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Q&A Part One: Fluke Networks Talks About AANPM

Pete Goldin
APMdigest

In APMdigest's exclusive interview, Doug Roberts, Director of Enterprise Products at Fluke Networks, discusses Application Aware Network Performance Management (AANPM) and its relation to — and difference from — Application Performance Management (APM) and traditional Network Performance Management (NPM).

APM: What is AANPM? How is it different from traditional NPM?

DR: Application Aware Network Performance Management (AANPM) is an approach to monitoring, troubleshooting and analyzing both networks and application systems. Whereas traditional Network Performance Management (NPM) focuses on monitoring the health of devices, AANPM takes a more holistic view to address the complex issues facing business application systems today.

There is a real need for management platforms to broaden their visibility to include both network and application analytics. Data must be correlated to enable network engineers to quickly locate problems, regardless of their source — network or server, wired or wireless, physical or virtual, local or remote, real-time or back-in-time, client or cloud.

APM: Are AANPM and Network Performance Monitoring and Diagnostics (NPMD) referring to the same tool?

DR: While different analyst firms use different terms, they all essentially boil down to the same thing. The traditional NPM approach of monitoring the health of a network endpoint and its traffic/utilization is no longer enough. When you see ANPM, AANPM or NPMD they are all referring to the same technological leap forward: network monitoring tools that understand the applications being delivered on the network and the quality of that delivery.

APM: Explain the difference between APM and AANPM.

DR: While both APM and AANPM seek to answer the question of why performance is slow, they are typically targeted at different users.

An application owner or DevOps team needs deep visibility into where performance bottlenecks are occurring within an application, perhaps even down to the module or line of code. This is typically accomplished by instrumenting the application server with an agent to monitor application behavior. These APM tools may have some understanding of the network, but not where or why there is a network problem. The agent-based nature of these approaches often limits what applications can be monitored by an APM solution (such as Java, .Net, Ruby, PHP etc.).

On the other hand, network teams want to quickly identify whether a performance problem is actually due to either a network, server or application slowdown since they’re typically burdened with proving the network isn’t the cause. When a network issue does occur, they need to quickly identify where the problem is located and what’s contributing to it. Using AANPM tools, they can quickly see where the issue is located within the network, what the user is doing and what’s causing that network performance slowdown. This provides a complete picture of the application, the network and the actual end-user experience.

APM: Is AANPM designed to augment or replace APM?

DR: It’s a little bit of both. APM and AANPM are typically used by different IT functions to monitor different things, which means they can live side by side in the same environment, monitoring performance from different perspectives. Since APM requires agents, it is typically limited to supporting specific platforms like Java, .NET, Ruby, PHP, etc. But what about the rest of the applications in the IT environment? Because AANPM solutions inspect data as it traverses the wire, they can offer broader application performance monitoring without being tied to the specific platform on which the application is running.

Given that AANPM can provide both broad and deep visibility into application transactions, many customers find they have enough visibility into applications and networks by leveraging AANPM’s ability to identify poorly performing application behavior and transactions across the network.

Many vendors, including Fluke Networks, offer integration between APM and AANPM. While both technologies will typically monitor the same critical applications, the workflows will typically branch early to cover the distinct use cases of an APM user versus a network-focused user.

Read Part Two of this interview

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Q&A Part One: Fluke Networks Talks About AANPM

Pete Goldin
APMdigest

In APMdigest's exclusive interview, Doug Roberts, Director of Enterprise Products at Fluke Networks, discusses Application Aware Network Performance Management (AANPM) and its relation to — and difference from — Application Performance Management (APM) and traditional Network Performance Management (NPM).

APM: What is AANPM? How is it different from traditional NPM?

DR: Application Aware Network Performance Management (AANPM) is an approach to monitoring, troubleshooting and analyzing both networks and application systems. Whereas traditional Network Performance Management (NPM) focuses on monitoring the health of devices, AANPM takes a more holistic view to address the complex issues facing business application systems today.

There is a real need for management platforms to broaden their visibility to include both network and application analytics. Data must be correlated to enable network engineers to quickly locate problems, regardless of their source — network or server, wired or wireless, physical or virtual, local or remote, real-time or back-in-time, client or cloud.

APM: Are AANPM and Network Performance Monitoring and Diagnostics (NPMD) referring to the same tool?

DR: While different analyst firms use different terms, they all essentially boil down to the same thing. The traditional NPM approach of monitoring the health of a network endpoint and its traffic/utilization is no longer enough. When you see ANPM, AANPM or NPMD they are all referring to the same technological leap forward: network monitoring tools that understand the applications being delivered on the network and the quality of that delivery.

APM: Explain the difference between APM and AANPM.

DR: While both APM and AANPM seek to answer the question of why performance is slow, they are typically targeted at different users.

An application owner or DevOps team needs deep visibility into where performance bottlenecks are occurring within an application, perhaps even down to the module or line of code. This is typically accomplished by instrumenting the application server with an agent to monitor application behavior. These APM tools may have some understanding of the network, but not where or why there is a network problem. The agent-based nature of these approaches often limits what applications can be monitored by an APM solution (such as Java, .Net, Ruby, PHP etc.).

On the other hand, network teams want to quickly identify whether a performance problem is actually due to either a network, server or application slowdown since they’re typically burdened with proving the network isn’t the cause. When a network issue does occur, they need to quickly identify where the problem is located and what’s contributing to it. Using AANPM tools, they can quickly see where the issue is located within the network, what the user is doing and what’s causing that network performance slowdown. This provides a complete picture of the application, the network and the actual end-user experience.

APM: Is AANPM designed to augment or replace APM?

DR: It’s a little bit of both. APM and AANPM are typically used by different IT functions to monitor different things, which means they can live side by side in the same environment, monitoring performance from different perspectives. Since APM requires agents, it is typically limited to supporting specific platforms like Java, .NET, Ruby, PHP, etc. But what about the rest of the applications in the IT environment? Because AANPM solutions inspect data as it traverses the wire, they can offer broader application performance monitoring without being tied to the specific platform on which the application is running.

Given that AANPM can provide both broad and deep visibility into application transactions, many customers find they have enough visibility into applications and networks by leveraging AANPM’s ability to identify poorly performing application behavior and transactions across the network.

Many vendors, including Fluke Networks, offer integration between APM and AANPM. While both technologies will typically monitor the same critical applications, the workflows will typically branch early to cover the distinct use cases of an APM user versus a network-focused user.

Read Part Two of this interview

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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 ...

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