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What You Should Be Monitoring to Ensure Digital Performance - Part 4

APMdigest asked experts from across the IT industry for their opinions on what IT departments should be monitoring to ensure digital performance. Part 4 covers the infrastructure, including the cloud and the network.

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 1

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 2

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 3

DATA

Data performance monitoring is the most important aspect to ensure digital performance. Data transformed into content will dictate the end user experience. Data represented as text, images, video or voxels in extended reality requires continual monitoring to ensure quality of experience. IT departments can determine the amount of investment required to modify the network and application components based upon data performance. Data visualization formats can also be modified to function on the status quo infrastructure until the upgrade investments are in place.
Dos Dosanjh
Director, Technical Marketing, Quali

Monitor slow flow data - collected by standard discovery tools to map changes in network, apps, data, location or users. And fast flow data - collected by log analyzers, webcasters, and real time discovery to overlay changes to dependency map.
Jeanne Morain
Author and Strategist, iSpeak Cloud

BIG DATA TECHNOLOGIES

Organizations need to be able to monitor the big data technology that modern applications are increasingly reliant upon. These apps need fast access to technologies such as Hadoop, Kafka, Spark and Hbase, in order to make business critical decisions across all verticals, including financial services, retail, manufacturing, healthcare and telecom. For example, in finance, fraud detection leverages streaming data from systems like Kafka and Spark Streaming to collect and process information in order to detect any irregular patterns and prevent fraudulent transactions. Streaming apps like these have complex distributed architectures and produce massive volumes of data that is constantly changing. This makes them susceptible to performance issues, jeopardizing the important business process they were supporting. It's critical that enterprises monitor these modern data apps with a strong application performance management (APM) platform that has end-to-end observability and AI-driven automation at the core.
Kunal Agarwal
CEO, Unravel Data

MAINFRAME

Ever since servers of all types began processing transactions between businesses and the web/mobile devices, the need for millisecond performance between the end-user and the mainframe back-end data repository has existed. Along this path, there are numerous moving parts that contribute to a delightful or disastrous user experience. Focus must be given to monitoring mainframe performance as most web and mobile applications end with a purchase, a bank account deposit, or some exchange that ultimately takes place on a back-end mainframe.
Kelly Vogt
Performance Consultant, Compuware

MIDDLEWARE

One component that people often miss: the middleware. Whether it be on-premises ESBs, cloud-based iPaaS, or some combination, if the middleware has an issue, it can adversely impact the customer experience.
Jason Bloomberg
President, Intellyx

INTERACTIONS BETWEEN CLOUDS

As organizations increasingly adopt multi-cloud strategies, there's a growing need to monitor not just the performance (speed, reliability) of individual cloud infrastructures themselves, but also the interactions between these platforms. When deploying a multi-cloud environment, fast, reliable interoperability between multiple cloud regions and providers can be the key to strong performance for entire end-to-end componentized applications.
Mehdi Daoudi
CEO and Founder, Catchpoint

NETWORK

Digital performance is a full-stack affair, so it's essential to monitor the network at the wire level all the way to the applications and real user experience.
Jason Bloomberg
President, Intellyx

The most important metric for IT teams to monitor is the performance of the network.
Douglas Roberts
VP and General Manager, Viavi Enterprise and Cloud Business Unit

Digital performance monitoring requires complete network visibility to expose hidden problems and soon-to-be problems.
Keith Bromley
Senior Manager, Solutions Marketing, Ixia Solutions Group a Keysight Technologies business

Networks can be needy: They often require constant attention to ensure continuous uptime and properly defend against cyberattacks. Traditional symptom-based SNMP monitoring isn't enough to ensure (or enhance) digital performance – IT teams need to leverage proactive network monitoring and contextualized visibility. Waiting for a problem to occur and then trying to track down the source with an outdated map or protocols results in more time troubleshooting and increased MTTR, leaving less time and brain space for making strategic updates or otherwise optimizing digital performance. Instead of always operating in crisis mode, network teams need to employ network automation to continuously monitor for underlying faults, identify problems in context to speed recovery and proactively enforce best practices.
Jason Baudreau
Product Specialist, NetBrain

SD-WAN

Ensuring digital performance today can be a proxy for keeping employees productive. When networks are slow, people are slow. The adoption of SD-WAN is enticing for large enterprises seeking to lower costs or increase flexibility for remote locations, but it's not a silver bullet and what's missing from this discussion is end-to-end performance baselining. SD-WAN has no effect on issues outside of the WAN and the application delivery path is constantly changing so monitoring before, during, and after SD-WAN deployment across the entire connection is essential to finding and fixing issues that degrade user experience no matter where the issue occurs.
Sean Armstrong
VP of Product, AppNeta

Read What You Should Be Monitoring to Ensure Digital Performance - Part 5, the final installment, with some recommendations you may not have thought about.

The Latest

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...

