Skip to main content

Public Sector Challenged by IT Complexity

Pete Goldin
APMdigest

Despite rapid adoption of new technologies to improve operations, a new survey from Clarus Research Group and Splunk found half of public sector IT professionals (51 percent) feel new IT technology paradigms, such as cloud and DevOps, are adding complexity to their organization rather than simplifying operations.

The findings also revealed that lack of resources remains a substantial problem for public sector. Selected by nearly half (44 percent) of respondents, public sector IT professionals cited insufficient IT resources (i.e. budget and personnel) as the biggest risk to their organization or agency over the next year.

While 71 percent of public sector IT professionals agree insights from IT data are important to their organization, the combination of increased complexity, limited resources and continued use of manual processes is making it difficult for public sector organizations to gain valuable insights from their IT data and achieve greater visibility into systems.

Additional findings include:

■ Lack of funding and budget constraints was selected by close to half (45 percent) of respondents as the top difficulty in managing IT operations.

■ Nearly four in 10 (38 percent) say complexity of IT systems and technology is a top difficulty in managing IT operations.

■ More than half (53 percent) of public sector IT decision makers feel their organization does not have end-to-end visibility across IT systems to foresee issues ahead of time, which often results in operational inefficiencies, delays and waste.

■ Almost two-thirds (64 percent) of respondents revealed their organization is still using manual processes to gather information to solve issues and 58 percent admitted their troubleshooting is manual and ad hoc. Nearly half (48 percent) also say they either don’t have or don’t know if they have the ability to pinpoint problems because their systems are managed in silos.

IT data formats and ingestion is another obstacle public sector organizations face when trying to gain insights. According to the survey, half (50 percent) of public sector IT pros say data in different formats or types has been a problem when trying to diagnose IT issues, and 40 percent agreed that data ingestion and normalization is cumbersome and tedious. These challenges are undoubtedly affecting organizations’ abilities to be operationally and financially efficient. The vast amount of data and formats available make it difficult for public sector organizations to determine where to start and what is relevant to the problem.

The survey also revealed the IT technologies that public sector organizations will expand use of over the next few years. Server monitoring and analytics (74 percent) and network infrastructure monitoring analytics (71 percent) were the top IT solutions decision makers expect to expand more. In addition, nearly seven in 10 public sector IT pros (69 percent) said they expect to see use of commercial off-the-shelf (COTS) solutions increase, including nearly nine of 10 (87 percent) federal national security respondents.

Methodology: Clarus Research Group surveyed 634 federal, state and local government and higher education IT decision makers. The survey was conducted on behalf of Splunk through online interviews in May 2016.

Pete Goldin is Editor and Publisher of APMdigest

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 ...

Public Sector Challenged by IT Complexity

Pete Goldin
APMdigest

Despite rapid adoption of new technologies to improve operations, a new survey from Clarus Research Group and Splunk found half of public sector IT professionals (51 percent) feel new IT technology paradigms, such as cloud and DevOps, are adding complexity to their organization rather than simplifying operations.

The findings also revealed that lack of resources remains a substantial problem for public sector. Selected by nearly half (44 percent) of respondents, public sector IT professionals cited insufficient IT resources (i.e. budget and personnel) as the biggest risk to their organization or agency over the next year.

While 71 percent of public sector IT professionals agree insights from IT data are important to their organization, the combination of increased complexity, limited resources and continued use of manual processes is making it difficult for public sector organizations to gain valuable insights from their IT data and achieve greater visibility into systems.

Additional findings include:

■ Lack of funding and budget constraints was selected by close to half (45 percent) of respondents as the top difficulty in managing IT operations.

■ Nearly four in 10 (38 percent) say complexity of IT systems and technology is a top difficulty in managing IT operations.

■ More than half (53 percent) of public sector IT decision makers feel their organization does not have end-to-end visibility across IT systems to foresee issues ahead of time, which often results in operational inefficiencies, delays and waste.

■ Almost two-thirds (64 percent) of respondents revealed their organization is still using manual processes to gather information to solve issues and 58 percent admitted their troubleshooting is manual and ad hoc. Nearly half (48 percent) also say they either don’t have or don’t know if they have the ability to pinpoint problems because their systems are managed in silos.

IT data formats and ingestion is another obstacle public sector organizations face when trying to gain insights. According to the survey, half (50 percent) of public sector IT pros say data in different formats or types has been a problem when trying to diagnose IT issues, and 40 percent agreed that data ingestion and normalization is cumbersome and tedious. These challenges are undoubtedly affecting organizations’ abilities to be operationally and financially efficient. The vast amount of data and formats available make it difficult for public sector organizations to determine where to start and what is relevant to the problem.

The survey also revealed the IT technologies that public sector organizations will expand use of over the next few years. Server monitoring and analytics (74 percent) and network infrastructure monitoring analytics (71 percent) were the top IT solutions decision makers expect to expand more. In addition, nearly seven in 10 public sector IT pros (69 percent) said they expect to see use of commercial off-the-shelf (COTS) solutions increase, including nearly nine of 10 (87 percent) federal national security respondents.

Methodology: Clarus Research Group surveyed 634 federal, state and local government and higher education IT decision makers. The survey was conducted on behalf of Splunk through online interviews in May 2016.

Pete Goldin is Editor and Publisher of APMdigest

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 ...