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5 Network Predictions for 2018

Mark Milinkovich

Looking back on this year, we can see threads of what the future holds in enterprise networking. Specifically, taking a closer look at the biggest news and trends of this year, IT areas where businesses are investing and perspectives from the analyst community, as well as our own experiences, here are five network predictions for the coming year.

1. Focus on ML and AI for NPM will move beyond the hype

The focus on machine learning and artificial intelligence for network performance management (NPM) will move beyond the hype and become pragmatic. As software defined and multi cloud networks become the new normal, NPM platforms will need to gather deep analytical insights across these complex environments to proactively support network engineers and IT operations. These insights help deliver optimized application, device and user performance across the network. It also enables the network to continuously learn, spot and address abnormalities in network traffic, and dynamically adjust network policies to account for changes in usage or user behavior. Ultimately, this will help prevent network problems before they occur resulting in faster responses to incidents and better online experiences.

2. Digital transformation will create a new generation of network engineers

According to Gartner’s 2017 CEO survey, 42 percent of CEOs are now taking a digital-first approach to business change or taking digital to the core of their enterprise model. As “digital-first” continues to be a priority, it’s creating new demands on network teams. This includes managing increasing complexity of the network as innovations such as software-defined, IoT, and multi-cloud proliferate. This will simply be the way that business gets done. To support it, the network engineer, architect, and operator will not only be the keeper of the network, they will be enablers of digital transformation and custodians of the digital experience for the enterprise’s employees and customers.

3. Automated network configuration will be at the top of the IT agenda

At the recent Gartner Infrastructure and Operations conference, approximately 2000 CIOs were asked which IT initiative they’ll spend money on in 2018. Over 61 percent answered network configured automation (NCA). Clearly, the need to automate basic tasks is in demand, especially as organizations want to free up resources and invest in technologies that will support their path to self-healing networks.

4. It will be obvious which companies have embraced NetOps

By 2020, it will be obvious which companies have embraced NetOps because they’ll be more agile, responsive to customers and partners, and deliver stronger financial results. At its core, NetOps is all about building and managing a flexible network that quickly responds to business needs and adapts to the applications and services being used. To succeed in this goal requires greater visibility across the network along with automated workflows and analytics that connect networking, engineering and IT operations teams and provide deeper insights into the performance of the network and the user experiences, applications, and devices running on it.

5. Continued growth of SD-WAN will create higher demand for improved network visibility across hybrid infrastructures

Analysts at IDC have forecasted that by 2021, SD-WAN will realize a compound annual growth rate (CAGR) of 69.9 percent, reaching $8.05 billion. As networks become more software-defined, there will be an increased need for greater visibility across the entire network and analytics to separate the signal from the increasing noise in the traffic.

There’s no question that the network has shifted to the center of the organization. Without it, we can’t collaborate with colleagues, engage customers and partners, and move business forward. In 2018, we’ll continue to see more resources dedicated to the network as the primary business enabler.

Hot Topics

The Latest

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 ...

5 Network Predictions for 2018

Mark Milinkovich

Looking back on this year, we can see threads of what the future holds in enterprise networking. Specifically, taking a closer look at the biggest news and trends of this year, IT areas where businesses are investing and perspectives from the analyst community, as well as our own experiences, here are five network predictions for the coming year.

1. Focus on ML and AI for NPM will move beyond the hype

The focus on machine learning and artificial intelligence for network performance management (NPM) will move beyond the hype and become pragmatic. As software defined and multi cloud networks become the new normal, NPM platforms will need to gather deep analytical insights across these complex environments to proactively support network engineers and IT operations. These insights help deliver optimized application, device and user performance across the network. It also enables the network to continuously learn, spot and address abnormalities in network traffic, and dynamically adjust network policies to account for changes in usage or user behavior. Ultimately, this will help prevent network problems before they occur resulting in faster responses to incidents and better online experiences.

2. Digital transformation will create a new generation of network engineers

According to Gartner’s 2017 CEO survey, 42 percent of CEOs are now taking a digital-first approach to business change or taking digital to the core of their enterprise model. As “digital-first” continues to be a priority, it’s creating new demands on network teams. This includes managing increasing complexity of the network as innovations such as software-defined, IoT, and multi-cloud proliferate. This will simply be the way that business gets done. To support it, the network engineer, architect, and operator will not only be the keeper of the network, they will be enablers of digital transformation and custodians of the digital experience for the enterprise’s employees and customers.

3. Automated network configuration will be at the top of the IT agenda

At the recent Gartner Infrastructure and Operations conference, approximately 2000 CIOs were asked which IT initiative they’ll spend money on in 2018. Over 61 percent answered network configured automation (NCA). Clearly, the need to automate basic tasks is in demand, especially as organizations want to free up resources and invest in technologies that will support their path to self-healing networks.

4. It will be obvious which companies have embraced NetOps

By 2020, it will be obvious which companies have embraced NetOps because they’ll be more agile, responsive to customers and partners, and deliver stronger financial results. At its core, NetOps is all about building and managing a flexible network that quickly responds to business needs and adapts to the applications and services being used. To succeed in this goal requires greater visibility across the network along with automated workflows and analytics that connect networking, engineering and IT operations teams and provide deeper insights into the performance of the network and the user experiences, applications, and devices running on it.

5. Continued growth of SD-WAN will create higher demand for improved network visibility across hybrid infrastructures

Analysts at IDC have forecasted that by 2021, SD-WAN will realize a compound annual growth rate (CAGR) of 69.9 percent, reaching $8.05 billion. As networks become more software-defined, there will be an increased need for greater visibility across the entire network and analytics to separate the signal from the increasing noise in the traffic.

There’s no question that the network has shifted to the center of the organization. Without it, we can’t collaborate with colleagues, engage customers and partners, and move business forward. In 2018, we’ll continue to see more resources dedicated to the network as the primary business enabler.

Hot Topics

The Latest

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 ...