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IT Pros Say: Cloud Needs a Makeover

Josh Stella

It's not especially surprising that a new IT survey shows that cloud use for business and government poses challenges. All transformative technologies do. It's the extent of agreement — 96 percent say cloud needs a "makeover" — and nature of the challenges that's worth examining. In significant numbers across the board, respondents cited cloud complexity, compliance and security, cost control, speed of delivery, and domain expertise as the cloud problems their organizations were working to overcome this year.

The Three Cs and Beyond

Compliance, complexity, and cost were the obstacles to effective cloud management that garnered the three top trouble spots. The survey yielded specific complaints around each of those.

Compliance refers to businesses and government agencies or their contractors making certain that internal policies (usually structured around security and system reliability concerns) and regulatory demands (around NIST SP 800-53, HIPAA, ITAR, and other laws) are met. In the survey, almost 44 percent of respondents identified ensuring compliance and security as a top cloud challenge. 39 percent said security and compliance "is slowing us down."

And, when asked to prioritize the chief reason that cloud needs an overhaul, the second most popular response was "it needs to be easier to keep secure," with "it needs to be simplified and easier to use" coming in at number one.

Indeed, turning to ease of use, the nature of cloud's complexity problem was laid bare in several parts of the survey as well. Almost 42 percent said that "managing increasing cloud complexity" was a foremost concern. When asked why their company failed to get the most out of cloud, respondents emphasized that C-level executives (26.1 percent), IT leadership (35.8 percent), and developers (20.3 percent) "don't understand cloud complexity."

Contributing directly to the complexity conundrum are the number of tools and services organizations use and the nature of the problems that tooling can create. In order to make the cloud deliver on business expectations, more than half of the respondents cited high numbers of tools and services in use: 30.6 percent at 6 to 10, 15.8 percent at 11 to 15, and 6.8 percent at 15 or more. Another 38.4 percent use at least 3 to 5 tools and services to make cloud deliver. Tooling developed in house wasn't an answer to complexity either. A whopping 83 percent of respondents indicated that creating in-house solutions only leads to more problems.

The specific complaints are enlightening: in-house tooling requires specialists and time to maintain the tools; in-house tooling involves a lot of egos and, thus, a lot of politics; adopting newly available cloud services is made difficult with our in-house tooling; and, adopting new application architectures is made difficult with our in-house tooling.

The survey further revealed a direct relationship between complexity via tooling and the other top trouble spot, cost. Nearly 70 percent of respondents said they were spending almost as much or more on cloud tooling and services than on the cloud itself! Controlling costs overall was a chief problem that 47.7 percent of respondents were working to overcome this year, with some noting that not only does cloud need to be less expensive in general, but it needs to be easier to reduce costs. Nevertheless, compared with traditional data center operations, 57.7 percent agreed that the cloud had saved them money. A shadow on that strong figure is that another 25 percent were not achieving the savings they expected with the cloud.

In addition to compliance, complexity, and cost issues, almost 36 percent of respondents were concerned about meeting business agility demands — referring to the speed at which they could deliver their product to market with cloud utilized. Finally, a significant 26.5 percent worried about acquiring personnel with sufficient domain expertise in the cloud to make their organization efficient.

What's the Solution?

Undoubtedly, different practitioners will advocate different approaches to the cloud problems this survey and other surveys point out. But, if you can easily go fast, see everything, and keep a system right with one holistic approach, you can dramatically reduce the time spent and money wasted on complicated, multi-tooled operations and compliance regimes that don't take full advantage of cloud's innate character.

No matter the route chosen, businesses and government need an easy-to-understand solution, built for and with cloud, that requires only basic domain knowledge to operate, but that's powerful enough to manage scaled systems.

Survey Methodology: Just over half of the survey respondents identified as IT operations personnel. Others included developers, cloud architects, DevOps engineers, and executives. Organizationally, commercial enterprises, government agencies, small/mid-sized businesses, and startups were all represented. And, the survey covered all phases of cloud maturity in its field of respondents: 35.5 percent using a mix of cloud and on-premise data centers, 29 percent planning to adopt the cloud within the next year, 20.6 percent in the process of transitioning to the cloud, 14.8 percent fully in the cloud.

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 ...

