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

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

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

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...