Your customer needs a server that will support a new Big Data analytics solution. The customer requires parallel processing and a server that will use high core counts and memory capacity.
Which server should you recommend?
* Understanding the Requirements:
The customer needs a server to support a new Big Data analytics solution.
The solution requires parallel processing capabilities.
High core counts and memory capacity are critical requirements.
* Server Options:
DL325 (A): A single-socket server designed for virtualization and I/O intensive workloads. While capable, it might not meet the high core and memory demands for Big Data analytics as effectively as other options.
SY480 (B): A blade server designed for high-density environments, but it might not offer the same level of core and memory capacity as other rack-mounted options for Big Data analytics.
DL385 (C): A dual-socket server optimized for high core counts and memory capacity, making it suitable for Big Data analytics and parallel processing workloads.
DL380 (D): A versatile dual-socket server with a balance of performance and expandability, but the DL385 is specifically designed to maximize core count and memory capacity.
* Why DL385 (C) is the Best Fit:
High Core Count: The DL385 Gen10 Plus server supports AMD EPYC processors, which offer high core counts, ideal for parallel processing required in Big Data analytics.
Memory Capacity: It supports up to 4TB of memory, ensuring the capacity needed for large-scale data processing tasks.
Optimized for Performance: The DL385 is designed for demanding workloads, providing the necessary performance for Big Data analytics.
* Reference:
HPE DL385 Gen10 Plus Server: HPE DL385 Gen10 Plus
Big Data Analytics Solutions: HPE Big Data Solutions
Comparison of HPE Servers: HPE ProLiant Servers
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