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.

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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.

Related Links

Hot Topics

The Latest

AI is Moving Fast, and Enterprise File Data Is Not Ready

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Move Fast Without the Usual Quality Penalty

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

When the Observability Bill Arrives for Agentic AI

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

AI is Breaking Enterprise Log Management

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

How Edge Intelligence Will Redefine Secure Connectivity

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

Production Inference Shifts Decisively to Private Cloud

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

Why DevOps Teams Build GenAI Tooling While Most Organizations Still Rely on Manual Monitoring

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Why Cloud Reliability Comes Down to People and How to Improve It

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

Why IT Keeps Getting Handed an AI Training Problem It Can't Solve Alone

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

Bringing IBM i Into the Modern Observability Stack: The Missing Piece of Enterprise AIOps

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...