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X7513A - Sun Fire B100x AMD Athlon 1.53GHz CPU 1GB RAM 30GB Hard Drive Blade Server
- AMD Athlon CPU
- 1.53GHz Processor Speed
- 1GB RAM
- 30GB Hard Drive
- Blade Server Form Factor
- Designed for Sun Blade chassis
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Key specifications
See full specs ↓- Model
- Fire B100x
- CPU
- AMD Athlon
- CPU Speed
- 1.53GHz
- RAM
- 1GB
- Hard Drive
- 30GB
- Form Factor
- Blade Server
Product details
The Sun X7513A Fire B100x is a blade server featuring an AMD Athlon processor, 1GB of RAM, and a 30GB hard drive. It is designed for high-density computing environments within a blade chassis.
Technical Information
| Model | Fire B100x |
| CPU | AMD Athlon |
| CPU Speed | 1.53GHz |
Additional Specifications
| RAM | 1GB |
| Hard Drive | 30GB |
| Form Factor | Blade Server |
Description
The Sun X7513A, identified as the Fire B100x, is a compact blade server designed for deployment within Sun Microsystems' blade server chassis. This server node is equipped with an AMD Athlon processor running at 1.53GHz, providing sufficient processing power for a range of general-purpose computing tasks. It comes with 1GB of RAM, suitable for operating systems and applications that do not require extensive memory resources, and a 30GB hard drive for local storage of the operating system and essential data. The blade form factor of the Fire B100x is central to its design philosophy. Blade servers are engineered for high-density computing, allowing multiple server nodes to be housed within a single chassis. This approach conserves rack space, reduces power consumption and cooling requirements compared to traditional rack-mount servers, and simplifies network and power management through the shared infrastructure of the blade enclosure. This specific configuration of the Sun Fire B100x is well-suited for environments that need to deploy a large number of compute nodes for tasks such as web serving, application hosting, or other workloads where individual node resources can be modest. Its integration into a Sun blade system allows for centralized management and efficient resource utilization, making it a practical choice for scalable computing deployments.
Condition: Refurbished
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