Skip to main content

Moving to the Cloud? Now What?

Insights from a cloud survey

Given all the talk about virtualization and cloud computing these days, and the number of vendors promoting related products, it should come as no surprise that enterprise companies are rapidly migrating applications to virtual and cloud environments. A recent survey of IT managers in North America, conducted by Precise, revealed that 41 percent of companies have migrated sales and marketing, HR, finance and/or ERP applications to the cloud this year. Participants told us that they would continue their aggressive push to the cloud next year.

Here are a few highlights:

• In 2011, 39% of organizations moved email and collaboration systems to virtual infrastructure, followed by IT management (33%) sales & marketing (20%) finance/HR/ERP (21%) and security (13%).

• In 2012, 33% of respondents report that they will move finance/ERP /HR applications to the cloud, followed by e-mail and collaboration software (23%) and IT management applications (21%).

Given the public perception that security and reliability are weaker in the public cloud, enterprises are favoring private clouds today and in the near future, according to our survey. Eventually, 37% of companies say they will migrate 61% or more of their applications to a private cloud environment, while only 6% of companies will do the same on a public cloud service.

This is all positive news. In a volatile global economy, virtualization and cloud computing offers enhanced agility, scalability and efficiencies for companies needing to do more with less. As the virtualization and cloud industry has matured, there are now many flavors and service providers to choose from, as dictated by your unique needs and budget. Many companies expect that after migrating, they will have more flexibility to meet business objectives and will also save money on capital investments and staff. These are valid expectations, which have already proven out in companies large and small in the past few years.

It's not all rosy, of course. The cloud is still a new infrastructure, one which is much more dynamic and flexible compared with older, static networks, physical servers and rigid legacy applications. The cloud can create more complexity and risk if an organization is unprepared to manage security, reliability, and transaction performance through the various physical and virtual layers. Because of the nature of dynamic provisioning in the cloud and server cluster architecture, it's difficult to determine which server, VM, or application instance is to blame when troubleshooting issues.

Another potential pitfall is that the shared-resource model of the cloud can become a double-edged sword. The cloud architecture can save costs through optimization of resources, yet it also increases the chances of resource contention by orders of magnitude. Your slow application may be a result of someone else's app residing on the same server or sharing the same storage pool.

The survey found that IT's number-one virtualization concern is maintaining performance and being able to effectively troubleshoot problems. After slow performance (41%), the second leading problem of managing applications in the cloud is slow time to identify the root cause of issues. This is a tough balancing act for the CIO, who needs to deliver IT agility for the business, yet at the same time deliver adequate protection for data and applications. IT service delivery folks are increasingly looking at products and services that will help run critical applications in production. It's kind of like buying insurance -- you really need it when you’re talking about high-priority business applications.

Application management technology must step up for cloud computing. It needs to see through all the virtual layers where there is constant change from moving VMs and contention on resources. The only answer is automation -- at a much grander and faster pace than in the past. It is the win-win-win for CIOs: agile provisioning, lower cost, and reliable applications.

About Zohar Gilad

Zohar Gilad is Executive Vice President, Products, Marketing and Channels at Precise Software. Before joining Precise, Zohar held several senior executive positions with Mercury Interactive, acquired by HP in 2006. At Mercury, Zohar drove expansion into new markets, creating new product categories: Load Testing, Quality Management, Application Management, and finally Business Technology Optimization. From 2000-2003, as the General Manager of the Application Management business unit, he helped grow the business from $0 to about $100M a year. Prior to joining Mercury, Zohar held software development positions at IBM and Daisy Systems.

Related Links:

www.precise.com

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 ...

Moving to the Cloud? Now What?

Insights from a cloud survey

Given all the talk about virtualization and cloud computing these days, and the number of vendors promoting related products, it should come as no surprise that enterprise companies are rapidly migrating applications to virtual and cloud environments. A recent survey of IT managers in North America, conducted by Precise, revealed that 41 percent of companies have migrated sales and marketing, HR, finance and/or ERP applications to the cloud this year. Participants told us that they would continue their aggressive push to the cloud next year.

Here are a few highlights:

• In 2011, 39% of organizations moved email and collaboration systems to virtual infrastructure, followed by IT management (33%) sales & marketing (20%) finance/HR/ERP (21%) and security (13%).

• In 2012, 33% of respondents report that they will move finance/ERP /HR applications to the cloud, followed by e-mail and collaboration software (23%) and IT management applications (21%).

Given the public perception that security and reliability are weaker in the public cloud, enterprises are favoring private clouds today and in the near future, according to our survey. Eventually, 37% of companies say they will migrate 61% or more of their applications to a private cloud environment, while only 6% of companies will do the same on a public cloud service.

This is all positive news. In a volatile global economy, virtualization and cloud computing offers enhanced agility, scalability and efficiencies for companies needing to do more with less. As the virtualization and cloud industry has matured, there are now many flavors and service providers to choose from, as dictated by your unique needs and budget. Many companies expect that after migrating, they will have more flexibility to meet business objectives and will also save money on capital investments and staff. These are valid expectations, which have already proven out in companies large and small in the past few years.

It's not all rosy, of course. The cloud is still a new infrastructure, one which is much more dynamic and flexible compared with older, static networks, physical servers and rigid legacy applications. The cloud can create more complexity and risk if an organization is unprepared to manage security, reliability, and transaction performance through the various physical and virtual layers. Because of the nature of dynamic provisioning in the cloud and server cluster architecture, it's difficult to determine which server, VM, or application instance is to blame when troubleshooting issues.

Another potential pitfall is that the shared-resource model of the cloud can become a double-edged sword. The cloud architecture can save costs through optimization of resources, yet it also increases the chances of resource contention by orders of magnitude. Your slow application may be a result of someone else's app residing on the same server or sharing the same storage pool.

The survey found that IT's number-one virtualization concern is maintaining performance and being able to effectively troubleshoot problems. After slow performance (41%), the second leading problem of managing applications in the cloud is slow time to identify the root cause of issues. This is a tough balancing act for the CIO, who needs to deliver IT agility for the business, yet at the same time deliver adequate protection for data and applications. IT service delivery folks are increasingly looking at products and services that will help run critical applications in production. It's kind of like buying insurance -- you really need it when you’re talking about high-priority business applications.

Application management technology must step up for cloud computing. It needs to see through all the virtual layers where there is constant change from moving VMs and contention on resources. The only answer is automation -- at a much grander and faster pace than in the past. It is the win-win-win for CIOs: agile provisioning, lower cost, and reliable applications.

About Zohar Gilad

Zohar Gilad is Executive Vice President, Products, Marketing and Channels at Precise Software. Before joining Precise, Zohar held several senior executive positions with Mercury Interactive, acquired by HP in 2006. At Mercury, Zohar drove expansion into new markets, creating new product categories: Load Testing, Quality Management, Application Management, and finally Business Technology Optimization. From 2000-2003, as the General Manager of the Application Management business unit, he helped grow the business from $0 to about $100M a year. Prior to joining Mercury, Zohar held software development positions at IBM and Daisy Systems.

Related Links:

www.precise.com

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 ...