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HP 867055-B21 ProLiant XL170r Gen10 1U Node Configure-to-Order Server
- 1U Rack Server Node.
- Compatible with HPE Synergy or Apollo chassis.
- Gen10 architecture.
- Configure-to-Order (CTO) model, allowing customization.
- Designed for high-density computing.
- Supports various Intel Xeon Scalable processors.
- Offers flexible storage and memory configurations.
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Typically 1-2 handling + 3-7 transit days
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For government, enterprise, data center, and small business customers.
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Product Overview
The HP 867055-B21 is a ProLiant XL170r Gen10 server node, designed as a 1U compute sled for high-density computing environments. It offers a configurable platform for various workloads within the HPE Synergy or Apollo systems.
Technical Information
| Product Type | Server Node |
| Form Factor | 1U Rack |
| Chassis Compatibility | HPE Synergy / Apollo |
| Generation | Gen10 |
Additional Specifications
| Configuration | Configure-to-Order (CTO) |
| Processor Support | Intel Xeon Scalable Processors |
| Memory Type | DDR4 |
Product Description
The HP 867055-B21 is a 1U server node belonging to the Hewlett Packard Enterprise (HPE) ProLiant XL170r Gen10 family. This model is specifically designed to function as a compute sled within HPE's Synergy or Apollo modular infrastructure platforms. These platforms are engineered for high-density computing, allowing organizations to deploy significant processing power and storage in a compact footprint. As a Configure-to-Order (CTO) unit, the 867055-B21 provides flexibility, enabling customers to specify the exact components required for their specific workloads. This typically includes selecting the appropriate Intel Xeon Scalable processors, configuring memory (DDR4 DIMMs) capacity and speed, and choosing storage options such as NVMe or SAS/SATA drives, depending on the chassis's capabilities. The ProLiant XL170r Gen10 node is optimized for performance, efficiency, and scalability. It is well-suited for a wide range of applications, including virtualization, high-performance computing (HPC), big data analytics, and cloud environments, where maximizing compute density and resource utilization is paramount.
