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2022 Network Performance Management Predictions

As part of APMdigest's list of 2022 predictions, industry experts offer thoughtful and insightful predictions on how Network Performance Management (NPM) and related technologies will evolve and impact business in 2022.

NETWORK OBSERVABILITY

Network performance management (NPM) vendors will start evolving toward network observability to serve an IT industry that is embracing multi-cloud, edge cloud, work-from-anywhere, and internet-based WANs. Deep visibility into traditional on-premises networks simply isn't enough for modern IT Operations teams. Via organic development and mergers and acquisitions, NPM vendors will add AIOps, security monitoring, cloud monitoring, and digital experience monitoring to their core NPM capabilities to provide total visibility into digital operations. NetOps teams are trying to align with SecOps and DevOps, and network observability solutions from their traditional NPM vendors would certainly help them accomplish this.
Shamus McGillicuddy
VP of Research, Network Infrastructure and Operations, Enterprise Management Associates (EMA)

Network observability will continue to be important. We spent a lot of time with the magnifying glass on the "work from anywhere user," and that will swing a little bit back into the physical locations because of office openings.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

IMPROVING USER INTERFACES FOR NPM

IT Central Station users are looking forward to seeing an improvement in the user interfaces of network management applications. It is currently difficult to transfer an interface from one virtual domain to another and our users would like to see this transition simplified.
Russell Rothstein
Founder and CEO, IT Central Station, (soon to be PeerSpot)

CONVERGENCE OF NPM, APM AND SECURITY

Accelerated digital transformation has propelled the move to cloud and SaaS applications. Cloud provider selection is now being driven more by business outcomes instead of IT requirements, forcing a diverse multi-cloud environment. This is creating big visibility challenges for NetOps teams as they're tasked to deliver optimized performance securely. In 2022, IT operations will finally adopt a single source of visibility for application performance management and network security that will allow NetOps and SecOps teams to be truly aligned. This will likely come in the form of network performance monitoring solutions that are adding security functionality, like the ability to see into encrypted traffic (or NDR solutions).
Thomas Pore
Director of Security Products, LiveAction

CONVERGENCE OF NPM WITH BROADER OBSERVABILITY

As IT environments become more hybrid, more distributed, more complex, IT teams will evolve their network monitoring practices to support broader observability objectives. This requires breaking down traditional IT silos, capturing full-fidelity telemetry from the entire digital ecosystem, and transforming massive amounts of data into actionable insights that can be used across IT domains to accelerate decision-making and problem resolution.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

AI ASSISTANTS AND AIOPS JOIN NPM

AI assistants that can manage and troubleshoot networks on par with human domain experts, will be promoted to a member of the IT team in 2022. In the enterprise, AI, machine learning and AIOps ultimately have the potential to become as trusted a source as the most experienced IT domain expert. While we're not there yet, in the coming year we can expect AI assistants and conversational interfaces to take on a more serious and trusted role in the enterprise. At present, AI conversational interfaces can answer up to 70% of support tickets with the same effectiveness as a domain expert. As network complexity and distributed workloads increase, AIOps and virtual AI assistants will become viewed as an essential member of IT teams. Further, as cloud services continue to scale to provide unlimited, cost-effective processing and storage, both enterprises and technology providers will be empowered to adopt AI assistants across various support teams — feeding in the volume and quality of data necessary to train AI technologies to increase their accuracy.
Bob Friday
VP and CTO, Juniper Networks AI-Driven Enterprise

AI/ML ENHANCE NETWORK PERFORMANCE

The industry will see significant growth in investment in AI/ML and automation. Based on testing, we see significant growth in AI/ML and automation to enhance network performance and fault management. In particular, more operators are investing in active testing and assurance systems to inject synthetic traffic into their networks to emulate real users and services, instead of relying on static, passive probes. And they're seeking to pair these systems with AI/ML algorithms that can make good decisions in real time for where, when, and what to actively test to improve services or isolate faults, without requiring human intervention. We also expect to see early efforts in using AI/ML to enhance security, and in running testing workloads from public cloud.
Steve Douglas
Head of Market Strategy, Spirent Communications

LOAD BALANCERS WILL DISAPPEAR

Centralized load balancers will disappear within 3-4 years. Unlike many of our processes and technologies for managing modern applications, load balancers have remained largely unchanged and are ripe for disruption. Centralized load balancers simply do not make sense in a decentralized world. They add an extra hop in the network, increase latency and are not portable.
Marco Palladino,
CTO and Co-Founder, Kong

RIP AND REPLACE NETWORKING

There's going to be a lot of refresh activity in the enterprise as offices with in person employees ramp back up. I expect IT spending will change. Prior to the pandemic spending was focused on endpoint and security and cloud, and now I see spending shifting towards hardware refresh in the coming year. Security will still be an active topic, but it's going to push more to the cloud because more and more workloads are moving to the cloud.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

Hot Topics

The Latest

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

2022 Network Performance Management Predictions

As part of APMdigest's list of 2022 predictions, industry experts offer thoughtful and insightful predictions on how Network Performance Management (NPM) and related technologies will evolve and impact business in 2022.

