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APM and Observability: Cutting Through the Confusion — Part 2

Pete Goldin
APMdigest

One of the key questions this APMdigest series seeks to answer: Is APM still relevant, or is it being replaced by Observability tools?

Start with: APM and Observability - Cutting Through the Confusion - Part 1

"APM still serves a purpose, especially for teams managing tightly scoped monoliths or those early in their cloud native journey," says Brian Douglas, Head of Ecosystem, Cloud Native Computing Foundation (CNCF). "It provides fast, out-of-the-box insights into application health."

"APM remains a vital tool in the shed; it hasn't been replaced by observability, but rather complemented by it," adds Juraci Paixão Kröhling, Software Engineer at OllyGarden. "APM excels at providing clear, often specialized views into known application performance characteristics, making it accessible even to those who aren't telemetry experts. Observability offers a broader, more exploratory capability, but APM's focused approach to monitoring specific, critical application pathways and performance indicators continues to offer distinct value, much like a dedicated pruning shear is still essential even when you have a multi-purpose garden tool."

Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions, agrees, "APM continues to be a vital part of the modern monitoring stack — it hasn't been replaced by observability, and that's for good reason. While observability offers a broader, more flexible approach to understanding complex systems, APM plays a foundational role in tracking performance metrics, monitoring application health, and providing visibility into the end-user experience. These capabilities are especially critical for ensuring stability and performance in production environments."

With this in mind, the following are advantages that the experts say make APM unique and essential. In some of these specific cases, the experts even say APM is better suited than Observability.

Insight into App Performance

I believe APM still delivers specific advantages that aren't always fully met by broader observability tools. APM solutions often exhibit a greater degree of polish and specialization when it comes to capabilities like real user monitoring, precise transaction tracing, and automated instrumentation for widely used application frameworks. These particular features allow teams to gain rapid insights into application performance with minimal initial configuration.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM remains a critical capability within a broader observability strategy. While observability offers a more holistic view across modern cloud-native environments, the granular insights that APM provides into application performance are still essential for root-cause analysis, service-level management, and ensuring user satisfaction.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

APM alone helps answer application-centric questions like, "Is there an issue?" and "Where is the issue coming from?" With APM, the focus is on monitoring the reliability and performance of apps, services and dependencies primarily through the lens of RED (rate, errors and duration) metrics, distributed traces, and code profiles (code-level performance).
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

It's a matter of focus. APM is specifically looking at the application as the subject, the system-under-test, the primary culprit. While observability is a broad-based field — ie. think of a telescope scanning all stars and planets across a night sky for new phenomena — APM is landing on one of those distant bodies and taking soil samples. I would not expect a generic observability platform to understand the nature of this specific metric value, log error message, or crash dump for this specific application. There's a time and a place to double-click on an object on a big end-to-end architecture block diagram and look inside it. That's where APM shines. Asking if observability "replaced" APM is like asking if "car" has replaced "engine." Applications remain the vital engine at the heart of our distributed systems.
Peter Corless
Director, Product Marketing, StarTree

Tight Integration with Application Frameworks

APM tools are often more opinionated and tightly integrated with specific application frameworks. That can be a benefit when you need easy-to-read dashboards, automatic instrumentation, or transaction tracing out of the box. 
Gurjeet Arora
CEO and Co-Founder, Observo AI

End-User Experience Visibility

APM platforms frequently provide readily available, curated dashboards, robust SLA tracking, and out-of-the-box business transaction monitoring. These functionalities can prove especially beneficial for development and product teams whose primary focus lies in ensuring optimal end-user performance and satisfaction.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM tools often provide rich, user-experience-centric views (like detailed monitoring dashboards), which aren't always the focus of broader observability solutions.
Gurjeet Arora
CEO and Co-Founder, Observo AI

Digital Experience Monitoring

APM capabilities can sometimes be called Digital Experience Monitoring (DXM) and include things like Real-User Monitoring (RUM) and Synthetic Monitoring — elements outside of MELT (Metrics, Events, Logs, Traces) that typically power observability but may still be needed for specific use cases. APM often provides deeper code-level visibility and user journey tracking that may not be fully addressed in broader observability platforms.
Paul Appleby
CEO, Virtana

Synthetic Monitoring

While observability tools can cover most use cases for APM, it is appropriate to consider APM tools for simpler monitoring by the business. Observability solutions do not deliver multi-site synthetic transactions. Traditionally, APM tools are much better suited to deliver multi-location synthetic monitoring. Site performance isolation by probing the same application from different sites, or off-hour validation, or simply ad hoc validation to determine if a fix actually improved user performance will always best be covered by synthetic monitoring. 
Harald Burose
Director, Product Management, Research & Development, OpenText

Better Instrumentation for Monolithic and Legacy Environments

APM remains critical for organizations that need detailed, application-specific insights such as transaction tracing and code-level diagnostics, particularly in monolithic or legacy systems.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

