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Gartner Highlights Five Things That Private Cloud Is Not

Ongoing hype around private cloud computing is creating misperceptions about private cloud, according to Gartner, Inc. To help reduce the hype and identify the real value of private cloud computing for IT leaders, Gartner explains five common misconceptions about private cloud.

"The growth of private cloud computing is being driven by the rapid penetration of virtualization and virtualization management, the growth of cloud computing offerings and pressure to deliver IT faster and cheaper," said Tom Bittman, vice president and distinguished analyst at Gartner. "However, in the rush to respond to these pressures, IT organizations need to be careful to avoid the hype, and, instead, should focus on a private cloud computing effort that makes the most business sense."

The five misconceptions about private cloud and the corresponding realities are:

1. Private Cloud Is Not Virtualization

Server and infrastructure virtualization are important foundations for private cloud computing. However, virtualization and virtualization management are not, by themselves, private cloud computing. Virtualization makes it easier to dynamically and granularly pool and reallocate infrastructure resources (servers, desktop, storage, networking, middleware, etc.). However, virtualization can be enabled in many ways, including virtual machines, operating systems (OSs) or middleware containers, robust OSs, storage abstraction software, grid computing software, and horizontal scaling and cluster tools.

Private cloud computing leverages some form of virtualization to create a cloud computing service. Private cloud computing is a form of cloud computing that is used by only one organization, or that ensures that an organization is completely isolated from others.

2. Private Cloud Is Not Just About Cost Reduction

An enterprise can reduce operational costs with a private cloud by eliminating common, rote tasks for standard offerings. A private cloud can reallocate resources more efficiently to meet enterprise requirements, possibly by reducing capital expenses for hardware.

However, private clouds require investment in automation software, and the savings alone might not justify the cost. As such, cost reduction is not the primary benefit of private cloud computing. The benefits of self-service, automation behind the self-service interface and metering tied to usage are primarily agility, speed to market, ability to scale to dynamic demand or to go after short windows of opportunity, and ability for a business unit to experiment.

3. Private Cloud Is Not Necessarily On-Premises

Private cloud computing is defined by privacy, not location, ownership or management responsibility. While the majority of private clouds will be on-premises (based on the evolution of existing virtualization investments), a growing percentage of private clouds will be outsourced and/or off-premises. Third-party private clouds will have a more flexible definition of "privacy." A third-party private cloud offering might share data center facilities with others, could share equipment over time (from a pool of available resources), and could share resources, but be isolated by a virtual private network (VPN) and everything in between.

4. Private Cloud Is Not Only Infrastructure as a Service (IaaS)

Server virtualization is a major trend and, therefore, a major enabler for private cloud computing. However, private cloud is not limited in any way to IaaS. For example, with development and test offerings, enabling higher-level Platform as a Service (PaaS) offerings for developers makes more sense than a simple virtual machine provisioning service.

Today, the fastest growing segment of cloud computing is IaaS. However, IaaS only provides the lowest-level data center resources in an easy-to-consume way, and doesn't fundamentally change how IT is done. Developers will use PaaS to create new applications designed to be cloud-aware, producing fundamentally new services that could be very differentiating, compared with old applications.

5. Private Cloud Is Not Always Going to Be Private

In many ways, Gartner analysts said that private cloud is a stopgap measure. Over time, public cloud services will mature, improving service levels, security and compliance management. New public cloud services targeting specific requirements will emerge. Some private clouds will be moved completely to the public cloud. However, the majority of private cloud services will evolve to enable hybrid cloud computing, expanding the effective capacity of a private cloud to leverage public cloud services and third-party resources.

"By starting with a private cloud, IT is positioning itself as the broker of all services for the enterprise, whether they are private, public, hybrid or traditional," Mr. Bittman said. "A private cloud that evolves to hybrid or even public could retain ownership of the self-service, and, therefore, the customer and the interface. This is a part of the vision for the future of IT that we call 'hybrid IT.'"

