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

Alan Conboy
Scale Computing

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.

Start with Hyperconverged Infrastructure Part 1 - A Modern Infrastructure for Modern Manufacturing

Hyperconverged – What's Included?

Hyperconverged infrastructure is sometimes referred to as a "data center in a box" because, after the initial cabling and minimal networking configuration, it has all of the features and functionality of the traditional 3-2-1 virtualization architecture (except that single point of failure).

Rapid Deployment

Hyperconverged infrastructure systems can be deployed more rapidly than other virtualization solutions because of the appliance-based architecture. Racking and networking are often the most time-consuming factors in implementation. Deployment times vary by vendor, especially if there is a third party hypervisor to install and VSAs to configure but with a native hypervisor pre-loaded, an entire cluster of appliances can be up and running in under an hour.

Management

Hyperconverged infrastructure solutions can generally be managed from a single management interface, eliminating the multiple management consoles and interfaces found in 3-2-1 architectures. This is not necessarily the case for hyperconverged infrastructure solutions using third-party hypervisors which typically end up using two interfaces. For hyperconverged infrastructures with a native hypervisor included, this single interface approach significantly reduces management time and effort and simplifies management tasks for the administrator.

Backup and Disaster Recovery (DR)

Backup and disaster recovery are included at no extra cost in some hyperconverged infrastructure solutions to help eliminate yet another vendor from your IT environment. And truly, backup, failover, failback, and recovery should be a part of every IT environment. In that line of thought, it makes perfect sense to include these features natively in hyperconverged infrastructure solutions. Unlike third-party solutions, native solutions are typically embedded in the storage layer and allow innate awareness of block changes for cleaner backup, replication, and recovery options.

Clustering

Although a hyperconverged infrastructure can sometimes be deployed as a single appliance for selected use cases, it is usually deployed as a cluster of appliances for high availability (HA). This way, not only can an appliance absorb the loss of a disk drive, but the cluster can absorb the loss of an entire appliance. Clustering also allows the hyperconverged infrastructure system to scale seamlessly by adding more appliances to the cluster. Some hyperconverged infrastructure solutions require clustering appliances of the same model and configuration while others allow clustering of dissimilar appliances.

Software and Hardware Updates

Doing regular system software and firmware updates can be a dreaded task, but hyperconverged infrastructures tend to make this process easy. By owning the entire virtualization, server, and storage stack, and operating in a highly available cluster, updates can be performed automatically across the entire cluster. All software layers (hardware firmware, hypervisor, storage, and management) can be upgraded in unison as a single, fully tested system to eliminate component compatibility concerns. VMs can be automatically moved from appliance to appliance in the cluster as updates are made to keep all systems operational. hyperconverged infrastructure can eliminate downtime and headaches when performing updates.

Lower Cost of Ownership

A hyperconverged infrastructure may not always be the lowest cost solution in terms of the initial Capex investment ― although it often is because the ease of scalability allows organizations to purchase only the needed appliances and does not require excessive over-provisioning in the initial investment. Buying only what you need, when you need it, can lead to significant savings. In addition to Capex savings, a hyperconverged infrastructure provides considerable Opex savings over time by greatly reducing the costs of management and maintenance. Simplifying an IT environment with a hyperconverged infrastructure can save over 50 percent in the total cost of ownership over 3-2-1 solutions.

So, What's In It for Manufacturing Organizations?

Hyperconverged Infrastructure is designed as a replacement for 3-2-1 architecture to eliminate excess cost and complexity. Therefore, it can benefit any size organization that requires a robust virtualization environment. However, the extreme simplicity of a hyperconverged infrastructure makes it most beneficial in use cases where IT staff is limited. Small and medium business (SMB) and distributed enterprises with many remote offices or branch offices (ROBO) typically have staffing issues that make a hyperconverged infrastructure an ideal choice.

