George Crump

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Understanding the ROI of on-premises AI versus cloud AI costs is crucial for enterprises seeking to leverage artificial intelligence without incurring excessive expenses. Organizations that embrace AI quickly realize two truths: the technology can revolutionize their operations, and the public cloud’s AI capabilities can become prohibitively expensive as adoption grows.

the ROI of on-premises AI

Public cloud providers charge per token or query, causing costs to rise rapidly as AI usage expands, effectively penalizing success. In contrast, on-premises AI solutions like VergeOS, which integrates VergeIQ, treat AI as a resource rather than a separate workload. VergeIQ, integrated into VergeOS, offers a flat, one-time cost model, empowering enterprises to leverage AI without incurring unpredictable expenses.

The Hidden Cost of Public Cloud AI

Public cloud AI services initially appear attractive due to the theoretical ease of deployment and assumption of low entry costs. Yet, as organizational usage expands, the token-based pricing results in rapidly escalating expenses. As more departments, teams, and applications begin to utilize AI, costs rise dramatically, complicating budget forecasting and potentially forcing restrictions on usage, which undermines the core value of implementing AI solutions.

The Financial Advantage of On-Premises AI

VergeOS combined with VergeIQ offers a fundamentally different financial model. After an initial investment in infrastructure, enterprises receive unlimited AI capabilities under their control, without ongoing per-token costs. This approach enables predictable budgeting and substantial long-term savings, encouraging broader adoption of AI throughout the organization without additional financial penalties.

The On-Premises AI TCO Benefits with VergeIQ

1. Predictable Budgeting and Cost Control

the ROI of on-premises AI

VergeIQ employs a straightforward flat-fee pricing model, eliminating unpredictable expenses associated with usage-based cloud services. Organizations can accurately forecast budgets, enabling consistent financial planning without surprises as AI utilization expands across departments.

2. Accelerated Enterprise Adoption

Without the constraint of per-token or per-query charges, enterprises can freely encourage widespread AI adoption throughout their organization. This empowers innovation, encourages experimentation, and maximizes the organizational benefits derived from AI without financial hesitation.

3. Enhanced Data Privacy and Compliance

Deploying AI on-premises with VergeIQ ensures sensitive data stays securely within your enterprise environment, eliminating the need to spend valuable time sanitizing or anonymizing datasets. This approach reduces operational costs associated with data preparation. It decreases risks and potential expenses related to the exposure or breach of proprietary data, ensuring full compliance with stringent privacy regulations.

4. The ROI of On-Premises AI Lowers TCO

Integrating AI directly within VergeOS eliminates third-party software costs, reduces infrastructure complexity, and minimizes ongoing operational expenses. The combination of simplified management, reduced external dependencies, and predictable costs results in a notably lower total cost of ownership compared to cloud-based alternatives.

5. On-Premises AI Improves Sustainability and Efficiency

VergeIQ leverages VergeOS’s efficient infrastructure management, optimizing hardware resource usage and decreasing power consumption. This aligns with corporate sustainability initiatives, helping enterprises meet environmental goals while reducing energy expenses associated with AI workloads.

Realize Immediate Business Value with On-Premises AI

VergeIQ allows secure analysis of proprietary data, internal process optimization, and infrastructure automation within your data center. Immediate operational improvements translate directly into measurable business value. The predictable flat-fee model ensures a rapid return on investment (ROI) and eliminates financial surprises associated with cloud-based AI.

The ROI of on-premises AI Means No Operational Overhead

Private or on-premises AI solutions carry a reputation for significant operational overhead due to their complexity and reliance on multiple third-party components. VergeIQ, however, transforms this narrative. Integrated directly within VergeOS, VergeIQ simplifies operations by providing vendor-neutral AI resources alongside built-in virtualization, storage, and networking. This unified approach makes AI capabilities instantly accessible upon installing VergeOS, removing the need for separate installations or complex third-party setups.

the ROI of on-premises AI

Additionally, VergeIQ’s built-in OpenAI-compatible API ensures compatibility with tools and platforms such as LangChain, AutoGPT, ChatGPT interfaces, and other OpenAI-compatible solutions. Enterprises can rapidly integrate existing applications and workflows without retraining teams or re-engineering software. As a result, organizations benefit from powerful, operationally streamlined AI capabilities that reduce complexity, minimize overhead, and accelerate ROI—all fully controlled within their own data centers.

Catch an exclusive preview of VergeIQ during our live webinar and demonstration on June 12 at 1:00pm ET. Register here.

Conclusion: Sustainable AI Investment with VergeIQ

Enterprises have clear choices in adopting AI: escalating public cloud costs or predictable, secure, and cost-effective on-premises AI with VergeOS and VergeIQ. By selecting on-premises AI, organizations gain financial sustainability, complete data control, and a lasting competitive advantage. Reducing costs is just one of the requirements for AI. To learn more, read “Enterprise AI: Key Requirements and Why It Matters.”

the ROI of on-premises AI

With VergeOS and VergeIQ, embracing AI becomes a strategic investment rather than an unpredictable expense, positioning your enterprise to leverage AI’s transformative potential without financial uncertainty.

