Challenges Enterprises Face in Supporting Growing Edge Workloads With Current Infrastructure – NGD/Dimensional Research

By 2025, IDC Corp. predicts organizations will churn out 175ZB of data.

However, a new survey of more than 300 storage professionals by computational storage leader NGD Systems, Inc. found that bottlenecks and compute problems continue to plague IT pros as they struggle to support their growing edge workloads.

In the study entitled The State of Storage and Edge Computing conducted by Dimensional Research, barely one in 10 respondents gave themselves an A grade for their compute and storage capabilities.

The study, designed to understand the adoption and challenges of edge-related workloads, discovered that while enterprises are rapidly deploying technologies for real-time analytics, ML and IoT, they are still utilizing legacy storage solutions that are not designed for such data-intensive workloads. In fact, 54% of respondents said their processing of edge applications is a bottleneck, and they desire faster and more intelligent storage solutions.

Edge platforms are driving the need for more localized compute capability, and 60% of storage professionals reported they are using NVMe SSDs to speed up the processing of large data sets; however, this has not solved their needs. As AI and other data-intensive deployments increase, data needs to be moved over increasingly longer distances, which causes network bottlenecks and delays analytic results. These issues have provoked pros to look to new computational models that have a lower power footprint and to storage devices with smaller form-factors, which is why 89% of respondents said they expect real value from computational storage.

“We were not surprised to find that while more than half of respondents are actively using edge computing, more than 70% are using legacy GPUs, which will not reduce the network bandwidth, power and footprint necessary to analyze mass data-sets in real time,” said Nader Salessi, CEO and founder, NGD. “Computational Storage provides an innovative solution to today’s architecture, in which compute moves closer to where data is generated, rather than the data being moved up to compute. This is why computational storage is ideal for any organization deploying edge computing as its new model; it makes it possible to process data right where it’s created and needed, speeding up the time to analyze petabytes of data.”

The survey revealed that with the rapid growth of edge computing, compute cost and speed are still major challenges, as more organizations look for faster and more intelligent storage solutions:
• 55% of respondents are using edge computing
• 71% of respondents are using edge computing for real time analytics
• 61% of respondents ay the cost of traditional storage solutions continues to plague their applications
• 57% said faster access to storage would improve their compute abilities

The study also found that respondents are using the industry-standard NVMe interface to speed up data processing:
• 86% expect storage’s future to rely on NVMe SSDs
• 60% are using NVMe SSDs in their work environments
• 63% said NVMe SSDs helped with superior storage speed
• 67% reported budget and cost as issues preventing the use of NVMe SSDs

Additional findings include:
• 46% of respondents say they do not have the infrastructure in place to do proper compute at the data-generation site
• 70% of respondents said they are using GPUs to help improve workload performance
• 73% of respondents want lower power consumption
• 81% said they desire a smaller footprint

Methodology
Storage professionals and software developers responsible for data-intensive workloads were invited to participate in a survey on their companies’ approach to AI, ML, Edge computing and real-time analytics. A total of 307 participants that develop, deploy, or manage data-intensive applications completed the survey. Participants were from all five continents.