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Private Cloud Outlook 2025: A Definitive Cloud Reset

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom.

More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so.

Private cloud is also now a strategic equal for AI and cloud-native apps, with 66% preferring to run container and Kubernetes-based applications on private cloud or a mix of public and private, while 55% prefer private cloud for AI model training, tuning and inference.

"This report makes it clear: private cloud is a strategic platform for IT modernization," said Prashanth Shenoy, VP of Product Marketing, VMware Cloud Foundation Division (VCF) at Broadcom. "Customers are intentionally architecting for flexibility, placing workloads in environments that offer the best balance of performance, control, and cost efficiency. The cloud reset presents an opportunity to create a more effective, secure and cost-efficient IT environment. Organizations that strategically adopt a modern private cloud can better support secure GenAI innovation, improve fiscal visibility, and accelerate workload repatriation."

Security, GenAI, and Cost Predictability Accelerate the Shift to Private Cloud

As IT leaders modernize their infrastructure, they are increasingly turning to private cloud to meet a range of critical needs, from securing sensitive data to managing unpredictable GenAI workloads to improving financial visibility.

  • 92% trust private cloud for security and compliance needs.
  • 66% are "very" or "extremely" concerned about public cloud compliance, and security is cited as the leading driver for workload repatriation from public cloud.
  • Data privacy and security concerns (49%) top the list of GenAI adoption challenges.
  • Organizations are choosing private cloud environments for AI workloads at nearly the same rate as public cloud (55% vs. 56%).
  • 90% value private cloud’s financial visibility and predictability.
  • 94% report at least some level of waste on public cloud spend.
  • 49% believe more than 25% of their public cloud spend is wasted, creating significant optimization opportunities.

Accelerating the Private Cloud Momentum

Real-world public cloud experiences, the rapid rise of GenAI workloads, and increasing demands for security, compliance, and cost predictability are driving this strategic cloud realignment. To fully capitalize on private cloud advantages, organizations must address two key challenges: overcoming siloed IT teams and a perpetuating skills gap.

Respondents identified siloed IT teams present the greatest challenge to private cloud adoption (33%), and 30% cite a lack of in-house skills/expertise as a barrier to private cloud adoption. Organizations that transition from technology silos to platform teams can focus on upskilling staff to permanently close the skills gap and reduce reliance on professional services. The report found that 81% are now structuring their technical organizations around a platform team rather than technology silos.

Methodology: The report is based on a global survey conducted by market research firm Illuminas on behalf of Broadcom. The survey was fielded from March 6 to April 4, 2025, and included 1,800 senior IT decision-makers across small, medium-sized, and large enterprises in North America, Europe, and Asia Pacific. Respondents represented sectors such as financial services, government, healthcare, insurance, and pharmaceuticals.

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

Private Cloud Outlook 2025: A Definitive Cloud Reset

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom.

More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so.

Private cloud is also now a strategic equal for AI and cloud-native apps, with 66% preferring to run container and Kubernetes-based applications on private cloud or a mix of public and private, while 55% prefer private cloud for AI model training, tuning and inference.

"This report makes it clear: private cloud is a strategic platform for IT modernization," said Prashanth Shenoy, VP of Product Marketing, VMware Cloud Foundation Division (VCF) at Broadcom. "Customers are intentionally architecting for flexibility, placing workloads in environments that offer the best balance of performance, control, and cost efficiency. The cloud reset presents an opportunity to create a more effective, secure and cost-efficient IT environment. Organizations that strategically adopt a modern private cloud can better support secure GenAI innovation, improve fiscal visibility, and accelerate workload repatriation."

Security, GenAI, and Cost Predictability Accelerate the Shift to Private Cloud

As IT leaders modernize their infrastructure, they are increasingly turning to private cloud to meet a range of critical needs, from securing sensitive data to managing unpredictable GenAI workloads to improving financial visibility.

  • 92% trust private cloud for security and compliance needs.
  • 66% are "very" or "extremely" concerned about public cloud compliance, and security is cited as the leading driver for workload repatriation from public cloud.
  • Data privacy and security concerns (49%) top the list of GenAI adoption challenges.
  • Organizations are choosing private cloud environments for AI workloads at nearly the same rate as public cloud (55% vs. 56%).
  • 90% value private cloud’s financial visibility and predictability.
  • 94% report at least some level of waste on public cloud spend.
  • 49% believe more than 25% of their public cloud spend is wasted, creating significant optimization opportunities.

Accelerating the Private Cloud Momentum

Real-world public cloud experiences, the rapid rise of GenAI workloads, and increasing demands for security, compliance, and cost predictability are driving this strategic cloud realignment. To fully capitalize on private cloud advantages, organizations must address two key challenges: overcoming siloed IT teams and a perpetuating skills gap.

Respondents identified siloed IT teams present the greatest challenge to private cloud adoption (33%), and 30% cite a lack of in-house skills/expertise as a barrier to private cloud adoption. Organizations that transition from technology silos to platform teams can focus on upskilling staff to permanently close the skills gap and reduce reliance on professional services. The report found that 81% are now structuring their technical organizations around a platform team rather than technology silos.

Methodology: The report is based on a global survey conducted by market research firm Illuminas on behalf of Broadcom. The survey was fielded from March 6 to April 4, 2025, and included 1,800 senior IT decision-makers across small, medium-sized, and large enterprises in North America, Europe, and Asia Pacific. Respondents represented sectors such as financial services, government, healthcare, insurance, and pharmaceuticals.

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...