NETWORK OBSERVABILITY

Network performance management (NPM) vendors will start evolving toward network observability to serve an IT industry that is embracing multi-cloud, edge cloud, work-from-anywhere, and internet-based WANs. Deep visibility into traditional on-premises networks simply isn't enough for modern IT Operations teams. Via organic development and mergers and acquisitions, NPM vendors will add AIOps, security monitoring, cloud monitoring, and digital experience monitoring to their core NPM capabilities to provide total visibility into digital operations. NetOps teams are trying to align with SecOps and DevOps, and network observability solutions from their traditional NPM vendors would certainly help them accomplish this.
Shamus McGillicuddy
VP of Research, Network Infrastructure and Operations, Enterprise Management Associates (EMA)

Network observability will continue to be important. We spent a lot of time with the magnifying glass on the "work from anywhere user," and that will swing a little bit back into the physical locations because of office openings.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

IMPROVING USER INTERFACES FOR NPM

IT Central Station users are looking forward to seeing an improvement in the user interfaces of network management applications. It is currently difficult to transfer an interface from one virtual domain to another and our users would like to see this transition simplified.
Russell Rothstein
Founder and CEO, IT Central Station, (soon to be PeerSpot)

CONVERGENCE OF NPM, APM AND SECURITY

Accelerated digital transformation has propelled the move to cloud and SaaS applications. Cloud provider selection is now being driven more by business outcomes instead of IT requirements, forcing a diverse multi-cloud environment. This is creating big visibility challenges for NetOps teams as they're tasked to deliver optimized performance securely. In 2022, IT operations will finally adopt a single source of visibility for application performance management and network security that will allow NetOps and SecOps teams to be truly aligned. This will likely come in the form of network performance monitoring solutions that are adding security functionality, like the ability to see into encrypted traffic (or NDR solutions).
Thomas Pore
Director of Security Products, LiveAction

CONVERGENCE OF NPM WITH BROADER OBSERVABILITY

As IT environments become more hybrid, more distributed, more complex, IT teams will evolve their network monitoring practices to support broader observability objectives. This requires breaking down traditional IT silos, capturing full-fidelity telemetry from the entire digital ecosystem, and transforming massive amounts of data into actionable insights that can be used across IT domains to accelerate decision-making and problem resolution.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

AI ASSISTANTS AND AIOPS JOIN NPM

AI assistants that can manage and troubleshoot networks on par with human domain experts, will be promoted to a member of the IT team in 2022. In the enterprise, AI, machine learning and AIOps ultimately have the potential to become as trusted a source as the most experienced IT domain expert. While we're not there yet, in the coming year we can expect AI assistants and conversational interfaces to take on a more serious and trusted role in the enterprise. At present, AI conversational interfaces can answer up to 70% of support tickets with the same effectiveness as a domain expert. As network complexity and distributed workloads increase, AIOps and virtual AI assistants will become viewed as an essential member of IT teams. Further, as cloud services continue to scale to provide unlimited, cost-effective processing and storage, both enterprises and technology providers will be empowered to adopt AI assistants across various support teams — feeding in the volume and quality of data necessary to train AI technologies to increase their accuracy.
Bob Friday
VP and CTO, Juniper Networks AI-Driven Enterprise

AI/ML ENHANCE NETWORK PERFORMANCE

The industry will see significant growth in investment in AI/ML and automation. Based on testing, we see significant growth in AI/ML and automation to enhance network performance and fault management. In particular, more operators are investing in active testing and assurance systems to inject synthetic traffic into their networks to emulate real users and services, instead of relying on static, passive probes. And they're seeking to pair these systems with AI/ML algorithms that can make good decisions in real time for where, when, and what to actively test to improve services or isolate faults, without requiring human intervention. We also expect to see early efforts in using AI/ML to enhance security, and in running testing workloads from public cloud.
Steve Douglas
Head of Market Strategy, Spirent Communications

LOAD BALANCERS WILL DISAPPEAR

Centralized load balancers will disappear within 3-4 years. Unlike many of our processes and technologies for managing modern applications, load balancers have remained largely unchanged and are ripe for disruption. Centralized load balancers simply do not make sense in a decentralized world. They add an extra hop in the network, increase latency and are not portable.
Marco Palladino,
CTO and Co-Founder, Kong

RIP AND REPLACE NETWORKING

There's going to be a lot of refresh activity in the enterprise as offices with in person employees ramp back up. I expect IT spending will change. Prior to the pandemic spending was focused on endpoint and security and cloud, and now I see spending shifting towards hardware refresh in the coming year. Security will still be an active topic, but it's going to push more to the cloud because more and more workloads are moving to the cloud.
Phillip Gervasi
Senior Technical Evangelist, Riverbed

Hot Topics

The Latest

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...