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Four Practical Steps to Private Cloud Computing

If it is your job to translate overhyped demands to take your business ‘To The Cloud!’ you know there is not enough reality in cloud computing. You cannot start from scratch, nor can you simply deploy dynamic virtualization and call it done. You must accommodate legacy investments, architectural spaghetti, ‘technical debt’, manual processes and more. So where do you start?

In our recent book, Visible Ops - Private Cloud: From Virtualization to Private Cloud in 4 Practical Steps, my co-authors (Kurt Milne, Jeanne Morain) and I spoke with dozens of IT leaders about their experiences building their own ‘private clouds’. By documenting the successes and failures common to the best performers, we came up with a realistic stepwise process that builds on legacy investments, capitalizes on existing skills, and incorporates necessary processes, to deliver the benefits of cloud computing.

Phase 1: Cut through the cloud clutter

The first step entails planning and communicating objectives, managing initial proof of concept efforts, and developing competency roadmaps.

Successful cloud implementations result from executing a business strategy, not rolling out new IT projects. You need to cut through the hype by establishing a service portfolio view of infrastructure and applications, measuring current service performance and cost, setting goals for service improvement, and establishing some initial success, before you start transforming virtual infrastructure into private cloud.

Understanding application performance and response times, service fulfillment cycles, service level metrics, key competencies, operating and capital costs, etc. allows you to plan achievable improvements. This in turn helps to cut through the hype in order to show your business what they should realistically expect from your private cloud strategy.

Phase 2: Design services, not systems

With a plan in place, start to design business optimized cloud services, enable one-touch service ordering, and implement a repeatable approach for build and deploy.
Business services must be standardized, cataloged, and automated to establish repeatable user-driven onramps to deploying resources. This requires a new approach to Business Service Management to avoid an ever-expanding complex catalog of bespoke ‘services’ that are never deployed the same way twice.

This is a critical difference between building virtualized applications and delivering cloud services. IT-centric approaches that elevate administrative complexity and control will not work in dynamic cloud environments. Some essential aspects of legacy BSM frameworks remain important, but cloud computing will kill complex controls in favor of simplified enablement that puts business users in charge.

Phase 3: Orchestrate and optimize resources

With service design complete, you should update monitoring and alerting, codify policy-based event responses, and automate resource changes and workload moves.
Technologies like application performance management, resource optimization, and process automation are immensely important in a private cloud environment. An effective private cloud relies on technologies that monitor real-time performance of end-to-end business services, detect variations from defined performance models, diagnose the true root cause of problems, match performance requirements to available resource pool capacity, and automatically adjust and optimize resource allocation to match.

This is much more than just response time measurement and live migration. Effective private clouds optimize complete business services, not just virtual machines. Live migration is important, but not sufficient, to deliver a successful private cloud.

Phase 4: Align and accelerate business results

With the heavy technology lifting done, complete the transition to a resource rental model by reshaping consumption behavior and streamlining response to business needs.

This entails moving targeted workloads to your private cloud to leverage its benefits, understanding and communicating the service cost, quality, and agility measures of each cloud environment, and actively reshaping demand for IT resources using a rental model.

This change in business behavior enables private cloud to be successful in ways automated virtualization cannot. Virtualization is an IT-centric technology that does not require business users to change their behaviors, as IT is still in charge. With cloud computing, business users are in charge, so they must ‘learn’ some of the discipline needed to maintain acceptable cost, security, risk, performance, etc.

Summary

This is of course a simplified version of the practical four-step process from virtualization to cloud. Clearly developing and delivering your own private cloud is not even this simple. However, with a concise, practical, and realistic approach born of the real-world successes and failures of those who have already done it, as documented in Visible Ops - Private Cloud: From Virtualization to Private Cloud in 4 Practical Steps, you can achieve phenomenal results, drive IT efficiency, and deliver significant business benefits with your own private cloud.

About Andi Mann

Andi Mann is Vice President of Strategic Solutions at CA Technologies. With over 20 years’ experience across four continents, Andi has deep expertise of enterprise software on cloud, mainframe, midrange, server and desktop systems. Andi has worked within IT departments for governments and corporations, from small businesses to global multi-nationals; with several large enterprise software vendors; and as a leading industry analyst advising enterprises, governments, and IT vendors – from startups to the worlds’ largest companies. He has been widely published including in the New York Times, USA Today, CIO, ComputerWorld, InformationWeek, TechTarget, and more. He has presented around the world on virtualization, cloud, automation, and IT management, at events such as Gartner ITxpo, VMworld, CA World, Interop, Cloud Computing Expo, SAPPHIRE, Citrix Synergy, Cloud Slam, and others. Andi is a co-author of the popular handbook, Visible Ops – Private Cloud; he blogs at Andi Mann – Übergeek, and tweets as @AndiMann.