Filed Under: AI

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Delivers secure, private, easy-to-use AI that installs in minutes

Ann Arbor, MI — June 3, 2025 — VergeIO, the developer of VergeOS—the first software-defined platform to unify virtualization, storage, and networking—today announced VergeIQ, a fully integrated Enterprise AI infrastructure solution enabling enterprises and research institutions to securely, efficiently, and easily deploy and manage private AI environments.

VergeIQ is not a bolt-on or standalone AI stack. It is seamlessly integrated as a core component of VergeOS, enabling enterprises to rapidly deploy AI infrastructure and capabilities within their existing data centers in minutes, rather than months.

“With VergeIQ, we’re removing the complexity and hurdles enterprises face when adopting AI,” said Yan Ness, CEO of VergeIO. “Organizations want to leverage the power of AI for competitive advantage without losing control of their most sensitive data. VergeIQ provides exactly that—enterprise-ready AI fully integrated within VergeOS, entirely under your control.”

“AI has quickly become a strategic priority across every industry, but organizations encounter significant challenges around infrastructure complexity and data governance,” said Scott Sinclair, Practice Director of the Infrastructure, Cloud, and DevOps segment at Enterprise Strategy Group (ESG). “VergeIQ directly addresses these pain points by making private, secure AI deployment achievable for enterprises of all sizes. This innovation will help drive the next wave of enterprise AI adoption.”

Integrated Enterprise AI Infrastructure

VergeIQ is designed for enterprises needing secure AI capabilities, data privacy, and near-bare-metal performance. Customers can select and deploy various Large Language Models (LLMs)—such as LLaMa, Mistral, and Falcon—and immediately begin using them on their own data within VergeOS’ secure, tenant-aware infrastructure.

Unlike traditional AI stacks that rely on complex third-party infrastructure or GPU virtualization tools like NVIDIA vGPU, VergeIQ provides native GPU pooling and clustering, eliminating external licensing complexity. This native integration ensures dynamic, efficient GPU resource utilization across virtual data centers.

Key Highlights of VergeIQ

  • Private, Secure Deployment: Fully on-premises, air-gapped, or disconnected deployments ensuring total data sovereignty, compliance, and security.
  • Rapid LLM Deployment: Instantly deploy popular pre-trained LLMs, including LLaMa, Falcon, OpenAI, Claude, and Mistral, without complex setup or custom training.
  • OpenAI API Routing: A built-in OpenAI-compatible API router simplifies the integration and interaction of diverse large language models (LLMs) within your workflows.
  • Vendor-Agnostic GPU Support: Utilize any standard GPU hardware, avoiding vendor lock-in and enhancing flexibility in infrastructure decisions.
  • Dynamic GPU/CPU Orchestration: Automatically manage and optimize the loading and utilization of AI models across available GPU and CPU resources, maximizing infrastructure efficiency and scalability.
  • GPU Sharing and Clustering: Dynamic, intelligent pooling and sharing of GPU resources across clusters to ensure optimal usage, performance, and cost-efficiency.
  • Infrastructure Intelligence: Directly query IT infrastructure to extract actionable insights and simplify operational decision-making rapidly.

VergeIQ will be available as a seamless upgrade of VergeOS to all existing customers, providing full enterprise AI capabilities immediately upon upgrade.

To learn more about VergeIQ and see it in action, register for our upcoming webinar on June 12th at www.verge.io.

About VergeIO

VergeIO is the company behind VergeOS, the world’s first unified data center operating system. VergeOS simplifies and integrates virtualization, storage, and networking into a single, scalable software platform that spans from the edge to the core. With the addition of VergeIQ, VergeIO is redefining how enterprises build, deploy, and manage private and secure AI infrastructure.

To schedule a demonstration or join the VergeIQ Early Access program, visit www.verge.io.

Media Contact:
Judy Smith
JPR Communications
[email protected]
(818) 522-9673

Filed Under: Press Release

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Enterprise AI

Organizations across every industry recognize the transformational potential of generative AI. However, deploying these powerful capabilities on-premises has historically been complex, costly, and difficult to manage. Until now. Introducing VergeIQ—an integrated generative AI capability built directly into VergeOS, the unified data center operating system.

With VergeIQ, generative AI becomes another powerful infrastructure resource, seamlessly integrated alongside virtualization, storage, and networking within VergeOS. Once VergeOS is installed, your enterprise immediately gains access to VergeIQ—no additional software, no complicated setups, and no dedicated AI infrastructure required. VergeIQ is built-in, turnkey, and available to IT to help with infrastructure tasks and the organization at large to gain AI insights into proprietary data.

