Blog Archives

Create Private AI With Existing Servers

Artificial intelligence is now central to IT strategy, yet many organizations assume that meaningful progress requires new infrastructure. The assumption comes from the demands of AI workloads. They require substantial CPU and GPU power, high-throughput storage, and fast data movement.

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Reimagining VDI: The Impact of VMware Exit

A VMware exit presents an opportunity for IT leaders to reassess virtual desktop infrastructure (VDI) and infrastructure strategy as costs decrease and new compliance and security pressures arise. Embracing an infrastructure-wide consolidation can simplify operations, reduce costs, and enhance readiness for AI, transforming complex systems into a unified architecture.

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Why Cloud Repatriation is Critical Post-VMware Exit

83% of enterprise CIOs are now planning to bring workloads back on-premises—nearly doubling from 43% in late 2020. This dramatic shift toward cloud repatriation intersects perfectly with the current VMware migration crisis, creating an unprecedented opportunity for comprehensive infrastructure consolidation. The timing isn’t coincidental, and the economic case is compelling.

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Leveraging Hardware Diversity for Multi-Site IT Efficiency

Multi-site IT succeeds when hardware diversity meets software consistency—delivering flexibility, predictability, and simplicity across Edge, ROBO, Venues, and the core with VergeOS Virtual Data Centers.

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AFA Deduplication vs vSAN

The transition from VMware requires careful consideration of deduplication and storage options. All-Flash Arrays (AFAs) excel in performance but are costly, while vSAN faces latency issues due to its complex architecture. Integrated ultraconverged systems like VergeOS eliminate trade-offs, improving efficiency and reducing costs by unifying deduplication with core hypervisor functions.

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Rethinking ROBO and Edge

Enterprises with distributed operations are being compelled to reassess their ROBO and Edge strategies following Broadcom’s acquisition of VMware. Long-held assumptions about how to manage infrastructure at remote offices, branch offices (ROBO), and edge locations need to be reexamined. Beyond

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Solving Shadow AI Risk

An effective enterprise AI strategy must address the risks of Shadow AI, where employees use unauthorized AI tools. With 46-50% of employees engaging with these tools, organizations should avoid complete bans and consider partnerships with specialized cloud providers, on-premises solutions, or hybrid approaches to ensure productivity while safeguarding security and compliance.

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Practical Use Cases for On-Premises AI

There are practical use cases for on-premises AI versus using AI in the public cloud, particularly in situations that require enhanced security, data control, and regulatory compliance. By examining these specific examples, IT professionals can gain a deeper understanding of

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Enterprise AI: Key Requirements and Why It Matters

Enterprise adoption of artificial intelligence (AI) has quickly evolved from experimental projects to mission-critical business drivers. Organizations across industries are now recognizing that AI is no longer a futuristic technology, but a foundational capability, required NOW, to enable innovation, efficiency,

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Leveraging Existing Hardware is Efficient

Repurposing existing hardware with the right infrastructure software improves IT operational efficiency by extending hardware life, reducing costs, and delivering near-bare-metal performance with high availability and resiliency.

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