IBM Spectrum Computing Reviews

I'm using it in a high-performance computing solution on a specific cloud project requiring HPC to be provisioned through private and public cloud services.

The project has been in execution for five years, and Spectrum Computing has been used exclusively for high-performance computing solutions. One notable feature of IBM was its ability to handle OpenStack and closed-box software, unlike Huawei, which had limitations. Although very open, Pure Storage was limited to all-flash, making it more expensive as we don't always need all-flash storage.

The comparison was challenging, but the IBM Spectrum Scale offered a balanced solution. Our engineers rated its analytics capabilities equally high as Pure Storage. For workload management, Spectrum Computing provided effective solutions that met our needs. Workload management is part of a complete solution that uses different tools. There were the cloud and HPC parts; within HPC, there were parts like liquid cooling, simple computing, storage, and orchestration. The orchestration team handled the workload management.

IBM operates in my market, particularly in Pakistan, UAE, and other regions. In Pakistan, IBM's disadvantage is the lack of OEM support and presence. While there are many on-ground technical support and hands-on resources, the absence of direct OEM involvement is a significant drawback. Our team chose IBM independently due to the long-term financial advantages and scalability. Without IBM's marketing or guidance, we decided on IBM based on our specific HPC needs, which favored IBM. However, other storage options like Huawei might have been more advantageous for different solutions.

I have worked with IBM Spectrum Computing for the past six years.

IBM Spectrum Computing is highly scalable and provides excellent integration capabilities.

Deployment took about three to four months due to some import parts, but the deployment time was just a few days. Any challenges we faced were manageable due to our team of IBM-certified engineers. We have backend support through our partnerships if there are issues, and problems are typically resolved quickly.

Although we recently deployed it and are currently assessing ROI, initial impressions are positive. We deployed it in the education sector to test costs and benefits, and within a year, we expect to have precise analytics on ROI.

We needed a parallel file system, so we compared IBM with Huawei, Pure Storage, and NetApp. We chose IBM due to its pricing and technical capabilities, which met our specific requirements for parallel file computing on the cloud.

Despite this, integrating AI and ML features with IBM Spectrum Computing has succeeded. Overall, I would rate IBM Spectrum Computing an eight.