Why On-Premises and Secure AI Matters

Deploying AI completely on-premises is fundamental to achieving genuinely private or sovereign AI capabilities. Hosting AI within your own data center infrastructure ensures full control over sensitive or proprietary information, eliminating the risks associated with external or cloud-based providers. By keeping data entirely within organizational boundaries, enterprises can confidently meet stringent regulatory requirements and compliance standards. An on-premises approach prevents data exposure during transmission and storage in external environments, making it the most reliable way to ensure true data privacy, security, and sovereignty.

How VergeIQ Makes Enterprise AI Practical

Traditional enterprise AI deployments typically require standalone environments, expensive hardware stacks, and deep technical expertise. By introducing VergeIQ, we are breaking down these barriers by embedding AI as a resource natively within the VergeOS platform. This unified approach simplifies deployment, reduces costs, enhances performance, and eliminates the complexity typically associated with generative AI infrastructure.

As a result, enterprises can immediately and privately begin leveraging powerful generative AI models, such as LLaMa, Qwen, Phi, Gemma, within minutes after installing VergeOS. VergeIQ’s design allows you to securely and privately interact with your sensitive documents, proprietary code, and confidential internal datasets, without ever sending your information outside your infrastructure.

Enterprise AI with Day 1 Value

Rapid Analysis and Insights from Internal Documents

From day one, your users will be able to securely upload a wide range of common document types, including PDFs, documents, spreadsheets, text files, HTML pages, and more. VergeIQ quickly processes these documents and generates secure, context-rich summaries, actionable insights, and content tailored to your organization’s information within your own infrastructure. No data leaves your control.

Use Enterprise AI to Securely Explore Proprietary Source Code

For software development teams, VergeIQ is invaluable. It lets you instantly audit, analyze, and optimize your proprietary software codebases, without ever sending sensitive intellectual property off-premises. Developers can quickly identify potential issues, create clear documentation, and accelerate software delivery, all securely within the VergeOS environment.

Accelerate Infrastructure Automation

VergeIQ simplifies infrastructure automation, enabling IT teams to rapidly generate accurate scripts, infrastructure-as-code (IaC) definitions, and workflows. Instead of relying solely on manual scripting, you can securely query VergeIQ to generate automation code tailored to your environment, significantly accelerating infrastructure management across your entire data center.

Use Enterprise AI to Generate Tailored Enterprise Content

VergeIQ empowers business and marketing teams by quickly generating internal documentation, knowledge-base articles, HR policies, or customer communications from your secure, private data sources. Enterprises can confidently produce content that is not only accurate and relevant but also fully compliant with their governance requirements.

Infrastructure Intelligence

And of course, VergeIQ supports querying your IT infrastructure itself. By leveraging the power of VergeIQ, infrastructure teams can obtain immediate operational insights, analyze workloads, predict capacity requirements, and simplify day-to-day operational decision-making. All infrastructure data remains secure, private, and fully accessible within your data center.

Why VergeIQ Makes Sense for Enterprise AI

Hardware Abstraction without Compromise

VergeIQ incorporates intelligent GPU orchestration, vendor-agnostic GPU support, dynamic resource pooling, and highly optimized storage performance. This ensures maximum hardware efficiency, near-bare-metal performance, and lower power consumption. By leveraging VergeOS’s unified architecture, organizations can reach their sustainability goals while enhancing productivity and reducing costs.

Ready to see VergeIQ in action? Register for our world-premier webinar on June 12th.

OpenAI Ready

VergeIQ includes a built-in API router compatible with OpenAI, delivering a smooth and familiar experience for developers. Existing code, scripts, and integrations written for OpenAI APIs can work unchanged, except that your AI models run locally on your infrastructure. This means reduced latency, increased security, and complete data sovereignty, all without the complexity typically associated with private AI deployments.

Use Enterprise AI and gain Operational Simplicity

Enterprise AI

No Additional Installation Required

A defining characteristic of VergeIQ is its total integration within VergeOS. VergeOS is already recognized as a leading alternative to VMware, helping enterprises simplify their infrastructure and reduce costs. With VergeIQ, the same installation that handles virtualization, storage (VergeFS), and networking (VergeFabric) also provides comprehensive generative AI capabilities—no additional installations, complicated AI stacks, or specialized training needed.

VMware Exit Today, AI Tomorrow—One Platform, Two Major Wins

For many of our customers, transitioning away from VMware to a simpler, cost-effective infrastructure is the top priority. VergeOS is a leading VMware alternative, designed specifically to streamline this process. Introducing VergeIQ shouldn’t change that priority; it should accelerate it, as it is already included with the VergeOS deployment you’ll use as your VMware alternative. Once you’ve completed your migration away from VMware, you’ll immediately have access to a complete generative AI platform, right within your own data center.

But if you’re not ready to exit VMware just yet, you don’t have to wait. You can deploy VergeOS alongside your existing VMware infrastructure right now, instantly gaining access to VergeIQ’s generative AI capabilities. Begin benefiting from VergeIQ immediately, then transition from VMware to VergeOS when the timing works best for your organization.

