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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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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...