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2018 Network Performance Management Predictions

Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how Network Performance Management (NPM) and related technologies will evolve and impact business in 2018.

Start with 2018 Application Performance Management Predictions - Part 1

The end to finger-pointing in network outages

2018 will see an evolution of relationships between service providers and their clients as these relationships become increasingly data driven. We will soon see less finger pointing between service providers and corporate IT and network teams when service outages occur. Instead there will be more mutual accountability as clients are able to independently access more forensic data sources associated with an outage and determine exactly what happened and where everything went wrong. This is causing service providers to move beyond simple outage portals to greater transparency with clients. Organizations no longer have to rely on their providers to tell them when there is a problem.
Alex Henthorn-Iwane
VP of Product Marketing, ThousandEyes

Real-time NPM

Truly real-time network performance monitoring (NPM) will become critical to the success of enterprises. In 2018, real-time NPM will break through to become a vital part of network troubleshooting. In the past, NPM solution providers had called their products "real-time" even though their dashboards had delays of several minutes. Those delays are no longer acceptable. We're now moving into an era when real-time has a gap no longer than a few seconds.
Larry Zulch
President, Savvius

APPLICATION AWARE NETWORKS AND NPM

For enterprises, the existing lack of SLA and performance visibility into business-critical applications in use at remote and branch offices will only increase as applications continue their steady march toward SaaS-based turnkey solutions and hybrid or fully public cloud architectures. We're seeing an application evolution. We're also seeing increasingly broad availability of lower cost, high-capacity (but highly variable quality) public Internet connections and corporate-owned MPLS-based (and steadily increasing LTE) networks. This combination of trends will render traditional infrastructure and application-agnostic, metrics-only monitoring techniques near useless.
Matt Stevens
CEO, AppNeta

AI AND ML APPLIED TO NPM

Machine learning and artificial intelligence consistently make the year end lists of predictions of what's going to be hot in the coming year. Yet the focus has primarily been on applications. In 2018, we'll see more machine learning and artificial intelligence applied to network performance management. 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 the network engineers and IT operations to deliver optimized application, device and user performance across the network. This will enable 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. This helps prevent network problems before they occur, resulting in faster responses to incidents, and delivers better online experiences.
Mark Milinkovich
Director of Product Marketing, LiveAction

INTELLIGENT AUTOMATION

Enterprises want to be in complete control, and engineers want to have the ability to customize workflows and processes to best suit their needs. Intent-based automation takes software-defined automation to the next level. Automation gives enterprises the flexibility to customize and predefine internal network workflows. Once users define the pathway, intent-based automation will manipulate the network to enforce policies and deliver the desired outcome.Intent-based automation eliminates the need for manual scaling by automating the process with pre-defined intent. Although it is still in its early stages, it has the potential to play an integral role in software-defined implementations by making automation smarter and more intuitive.
Murali Palanisamy
CTO, AppViewX

In response to the growing adoption of technologies like SDN and NFV orchestration, along with maturation of artificial intelligence and machine learning techniques, we will see a whole new level of automation for Communication Service Providers (CSPs) where the network can begin to anticipate failures or overruns, mitigate risk and preemptively prevent problems before they happen. Recognized as intelligent automation, it will lead to more streamlined and responsive service delivery, which will ultimately lead to better customer satisfaction.
Kevin Wade
Senior Director of Solutions, Ciena's Blue Planet Division

Cloud Baselining

Cloud continues to make enterprise networks and IT systems more efficient and cost-effective. But since cloud migration pushes more traffic across networks and services that are outside the corporate borders, old expectations of network performance don't necessarily hold up. Service level agreements that have stood for years will suddenly find themselves in jeopardy in the cloud era. Network engineers may find themselves in the position of having customer success teams ask them to restore service to a level that never existed nor was possible in the first place on cloud networks. Savvy network teams will spend a lot more time this year baselining both app and underlying network performance levels to define what is the new normal in the cloud era as network traffic navigates more and more dependencies between the origin and destination.
Alex Henthorn-Iwane
VP of Product Marketing, ThousandEyes

CONVERGENCE OF NETWORK AND SECURITY OPERATIONS

Network and Security operations have been converging for several years, and this trend will accelerate in 2018. This will be driven by the fact that each discipline requires similar information about the network, which is based on access to the network traffic and the reported metrics of network and application activity.
Larry Zulch
President, Savvius

THREAT INTELLIGENCE GATEWAYS

Despite spending more than $80B annually on security measures, the past 16 months have seen network outages of unprecedented proportions, with more than 1 billion crucial records lost to data breaches. With billions of IP addresses, how many should have access to the network and its assets? Current approaches filter and manage every part of the traffic, the good, bad and of course the ugly. By managing and filtering everything, the process becomes complicated and overwhelming. What is on the horizon to help with these attacks? Prediction: A new breed of security solutions called Threat Intelligent Gateways will emerge as organizations need to stop the increasing volume of threats. This perimeter protection provides an opportunity for regional carriers, hosting & service providers and CDNs to create more value for their customers. Ultimately, the Threat Intelligence Gateways will deliver better-managed network traffic and provide a powerful dynamic security perimeter that scales with threats from outside sources.
Carolyn Raab
VP of Product Management, Corsa

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...