VergeIQ is ready to deliver value from day one—not only helping you leverage AI to streamline infrastructure management but also supporting a wide range of additional enterprise use cases, as we’ll explore in detail below.

Availability Timeline

VergeIQ will begin preview demonstrations throughout June 2025. The Early Access Program is scheduled to open in July 2025, with General Availability set for August 2025. Existing VergeOS customers will seamlessly upgrade to receive VergeIQ capabilities as a part of their current infrastructure.

Conclusion: Transform Your Organization with Enterprise AI Today

Introducing VergeIQ as an integrated resource of VergeOS means that private generative AI is no longer a future aspiration—it’s a present-day reality. It meets all the requirements of Enterprise AI, allowing organizations to deploy, securely manage, and immediately benefit from generative AI models directly within their own data centers. VergeIQ provides the control, simplicity, and security enterprises demand, paired with the powerful generative AI capabilities that organizations increasingly require.

Ready to see VergeIQ in action? Register for our world-premier webinar on June 12th.

Filed Under: AI

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The hidden costs of HCI often prevent IT professionals, who are looking to exit VMware, from seriously considering the architecture as a viable alternative. Hyperconverged Infrastructure (HCI) vendors capitalize on this scenario, positioning their solutions as streamlined platforms that seamlessly unify virtualization, compute, storage, and networking. However, this initial promise of simplified infrastructure management frequently masks significant hidden costs and complexities.

The hidden costs of HCI

Initially intended to unify infrastructure components, traditional HCI has failed to deliver true integration. Compute, storage, and networking resources remain operationally separate, requiring distinct layers in the form of virtual machines (VMs) communicating with the hypervisor. Commonly deployed solutions utilize separate VMs for storage management (e.g., Nutanix’s CVM or VMware’s vSAN), distinct networking stacks (Nutanix Flow, VMware NSX), and individual management VMs (Nutanix Prism, VMware vCenter). True operational simplification remains elusive; what began as convergence is merely the virtualization of legacy three-tier architectures.

How VergeOS Solves the Convergence Problem

VergeOS achieves true convergence through its ultraconverged design. By integrating storage, networking, virtualization, and data services directly into a unified operating environment, VergeOS eliminates silos and redundant communication layers. This cohesive design simplifies operations, reducing complexity, administrative overhead, and resource inefficiency.

Dive deeper with our on-demand webinar: “Comparing HCI as VMware Alternatives.”

The Efficiency Problem

The hidden costs of HCI include its inability to deliver meaningful infrastructure efficiency. Despite sharing hardware, HCI components remain distinct entities, each consuming substantial resources. Dedicated storage VMs, management VMs, separate networking stacks, and additional abstraction layers cumulatively drain compute cycles and memory. Application VMs running within these infrastructures consequently suffer degraded performance and higher latency, forcing organizations to compensate with additional hardware investment rather than benefiting from the initially promised efficiency gains.

For instance, a typical I/O operation in an HCI environment begins at the hypervisor level, proceeds through a storage controller (virtualized as a separate VM), traverses network infrastructure, and finally reaches physical storage media. Each extra step consumes CPU resources, adds latency, and reduces performance efficiency. As workloads scale, the cumulative impact of these inefficiencies affects application responsiveness and resource utilization.

Some HCI vendors utilize data locality to mitigate some of these issues; however, this technology further complicates operations and negatively impacts performance during node or drive failure.

The hidden costs of HCI

How VergeOS Solves the Efficiency Problem

VergeOS integrates all services, including storage and networking, directly into its operating system, eliminating performance overhead associated with separate management virtual machines or additional software layers. Its lightweight architecture ensures maximum resource efficiency, optimizing performance and dramatically reducing hardware requirements and infrastructure costs.

The High Cost of HCI Inefficiency

The hidden costs of HCI inefficiencies necessitate significant investment in higher-performance hardware to compensate for architectural shortcomings. IT must procure more powerful servers, increased core counts, expanded memory, and faster networking. Furthermore, licensing models that charge per CPU core or capacity exacerbate costs, forcing organizations into substantial capital expenditures. These license models compel customers to purchase less optimal hardware to contain software licensing costs.

How VergeOS Reduces the Cost of Inefficiency

With a streamlined architecture, VergeOS maximizes hardware resource utilization. Its efficient code base and integrated design enable organizations to achieve optimal performance using commodity or existing hardware, reducing initial capital expenditures and ongoing operational expenses. VergeIO licenses VergeOS per-server without penalties for using high-core-count or high-capacity servers.

The High Cost of HCI Data Availability

HCI solutions employ synchronous mirroring—continuous real-time data duplication across nodes—to protect against hardware failures. Vendors commonly refer to redundancy levels as Replication Factor (RF) or Fault Tolerance Level (“failures to tolerate” or FTT). Nutanix refers to protection from one node failure as Replication Factor 2 (RF2), meaning two copies of data are maintained. VMware terms this configuration Failures to Tolerate of 1 (FTT=1).