For a small to mid-sized manufacturing organization, the entire IT staff may be as small as only one full-time or even part-time IT administrator. The complexity of a 3-2-1 architecture can be extremely challenging. It can require levels of training and certification that make managing administrators either under-trained or too expensive to afford. The simplicity of a hyperconverged infrastructure, in turn, can allow it to be managed easily by a junior administrator or allow a more senior administrator to simply spend less time managing the infrastructure and more time delivering better applications and services and improving the business.

In a distributed manufacturing organization, remote offices and branch offices rarely have dedicated IT staff. These remote locations often require frequent visits from IT staff which can result in high travel costs and lower productivity. The simplicity of a hyperconverged infrastructure includes multiple redundancies for high availability, failure handling, and self-healing. A failed drive at a remote site does not cause an outage and does not require immediate replacement, cutting down on IT staff visits. Greater uptime and accessible remote monitoring and management lead to lower travel costs of IT staff to these locations and significantly lower operating costs ― not to mention the increase in productivity

How Do I Start?

Hyperconverged infrastructure is a revolutionary way for manufacturing organizations to think about IT infrastructure that reduces IT investments in terms of both money and manpower. Although it may be difficult to determine whether a solution is truly hyperconverged, or some other pretender, it is worth investigating hyperconverged infrastructure solutions to learn if/how your organization can gain the maximum benefit of modern IT infrastructure.

Here's where to start ― when speaking with a potential vendor ask:

■ Does the solution provide a native hypervisor or does it require an additional purchase of hypervisor licensing and support?

■ Does the solution offer hypervisor-embedded storage or does it use virtual storage appliances (VSAs)?

■ Can the solution combine and scale with dissimilar appliance models and configurations?

■ Does the solution offer native backup and DR capabilities?

■ Does the solution integrate with cloud computing? How?

As the manufacturing industry and its associated compute requirements continue to evolve, hyperconverged infrastructure is the next logical step in on-premises and cloud-integrated virtualization infrastructure. Standing still with more traditional virtualization solutions like the 3-2-1 architecture may end up costing organizations far more in capital, manpower, and training than switching over to the simplicity and savings of a hyperconverged infrastructure solution.

Alan Conboy is the Office of the CTO at Scale Computing

The Latest

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

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

Alan Conboy
Scale Computing

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.

Start with Hyperconverged Infrastructure Part 1 - A Modern Infrastructure for Modern Manufacturing

Hyperconverged – What's Included?

Hyperconverged infrastructure is sometimes referred to as a "data center in a box" because, after the initial cabling and minimal networking configuration, it has all of the features and functionality of the traditional 3-2-1 virtualization architecture (except that single point of failure).

Rapid Deployment

Hyperconverged infrastructure systems can be deployed more rapidly than other virtualization solutions because of the appliance-based architecture. Racking and networking are often the most time-consuming factors in implementation. Deployment times vary by vendor, especially if there is a third party hypervisor to install and VSAs to configure but with a native hypervisor pre-loaded, an entire cluster of appliances can be up and running in under an hour.

Management

Hyperconverged infrastructure solutions can generally be managed from a single management interface, eliminating the multiple management consoles and interfaces found in 3-2-1 architectures. This is not necessarily the case for hyperconverged infrastructure solutions using third-party hypervisors which typically end up using two interfaces. For hyperconverged infrastructures with a native hypervisor included, this single interface approach significantly reduces management time and effort and simplifies management tasks for the administrator.

Backup and Disaster Recovery (DR)

Backup and disaster recovery are included at no extra cost in some hyperconverged infrastructure solutions to help eliminate yet another vendor from your IT environment. And truly, backup, failover, failback, and recovery should be a part of every IT environment. In that line of thought, it makes perfect sense to include these features natively in hyperconverged infrastructure solutions. Unlike third-party solutions, native solutions are typically embedded in the storage layer and allow innate awareness of block changes for cleaner backup, replication, and recovery options.

Clustering

Although a hyperconverged infrastructure can sometimes be deployed as a single appliance for selected use cases, it is usually deployed as a cluster of appliances for high availability (HA). This way, not only can an appliance absorb the loss of a disk drive, but the cluster can absorb the loss of an entire appliance. Clustering also allows the hyperconverged infrastructure system to scale seamlessly by adding more appliances to the cluster. Some hyperconverged infrastructure solutions require clustering appliances of the same model and configuration while others allow clustering of dissimilar appliances.