IT Pros Say: Cloud Needs a Makeover

Josh Stella

It's not especially surprising that a new IT survey shows that cloud use for business and government poses challenges. All transformative technologies do. It's the extent of agreement — 96 percent say cloud needs a "makeover" — and nature of the challenges that's worth examining. In significant numbers across the board, respondents cited cloud complexity, compliance and security, cost control, speed of delivery, and domain expertise as the cloud problems their organizations were working to overcome this year.

The Three Cs and Beyond

Compliance, complexity, and cost were the obstacles to effective cloud management that garnered the three top trouble spots. The survey yielded specific complaints around each of those.

Compliance refers to businesses and government agencies or their contractors making certain that internal policies (usually structured around security and system reliability concerns) and regulatory demands (around NIST SP 800-53, HIPAA, ITAR, and other laws) are met. In the survey, almost 44 percent of respondents identified ensuring compliance and security as a top cloud challenge. 39 percent said security and compliance "is slowing us down."

And, when asked to prioritize the chief reason that cloud needs an overhaul, the second most popular response was "it needs to be easier to keep secure," with "it needs to be simplified and easier to use" coming in at number one.

Indeed, turning to ease of use, the nature of cloud's complexity problem was laid bare in several parts of the survey as well. Almost 42 percent said that "managing increasing cloud complexity" was a foremost concern. When asked why their company failed to get the most out of cloud, respondents emphasized that C-level executives (26.1 percent), IT leadership (35.8 percent), and developers (20.3 percent) "don't understand cloud complexity."

Contributing directly to the complexity conundrum are the number of tools and services organizations use and the nature of the problems that tooling can create. In order to make the cloud deliver on business expectations, more than half of the respondents cited high numbers of tools and services in use: 30.6 percent at 6 to 10, 15.8 percent at 11 to 15, and 6.8 percent at 15 or more. Another 38.4 percent use at least 3 to 5 tools and services to make cloud deliver. Tooling developed in house wasn't an answer to complexity either. A whopping 83 percent of respondents indicated that creating in-house solutions only leads to more problems.

The specific complaints are enlightening: in-house tooling requires specialists and time to maintain the tools; in-house tooling involves a lot of egos and, thus, a lot of politics; adopting newly available cloud services is made difficult with our in-house tooling; and, adopting new application architectures is made difficult with our in-house tooling.

The survey further revealed a direct relationship between complexity via tooling and the other top trouble spot, cost. Nearly 70 percent of respondents said they were spending almost as much or more on cloud tooling and services than on the cloud itself! Controlling costs overall was a chief problem that 47.7 percent of respondents were working to overcome this year, with some noting that not only does cloud need to be less expensive in general, but it needs to be easier to reduce costs. Nevertheless, compared with traditional data center operations, 57.7 percent agreed that the cloud had saved them money. A shadow on that strong figure is that another 25 percent were not achieving the savings they expected with the cloud.

In addition to compliance, complexity, and cost issues, almost 36 percent of respondents were concerned about meeting business agility demands — referring to the speed at which they could deliver their product to market with cloud utilized. Finally, a significant 26.5 percent worried about acquiring personnel with sufficient domain expertise in the cloud to make their organization efficient.

What's the Solution?

Undoubtedly, different practitioners will advocate different approaches to the cloud problems this survey and other surveys point out. But, if you can easily go fast, see everything, and keep a system right with one holistic approach, you can dramatically reduce the time spent and money wasted on complicated, multi-tooled operations and compliance regimes that don't take full advantage of cloud's innate character.

No matter the route chosen, businesses and government need an easy-to-understand solution, built for and with cloud, that requires only basic domain knowledge to operate, but that's powerful enough to manage scaled systems.

Survey Methodology: Just over half of the survey respondents identified as IT operations personnel. Others included developers, cloud architects, DevOps engineers, and executives. Organizationally, commercial enterprises, government agencies, small/mid-sized businesses, and startups were all represented. And, the survey covered all phases of cloud maturity in its field of respondents: 35.5 percent using a mix of cloud and on-premise data centers, 29 percent planning to adopt the cloud within the next year, 20.6 percent in the process of transitioning to the cloud, 14.8 percent fully in the cloud.

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 ...