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

APMdigest asked experts from across the IT industry for their opinions on what IT departments should be monitoring to ensure digital performance. Part 3 covers the development side.

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

CODE ERRORS

Code-level issues are a common cause of application slowness and have fueled the need for distributed transaction tracing, which can help isolate the exact line of code with errors. This type of monitoring can also be effectively applied in both pre- and post-production environments, enabling us to prevent performance issues before they impact end users as well as help isolate them when they do occur.
When this type of application monitoring is done in context of infrastructure dependencies, it helps distinguish if there are other issues affecting application code processing, such as a bottleneck in the application server, long-running database queries, slow third-party calls, or other issues that may be associated with the application ecosystem. Applications are the heart of IT workloads, and application performance monitoring is critical to effectively ensure the performance of digital services.
John Worthington
Director, Product Marketing, eG Innovations

Digital performance is complex and can be measured in many ways, but one critical consideration is how well does the application do what it is supposed to do? Is it meeting a functional performance metric for customer expectations? To ensure this, organizations need to look at the "fingerprint" of each error in code to discern its importance as well as look at the number of critical errors per release. This dictates the overall functional reliability of the code. It also requires you to be code-aware, monitoring from inside the application at runtime, not surrounding it or listening to the exhaust.
Tal Weiss
CTO and Co-Founder, OverOps

Most people already know to monitor the obvious things, like total latency to response. But my favorite monitor comes from Anatoly Mikhaylov's talk at DASH this year. He spoke about finding massive infrastructure costs hidden in error codes. Adding APM monitoring to the errors in your endpoints can show costs you wouldn't otherwise see.
Kirk Kaiser
APM Developer Advocate, Datadog

APPLICATION RELEASE

When automating you application release, it's important to remember what you need to monitor. This will allow you to go as fast as possible, but also make sure you are doing it efficiently. Monitor your lead time, success vs failure rate and mean time to recovery will ensure you focus on value rather than on effort.
Yaniv Yehuda
Co-Founder and CTO, DBmaestro

API

One key area to make sure you monitor: API calls. There aren't many applications I come across these days that do not include some 3rd-party API, be it for authentication, analytics, storage, or customer relationship management. Such API calls can so greatly impact digital performance that not monitoring them to identify things such as performance slowdowns and dependencies is a prescription for pain.
Jean Tunis
Senior Consultant and Founder of RootPerformance

Cloud, containers and microservices are creating increasingly ephemeral, modular and volatile IT environments. In these dynamic environments, traditional monitoring approaches fail. A modern monitoring approach is required to provide complete visibility into the applications, containers, host and underlying supporting infrastructure. This includes having visibility into the performance of and data returning from APIs which have become a key component to any microservices architecture. A modern monitoring approach includes the analytics and intelligence to understand how changes might impact the overall user experience and flexible monitoring techniques that don't overload the containerized application environment.
Amy Feldman
Director, Product Marketing, CA Technologies

Finding a tool that fits seamlessly into your workflows, setting performance benchmarks, validating payloads, and getting visibility into the performance of API transactions is critical to help teams get rapidly identify and fix issues in production so that the delivered digital experience matches the vision for end-users.
Anand Sundaram
VP of Product, AlertSite UXM, SmartBear

APIs are the fundamental building block of modern software. While engineering teams have built extensive monitoring systems to check the health of code execution paths, they have little visibility into what's going on with APIs. An API failure can bring down systems and without proper monitoring in place, it can be very hard to debug what's going on.
Abhinav Asthana
CEO, Postman

CONTAINERS

The nature of development means systems are going to spring into existence and then back out again often, and that this rapid change is OK, which means your monitoring needs to be OK with it. The ability to monitor containers, ephemeral services, and the like, is a must.
Leon Adato
Head Geek, SolarWinds

MICROSERVICES

Real users who recently reviewed APM solutions in the IT Central Station community recommend monitoring microservices. Click here to learn more.
Russell Rothstein
Founder and CEO, IT Central Station

Let's go to the extreme and say you could only monitor one thing — that one thing would be microservice response time. In this brave new world, it's actually quite difficult to understand how well your revenue-critical application is performing. While traditional metrics still matter (CPU, memory, disk, etc), your response time on a microservice-by-microservice basis is the thing that matters the most. This single metric will tell you more about the customer experience than anything else. It will indicate downtime or more subtle performance problems in your application. While this metric alone will not tell you "why" something is going on, it will tell you "what" is happening and allow you to quickly isolate a problem to a handful of services or some set of underlying infrastructure.
Apurva Davé
CMO, Sysdig

IO PATH

As you evolve and enhance your company's hybrid data center infrastructure to keep pace with your industry, understanding your unique workload I/O DNA is paramount to success. Real-time monitoring of the I/O path – from the virtual server to the storage array – is essential to ensuring digital performance. For mission-critical applications, understanding the performance of each and every transaction is the cornerstone of customer satisfaction and revenue assurance.
Len Rosenthal
CMO, Virtual Instruments

Read Len Rosenthal's new blog on APMdigest: Infrastructure Monitoring for Digital Performance Assurance.

Read What You Should Be Monitoring to Ensure Digital Performance - Part 4, covering the infrastructure, including the cloud and the network.