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For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

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Four Practical Steps to Private Cloud Computing

If it is your job to translate overhyped demands to take your business ‘To The Cloud!’ you know there is not enough reality in cloud computing. You cannot start from scratch, nor can you simply deploy dynamic virtualization and call it done. You must accommodate legacy investments, architectural spaghetti, ‘technical debt’, manual processes and more. So where do you start?

In our recent book, Visible Ops - Private Cloud: From Virtualization to Private Cloud in 4 Practical Steps, my co-authors (Kurt Milne, Jeanne Morain) and I spoke with dozens of IT leaders about their experiences building their own ‘private clouds’. By documenting the successes and failures common to the best performers, we came up with a realistic stepwise process that builds on legacy investments, capitalizes on existing skills, and incorporates necessary processes, to deliver the benefits of cloud computing.

Phase 1: Cut through the cloud clutter

The first step entails planning and communicating objectives, managing initial proof of concept efforts, and developing competency roadmaps.

Successful cloud implementations result from executing a business strategy, not rolling out new IT projects. You need to cut through the hype by establishing a service portfolio view of infrastructure and applications, measuring current service performance and cost, setting goals for service improvement, and establishing some initial success, before you start transforming virtual infrastructure into private cloud.

Understanding application performance and response times, service fulfillment cycles, service level metrics, key competencies, operating and capital costs, etc. allows you to plan achievable improvements. This in turn helps to cut through the hype in order to show your business what they should realistically expect from your private cloud strategy.

Phase 2: Design services, not systems

With a plan in place, start to design business optimized cloud services, enable one-touch service ordering, and implement a repeatable approach for build and deploy.
Business services must be standardized, cataloged, and automated to establish repeatable user-driven onramps to deploying resources. This requires a new approach to Business Service Management to avoid an ever-expanding complex catalog of bespoke ‘services’ that are never deployed the same way twice.

This is a critical difference between building virtualized applications and delivering cloud services. IT-centric approaches that elevate administrative complexity and control will not work in dynamic cloud environments. Some essential aspects of legacy BSM frameworks remain important, but cloud computing will kill complex controls in favor of simplified enablement that puts business users in charge.

Phase 3: Orchestrate and optimize resources

With service design complete, you should update monitoring and alerting, codify policy-based event responses, and automate resource changes and workload moves.
Technologies like application performance management, resource optimization, and process automation are immensely important in a private cloud environment. An effective private cloud relies on technologies that monitor real-time performance of end-to-end business services, detect variations from defined performance models, diagnose the true root cause of problems, match performance requirements to available resource pool capacity, and automatically adjust and optimize resource allocation to match.

This is much more than just response time measurement and live migration. Effective private clouds optimize complete business services, not just virtual machines. Live migration is important, but not sufficient, to deliver a successful private cloud.

Phase 4: Align and accelerate business results

With the heavy technology lifting done, complete the transition to a resource rental model by reshaping consumption behavior and streamlining response to business needs.

This entails moving targeted workloads to your private cloud to leverage its benefits, understanding and communicating the service cost, quality, and agility measures of each cloud environment, and actively reshaping demand for IT resources using a rental model.

This change in business behavior enables private cloud to be successful in ways automated virtualization cannot. Virtualization is an IT-centric technology that does not require business users to change their behaviors, as IT is still in charge. With cloud computing, business users are in charge, so they must ‘learn’ some of the discipline needed to maintain acceptable cost, security, risk, performance, etc.

Summary

This is of course a simplified version of the practical four-step process from virtualization to cloud. Clearly developing and delivering your own private cloud is not even this simple. However, with a concise, practical, and realistic approach born of the real-world successes and failures of those who have already done it, as documented in Visible Ops - Private Cloud: From Virtualization to Private Cloud in 4 Practical Steps, you can achieve phenomenal results, drive IT efficiency, and deliver significant business benefits with your own private cloud.

About Andi Mann

Andi Mann is Vice President of Strategic Solutions at CA Technologies. With over 20 years’ experience across four continents, Andi has deep expertise of enterprise software on cloud, mainframe, midrange, server and desktop systems. Andi has worked within IT departments for governments and corporations, from small businesses to global multi-nationals; with several large enterprise software vendors; and as a leading industry analyst advising enterprises, governments, and IT vendors – from startups to the worlds’ largest companies. He has been widely published including in the New York Times, USA Today, CIO, ComputerWorld, InformationWeek, TechTarget, and more. He has presented around the world on virtualization, cloud, automation, and IT management, at events such as Gartner ITxpo, VMworld, CA World, Interop, Cloud Computing Expo, SAPPHIRE, Citrix Synergy, Cloud Slam, and others. Andi is a co-author of the popular handbook, Visible Ops – Private Cloud; he blogs at Andi Mann – Übergeek, and tweets as @AndiMann.

Related Links:

12 Things You Need to Know About Application Performance Management in the Cloud

Hot Topics

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...