Our company is a platinum partner with HPE, and we continue to deal with HPE. We sell many of their hardware products. Depending on the requirement or deal, we may sell HPE Converged System, hardware, or converged systems. I have worked on a range of HPE hardware, including BL380, DL385, and Apollo servers, Apollo 20, Apollo 6500, MSA, and Cray storage. I find HPE Apollo Systems to be scalable and efficient for AI initiatives. The environmental efficiency has a significant impact on operational costs. Overall rating for HPE Apollo Systems: 8 out of 10.
We don't request technical support from the local HPE because we have in-house engineers. HPE Apollo is a good product, but it has to improve its support to all the distributors and appoint value-added distributions. Overall, I rate HPE Apollo a seven out of ten.
Solution integration Architect (HPE, Dell, Vmware, AWS, Azure) at Computer Marketing Company Pvt Ltd
Real User
2023-06-16T09:35:00Z
Jun 16, 2023
Ideally, any work-intensive requirement platform for HPC and deep learning, and GPU-intensive platforms must use HPE Apollo. It is one of the best solutions we have at the moment for HPC and deep learning. I rate the solution a nine out of ten.
I rate this solution a ten out of ten. Unfortunately, I have been working with it for only two months, so I cannot give advice to others. However, the solution is good and can be improved by including automatic implementation in the next update.
Head of TV Engineering and Operations at a comms service provider with 10,001+ employees
Real User
2021-04-17T13:32:36Z
Apr 17, 2021
I can recommend this solution. It is easy to maintain. If you have an infrastructure team, you won't have any problem with it. I would rate HPE Apollo a nine out of ten.
The HPE Apollo high-density server family is built for the highest levels of performance and efficiency. They are rack-scale compute, storage, networking, power and cooling – massively scale-up and scale-out – solutions for your big data analytics, object storage and high-performance computing (HPC) workloads. From water-cooling that’s 1,000X more efficient than air, to “right-sized scaling” with 2X the compute density for workgroup and private cloud workloads, the HPE Apollo line is a dense,...
Our company is a platinum partner with HPE, and we continue to deal with HPE. We sell many of their hardware products. Depending on the requirement or deal, we may sell HPE Converged System, hardware, or converged systems. I have worked on a range of HPE hardware, including BL380, DL385, and Apollo servers, Apollo 20, Apollo 6500, MSA, and Cray storage. I find HPE Apollo Systems to be scalable and efficient for AI initiatives. The environmental efficiency has a significant impact on operational costs. Overall rating for HPE Apollo Systems: 8 out of 10.
We don't request technical support from the local HPE because we have in-house engineers. HPE Apollo is a good product, but it has to improve its support to all the distributors and appoint value-added distributions. Overall, I rate HPE Apollo a seven out of ten.
Ideally, any work-intensive requirement platform for HPC and deep learning, and GPU-intensive platforms must use HPE Apollo. It is one of the best solutions we have at the moment for HPC and deep learning. I rate the solution a nine out of ten.
I rate this solution a ten out of ten. Unfortunately, I have been working with it for only two months, so I cannot give advice to others. However, the solution is good and can be improved by including automatic implementation in the next update.
I would recommend the solution to others. I rate HPE Apollo an eight out of ten.
I rate HPE Apollo an eight out of ten.
I can recommend this solution. It is easy to maintain. If you have an infrastructure team, you won't have any problem with it. I would rate HPE Apollo a nine out of ten.