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Should I Stay or Should I Go? A Cloudy Decision

Scott Leatherman
Virtana

If you've been operating in the cloud for some time now, chances are your business has changed since you first made that move and particularly during the current climate. Has your cloud usage grown considerably — and your OpEx costs? Is that just the cost of doing business in the cloud? It doesn't have to be. Here's how you can rationalize your infrastructure and determine if there are cloud expenses you can reclaim and even if it makes sense to move some of your cloud deployments into co-location.

The rush to the public cloud has now slowed as organizations realized that it is not a "one size fits all" solution. The main issue is the lack of deep visibility into the performance of applications provided by the host. Our own research has recently revealed that 32% of public cloud resources are currently under-utilized, and without proper direction and guidance, this will remain the case. What is needed is real-time data and intelligent recommendations to lower costs and assure performance.

The Need for AIOps

In order to optimize cloud resources, a third-party AIOps based resource is needed. This will provide an independent and granular view of how applications are using capacity and if it is right-sized. In addition, it will monitor the performance of the applications in real-time and provide metrics and analytics to eliminate bottlenecks. The allocated capacity can also be monitored to ensure an accurate match to workload requirements via real-time performance data.

Although the major hosts provide cost optimization tools, these are not very accurate. Analysis of billing and how it matches capacity over time as well as in real-time is what is needed for the cloud to remain a vital part in IT infrastructure. Armed with this information you can plan capacity purchases and discover wasted spend. By using a single platform for cloud management, you can monitor your infrastructure, plan capacity, and eliminate performance risks. Performance bottlenecks can be predicted before they affect clients and SLAs with multi-conditional alerting powered by advanced anomaly detection.

Cloud solutions are not only publicly provided by the likes of AWS and Azure. Co-location is also a strong option where your applications are managed on your behalf by a system integrator. This is increasingly becoming a stronger option for more business-critical applications. But to determine which is best for you, you need to start with the facts.

The "Cloud" promises IT organizations unprecedented value in the form of business agility, faster innovation, superior scalability and most importantly — cost savings. For many organizations, it is at the core of their IT digital transformation strategy. It is a disruptive force that requires application workload behavior knowledge, careful planning and collaboration from well-informed, trusted advisors.

2 Paths to the Cloud

As a first step, enterprises frequently target a subset of their less critical on-premises applications for migration to the public cloud. Typically, organizations will take one of two paths to the cloud.

A. Going cloud-native. Rewrite your application to use resources offered by a cloud provider.

B. Lift and shift. Very minimal or zero code changes to the application. Largely, just replicate the application in the cloud.

The faster time-to-production choice is to "lift and shift" the targeted applications to a Cloud Service Provider's Infrastructure as a Service (IaaS). In the lift and shift option, the advantage is a reduction in the cost incurred in the physical infrastructure like hardware, floor space, cooling, security etc. and the management of that infrastructure. Savings will differ depending on your unique computing resource needs, workload refactoring and business models.

Answering the Key Questions

Even in its simplest form, IaaS migrations must be carefully planned requiring answers to some fundamental questions:

1. Will my application perform as expected in a public cloud? (Application Fitness)

2. How much will it cost to run my applications in a public cloud? (OpEx)

3. Which cloud service provider is the best choice for my applications? (Cost and Fit)

IT managers need answers to these questions before the actual migration is performed. As most internal IT organizations don't have deep cloud expertise, the question becomes who you can trust to provide you with the answers — to help you make better business decisions.

As technology and the cloud stands to play an ever-increasing role throughout organizations, ensuring that you're adopting the right type of infrastructure specifically for your business has never been more vital for continued success. Choosing a service that provides the answers to your key questions before the actual migration takes place and prepares you with vital insights into your applications and workloads targeted for cloud migration has to be an important part of the decision-making process.

As organizations continue to battle the COVID-19 storm, understanding the product that will overhaul your IT infrastructure, before you fully buy into it, is going to provide the confidence and assurance you need to make that decision a little less cloudy.

