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Network Agility - What It Is and How to Achieve It

Jay Botelho

If you work in the field of IT, you've most likely heard the term "network agility" being thrown around more and more lately. It's becoming a major focus for many network operations (NetOps) teams today and is even ranked third on the list of the top 10 trends impacting infrastructure and operations this year, according to Gartner. On top of that, a recent survey we conducted also found the top goal for networking and IT teams in 2019 is improving network agility. To better understand why this concept is so important today and how it can enable organizations to better support key IT objectives and overall business operations, we must first examine exactly what it is.

The term network agility technically refers to the degree to which an organization's network infrastructure can leverage automated configurations and policies to self-manage and operate "autonomously." But it's also commonly used to describe when NetOps teams are equipped with tools that provide visibility, flexibility and scalability, which are required to manage and respond to the major technologies and trends impacting their connected businesses.

The widespread, ongoing adoption of innovative technologies related to SD-WAN, cloud services, 5G, etc. means that today's networks are in a constant state of flux. Although these technologies offer tremendous business benefits, they can also add tremendous complexity as well, creating major obstacles that prevent network agility. For example, NetOps teams today report dealing with issues like a lack of visibility across all domains of the network, spending too much time troubleshooting, and an inability to proactively monitor the network. It's virtually impossible to achieve the level of network agility that businesses require today with these obstacles standing in the way.

A Closer Look at How Complex Networks Impact Agility

As the number of mobile devices, cloud-based networks and applications have continued to increase, network teams are decreasing in size and struggling to find ways to monitor everything effectively and meet the network agility needs of the business. And of course end-users, partners, customers and executives still expect a high-performing network. This challenge won't go away any time soon — it'll only become more complex and difficult for NetOps to monitor effectively as more new technology initiatives, devices and applications are introduced. Just look at recent IDC projections that predict the SDN market will reach $13.8B by 2021, or the fact that 75.4B IoT devices will be in use by 2025, according to IHS forecasts.

NetOps teams need better visibility and troubleshooting capabilities

In order to achieve a level of network agility that supports business objectives today, NetOps teams need better visibility and troubleshooting capabilities. Legacy tools designed for highly specific network domain use cases like VoIP and video quality simply won't cut it today. Without granular insight into every aspect of the network, IT teams are left with major blind spots, which can lead to unnecessary and time-consuming troubleshooting tasks and downtime that can put the business in jeopardy.

To compensate for blind spots caused by the use of legacy tools, many network teams purchase various point solutions to monitor specific parts of the network. In fact, according to EMA research, 83% of enterprises use multiple monitoring tools; 49% use between 4 and 10 NPMD tools; and 27% are using more than 11 tools. That's too many tools! With individual subscriptions, service contracts, renewal programs, etc. for each, the costs can be exorbitant. But beyond those factors, the lack of integration and cumbersome workflows involved with toggling between that many solutions can stymie the productivity and effectiveness of NetOps teams, which can cost businesses even more dearly. Having to rely on more than 10 tools to manage the network doesn't sound very agile, does it?

Achieving Network Agility

In order to achieve network agility and to properly maintain and optimize today's increasingly complex networks, NetOps teams need unified, single-vendor network performance monitoring and diagnostics solutions. A centralized network management solution can significantly reduce cost and visibility issues brought on by tool sprawl, providing complete insight across the entire enterprise (from SD-WAN and wireless environments to the cloud and more).

Solutions that ingest multiple data types including packet data, SNMP, NetFlow, IPFIX, and more, provide IT administrators a comprehensive, real-time view of the network, while providing the data needed for root-cause analysis. This can empower them to proactively monitor and identify issues across the network as they are happening, regardless of the complex network initiatives or technologies involved.

This level of visibility provides network teams with the agility they need to keep up with the demands, changes and issues of today's networks and better enables them to support their business' strategic goals and the bottom line.

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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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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 ...

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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.

Network Agility - What It Is and How to Achieve It

Jay Botelho

If you work in the field of IT, you've most likely heard the term "network agility" being thrown around more and more lately. It's becoming a major focus for many network operations (NetOps) teams today and is even ranked third on the list of the top 10 trends impacting infrastructure and operations this year, according to Gartner. On top of that, a recent survey we conducted also found the top goal for networking and IT teams in 2019 is improving network agility. To better understand why this concept is so important today and how it can enable organizations to better support key IT objectives and overall business operations, we must first examine exactly what it is.

The term network agility technically refers to the degree to which an organization's network infrastructure can leverage automated configurations and policies to self-manage and operate "autonomously." But it's also commonly used to describe when NetOps teams are equipped with tools that provide visibility, flexibility and scalability, which are required to manage and respond to the major technologies and trends impacting their connected businesses.

The widespread, ongoing adoption of innovative technologies related to SD-WAN, cloud services, 5G, etc. means that today's networks are in a constant state of flux. Although these technologies offer tremendous business benefits, they can also add tremendous complexity as well, creating major obstacles that prevent network agility. For example, NetOps teams today report dealing with issues like a lack of visibility across all domains of the network, spending too much time troubleshooting, and an inability to proactively monitor the network. It's virtually impossible to achieve the level of network agility that businesses require today with these obstacles standing in the way.

A Closer Look at How Complex Networks Impact Agility

As the number of mobile devices, cloud-based networks and applications have continued to increase, network teams are decreasing in size and struggling to find ways to monitor everything effectively and meet the network agility needs of the business. And of course end-users, partners, customers and executives still expect a high-performing network. This challenge won't go away any time soon — it'll only become more complex and difficult for NetOps to monitor effectively as more new technology initiatives, devices and applications are introduced. Just look at recent IDC projections that predict the SDN market will reach $13.8B by 2021, or the fact that 75.4B IoT devices will be in use by 2025, according to IHS forecasts.

NetOps teams need better visibility and troubleshooting capabilities

In order to achieve a level of network agility that supports business objectives today, NetOps teams need better visibility and troubleshooting capabilities. Legacy tools designed for highly specific network domain use cases like VoIP and video quality simply won't cut it today. Without granular insight into every aspect of the network, IT teams are left with major blind spots, which can lead to unnecessary and time-consuming troubleshooting tasks and downtime that can put the business in jeopardy.

To compensate for blind spots caused by the use of legacy tools, many network teams purchase various point solutions to monitor specific parts of the network. In fact, according to EMA research, 83% of enterprises use multiple monitoring tools; 49% use between 4 and 10 NPMD tools; and 27% are using more than 11 tools. That's too many tools! With individual subscriptions, service contracts, renewal programs, etc. for each, the costs can be exorbitant. But beyond those factors, the lack of integration and cumbersome workflows involved with toggling between that many solutions can stymie the productivity and effectiveness of NetOps teams, which can cost businesses even more dearly. Having to rely on more than 10 tools to manage the network doesn't sound very agile, does it?

Achieving Network Agility

In order to achieve network agility and to properly maintain and optimize today's increasingly complex networks, NetOps teams need unified, single-vendor network performance monitoring and diagnostics solutions. A centralized network management solution can significantly reduce cost and visibility issues brought on by tool sprawl, providing complete insight across the entire enterprise (from SD-WAN and wireless environments to the cloud and more).

Solutions that ingest multiple data types including packet data, SNMP, NetFlow, IPFIX, and more, provide IT administrators a comprehensive, real-time view of the network, while providing the data needed for root-cause analysis. This can empower them to proactively monitor and identify issues across the network as they are happening, regardless of the complex network initiatives or technologies involved.

This level of visibility provides network teams with the agility they need to keep up with the demands, changes and issues of today's networks and better enables them to support their business' strategic goals and the bottom line.

Hot Topics

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.