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

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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

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How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

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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 ...

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Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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