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Reaping the Benefits of Cloud Begins with Facing the Realities of Implementation

Alastair Pooley
Snow Software

The flexibility and ease of deployment of cloud technology demonstrated its worth during the pandemic. Gartner expects global spending on cloud services will reach over $482 billion in 2022, up from $313 billion in 2020. With no end to its growth trajectory in sight, it's now time to review the current state of cloud infrastructure within the enterprise — how effective it has been and what else could be done to drive up its value.

A survey from Snow Software polled more than 500 IT leaders in the US and UK to determine the current state of cloud infrastructure. Nearly half of the IT leaders who responded agreed that cloud was critical to operations during the pandemic with the majority deploying a hybrid cloud strategy consisting of both public and private clouds. Unsurprisingly, over the last 12 months, the majority of respondents had increased overall cloud spend — a substantial increase over the 2020 findings.


Meanwhile, many IT leaders believe they will have to add to cloud services to support demand as hybrid working becomes the norm. This figure was significantly higher in the US compared to the UK.


Additionally, IT leaders plan to move less workloads to private cloud in 2021 compared to last year. In 2020, a fifth said they were bringing cloud workloads back on-premises whereas this year only three percent of US IT leaders and less than one percent of UK IT leaders plan to move workloads to private cloud.


When asked about the main reasons for relying on cloud computing, scalability and flexibility was cited by many of organizations, with another solid group of IT executives stating it is the best environment to develop, test and launch products and services.

However, many of them have found that they are now experiencing an array of cloud and infrastructure management challenges from cybersecurity threats to skill gaps.

Issues Arising

One area where this is particularly apparent is cybersecurity. Approximately one-third of IT leaders felt that mounting cybersecurity threats are their greatest infrastructure management challenge. This highlights that while the majority believe security is a core driver for cloud adoption, it is also a key concern for many IT departments who are not equipped with the right staff/skillset to adapt their security approach accordingly.

Additional challenges cited include lack of integration between new and old infrastructure technologies, meeting governance and compliance requirements and managing spend. Perhaps unsurprisingly, mitigating concerns about cybersecurity protections is at the top of IT leaders' list of cloud management challenges they'd wish to solve in the blink of an eye — along with a lack of skilled IT staff and lack of cloud standardization.


Cloud Brings Questions as Well as Answers

The acceleration of cloud infrastructure over the last year has caused some management challenges for organizations. Only a fraction of IT managers, and IT directors, rated themselves as experts in Cloud technology — highlighting that greater education is needed for mid-level executives for them to manage cloud infrastructure effectively.

These figures become even more worrying when it comes to managing spend. While the majority of respondents claimed leadership is familiar with cloud investment, a significant minority say leadership gets updates but do not question spend. Although there is no need for leadership to get involved if cloud spend is within budget, it has been found that cloud investments can sometimes bring unexpected (and expensive) costs. At that stage, leadership will jump in to understand the budget demands, but this can be tricky if they haven't previously been engaged.

Cloud investments are showing no sign of slowing down, and while the benefits cannot be denied, without the necessary training, education, and visibility to effectively implement and manage cloud, organizations could be limiting their ROI.

Alastair Pooley is CIO of Snow Software

Hot Topics

The Latest

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 ...

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.

Reaping the Benefits of Cloud Begins with Facing the Realities of Implementation

Alastair Pooley
Snow Software

The flexibility and ease of deployment of cloud technology demonstrated its worth during the pandemic. Gartner expects global spending on cloud services will reach over $482 billion in 2022, up from $313 billion in 2020. With no end to its growth trajectory in sight, it's now time to review the current state of cloud infrastructure within the enterprise — how effective it has been and what else could be done to drive up its value.

A survey from Snow Software polled more than 500 IT leaders in the US and UK to determine the current state of cloud infrastructure. Nearly half of the IT leaders who responded agreed that cloud was critical to operations during the pandemic with the majority deploying a hybrid cloud strategy consisting of both public and private clouds. Unsurprisingly, over the last 12 months, the majority of respondents had increased overall cloud spend — a substantial increase over the 2020 findings.


Meanwhile, many IT leaders believe they will have to add to cloud services to support demand as hybrid working becomes the norm. This figure was significantly higher in the US compared to the UK.


Additionally, IT leaders plan to move less workloads to private cloud in 2021 compared to last year. In 2020, a fifth said they were bringing cloud workloads back on-premises whereas this year only three percent of US IT leaders and less than one percent of UK IT leaders plan to move workloads to private cloud.


When asked about the main reasons for relying on cloud computing, scalability and flexibility was cited by many of organizations, with another solid group of IT executives stating it is the best environment to develop, test and launch products and services.

However, many of them have found that they are now experiencing an array of cloud and infrastructure management challenges from cybersecurity threats to skill gaps.

Issues Arising

One area where this is particularly apparent is cybersecurity. Approximately one-third of IT leaders felt that mounting cybersecurity threats are their greatest infrastructure management challenge. This highlights that while the majority believe security is a core driver for cloud adoption, it is also a key concern for many IT departments who are not equipped with the right staff/skillset to adapt their security approach accordingly.

Additional challenges cited include lack of integration between new and old infrastructure technologies, meeting governance and compliance requirements and managing spend. Perhaps unsurprisingly, mitigating concerns about cybersecurity protections is at the top of IT leaders' list of cloud management challenges they'd wish to solve in the blink of an eye — along with a lack of skilled IT staff and lack of cloud standardization.


Cloud Brings Questions as Well as Answers

The acceleration of cloud infrastructure over the last year has caused some management challenges for organizations. Only a fraction of IT managers, and IT directors, rated themselves as experts in Cloud technology — highlighting that greater education is needed for mid-level executives for them to manage cloud infrastructure effectively.

These figures become even more worrying when it comes to managing spend. While the majority of respondents claimed leadership is familiar with cloud investment, a significant minority say leadership gets updates but do not question spend. Although there is no need for leadership to get involved if cloud spend is within budget, it has been found that cloud investments can sometimes bring unexpected (and expensive) costs. At that stage, leadership will jump in to understand the budget demands, but this can be tricky if they haven't previously been engaged.

Cloud investments are showing no sign of slowing down, and while the benefits cannot be denied, without the necessary training, education, and visibility to effectively implement and manage cloud, organizations could be limiting their ROI.

Alastair Pooley is CIO of Snow Software

Hot Topics

The Latest

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 ...

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.