Hyperconverged Infrastructure Part 1 - A Modern Infrastructure for Modern Manufacturing
October 28, 2019

Alan Conboy
Scale Computing

Share this

Hyperconvergence is a term that is gaining rapid interest across the manufacturing industry due to the undeniable benefits it has delivered to IT professionals seeking to modernize their data center, or as is a popular buzzword today ― "transform." Today, in particular, the manufacturing industry is looking to hyperconvergence for the potential benefits it can provide to its emerging and growing use of IoT and its growing need for edge computing systems.

In manufacturing today, IoT (Internet of Things) or commonly referred to as IIoT (industrial IoT) presents the opportunity to enjoy huge gains across industrial processes, supply chain optimization, and so much more ― providing the ability to create an "intelligent" factory, and a much smarter business. Edge computing and IoT enables manufacturing organizations to decentralize the workload, and to collect and process data at the edge or nearest to where the work is actually happening, which can overcome the "last mile" latency issues. In addition to reducing complexity and enabling easier collection and initial analyzing of data in real time.

Edge data centers can also be leveraged to offload processing work near end users, acting as an intermediary between the IoT edge devices and larger enterprises hosting the high-end compute resources, for more in-depth processing and analytics. However, many manufacturing organizations have faced a number of hurdles as they have endeavored to deploy, manage and enjoy the benefits of IoT and edge computing. And, that's where hyperconvergence can make all of the difference.

Unfortunately, the common misuse and misunderstanding of the term hyperconvergence has led to confusion and continues to act as a barrier for those that could otherwise benefit tremendously from an IT, business agility and profitability standpoint. Let's try to clear up that confusion here.

The Inverted Pyramid of Doom

Prior to hyperconverged infrastructure (and converged infrastructure), there was and still is the inverted pyramid of doom, which refers to a 3-2-1 model of system architecture. While it commonly got the job done in a few key areas, it is the polar opposite of what a business wants or needs today.

The 3-2-1 model consists of virtualization servers or virtual machines (VMs) running three or more clustered host servers, connected by two network switches, backed by a single storage device ― most commonly, a storage area network (SAN). The problem here is that the virtualization host depends completely on the network, which in turn depends completely on the single SAN. In other words, everything rests upon a single point of failure ― the SAN. (Of course, the false yet popular argument that the SAN can't fail because of dual controllers is a story for another time.)

Introducing Hyperconverged

When hyperconvergence was first introduced, it meant a converged infrastructure solution that natively included the hypervisor for virtualization. The "hyper" wasn't just hype as it is today. This is a critical distinction as it has specific implications for how architecture can be designed for greater storage simplicity and efficiency.

Who can provide a native hypervisor? Anyone can, really. Hypervisors have become a market commodity with very little feature difference between them. With free, open source hypervisors like KVM, anyone can build on KVM to create a hypervisor unique and specialized to the hardware they provide in their hyperconverged appliances. Many vendors still choose to stay with converged infrastructure models, perhaps banking on the market dominance of Vmware ― even with many consumers fleeing the high prices of VMware licensing.

Saving money is only one of the benefits of hyperconverged infrastructure. By utilizing a native hypervisor, the storage can be architected and embedded directly with the hypervisor, eliminating inefficient storage protocols, files systems, and VSAs. The most efficient data paths allow direct access between the VM and the storage; this has only been achieved when the hypervisor vendor is the same as the storage vendor. When the vendor owns the components, it can design the hypervisor and storage to directly interact, resulting in a huge increase in efficiency and performance.

In addition to storage efficiency, having the hypervisor included natively in the solution eliminates another vendor which increases management efficiency. A single vendor that provides the servers, storage, and hypervisor makes the overall solution much easier to support, update, patch, and manage without the traditional compatibility issues and vendor finger-pointing. Ease of management represents a significant savings in both time and training from the IT budget.

Our Old Friend, the Cloud

The cloud has been around for some time now, and most manufacturing organizations have leveraged it already, whether from an on-premises, remote or public cloud platform, or more commonly a combination of each (i.e. hybrid-cloud).

As a fully functional virtualization platform, hyperconverged infrastructure can nearly always be implemented alongside other infrastructure solutions as well as integrated with cloud computing. For example, with nested virtualization in cloud platforms, a hyperconverged infrastructure solution can be extended into the cloud for a unified management experience.

Not only does a hyperconverged infrastructure work alongside and integrated with cloud computing but it offers many of the benefits of cloud computing in terms of simplicity and ease-of-management on premises. In fact, for most organizations, a hyperconverged infrastructure may be the private cloud solution that is best suited to their environment.

Like cloud computing, a hyperconverged infrastructure is so simple to manage that it lets IT administrators focus on apps and workloads rather than managing infrastructure all day as is common in 3-2-1. A hyperconverged infrastructure is not only fast and easy to implement, but it can be scaled out quickly when needed. A hyperconverged infrastructure should definitely be considered along with cloud computing for data center modernization.

Read Hyperconverged Infrastructure Part 2 - What's Included, What's in It for Me and How to Get Started

Alan Conboy is the Office of the CTO at Scale Computing
Share this

The Latest

December 03, 2024

We're at a critical inflection point in the data landscape. In our recent survey of executive leaders in the data space — The State of Data Observability in 2024 — we found that while 92% of organizations now consider data reliability core to their strategy, most still struggle with fundamental visibility challenges ...

December 02, 2024

From the accelerating adoption of artificial intelligence (AI) and generative AI (GenAI) to the ongoing challenges of cost optimization and security, these IT leaders are navigating a complex and rapidly evolving landscape. Here's what you should know about the top priorities shaping the year ahead ...

November 26, 2024

In the heat of the holiday online shopping rush, retailers face persistent challenges such as increased web traffic or cyber threats that can lead to high-impact outages. With profit margins under high pressure, retailers are prioritizing strategic investments to help drive business value while improving the customer experience ...

November 25, 2024

In a fast-paced industry where customer service is a priority, the opportunity to use AI to personalize products and services, revolutionize delivery channels, and effectively manage peaks in demand such as Black Friday and Cyber Monday are vast. By leveraging AI to streamline demand forecasting, optimize inventory, personalize customer interactions, and adjust pricing, retailers can have a better handle on these stress points, and deliver a seamless digital experience ...

November 21, 2024

Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...

November 20, 2024

New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...

November 19, 2024

Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...

November 18, 2024

SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...

November 14, 2024

Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...

November 13, 2024

AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...