APM is still a necessary tool because observability is an evolution, not a revolution. Many APM capabilities remain relevant, especially in legacy environments where APM agents for now offer better instrumentation than modern observability stacks. In those environments observability tools don't yet fully match APM's feature depth, so teams often still must use both side-by-side. The best solutions recognize this and allow users to ingest data from both, enabling comprehensive root cause analysis across systems.
Severin Neumann
Head of Community & Developer Relations, Causely

It's not just that observability is better than APM for everything and for all of the old use cases. It's not. APM solutions still have value depending on the era of architecture you are managing and the amount of time it will take to convert your overall infrastructure. What I mean is APM still has value for organizations that haven't fully transitioned to containerized architectures. APM tools can effectively manage and troubleshoot environments built on older architectures that observability tools aren't necessarily designed for or optimized to handle.
Jeff Cobb
Global Head of Product & Design, Chronosphere

User-Friendly Tooling

Tools that aspire to be overall "observability tools" can learn a lot from APM tooling about how to provide a great user experience that guides people quickly toward valuable information. With today's observability tools, there can be a learning curve when transitioning from an APM tool, because it's less clear how to ask the sorts of questions that APM tools provide pre-canned answers to. The additional benefits to observability may only become clear once teams master new skills like custom instrumentation or constructing queries. This is something I see us working to improve across the board in the observability space: how can we continue to get better at providing the full flexibility of observability with the friendliness of APM?
Emily Nakashima
VP of Engineering, Honeycomb

Out-of-the-Box Simplicity

APM provides highly specialized and curated user experiences tailored to specific, common performance analysis tasks, such as identifying slow database queries or mapping transaction flows with pre-built visualizations. These purpose-built interfaces often lower the barrier to entry, allowing software engineers or product teams who aren't observability specialists to quickly gain insights into application behavior without needing to master complex query languages. Observability's strength lies in its exploratory power, but it may not offer the same level of out-of-the-box simplicity for these well-trodden analytical paths.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

Immediate Value

In the case of simpler applications or needs, most APM tools can provide value immediately with targeted metrics and easy visualization. On the other hand, observability provides comprehensive system understanding through logs, metrics, and traces.
Sam Suthar
Founding Director, Middleware

Lower Cost

There is still broad usage of traditional APM tools, and they are absolutely appropriate because they do not carry the cost of observability tools with the massive data associated with traces and logs.
Harald Burose
Director, Product Management, Research & Development, OpenText

Go to: APM and Observability: Cutting Through the Confusion - Part 3, covering the limitations of APM and it's position as a component of Observability.

Pete Goldin is Editor and Publisher of APMdigest

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

APM and Observability: Cutting Through the Confusion — Part 2

Pete Goldin
APMdigest

One of the key questions this APMdigest series seeks to answer: Is APM still relevant, or is it being replaced by Observability tools?

Start with: APM and Observability - Cutting Through the Confusion - Part 1

"APM still serves a purpose, especially for teams managing tightly scoped monoliths or those early in their cloud native journey," says Brian Douglas, Head of Ecosystem, Cloud Native Computing Foundation (CNCF). "It provides fast, out-of-the-box insights into application health."

"APM remains a vital tool in the shed; it hasn't been replaced by observability, but rather complemented by it," adds Juraci Paixão Kröhling, Software Engineer at OllyGarden. "APM excels at providing clear, often specialized views into known application performance characteristics, making it accessible even to those who aren't telemetry experts. Observability offers a broader, more exploratory capability, but APM's focused approach to monitoring specific, critical application pathways and performance indicators continues to offer distinct value, much like a dedicated pruning shear is still essential even when you have a multi-purpose garden tool."

Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions, agrees, "APM continues to be a vital part of the modern monitoring stack — it hasn't been replaced by observability, and that's for good reason. While observability offers a broader, more flexible approach to understanding complex systems, APM plays a foundational role in tracking performance metrics, monitoring application health, and providing visibility into the end-user experience. These capabilities are especially critical for ensuring stability and performance in production environments."

With this in mind, the following are advantages that the experts say make APM unique and essential. In some of these specific cases, the experts even say APM is better suited than Observability.

