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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

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...