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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

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

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

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...