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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

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

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

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...