Hot Topics

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

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

APMdigest asked experts from across the IT industry for their opinions on what IT departments should be monitoring to ensure digital performance. Part 3 covers the development side.

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

CODE ERRORS

Code-level issues are a common cause of application slowness and have fueled the need for distributed transaction tracing, which can help isolate the exact line of code with errors. This type of monitoring can also be effectively applied in both pre- and post-production environments, enabling us to prevent performance issues before they impact end users as well as help isolate them when they do occur.
When this type of application monitoring is done in context of infrastructure dependencies, it helps distinguish if there are other issues affecting application code processing, such as a bottleneck in the application server, long-running database queries, slow third-party calls, or other issues that may be associated with the application ecosystem. Applications are the heart of IT workloads, and application performance monitoring is critical to effectively ensure the performance of digital services.
John Worthington
Director, Product Marketing, eG Innovations

Digital performance is complex and can be measured in many ways, but one critical consideration is how well does the application do what it is supposed to do? Is it meeting a functional performance metric for customer expectations? To ensure this, organizations need to look at the "fingerprint" of each error in code to discern its importance as well as look at the number of critical errors per release. This dictates the overall functional reliability of the code. It also requires you to be code-aware, monitoring from inside the application at runtime, not surrounding it or listening to the exhaust.
Tal Weiss
CTO and Co-Founder, OverOps

Most people already know to monitor the obvious things, like total latency to response. But my favorite monitor comes from Anatoly Mikhaylov's talk at DASH this year. He spoke about finding massive infrastructure costs hidden in error codes. Adding APM monitoring to the errors in your endpoints can show costs you wouldn't otherwise see.
Kirk Kaiser
APM Developer Advocate, Datadog

APPLICATION RELEASE

When automating you application release, it's important to remember what you need to monitor. This will allow you to go as fast as possible, but also make sure you are doing it efficiently. Monitor your lead time, success vs failure rate and mean time to recovery will ensure you focus on value rather than on effort.
Yaniv Yehuda
Co-Founder and CTO, DBmaestro

API

One key area to make sure you monitor: API calls. There aren't many applications I come across these days that do not include some 3rd-party API, be it for authentication, analytics, storage, or customer relationship management. Such API calls can so greatly impact digital performance that not monitoring them to identify things such as performance slowdowns and dependencies is a prescription for pain.
Jean Tunis
Senior Consultant and Founder of RootPerformance

Cloud, containers and microservices are creating increasingly ephemeral, modular and volatile IT environments. In these dynamic environments, traditional monitoring approaches fail. A modern monitoring approach is required to provide complete visibility into the applications, containers, host and underlying supporting infrastructure. This includes having visibility into the performance of and data returning from APIs which have become a key component to any microservices architecture. A modern monitoring approach includes the analytics and intelligence to understand how changes might impact the overall user experience and flexible monitoring techniques that don't overload the containerized application environment.
Amy Feldman
Director, Product Marketing, CA Technologies

Finding a tool that fits seamlessly into your workflows, setting performance benchmarks, validating payloads, and getting visibility into the performance of API transactions is critical to help teams get rapidly identify and fix issues in production so that the delivered digital experience matches the vision for end-users.
Anand Sundaram
VP of Product, AlertSite UXM, SmartBear

APIs are the fundamental building block of modern software. While engineering teams have built extensive monitoring systems to check the health of code execution paths, they have little visibility into what's going on with APIs. An API failure can bring down systems and without proper monitoring in place, it can be very hard to debug what's going on.
Abhinav Asthana
CEO, Postman

CONTAINERS

The nature of development means systems are going to spring into existence and then back out again often, and that this rapid change is OK, which means your monitoring needs to be OK with it. The ability to monitor containers, ephemeral services, and the like, is a must.
Leon Adato
Head Geek, SolarWinds

MICROSERVICES

Real users who recently reviewed APM solutions in the IT Central Station community recommend monitoring microservices. Click here to learn more.
Russell Rothstein
Founder and CEO, IT Central Station

Let's go to the extreme and say you could only monitor one thing — that one thing would be microservice response time. In this brave new world, it's actually quite difficult to understand how well your revenue-critical application is performing. While traditional metrics still matter (CPU, memory, disk, etc), your response time on a microservice-by-microservice basis is the thing that matters the most. This single metric will tell you more about the customer experience than anything else. It will indicate downtime or more subtle performance problems in your application. While this metric alone will not tell you "why" something is going on, it will tell you "what" is happening and allow you to quickly isolate a problem to a handful of services or some set of underlying infrastructure.
Apurva Davé
CMO, Sysdig

IO PATH

As you evolve and enhance your company's hybrid data center infrastructure to keep pace with your industry, understanding your unique workload I/O DNA is paramount to success. Real-time monitoring of the I/O path – from the virtual server to the storage array – is essential to ensuring digital performance. For mission-critical applications, understanding the performance of each and every transaction is the cornerstone of customer satisfaction and revenue assurance.
Len Rosenthal
CMO, Virtual Instruments

Read Len Rosenthal's new blog on APMdigest: Infrastructure Monitoring for Digital Performance Assurance.

Read What You Should Be Monitoring to Ensure Digital Performance - Part 4, covering the infrastructure, including the cloud and the network.

Hot Topics

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...