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20 Technologies to Support APM - Part 3

APMdigest continues the list, cataloging the many valuable tools available – beyond what is technically categorized as Application Performance Management (APM) – to support the goals of improving application performance and business service.

Start with Part 1

Start with Part 2

11. Network Performance Monitoring (NPM)

The performance and availability of the network is an essential factor in whether applications meet employee expectations. The rapid pace of innovation in mobile technology means that ensuring adequate network performance is becoming increasingly important. Therefore investing in a good network performance monitoring solution that is able to perform packet capture and analysis at a minimum in relation to the applications served is important and will enrich your APM strategy.
John Rakowski
Analyst, Infrastructure and Operations, Forrester Research

12. Application-Aware Network Performance Monitoring (AA-NPM)

The challenge is that APM has evolved into a mosaic of monitoring tools, analytic engines, and event processors that provide many solutions to different problems. When you step back and look at the big picture it all comes into focus, but when you're trying to rationalize one technology over another, things aren't so clear at close range. I have found that the simplicity and ease of use with agentless monitoring (i.e. wire data analytics) is a great place to start. You may also hear the terms Application Aware Infrastructure Performance Monitoring (AA-IPM) or Application Aware Network Performance Monitoring (AA-NPM) both of which are complimentary to APM and I believe to be an essential part of an overall APM solution.
Larry Dragich
Director of Enterprise Application Services at the Auto Club Group and Founder of the APM Strategies Group on LinkedIn.

13. Deep Packet Inspection (DPI)

When it comes to APM, Deep Packet Inspection (DPI) isn't the first thing that comes to mind, but it should be, and we consider it a must-have in supporting APM. The general consensus seems to be that flow-based technologies (NetFlow, sFlow, IPFIX, etc.) provide enough visibility regarding communication, and end-point solutions provide the details from the client point of view. But network and application analysis based on DPI can provide all this and more. DPI provides definitive latency measurements, and it quickly allows analysts to isolate the problem to the network or the application. Once isolated, payload information from packets in the communication path can provide insights that no other solution can – like error messages that are being returned but not correctly processed by applications. And when combined with network forensics (storing packets for detailed, post-incident analysis), critical application transactions can be unequivocally verified from days or even weeks ago, something that is not available in any other form of APM solution.
Jay Botelho
Director of Product Management, WildPackets

14. Network Packet Recording

Something that all enterprises should seek out is accurate network packet recording. It's imperative to have a solution that can capture, index and record network traffic with continuous 100% accuracy even during unpredictable traffic spikes. Accurate network packet recording enables IT teams to troubleshoot and diagnose network and application performance issues as soon as they arise, and help security teams investigate and contain security problems and help risk and compliance teams do their jobs. Operations teams can determine whether the problems reside within the IT infrastructure or within the applications running on the network – reducing time-to-resolution (TTR) and lowering operational expenditures (OPEX). Traditional detection tools won't cut it in an era where millions of dollars in revenue can be lost with milliseconds of downtime – the key is maintaining a network infrastructure that delivers continuous historical network visibility.
Mike Heumann
Sr. Director, Marketing (Endace), Emulex

15. Network Emulation

Network Emulation is a must have. The first part of an APM cycle is to ensure that applications are designed/suitable for the deployed environment. The Network (Mobile, WAN, Internet...) is a critical but often ignored component of this. One reason is the complexity of going about verifying applications in real world networks, however Network Emulation makes this easy by providing the ability to replicate the complete network environment. By re-creating all real world network conditions (restricted bandwidth, latency, loss, QoS etc), Network Emulation gives organizations an accurate assessment of whether an application is suitable for them, long before they try to manage, with APM, the unmanageable.
Jim Swepson
Pre-sales Technologist, iTrinegy

20 Technologies to Support APM - Part 4

Hot Topics

The Latest

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 ...

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 ...

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 ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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 ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

20 Technologies to Support APM - Part 3

APMdigest continues the list, cataloging the many valuable tools available – beyond what is technically categorized as Application Performance Management (APM) – to support the goals of improving application performance and business service.

Start with Part 1

Start with Part 2

11. Network Performance Monitoring (NPM)

The performance and availability of the network is an essential factor in whether applications meet employee expectations. The rapid pace of innovation in mobile technology means that ensuring adequate network performance is becoming increasingly important. Therefore investing in a good network performance monitoring solution that is able to perform packet capture and analysis at a minimum in relation to the applications served is important and will enrich your APM strategy.
John Rakowski
Analyst, Infrastructure and Operations, Forrester Research

12. Application-Aware Network Performance Monitoring (AA-NPM)

The challenge is that APM has evolved into a mosaic of monitoring tools, analytic engines, and event processors that provide many solutions to different problems. When you step back and look at the big picture it all comes into focus, but when you're trying to rationalize one technology over another, things aren't so clear at close range. I have found that the simplicity and ease of use with agentless monitoring (i.e. wire data analytics) is a great place to start. You may also hear the terms Application Aware Infrastructure Performance Monitoring (AA-IPM) or Application Aware Network Performance Monitoring (AA-NPM) both of which are complimentary to APM and I believe to be an essential part of an overall APM solution.
Larry Dragich
Director of Enterprise Application Services at the Auto Club Group and Founder of the APM Strategies Group on LinkedIn.

13. Deep Packet Inspection (DPI)

When it comes to APM, Deep Packet Inspection (DPI) isn't the first thing that comes to mind, but it should be, and we consider it a must-have in supporting APM. The general consensus seems to be that flow-based technologies (NetFlow, sFlow, IPFIX, etc.) provide enough visibility regarding communication, and end-point solutions provide the details from the client point of view. But network and application analysis based on DPI can provide all this and more. DPI provides definitive latency measurements, and it quickly allows analysts to isolate the problem to the network or the application. Once isolated, payload information from packets in the communication path can provide insights that no other solution can – like error messages that are being returned but not correctly processed by applications. And when combined with network forensics (storing packets for detailed, post-incident analysis), critical application transactions can be unequivocally verified from days or even weeks ago, something that is not available in any other form of APM solution.
Jay Botelho
Director of Product Management, WildPackets

14. Network Packet Recording

Something that all enterprises should seek out is accurate network packet recording. It's imperative to have a solution that can capture, index and record network traffic with continuous 100% accuracy even during unpredictable traffic spikes. Accurate network packet recording enables IT teams to troubleshoot and diagnose network and application performance issues as soon as they arise, and help security teams investigate and contain security problems and help risk and compliance teams do their jobs. Operations teams can determine whether the problems reside within the IT infrastructure or within the applications running on the network – reducing time-to-resolution (TTR) and lowering operational expenditures (OPEX). Traditional detection tools won't cut it in an era where millions of dollars in revenue can be lost with milliseconds of downtime – the key is maintaining a network infrastructure that delivers continuous historical network visibility.
Mike Heumann
Sr. Director, Marketing (Endace), Emulex

15. Network Emulation

Network Emulation is a must have. The first part of an APM cycle is to ensure that applications are designed/suitable for the deployed environment. The Network (Mobile, WAN, Internet...) is a critical but often ignored component of this. One reason is the complexity of going about verifying applications in real world networks, however Network Emulation makes this easy by providing the ability to replicate the complete network environment. By re-creating all real world network conditions (restricted bandwidth, latency, loss, QoS etc), Network Emulation gives organizations an accurate assessment of whether an application is suitable for them, long before they try to manage, with APM, the unmanageable.
Jim Swepson
Pre-sales Technologist, iTrinegy

20 Technologies to Support APM - Part 4

Hot Topics

The Latest

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 ...

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 ...

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 ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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 ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...