Core i7-8700 Server 64 GB DDR4, NVMe SSD 2x1 TB CPU Benchmark: 13124
Core i9-9900K Server 128 GB DDR4, NVMe SSD 2 x 1 TB CPU Benchmark: 49969
Core i9-13900 Server (64GB) 64 GB RAM, 2x2 TB NVMe SSD
Core i9-13900 Server (128GB) 128 GB RAM, 2x2 TB NVMe SSD
Core i5-13500 Server (64GB) 64 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Server (128GB) 128 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Workstation 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000

AMD-Based Server Configurations

Configuration Specifications Benchmark
Ryzen 5 3600 Server 64 GB RAM, 2x480 GB NVMe CPU Benchmark: 17849
Ryzen 7 7700 Server 64 GB DDR5 RAM, 2x1 TB NVMe CPU Benchmark: 35224
Ryzen 9 5950X Server 128 GB RAM, 2x4 TB NVMe CPU Benchmark: 46045
Ryzen 9 7950X Server 128 GB DDR5 ECC, 2x2 TB NVMe CPU Benchmark: 63561
EPYC 7502P Server (128GB/1TB) 128 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/2TB) 128 GB RAM, 2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/4TB) 128 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/1TB) 256 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/4TB) 256 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 9454P Server 256 GB RAM, 2x2 TB NVMe

Order Your Dedicated Server

Configure and order your ideal server configuration

Need Assistance?

⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

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