Tackling the Challenges of Modern Infrastructure Complexity

By Curtis Elgin

June 14, 2021

The HPC, AI, and data analytics sector has always been a relatively small part of the total computing market, which is dominated by enterprise business applications, personal computing, and the other more common data processing workloads.

For most of the modern era of computing, these types of computing have been only relevant in specific industries for specific use cases like research, engineering, and big data analysis.

However, as technology has improved, especially on the edge and in the cloud, leading organizations have begun to blur the lines between these compute-intensive practices and day-to-day enterprise workloads.

Of course, once these innovations begin, it’s impossible to go backward. Today, more and more enterprise workflows are leveraging HPC, AI, and big data tools to achieve organization goals and provide competitive advantage.

However, this trend is opening the door to a new set of problems for IT directors and managers. Previously, a single large, on-premises HPC cluster could support everyone that needed this resource. Now that these resources are needed for other, non-traditional departments – or even end users of a product or service – providing these resources and maintaining performance is proving to be challenging. This is compounded by current economic trends like remote work or ecommerce.

Meeting all these needs means moving away from monolithic clusters and centralized resources. Instead, it is best to democratize resources and distribute them through the organization. This could mean rightsizing clusters for different workloads or leveraging a hybrid-cloud infrastructure. This could also mean using composable infrastructure to improve the flexibility of their clusters.

With this approach, though, you are solving one problem and creating another. Now you need to find a way to integrate all of these resources and architectures to create a cohesive environment. This is where leveraging the right technology partnerships can make a massive influence on the success of your environment – specifically a new turn-key infrastructure for these workloads that can run across multiple sites and/or cloud providers.

This means that you can manage multiple classes of clusters with multiple application workloads, which is critical when you have a finite amount of compute and storage resources. Software that connects multiple computer and storage resources creates a single, larger system. You can then look at dependencies and availability of resources to decide when and how to run these workflows, improving productivity and reduces improves ROI (return on investment).

On an equally important front, this type of technology also enables the full range of system administration tasks from initial set up to deprovisioning, so that you can maximize usage of limited infrastructure resources with fewer staff hours. Just image the benefit to organizations who need a great deal of computing power! All the upside of HPC, AI, or data analytics without the tradeoffs you normally must deal with.

We recommend this type of technology for aerospace/defense, financial services, governmental researchers, healthcare/life sciences, media and entertainment, oil and gas clients, who often run multiple clusters and/or use cloud or edge devices. (Remember, edge devices are just another type of node, so system administration issues are similar.) This will reduce the need to run full, separate HPC/AI/data analytics and IT system admin teams, since those functions will overlap much more in the future.

However, enterprise organizations looking for ways to scale, reduce costs, address computing or organizational changes, and save time will also find this new technology a good option. This group is increasing not only because of the growing interest in AI but also COVID-driven interest in cloud, 5G telecommunications, and other trends.

At Silicon Mechanics, we build leading-edge HPC, AI, and storage solutions. Decades of experience has made us experts at building the right custom solution for our client’s goals, and we have developed strong relationships with leading technology companies to support these goals. When it comes to orchestrating multi-site, multi-cloud, or hybrid environments, we leverage the technology from our partner Ctrl IQ. And, as HPC, AI, and data analytics are more increasingly seen in enterprise organizations, we think this sort of technology will be deployed with increasing frequency.

Ctrl IQ’s multi-cloud, multi-site, and performance-focused orchestration solution opens access to AI, machine learning, and analytics workflows from anywhere. Their range of software tools are designed for speed and efficiency across multiple platforms and locations. Their solution works with all popular infrastructures and includes:

  • Rocky Linux: a supported, enterprise-grade version of Linux for cloud that was enterprise developed by Gregory Kurtzer, founder of CentOS and CEO of Ctrl IQ – which we think will help ensure close software collaboration between the two and, thus, additional value to our clients.
  • Warewulf: a scalable systems management suite designed to manage clusters of compute resources – which was also co-founded by Kurtzer.
  • Singularity: a containerization and reproducibility platform for HPC and AI.
  • Fuzzball: an intelligent, secure and performant orchestration platform for managed or hosted on-premises solutions.

Despite the complexity, using open source and containerized workflows to access data and compute resources allows Ctrl IQ to compound the savings benefits derived from cloud. And, critically for enterprise organizations, the architecture promotes security.

Beyond these technical elements, one of the things that we value the most – and that we think organizations that need to support these sorts of workloads will need to consider –is the depth of experience of the engineers behind this infrastructure orchestration and management platform.

At Silicon Mechanics, we pride ourselves on our ability to build the best infrastructure platform to meet your specific needs. That is why we’re always looking at complementary software for our cluster hardware. We are confident this new system management software from Ctrl IQ can help a wide variety of organizations who want to expand their use of HPC, AI, and data analytics, especially into the cloud or edge. We encourage you to learn more about whether it might be a good fit for your cluster.

To learn more about how Silicon Mechanics approaches system design, visit siliconmechanics.com.

 

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