To protect from two simultaneous node failures or multiple drive failures across nodes, Nutanix uses Replication Factor 3 (RF3)—three data copies—while VMware uses FTT=2. This triple redundancy greatly increases storage capacity and resource requirements. RF3 requires at least five nodes, becoming prohibitively expensive for smaller deployments. In larger environments, limiting resiliency to two node failures is insufficient, as risk increases with node count.

These requirements force prioritizing specific workloads for enhanced protection (RF3), relegating others to standard availability (RF2). Limited redundancy beyond RF3 leads organizations to increase the cluster count per site, resulting in cluster sprawl, which in turn causes additional administrative complexity, higher costs, and uneven availability guarantees.

To maintain performance during node failures, Nutanix and VMware require reserving a portion of resources on each server equal to the capacity of one full node. In a four-server environment, 25% of each server’s resources are reserved for failover, which substantially reduces the available capacity during regular production operations.

How VergeOS Delivers Cost-Effective Data Availability

VergeOS leverages ioGuardian, a deduplicated third-copy data protection method. This efficiently safeguards against multiple simultaneous hardware failures without excessive storage overhead or node count requirements of traditional RF3 implementations. ioGuardian provides robust availability at an economical cost, without requiring workload prioritization, delivering superior resilience at a lower price and complexity.

No reservation of server resources is required. If a node fails, VergeIO’s ioOptimize technology intelligently and automatically reallocates affected VMs to other nodes based on each VM’s resource demands and available server capacities.

The High Cost of HCI Data Protection

The Practice of Snapshotting

Snapshotting commonly provides additional recovery points beyond the capabilities of backup software. However, snapshot-intensive environments impose severe performance penalties, resulting in increased storage I/O and network resource demands. Frequent snapshots or long-term snapshot retention require complex metadata management, demanding more powerful servers, additional memory, and faster storage media. This results in escalated hardware and licensing costs, especially in per-core or per-capacity licensing models common to HCI.

Snapshot chains or numerous simultaneous snapshots greatly increase complexity, hindering disaster recovery processes. Restoring across heterogeneous hardware or hypervisor environments becomes challenging, restricting operational flexibility.

How VergeOS Simplifies Data Protection

VergeOS utilizes ioClone technology, integrated with its global inline deduplication, to create space-efficient, independent snapshots with minimal metadata overhead. ioClone’s architecture supports near-continuous snapshot execution and indefinite retention without performance degradation, enabling rapid and efficient data protection without the need for costly hardware upgrades or complex snapshot management. The combination of ioGuardian and ioClone also reduces the organization’s dependency on backup, lowering the costs of backup software licensing and backup hardware infrastructure.

The High Cost of HCI Inflexibility

The hidden costs of HCI architectures imposing strict hardware compatibility and homogeneity requirements are significant. Expanding storage or compute resources mandates identical hardware, limiting flexibility and increasing long-term infrastructure costs. Adding nodes of different brands, generations, or capabilities creates additional clusters, which fragment management and reduce efficiency.

How VergeOS Enhances Infrastructure Flexibility

VergeOS supports heterogeneous hardware environments, enabling organizations to integrate diverse hardware configurations into unified, scalable clusters seamlessly. This flexibility reduces costs, simplifies expansion, and maximizes investment longevity, enabling adaptive infrastructure growth without imposed constraints on homogeneity.

overcome the hidden costs of HCI inflexibility

An Example of The Hidden Costs of HCI vs. VergeOS

Consider a three-node infrastructure using traditional Hyperconverged Infrastructure (HCI), where the organization’s goal is to maintain continuous data availability even after two simultaneous node failures. Traditional HCI solutions, such as Nutanix or VMware vSAN, require at least five nodes configured with Replication Factor 3 (RF3), or a Fault Tolerance Level of 2 (FTT=2), ensuring continuous availability despite two node failures. In addition, these solutions require maintaining sufficient free storage capacity at all times to accommodate a complete rebuild in the event of node failures, thereby reserving capacity equivalent to an entire node, which further reduces usable storage space.

Because the customer wants to leverage their existing hardware—a heterogeneous mix of Dell and HPE servers—traditional HCI platforms present immediate compatibility and cost challenges. Traditional HCI requires uniform hardware for seamless operation, which adds complexity and cost.

Cost Analysis for Traditional HCI

Achieving protection from two simultaneous node failures requires:

  • Minimum Node Count: 5 nodes (uniform hardware required).
  • Replication Method: RF3 or FTT=2 (three synchronous copies of all data).
  • Usable Capacity: Reduced to approximately 33% due to triple mirroring overhead.
  • Reserved Free Capacity: Additional storage space equal to one node’s full storage capacity, always kept available to allow immediate rebuilds after failures.

