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Networking, Cybersecurity and Observability Are Converging

Harnessing the power of network-derived intelligence and insights is critical in detecting today's increasingly sophisticated security threats across hybrid and multi-cloud infrastructure, according to a new research study from IDC, conducted for Gigamon.

With 95% of organizations claiming to have experienced a ransomware attack in 2022, security remains top of mind for IT leaders regardless of their industry. According to the IDC White Paper, over 60% of respondents believe that today's observability solutions serve narrow requirements and fail to provide a complete view of current operating conditions.

To address today's rapidly evolving security requirements, enhancing traditional observability capabilities that rely on metrics, events, logs, and traces (MELT) with real-time network-derived intelligence and insights is essential to mitigate security risks across hybrid and multi-cloud infrastructure. Only with this deep observability can organizations find the greatest value from observability across both on-premises systems and cloud services, core and edge components, and cybersecurity functions.

"Networking, cybersecurity, and observability are becoming intertwined. IT organizations are looking to leverage an immutable source of truth and more collaborative management efforts to break down siloed technology approaches, position themselves for long-term success, and, ultimately, deliver the best possible business outcomes," said Mark Leary, Research Director with IDC. "Deep observability must be prioritized as IT organizations look to fully realize the transformational promise of a resilient and responsive digital infrastructure and continually maintain a strong security posture to meet today's digital business requirements."

Observability benefits include security, productivity and user experience

The top cited benefits of observability include security (34%), staff productivity (33%), and digital/user experience (25%). Observability also delivers a mix of both tactical (e.g., resolution, continuity, tracking) and strategic (e.g., experience, governance, innovation) benefits.

Deep observability will support automation

Over 75% of organizations use or plan to use deep observability solutions to support automation efforts in future years. Deep observability can enable a hierarchical platform-based approach in which detailed data and artificial intelligence (AI)/machine learning (ML)–driven analysis can produce a single source of truth, converge data and tools, and enable talent to deploy, operate, repair, and enhance digital infrastructures in a timely manner.

Cloud is priority

The market will see increased investments in cloud services over the next few years, with over half of respondents (51%) citing it as a priority. In fact, 72% of organizations strongly agree that cloud service intelligence should be leveraged to optimize costs and secure information. Cost from technical debt and the complexity of supporting multiple generations of infrastructure are some of the biggest barriers for organizations in achieving their digital infrastructure resiliency goals.

Network-derived intelligence can support Security

Network-derived intelligence can support adherence to SANS 20 Critical Security Controls, potentially eliminating 98% of possible attack vectors. Today, over 50% of respondents state that they actively share network intelligence across IT teams, and more than 60% of organizations are making progress in leveraging these insights in their security management practices.

"Over 90% of organizations operate in a hybrid and multi-cloud world, yet security blind spots remain a significant barrier for technology leaders looking to get the most out of their cloud investments," said Chaim Mazal, Chief Security Officer of Gigamon. "This research not only points to the critical role that deep observability plays in securing complex cloud environments but the necessary convergence of NetOps and SecOps teams in fortifying modern cybersecurity practices. "

Methodology: The findings are based on a survey, conducted by IDC, of over 900 global IT leaders across North America, APAC, and EMEA, which included a mix of major industries (financial, manufacturing, retail/wholesale, healthcare, transport/utilities, education, government, and professional services). All respondents held roles of manager or above, with key decision-making responsibilities for observability functions and solutions that span across IT operational domains, including networking, security, and cloud.

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Networking, Cybersecurity and Observability Are Converging

Harnessing the power of network-derived intelligence and insights is critical in detecting today's increasingly sophisticated security threats across hybrid and multi-cloud infrastructure, according to a new research study from IDC, conducted for Gigamon.

With 95% of organizations claiming to have experienced a ransomware attack in 2022, security remains top of mind for IT leaders regardless of their industry. According to the IDC White Paper, over 60% of respondents believe that today's observability solutions serve narrow requirements and fail to provide a complete view of current operating conditions.

To address today's rapidly evolving security requirements, enhancing traditional observability capabilities that rely on metrics, events, logs, and traces (MELT) with real-time network-derived intelligence and insights is essential to mitigate security risks across hybrid and multi-cloud infrastructure. Only with this deep observability can organizations find the greatest value from observability across both on-premises systems and cloud services, core and edge components, and cybersecurity functions.

"Networking, cybersecurity, and observability are becoming intertwined. IT organizations are looking to leverage an immutable source of truth and more collaborative management efforts to break down siloed technology approaches, position themselves for long-term success, and, ultimately, deliver the best possible business outcomes," said Mark Leary, Research Director with IDC. "Deep observability must be prioritized as IT organizations look to fully realize the transformational promise of a resilient and responsive digital infrastructure and continually maintain a strong security posture to meet today's digital business requirements."

Observability benefits include security, productivity and user experience

The top cited benefits of observability include security (34%), staff productivity (33%), and digital/user experience (25%). Observability also delivers a mix of both tactical (e.g., resolution, continuity, tracking) and strategic (e.g., experience, governance, innovation) benefits.

Deep observability will support automation

Over 75% of organizations use or plan to use deep observability solutions to support automation efforts in future years. Deep observability can enable a hierarchical platform-based approach in which detailed data and artificial intelligence (AI)/machine learning (ML)–driven analysis can produce a single source of truth, converge data and tools, and enable talent to deploy, operate, repair, and enhance digital infrastructures in a timely manner.

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The market will see increased investments in cloud services over the next few years, with over half of respondents (51%) citing it as a priority. In fact, 72% of organizations strongly agree that cloud service intelligence should be leveraged to optimize costs and secure information. Cost from technical debt and the complexity of supporting multiple generations of infrastructure are some of the biggest barriers for organizations in achieving their digital infrastructure resiliency goals.

Network-derived intelligence can support Security

Network-derived intelligence can support adherence to SANS 20 Critical Security Controls, potentially eliminating 98% of possible attack vectors. Today, over 50% of respondents state that they actively share network intelligence across IT teams, and more than 60% of organizations are making progress in leveraging these insights in their security management practices.

"Over 90% of organizations operate in a hybrid and multi-cloud world, yet security blind spots remain a significant barrier for technology leaders looking to get the most out of their cloud investments," said Chaim Mazal, Chief Security Officer of Gigamon. "This research not only points to the critical role that deep observability plays in securing complex cloud environments but the necessary convergence of NetOps and SecOps teams in fortifying modern cybersecurity practices. "

Methodology: The findings are based on a survey, conducted by IDC, of over 900 global IT leaders across North America, APAC, and EMEA, which included a mix of major industries (financial, manufacturing, retail/wholesale, healthcare, transport/utilities, education, government, and professional services). All respondents held roles of manager or above, with key decision-making responsibilities for observability functions and solutions that span across IT operational domains, including networking, security, and cloud.

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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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...