Scott Leatherman is CMO of Virtana

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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 ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Should I Stay or Should I Go? A Cloudy Decision

Scott Leatherman
Virtana

If you've been operating in the cloud for some time now, chances are your business has changed since you first made that move and particularly during the current climate. Has your cloud usage grown considerably — and your OpEx costs? Is that just the cost of doing business in the cloud? It doesn't have to be. Here's how you can rationalize your infrastructure and determine if there are cloud expenses you can reclaim and even if it makes sense to move some of your cloud deployments into co-location.

The rush to the public cloud has now slowed as organizations realized that it is not a "one size fits all" solution. The main issue is the lack of deep visibility into the performance of applications provided by the host. Our own research has recently revealed that 32% of public cloud resources are currently under-utilized, and without proper direction and guidance, this will remain the case. What is needed is real-time data and intelligent recommendations to lower costs and assure performance.

The Need for AIOps

In order to optimize cloud resources, a third-party AIOps based resource is needed. This will provide an independent and granular view of how applications are using capacity and if it is right-sized. In addition, it will monitor the performance of the applications in real-time and provide metrics and analytics to eliminate bottlenecks. The allocated capacity can also be monitored to ensure an accurate match to workload requirements via real-time performance data.

Although the major hosts provide cost optimization tools, these are not very accurate. Analysis of billing and how it matches capacity over time as well as in real-time is what is needed for the cloud to remain a vital part in IT infrastructure. Armed with this information you can plan capacity purchases and discover wasted spend. By using a single platform for cloud management, you can monitor your infrastructure, plan capacity, and eliminate performance risks. Performance bottlenecks can be predicted before they affect clients and SLAs with multi-conditional alerting powered by advanced anomaly detection.

Cloud solutions are not only publicly provided by the likes of AWS and Azure. Co-location is also a strong option where your applications are managed on your behalf by a system integrator. This is increasingly becoming a stronger option for more business-critical applications. But to determine which is best for you, you need to start with the facts.

The "Cloud" promises IT organizations unprecedented value in the form of business agility, faster innovation, superior scalability and most importantly — cost savings. For many organizations, it is at the core of their IT digital transformation strategy. It is a disruptive force that requires application workload behavior knowledge, careful planning and collaboration from well-informed, trusted advisors.

2 Paths to the Cloud

As a first step, enterprises frequently target a subset of their less critical on-premises applications for migration to the public cloud. Typically, organizations will take one of two paths to the cloud.

A. Going cloud-native. Rewrite your application to use resources offered by a cloud provider.

B. Lift and shift. Very minimal or zero code changes to the application. Largely, just replicate the application in the cloud.

The faster time-to-production choice is to "lift and shift" the targeted applications to a Cloud Service Provider's Infrastructure as a Service (IaaS). In the lift and shift option, the advantage is a reduction in the cost incurred in the physical infrastructure like hardware, floor space, cooling, security etc. and the management of that infrastructure. Savings will differ depending on your unique computing resource needs, workload refactoring and business models.

Answering the Key Questions

Even in its simplest form, IaaS migrations must be carefully planned requiring answers to some fundamental questions:

1. Will my application perform as expected in a public cloud? (Application Fitness)

2. How much will it cost to run my applications in a public cloud? (OpEx)

3. Which cloud service provider is the best choice for my applications? (Cost and Fit)

IT managers need answers to these questions before the actual migration is performed. As most internal IT organizations don't have deep cloud expertise, the question becomes who you can trust to provide you with the answers — to help you make better business decisions.

As technology and the cloud stands to play an ever-increasing role throughout organizations, ensuring that you're adopting the right type of infrastructure specifically for your business has never been more vital for continued success. Choosing a service that provides the answers to your key questions before the actual migration takes place and prepares you with vital insights into your applications and workloads targeted for cloud migration has to be an important part of the decision-making process.

As organizations continue to battle the COVID-19 storm, understanding the product that will overhaul your IT infrastructure, before you fully buy into it, is going to provide the confidence and assurance you need to make that decision a little less cloudy.

Scott Leatherman is CMO of Virtana

Hot Topics

The Latest

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 ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...