In this scenario, the customer faces:

  • The necessity of purchasing additional uniform hardware due to vendor compatibility guidelines.
  • Higher software licensing costs, typically calculated per CPU core.
  • Significant reserved resources on each node (compute and storage) are allocated exclusively for node failure scenarios.

This dramatically increases capital and operational expenses, requiring significant investment in new hardware and licenses, thereby negating the anticipated HCI savings.

Cost Analysis with VergeOS

In the same scenario, VergeOS offers substantial advantages:

  • Minimum Node Count: 3 nodes (uses existing Dell and HPE hardware).
  • Replication Method: Integrated distributed mirroring combined with VergeOS’s independent, deduplicated third data copy via ioGuardian, which can be installed on any available standby server.
  • Usable Capacity: Approximately 50% (due to two-way mirroring), augmented by ioGuardian’s deduplication efficiency.
  • Reserved Free Capacity: Minimal additional storage capacity needed due to ioGuardian’s efficient data protection strategy, reducing rebuild space requirements compared to traditional RF3 architectures.

With VergeOS, you benefit from:

  • No need for uniform hardware, allowing immediate use of existing Dell and HPE servers.
  • Reduced licensing and hardware costs, as no additional nodes or extensive resource reservations are required.
  • Enhanced data availability beyond traditional two-node failure protection without extensive reserved storage, reducing overhead and complexity.

Summary of Cost Benefits

Traditional HCI requires two additional nodes (totaling five) and mandates uniform hardware, increasing both capital and operational expenses, compounded by large reserved capacity requirements for rebuilding data. VergeOS provides superior resilience, operational continuity, and cost efficiency by leveraging existing heterogeneous hardware and substantially reducing the need for reserved rebuild capacity.

Conclusion

While hyperconverged infrastructure initially promises simplicity, efficiency, and cost savings, underlying architectural limitations quickly surface as substantial hidden costs. Challenges such as insufficient convergence, operational inefficiencies, costly availability and protection schemes, and restrictive infrastructure flexibility erode promised benefits. Organizations should carefully assess these hidden costs when evaluating HCI solutions, prioritizing converged, integrated infrastructures like VergeOS that fundamentally address these critical challenges, enabling efficient, cost-effective, and future-ready IT environments.

Register for our HCI Data Availability Analysis

Filed Under: HCI Tagged With: , , , ,

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Triple mirroring, or Replication Factor 3 (RF3), presents hidden challenges when evaluating VMware alternatives and hyperconverged architectures. Although RF3 enhances data resiliency beyond single drive or node failures, many organizations face unexpected costs, operational complexity, and scalability constraints, which are pronounced in smaller or larger deployments, where resource efficiency and manageability become critical issues. These unexpected triple mirroring challenges force most IT professionals to avoid the technology completely, but with the right design, a triple mirror can provide better availability at a lower cost.

The Basics of Triple Mirroring

Triple mirroring replicates data across three separate nodes or storage devices. This approach ensures data availability even if two nodes, or drives with those nodes, fail simultaneously, providing a higher degree of redundancy and resilience compared to dual replication (RF2). On the surface, this redundancy sounds ideal for critical workloads, but deeper examination reveals several substantial drawbacks.

Costly and Impractical for Small Environments

One major limitation of triple mirroring is its inefficiency in smaller environments. RF3 configurations require a minimum of five nodes to maintain adequate redundancy and quorum, even though the storage and computing demands may not necessitate this level of investment. For small data centers or departmental deployments, this requirement results in a prohibitively high entry cost, as the infrastructure must be oversized to achieve adequate redundancy.

Triple Mirroring requires five nodes

In these scenarios, the high infrastructure cost, coupled with a reduced usable storage capacity—approximately a 66% reduction compared to single-copy storage—can be problematic, as it inflates the total cost of ownership without providing proportional operational value.

Scalability Challenges for Large Deployments

At the opposite end of the spectrum, large-scale deployments find triple mirroring delivers diminishing returns. In environments spanning dozens or more nodes, the risk of multiple simultaneous failures increases. For instance, protecting against dual node failures in a 32-node cluster may prove insufficient, as larger clusters inherently present greater statistical risks. Consequently, the likelihood of multiple concurrent failures can quickly exceed what RF3 is designed to handle. Moreover, even if an organization was willing to implement a higher redundancy level, such as “quad-mirroring,” available solutions do not offer this capability.

As environments scale, the inefficiency of triple mirroring grows exponentially. It requires a substantial upfront investment in storage and computing capacity to maintain adequate redundancy across all nodes. These demands escalate infrastructure complexity, increasing management overhead and resource consumption.

The Hidden Costs of Triple Mirroring

Triple mirroring introduces hidden long-term costs that extend beyond maintaining a third copy of data. First, the third data copy requires deployment on identical, production-class servers and storage media, as triple mirroring technologies cannot dedicate specific nodes solely for data storage without also utilizing them for compute tasks.

