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
Top 10
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,...
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.