2018 Network Performance Management Predictions

Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how Network Performance Management (NPM) and related technologies will evolve and impact business in 2018.

Start with 2018 Application Performance Management Predictions - Part 1

The end to finger-pointing in network outages

2018 will see an evolution of relationships between service providers and their clients as these relationships become increasingly data driven. We will soon see less finger pointing between service providers and corporate IT and network teams when service outages occur. Instead there will be more mutual accountability as clients are able to independently access more forensic data sources associated with an outage and determine exactly what happened and where everything went wrong. This is causing service providers to move beyond simple outage portals to greater transparency with clients. Organizations no longer have to rely on their providers to tell them when there is a problem.
Alex Henthorn-Iwane
VP of Product Marketing, ThousandEyes

Real-time NPM

Truly real-time network performance monitoring (NPM) will become critical to the success of enterprises. In 2018, real-time NPM will break through to become a vital part of network troubleshooting. In the past, NPM solution providers had called their products "real-time" even though their dashboards had delays of several minutes. Those delays are no longer acceptable. We're now moving into an era when real-time has a gap no longer than a few seconds.
Larry Zulch
President, Savvius

APPLICATION AWARE NETWORKS AND NPM

For enterprises, the existing lack of SLA and performance visibility into business-critical applications in use at remote and branch offices will only increase as applications continue their steady march toward SaaS-based turnkey solutions and hybrid or fully public cloud architectures. We're seeing an application evolution. We're also seeing increasingly broad availability of lower cost, high-capacity (but highly variable quality) public Internet connections and corporate-owned MPLS-based (and steadily increasing LTE) networks. This combination of trends will render traditional infrastructure and application-agnostic, metrics-only monitoring techniques near useless.
Matt Stevens
CEO, AppNeta

AI AND ML APPLIED TO NPM

Machine learning and artificial intelligence consistently make the year end lists of predictions of what's going to be hot in the coming year. Yet the focus has primarily been on applications. In 2018, we'll see more machine learning and artificial intelligence applied to network performance management. 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 the network engineers and IT operations to deliver optimized application, device and user performance across the network. This will enable 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. This helps prevent network problems before they occur, resulting in faster responses to incidents, and delivers better online experiences.
Mark Milinkovich
Director of Product Marketing, LiveAction

INTELLIGENT AUTOMATION

Enterprises want to be in complete control, and engineers want to have the ability to customize workflows and processes to best suit their needs. Intent-based automation takes software-defined automation to the next level. Automation gives enterprises the flexibility to customize and predefine internal network workflows. Once users define the pathway, intent-based automation will manipulate the network to enforce policies and deliver the desired outcome.Intent-based automation eliminates the need for manual scaling by automating the process with pre-defined intent. Although it is still in its early stages, it has the potential to play an integral role in software-defined implementations by making automation smarter and more intuitive.
Murali Palanisamy
CTO, AppViewX

In response to the growing adoption of technologies like SDN and NFV orchestration, along with maturation of artificial intelligence and machine learning techniques, we will see a whole new level of automation for Communication Service Providers (CSPs) where the network can begin to anticipate failures or overruns, mitigate risk and preemptively prevent problems before they happen. Recognized as intelligent automation, it will lead to more streamlined and responsive service delivery, which will ultimately lead to better customer satisfaction.
Kevin Wade
Senior Director of Solutions, Ciena's Blue Planet Division

Cloud Baselining

Cloud continues to make enterprise networks and IT systems more efficient and cost-effective. But since cloud migration pushes more traffic across networks and services that are outside the corporate borders, old expectations of network performance don't necessarily hold up. Service level agreements that have stood for years will suddenly find themselves in jeopardy in the cloud era. Network engineers may find themselves in the position of having customer success teams ask them to restore service to a level that never existed nor was possible in the first place on cloud networks. Savvy network teams will spend a lot more time this year baselining both app and underlying network performance levels to define what is the new normal in the cloud era as network traffic navigates more and more dependencies between the origin and destination.
Alex Henthorn-Iwane
VP of Product Marketing, ThousandEyes

CONVERGENCE OF NETWORK AND SECURITY OPERATIONS

Network and Security operations have been converging for several years, and this trend will accelerate in 2018. This will be driven by the fact that each discipline requires similar information about the network, which is based on access to the network traffic and the reported metrics of network and application activity.
Larry Zulch
President, Savvius

THREAT INTELLIGENCE GATEWAYS

Despite spending more than $80B annually on security measures, the past 16 months have seen network outages of unprecedented proportions, with more than 1 billion crucial records lost to data breaches. With billions of IP addresses, how many should have access to the network and its assets? Current approaches filter and manage every part of the traffic, the good, bad and of course the ugly. By managing and filtering everything, the process becomes complicated and overwhelming. What is on the horizon to help with these attacks? Prediction: A new breed of security solutions called Threat Intelligent Gateways will emerge as organizations need to stop the increasing volume of threats. This perimeter protection provides an opportunity for regional carriers, hosting & service providers and CDNs to create more value for their customers. Ultimately, the Threat Intelligence Gateways will deliver better-managed network traffic and provide a powerful dynamic security perimeter that scales with threats from outside sources.
Carolyn Raab
VP of Product Management, Corsa

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...