Secondly, the significant expense associated with triple mirroring forces IT teams into complex trade-offs, as they manage multiple storage volumes with varying resiliency levels, with some set at RF2 and others at RF3. This dual-resiliency model increases complexity and compels IT to prioritize specific applications, granting them higher availability while relegating less critical applications to lower protection levels. Additionally, many solutions employing RF3 lack the flexibility to revert seamlessly from RF3 to RF2 or upgrade from RF2 to RF3 without requiring a complete recovery of VM data from backup, which adds further operational burdens, limits flexibility, and increases the risk of downtime.

A More Efficient Alternative with VergeIO ioGuardian

A far more efficient and powerful solution is VergeIO’s ioGuardian technology, which delivers the resiliency advantages of triple mirroring without the associated overhead and complexity. ioGuardian maintains an independent, deduplicated third copy of data on a single, cost-effective storage server, reducing storage overhead and increasing resiliency beyond two node failures.

Triple mirroring on a secondary server that extends beyond the capabilities of a triple mirror.

For smaller environments, ioGuardian offers an optimal approach by requiring only one additional, affordable storage server, eliminating the need for multiple fully provisioned nodes. In larger environments, ioGuardian provides extensive protection against numerous simultaneous node failures by delivering a robust, real-time, and accessible backup repository that is independent of the primary operational infrastructure. With ioGuardian, organizations no longer need to selectively allocate protection levels, ensuring comprehensive availability for all applications.

Simplified Management and Lower Costs with ioGuardian

VergeIO’s ioGuardian simplifies infrastructure management, reduces complexity, and lowers costs. Its dedicated storage server approach minimizes resource consumption, as the server focuses solely on secure data storage and recovery, rather than hosting active virtual workloads. Furthermore, ioGuardian’s global inline deduplication dramatically reduces storage capacity requirements, directly decreasing both capital and operational expenses.

How ioGuardian Works

By decoupling redundancy from operational nodes and centralizing it into ioGuardian’s dedicated backup repository, organizations achieve superior data resiliency. In scenarios involving multiple simultaneous node or drive failures—situations that even exceed the protections provided by RF3—ioGuardian immediately ensures continuous data availability through real-time redirection of requests. When production nodes detect missing or unavailable data blocks due to hardware failures, VergeOS transparently redirects these requests to redundant data blocks stored within the independent ioGuardian server, enabling uninterrupted application performance and seamless user access.

Eliminate Triple Mirroring. Backup and Data Availability in one simple solution.

Critically, ioGuardian maintains operational efficiency by deferring data migration back into primary production nodes until failed drives or nodes are physically replaced or explicitly marked for replacement. When the drives are replaced, ioGuardian automatically repopulates data onto the repaired or newly replaced hardware, minimizing unnecessary data movement and preserving the performance of the production infrastructure.

Additionally, ioGuardian serves as a comprehensive traditional backup solution. It enables organizations to restore virtual machines, individual files, or specific data versions directly from their repository when needed, providing reliable access to historical data snapshots. This capability simplifies recovery processes following data corruption events, accidental deletions, or ransomware attacks, thereby enhancing overall data integrity and reducing costs further.

Conclusion: Rethinking Triple Mirroring with VergeIO

While triple mirroring initially appears straightforward for ensuring data availability and redundancy, its hidden complexities, high costs, and scalability limitations often overshadow its intended benefits. Modern IT infrastructures demand more flexible, efficient, and scalable redundancy solutions. VergeIO’s ioGuardian offers organizations—from small departmental setups to large enterprise clusters—a simplified, robust, and cost-effective approach to data protection, surpassing traditional triple-mirroring strategies. Data redundancy is one aspect of a VMware Alternative’s capabilities that IT should consider. They should look for solutions that encompass all aspects of data availability as part of their selection process.

To explore these advantages further, join our upcoming live webinar, Comparing HCI Architecture.

Filed Under: Protection Tagged With: , ,

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Comparing VMware Alternative Storage

As part of a VMware exit, comparing the VMware alternative storage capabilities is as important as selecting an alternative hypervisor for the organization’s future infrastructure software. Organizations typically examine Nutanix’s Controller Virtual Machine (CVM) architecture against VergeIO’s integrated VergeFS storage within VergeOS. Although both approaches virtualize SAN functionality onto the same servers, creating a virtual SAN (vSAN), the two designs differ. These differences impact resource utilization, operational complexity, stability, and costs.

Understanding vSAN Resource Efficiency

Nutanix employs a storage-as-a-VM architecture using a dedicated CVM running on each node. This CVM consumes substantial resources—between 16GB and 32GB of RAM or more, alongside multiple virtual CPUs (up to 22 vCPUs per node). This significant resource footprint reduces available capacity for production workloads, driving higher infrastructure costs and decreasing resource efficiency, particularly in smaller environments.

VergeIO integrates storage directly into VergeOS via its VergeFS file system, eliminating the need for dedicated controller VMs. This integration ensures more node resources remain available for production workloads, improving resource efficiency without requiring additional hardware investments.