Additional information is available in the Gartner report: Five Things That Private Cloud Is Not

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Gartner Highlights Five Things That Private Cloud Is Not

Ongoing hype around private cloud computing is creating misperceptions about private cloud, according to Gartner, Inc. To help reduce the hype and identify the real value of private cloud computing for IT leaders, Gartner explains five common misconceptions about private cloud.

"The growth of private cloud computing is being driven by the rapid penetration of virtualization and virtualization management, the growth of cloud computing offerings and pressure to deliver IT faster and cheaper," said Tom Bittman, vice president and distinguished analyst at Gartner. "However, in the rush to respond to these pressures, IT organizations need to be careful to avoid the hype, and, instead, should focus on a private cloud computing effort that makes the most business sense."

The five misconceptions about private cloud and the corresponding realities are:

1. Private Cloud Is Not Virtualization

Server and infrastructure virtualization are important foundations for private cloud computing. However, virtualization and virtualization management are not, by themselves, private cloud computing. Virtualization makes it easier to dynamically and granularly pool and reallocate infrastructure resources (servers, desktop, storage, networking, middleware, etc.). However, virtualization can be enabled in many ways, including virtual machines, operating systems (OSs) or middleware containers, robust OSs, storage abstraction software, grid computing software, and horizontal scaling and cluster tools.

Private cloud computing leverages some form of virtualization to create a cloud computing service. Private cloud computing is a form of cloud computing that is used by only one organization, or that ensures that an organization is completely isolated from others.

2. Private Cloud Is Not Just About Cost Reduction

An enterprise can reduce operational costs with a private cloud by eliminating common, rote tasks for standard offerings. A private cloud can reallocate resources more efficiently to meet enterprise requirements, possibly by reducing capital expenses for hardware.

However, private clouds require investment in automation software, and the savings alone might not justify the cost. As such, cost reduction is not the primary benefit of private cloud computing. The benefits of self-service, automation behind the self-service interface and metering tied to usage are primarily agility, speed to market, ability to scale to dynamic demand or to go after short windows of opportunity, and ability for a business unit to experiment.

3. Private Cloud Is Not Necessarily On-Premises

Private cloud computing is defined by privacy, not location, ownership or management responsibility. While the majority of private clouds will be on-premises (based on the evolution of existing virtualization investments), a growing percentage of private clouds will be outsourced and/or off-premises. Third-party private clouds will have a more flexible definition of "privacy." A third-party private cloud offering might share data center facilities with others, could share equipment over time (from a pool of available resources), and could share resources, but be isolated by a virtual private network (VPN) and everything in between.

4. Private Cloud Is Not Only Infrastructure as a Service (IaaS)

Server virtualization is a major trend and, therefore, a major enabler for private cloud computing. However, private cloud is not limited in any way to IaaS. For example, with development and test offerings, enabling higher-level Platform as a Service (PaaS) offerings for developers makes more sense than a simple virtual machine provisioning service.

Today, the fastest growing segment of cloud computing is IaaS. However, IaaS only provides the lowest-level data center resources in an easy-to-consume way, and doesn't fundamentally change how IT is done. Developers will use PaaS to create new applications designed to be cloud-aware, producing fundamentally new services that could be very differentiating, compared with old applications.

5. Private Cloud Is Not Always Going to Be Private

In many ways, Gartner analysts said that private cloud is a stopgap measure. Over time, public cloud services will mature, improving service levels, security and compliance management. New public cloud services targeting specific requirements will emerge. Some private clouds will be moved completely to the public cloud. However, the majority of private cloud services will evolve to enable hybrid cloud computing, expanding the effective capacity of a private cloud to leverage public cloud services and third-party resources.

"By starting with a private cloud, IT is positioning itself as the broker of all services for the enterprise, whether they are private, public, hybrid or traditional," Mr. Bittman said. "A private cloud that evolves to hybrid or even public could retain ownership of the self-service, and, therefore, the customer and the interface. This is a part of the vision for the future of IT that we call 'hybrid IT.'"

Additional information is available in the Gartner report: Five Things That Private Cloud Is Not

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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 ...