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Internet and Cloud Creating Network Blind Spots

Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom.

The survey of more than 500 networking, operations, cloud, and architecture professionals also uncovered a surprising shortage of skilled workers requiring 65% of respondents to rely on third-party resources for network operations.

These findings paint a concerning picture as organizations struggle to meet demand for modern IT networks.

Cloud and Internet Reliance Leads to Greater Network Complexity

With 98% of companies using or planning to use cloud infrastructure and 95% enabling remote workers, the network has become increasingly more complex, as noted by 78% of respondents. Network endpoints are spread far and wide and often exist in workers' homes which makes it challenging to gain the visibility necessary to ensure uptime, performance, and security.

An additional challenge is the lack of information provided by ISPs and cloud providers, leading 80% to state that internet and cloud environments create network blind spots which can often create delays in issue remediation. These findings indicate that most companies don't have proper network operations and observability tools for today's modern IT environment.

Lack of Skilled Teams a Growing Challenge

When asked about the specific challenges they face with network operations management, 41% pointed to a lack of needed skillsets, while not having enough operations personnel was cited by 31%. Digging deeper to understand what is inhibiting teams' ability to grow, nearly half (48%) of respondents said candidates lack the needed skills, and 45% pointed to a general lack of available candidates.

Not surprisingly, 65% of organizations are turning to third parties for network operations support, a stop-gap measure to fill the void, but not a long-term solution. Thus, few teams are gaining the hands-on experience necessary to develop the capabilities they need to manage the network themselves. This means a greater reliance on tools and third-party data

Teams Lack Critical Data and Learn About Issues from Users

Unfortunately, 84% of network professionals indicated they regularly learn about issues from users, which means users are experiencing performance problems before the network team knows. This is a clear reflection of the lack of information network teams have access to. In fact, 95% of respondents say they do not get the information they need from ISPs and cloud providers. According to 76% of respondents, slow or missing data directly impedes resolution times.

"The results of this survey serve to highlight some of the biggest issues network operations teams are facing today," said Mike Melillo, Senior Director, Network Management Solutions, Broadcom. "Ensuring the performance of the network is mission-critical for every business. Yet, the data shows that teams aren't getting the support, staff, or tools they need to make their jobs simpler. Given the importance of the network for modern business, the industry needs to continue to work to collect, correlate and normalize multi-vendor network data that produces intelligent remediation recommendations and focused triage workflows and helps resolve the challenges captured in this research project."

Methodology: Networking, operations, cloud, and architecture professionals at medium to global enterprise companies representing all seniority levels were invited to participate in a survey on their company's network operations practices. The survey was administered electronically, and participants were offered a token compensation for their participation. A total of 505 qualified participants completed the survey. All participants had enterprise security responsibilities. Participants were from 5 continents, providing a global perspective.

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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 ...

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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.

Internet and Cloud Creating Network Blind Spots

Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom.

The survey of more than 500 networking, operations, cloud, and architecture professionals also uncovered a surprising shortage of skilled workers requiring 65% of respondents to rely on third-party resources for network operations.

These findings paint a concerning picture as organizations struggle to meet demand for modern IT networks.

Cloud and Internet Reliance Leads to Greater Network Complexity

With 98% of companies using or planning to use cloud infrastructure and 95% enabling remote workers, the network has become increasingly more complex, as noted by 78% of respondents. Network endpoints are spread far and wide and often exist in workers' homes which makes it challenging to gain the visibility necessary to ensure uptime, performance, and security.

An additional challenge is the lack of information provided by ISPs and cloud providers, leading 80% to state that internet and cloud environments create network blind spots which can often create delays in issue remediation. These findings indicate that most companies don't have proper network operations and observability tools for today's modern IT environment.

Lack of Skilled Teams a Growing Challenge

When asked about the specific challenges they face with network operations management, 41% pointed to a lack of needed skillsets, while not having enough operations personnel was cited by 31%. Digging deeper to understand what is inhibiting teams' ability to grow, nearly half (48%) of respondents said candidates lack the needed skills, and 45% pointed to a general lack of available candidates.

Not surprisingly, 65% of organizations are turning to third parties for network operations support, a stop-gap measure to fill the void, but not a long-term solution. Thus, few teams are gaining the hands-on experience necessary to develop the capabilities they need to manage the network themselves. This means a greater reliance on tools and third-party data

Teams Lack Critical Data and Learn About Issues from Users

Unfortunately, 84% of network professionals indicated they regularly learn about issues from users, which means users are experiencing performance problems before the network team knows. This is a clear reflection of the lack of information network teams have access to. In fact, 95% of respondents say they do not get the information they need from ISPs and cloud providers. According to 76% of respondents, slow or missing data directly impedes resolution times.

"The results of this survey serve to highlight some of the biggest issues network operations teams are facing today," said Mike Melillo, Senior Director, Network Management Solutions, Broadcom. "Ensuring the performance of the network is mission-critical for every business. Yet, the data shows that teams aren't getting the support, staff, or tools they need to make their jobs simpler. Given the importance of the network for modern business, the industry needs to continue to work to collect, correlate and normalize multi-vendor network data that produces intelligent remediation recommendations and focused triage workflows and helps resolve the challenges captured in this research project."

Methodology: Networking, operations, cloud, and architecture professionals at medium to global enterprise companies representing all seniority levels were invited to participate in a survey on their company's network operations practices. The survey was administered electronically, and participants were offered a token compensation for their participation. A total of 505 qualified participants completed the survey. All participants had enterprise security responsibilities. Participants were from 5 continents, providing a global perspective.

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.