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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

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 ...

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

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 ...