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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

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AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...