What You Should Be Monitoring to Ensure Digital Performance - Part 4

APMdigest asked experts from across the IT industry for their opinions on what IT departments should be monitoring to ensure digital performance. Part 4 covers the infrastructure, including the cloud and the network.

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 1

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 2

Start with What You Should Be Monitoring to Ensure Digital Performance - Part 3

DATA

Data performance monitoring is the most important aspect to ensure digital performance. Data transformed into content will dictate the end user experience. Data represented as text, images, video or voxels in extended reality requires continual monitoring to ensure quality of experience. IT departments can determine the amount of investment required to modify the network and application components based upon data performance. Data visualization formats can also be modified to function on the status quo infrastructure until the upgrade investments are in place.
Dos Dosanjh
Director, Technical Marketing, Quali

Monitor slow flow data - collected by standard discovery tools to map changes in network, apps, data, location or users. And fast flow data - collected by log analyzers, webcasters, and real time discovery to overlay changes to dependency map.
Jeanne Morain
Author and Strategist, iSpeak Cloud

BIG DATA TECHNOLOGIES

Organizations need to be able to monitor the big data technology that modern applications are increasingly reliant upon. These apps need fast access to technologies such as Hadoop, Kafka, Spark and Hbase, in order to make business critical decisions across all verticals, including financial services, retail, manufacturing, healthcare and telecom. For example, in finance, fraud detection leverages streaming data from systems like Kafka and Spark Streaming to collect and process information in order to detect any irregular patterns and prevent fraudulent transactions. Streaming apps like these have complex distributed architectures and produce massive volumes of data that is constantly changing. This makes them susceptible to performance issues, jeopardizing the important business process they were supporting. It's critical that enterprises monitor these modern data apps with a strong application performance management (APM) platform that has end-to-end observability and AI-driven automation at the core.
Kunal Agarwal
CEO, Unravel Data

MAINFRAME

Ever since servers of all types began processing transactions between businesses and the web/mobile devices, the need for millisecond performance between the end-user and the mainframe back-end data repository has existed. Along this path, there are numerous moving parts that contribute to a delightful or disastrous user experience. Focus must be given to monitoring mainframe performance as most web and mobile applications end with a purchase, a bank account deposit, or some exchange that ultimately takes place on a back-end mainframe.
Kelly Vogt
Performance Consultant, Compuware

MIDDLEWARE

One component that people often miss: the middleware. Whether it be on-premises ESBs, cloud-based iPaaS, or some combination, if the middleware has an issue, it can adversely impact the customer experience.
Jason Bloomberg
President, Intellyx

INTERACTIONS BETWEEN CLOUDS

As organizations increasingly adopt multi-cloud strategies, there's a growing need to monitor not just the performance (speed, reliability) of individual cloud infrastructures themselves, but also the interactions between these platforms. When deploying a multi-cloud environment, fast, reliable interoperability between multiple cloud regions and providers can be the key to strong performance for entire end-to-end componentized applications.
Mehdi Daoudi
CEO and Founder, Catchpoint

NETWORK

Digital performance is a full-stack affair, so it's essential to monitor the network at the wire level all the way to the applications and real user experience.
Jason Bloomberg
President, Intellyx

The most important metric for IT teams to monitor is the performance of the network.
Douglas Roberts
VP and General Manager, Viavi Enterprise and Cloud Business Unit

Digital performance monitoring requires complete network visibility to expose hidden problems and soon-to-be problems.
Keith Bromley
Senior Manager, Solutions Marketing, Ixia Solutions Group a Keysight Technologies business

Networks can be needy: They often require constant attention to ensure continuous uptime and properly defend against cyberattacks. Traditional symptom-based SNMP monitoring isn't enough to ensure (or enhance) digital performance – IT teams need to leverage proactive network monitoring and contextualized visibility. Waiting for a problem to occur and then trying to track down the source with an outdated map or protocols results in more time troubleshooting and increased MTTR, leaving less time and brain space for making strategic updates or otherwise optimizing digital performance. Instead of always operating in crisis mode, network teams need to employ network automation to continuously monitor for underlying faults, identify problems in context to speed recovery and proactively enforce best practices.
Jason Baudreau
Product Specialist, NetBrain

SD-WAN

Ensuring digital performance today can be a proxy for keeping employees productive. When networks are slow, people are slow. The adoption of SD-WAN is enticing for large enterprises seeking to lower costs or increase flexibility for remote locations, but it's not a silver bullet and what's missing from this discussion is end-to-end performance baselining. SD-WAN has no effect on issues outside of the WAN and the application delivery path is constantly changing so monitoring before, during, and after SD-WAN deployment across the entire connection is essential to finding and fixing issues that degrade user experience no matter where the issue occurs.
Sean Armstrong
VP of Product, AppNeta

Read What You Should Be Monitoring to Ensure Digital Performance - Part 5, the final installment, with some recommendations you may not have thought about.

The Latest

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...