Software and Hardware Updates

Doing regular system software and firmware updates can be a dreaded task, but hyperconverged infrastructures tend to make this process easy. By owning the entire virtualization, server, and storage stack, and operating in a highly available cluster, updates can be performed automatically across the entire cluster. All software layers (hardware firmware, hypervisor, storage, and management) can be upgraded in unison as a single, fully tested system to eliminate component compatibility concerns. VMs can be automatically moved from appliance to appliance in the cluster as updates are made to keep all systems operational. hyperconverged infrastructure can eliminate downtime and headaches when performing updates.

Lower Cost of Ownership

A hyperconverged infrastructure may not always be the lowest cost solution in terms of the initial Capex investment ― although it often is because the ease of scalability allows organizations to purchase only the needed appliances and does not require excessive over-provisioning in the initial investment. Buying only what you need, when you need it, can lead to significant savings. In addition to Capex savings, a hyperconverged infrastructure provides considerable Opex savings over time by greatly reducing the costs of management and maintenance. Simplifying an IT environment with a hyperconverged infrastructure can save over 50 percent in the total cost of ownership over 3-2-1 solutions.

So, What's In It for Manufacturing Organizations?

Hyperconverged Infrastructure is designed as a replacement for 3-2-1 architecture to eliminate excess cost and complexity. Therefore, it can benefit any size organization that requires a robust virtualization environment. However, the extreme simplicity of a hyperconverged infrastructure makes it most beneficial in use cases where IT staff is limited. Small and medium business (SMB) and distributed enterprises with many remote offices or branch offices (ROBO) typically have staffing issues that make a hyperconverged infrastructure an ideal choice.

For a small to mid-sized manufacturing organization, the entire IT staff may be as small as only one full-time or even part-time IT administrator. The complexity of a 3-2-1 architecture can be extremely challenging. It can require levels of training and certification that make managing administrators either under-trained or too expensive to afford. The simplicity of a hyperconverged infrastructure, in turn, can allow it to be managed easily by a junior administrator or allow a more senior administrator to simply spend less time managing the infrastructure and more time delivering better applications and services and improving the business.

In a distributed manufacturing organization, remote offices and branch offices rarely have dedicated IT staff. These remote locations often require frequent visits from IT staff which can result in high travel costs and lower productivity. The simplicity of a hyperconverged infrastructure includes multiple redundancies for high availability, failure handling, and self-healing. A failed drive at a remote site does not cause an outage and does not require immediate replacement, cutting down on IT staff visits. Greater uptime and accessible remote monitoring and management lead to lower travel costs of IT staff to these locations and significantly lower operating costs ― not to mention the increase in productivity

How Do I Start?

Hyperconverged infrastructure is a revolutionary way for manufacturing organizations to think about IT infrastructure that reduces IT investments in terms of both money and manpower. Although it may be difficult to determine whether a solution is truly hyperconverged, or some other pretender, it is worth investigating hyperconverged infrastructure solutions to learn if/how your organization can gain the maximum benefit of modern IT infrastructure.

Here's where to start ― when speaking with a potential vendor ask:

■ Does the solution provide a native hypervisor or does it require an additional purchase of hypervisor licensing and support?

■ Does the solution offer hypervisor-embedded storage or does it use virtual storage appliances (VSAs)?

■ Can the solution combine and scale with dissimilar appliance models and configurations?

■ Does the solution offer native backup and DR capabilities?

■ Does the solution integrate with cloud computing? How?

As the manufacturing industry and its associated compute requirements continue to evolve, hyperconverged infrastructure is the next logical step in on-premises and cloud-integrated virtualization infrastructure. Standing still with more traditional virtualization solutions like the 3-2-1 architecture may end up costing organizations far more in capital, manpower, and training than switching over to the simplicity and savings of a hyperconverged infrastructure solution.

Alan Conboy is the Office of the CTO at Scale Computing

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...