Sizing and Stability of vSAN Alternatives

Sizing complexities are inherent in Nutanix’s CVM-based model. Determining the ideal CVM size is critical yet challenging. Undersized CVMs lead to bottlenecks or instability, while oversized CVMs consume unnecessary resources. Nutanix users sometimes experience stability issues such as random CVM reboots, leading to a reactive response rather than root-cause analysis from support teams.

VergeIO’s integrated storage approach within the OS kernel eliminates these sizing complexities, providing predictable and stable performance without the risk of bottlenecks or instability. This inherent stability reduces operational overhead, making VergeIO a reliable VMware alternative with minimal administrative intervention.

Understanding vSAN: Performance

Comparing VMware Alternative Storage

When under load or insufficiently resourced, Nutanix’s CVMs negatively impact VM performance on the same node, leading to broader performance degradation across the cluster. VergeIO’s integrated approach ensures stable and consistent resource utilization, avoiding disruptions and translating directly into improved cluster reliability and responsiveness.

VergeIO consistently publishes detailed performance benchmarks, demonstrating VergeOS’s real-world capabilities. Nutanix, in contrast, has provided minimal transparency regarding vSAN performance. While no benchmark perfectly represents every customer scenario, VergeIO’s results offer valuable insights.

Recent VergeOS performance benchmarks show impressive outcomes, including over 1.5 million read IOPS, 23 GB/s throughput on a 25 GB/s network, and realistic 64k block sizes at less than one penny per IOPS. Independent testing by StorageReview demonstrated VergeOS handling 1,000 virtual desktops booting in 71 seconds. These benchmarks substantiate VergeIO’s superior performance and transparency claims compared to Nutanix.

Management and Troubleshooting a VMware Alternative

Nutanix’s separate CVM introduces additional management complexity, requiring administrators to monitor, maintain, and troubleshoot an extra software layer. Issues such as CVM reboots or resource contention complicate troubleshooting, increasing operational burdens.

By removing the separate CVM layer, VergeOS simplifies operations. Administrators gain straightforward monitoring, simplified diagnostics, and faster issue resolution, all integrated transparently within VergeOS.

Understanding vSAN Controller Resiliency

A key consideration when comparing the VMware alternative storage capabilities is how the solution handles resiliency. Nutanix promotes its distributed “leader” CVM architecture, allowing any node to assume cluster leadership. However, this approach offers limited practical advantage, as additional leader nodes beyond simultaneous node failure tolerance are redundant. Nutanix clusters configured with RF3 can survive two simultaneous node failures, reducing the practical value of additional leaders.

VergeIO’s ioGuardian provides redundancy and resilience beyond traditional N+2 redundancy. While conventional three-way mirroring (N+2) continuously replicates data across three nodes, ioGuardian enhances protection by maintaining an independent, deduplicated third copy, stored separately from the primary mirrored dataset. This highly available backup replaces traditional backups and becomes integral to your continuous availability strategy.

IoGuardian seamlessly and transparently serves data back to the production environment in real time during multi-node or multi-drive failures, even exceeding two nodes. Affected virtual machines instantly retrieve the necessary data from the ioGuardian storage, eliminating downtime and ensuring uninterrupted operations without manual intervention or complex recovery workflows.

Combining immediate real-time data availability, reduced infrastructure overhead, and simplified management, ioGuardian substantially surpasses the protection and operational simplicity achievable with standard N+2 redundancy approaches.

How a vSAN Impacts TCO

Nutanix’s CVMs impact total cost of ownership (TCO) beyond licensing. They require substantial resources, necessitating larger hardware configurations, increasing capital expenditures, and increasing ongoing licensing expenses.

In contrast, VergeIO’s integrated VergeFS reduces the software footprint, simplifies licensing with straightforward per-server pricing, and optimizes existing or commodity hardware. This approach considerably lowers infrastructure costs, positioning VergeIO as a cost-effective VMware alternative storage solution.

Summary of VergeOS Advantages

Comparing VMware alternative storage capabilities reveals that VergeIO’s integration of VergeFS into VergeOS provides significant practical advantages over Nutanix’s CVM-based storage model. It maximizes resource efficiency, ensures consistent and reliable performance, simplifies management, and reduces infrastructure and licensing costs. These combined advantages position VergeIO as an attractive VMware alternative storage solution, ideal for organizations seeking efficiency, stability, simplicity, and cost-effectiveness.

To further explore VMware alternative data availability and see these considerations in action, join our upcoming VergeIO webinar. Our experts will provide an in-depth comparison of hyperconverged and ultraconverged architectures, highlighting performance benchmarks, operational simplicity, and cost-efficiency. Register now to ensure your infrastructure decisions align with your organization’s strategic priorities.

Our latest white paper, “HCI Data Availability Analysis,” delves into the crucial issue of maintaining availability in Hyperconverged and Ultraconverged architectures by comparing how Nutanix and VergeIO ensure data access during hardware failures.

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