Hyper-Converged Scale Out vs. Scale Up
I received ample feedback from the vendor community regarding my Sydney, Australia VMUG Keynote. I discussed the considerations for when to select hyper-converged infrastructure (HCI). If you aren’t familiar with HCI, I wrote an introductory over on TechRepublic.com. One interesting point of contention is scale out vs. scale up. One of the primary design characteristics of HCI solutions is that most allow for natural “webscale” expansion via adding additional nodes to the cluster.
When these solutions were first introduced, this meant adding both compute and storage capacity with each expansion. It provides a simple linear scale-out design that improves both compute and storage performance. The disadvantage is that it’s inefficient. Customers unnecessarily expand storage capacity when only needing compute. Most major HCI vendors alleviated this challenge by offering compute and storage nodes individually. Storage and compute now scale out independently.
Notice I said storage and compute scale out instead of scaling up. The fundamental architecture of hardware based HCI solutions is a scale out design. Individual nodes are not intended to scale up. Meaning, if you need to increase the total memory of your cluster, you must scale out opposed to popping the cover and adding memory. Depending on the nature of your workloads, this could be a challenge.
HCI hardware vendors have good reason to limit choice in scaling up post implementation. The advantage of HCI is the tight integration of the management and hardware stacks. Restricting the number of configurations reduces support issues. Software only vendors such as VMware with its VSAN solution don’t give you the integrated hardware management but do allow you to scale up individual subsystems.
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Keith Townsend is a seasoned technology leader and Chief Technology Advisor at Futurum Group, specializing in IT infrastructure, cloud technologies, and AI. With expertise spanning cloud, virtualization, networking, and storage, Keith has been a trusted partner in transforming IT operations across industries, including pharmaceuticals, manufacturing, government, software, and financial services.
Keith’s career highlights include leading global initiatives to consolidate multiple data centers, unify disparate IT operations, and modernize mission-critical platforms for “three-letter” federal agencies. His ability to align complex technology solutions with business objectives has made him a sought-after advisor for organizations navigating digital transformation.
A recognized voice in the industry, Keith combines his deep infrastructure knowledge with AI expertise to help enterprises integrate machine learning and AI-driven solutions into their IT strategies. His leadership has extended to designing scalable architectures that support advanced analytics and automation, empowering businesses to unlock new efficiencies and capabilities.
Whether guiding data center modernization, deploying AI solutions, or advising on cloud strategies, Keith brings a unique blend of technical depth and strategic insight to every project.