Insight into App Performance

I believe APM still delivers specific advantages that aren't always fully met by broader observability tools. APM solutions often exhibit a greater degree of polish and specialization when it comes to capabilities like real user monitoring, precise transaction tracing, and automated instrumentation for widely used application frameworks. These particular features allow teams to gain rapid insights into application performance with minimal initial configuration.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM remains a critical capability within a broader observability strategy. While observability offers a more holistic view across modern cloud-native environments, the granular insights that APM provides into application performance are still essential for root-cause analysis, service-level management, and ensuring user satisfaction.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

APM alone helps answer application-centric questions like, "Is there an issue?" and "Where is the issue coming from?" With APM, the focus is on monitoring the reliability and performance of apps, services and dependencies primarily through the lens of RED (rate, errors and duration) metrics, distributed traces, and code profiles (code-level performance).
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

It's a matter of focus. APM is specifically looking at the application as the subject, the system-under-test, the primary culprit. While observability is a broad-based field — ie. think of a telescope scanning all stars and planets across a night sky for new phenomena — APM is landing on one of those distant bodies and taking soil samples. I would not expect a generic observability platform to understand the nature of this specific metric value, log error message, or crash dump for this specific application. There's a time and a place to double-click on an object on a big end-to-end architecture block diagram and look inside it. That's where APM shines. Asking if observability "replaced" APM is like asking if "car" has replaced "engine." Applications remain the vital engine at the heart of our distributed systems.
Peter Corless
Director, Product Marketing, StarTree

Tight Integration with Application Frameworks

APM tools are often more opinionated and tightly integrated with specific application frameworks. That can be a benefit when you need easy-to-read dashboards, automatic instrumentation, or transaction tracing out of the box. 
Gurjeet Arora
CEO and Co-Founder, Observo AI

End-User Experience Visibility

APM platforms frequently provide readily available, curated dashboards, robust SLA tracking, and out-of-the-box business transaction monitoring. These functionalities can prove especially beneficial for development and product teams whose primary focus lies in ensuring optimal end-user performance and satisfaction.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM tools often provide rich, user-experience-centric views (like detailed monitoring dashboards), which aren't always the focus of broader observability solutions.
Gurjeet Arora
CEO and Co-Founder, Observo AI

Digital Experience Monitoring

APM capabilities can sometimes be called Digital Experience Monitoring (DXM) and include things like Real-User Monitoring (RUM) and Synthetic Monitoring — elements outside of MELT (Metrics, Events, Logs, Traces) that typically power observability but may still be needed for specific use cases. APM often provides deeper code-level visibility and user journey tracking that may not be fully addressed in broader observability platforms.
Paul Appleby
CEO, Virtana

Synthetic Monitoring

While observability tools can cover most use cases for APM, it is appropriate to consider APM tools for simpler monitoring by the business. Observability solutions do not deliver multi-site synthetic transactions. Traditionally, APM tools are much better suited to deliver multi-location synthetic monitoring. Site performance isolation by probing the same application from different sites, or off-hour validation, or simply ad hoc validation to determine if a fix actually improved user performance will always best be covered by synthetic monitoring. 
Harald Burose
Director, Product Management, Research & Development, OpenText

Better Instrumentation for Monolithic and Legacy Environments

APM remains critical for organizations that need detailed, application-specific insights such as transaction tracing and code-level diagnostics, particularly in monolithic or legacy systems.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

APM is still a necessary tool because observability is an evolution, not a revolution. Many APM capabilities remain relevant, especially in legacy environments where APM agents for now offer better instrumentation than modern observability stacks. In those environments observability tools don't yet fully match APM's feature depth, so teams often still must use both side-by-side. The best solutions recognize this and allow users to ingest data from both, enabling comprehensive root cause analysis across systems.
Severin Neumann
Head of Community & Developer Relations, Causely

It's not just that observability is better than APM for everything and for all of the old use cases. It's not. APM solutions still have value depending on the era of architecture you are managing and the amount of time it will take to convert your overall infrastructure. What I mean is APM still has value for organizations that haven't fully transitioned to containerized architectures. APM tools can effectively manage and troubleshoot environments built on older architectures that observability tools aren't necessarily designed for or optimized to handle.
Jeff Cobb
Global Head of Product & Design, Chronosphere

User-Friendly Tooling

Tools that aspire to be overall "observability tools" can learn a lot from APM tooling about how to provide a great user experience that guides people quickly toward valuable information. With today's observability tools, there can be a learning curve when transitioning from an APM tool, because it's less clear how to ask the sorts of questions that APM tools provide pre-canned answers to. The additional benefits to observability may only become clear once teams master new skills like custom instrumentation or constructing queries. This is something I see us working to improve across the board in the observability space: how can we continue to get better at providing the full flexibility of observability with the friendliness of APM?
Emily Nakashima
VP of Engineering, Honeycomb

Out-of-the-Box Simplicity

APM provides highly specialized and curated user experiences tailored to specific, common performance analysis tasks, such as identifying slow database queries or mapping transaction flows with pre-built visualizations. These purpose-built interfaces often lower the barrier to entry, allowing software engineers or product teams who aren't observability specialists to quickly gain insights into application behavior without needing to master complex query languages. Observability's strength lies in its exploratory power, but it may not offer the same level of out-of-the-box simplicity for these well-trodden analytical paths.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

Immediate Value

In the case of simpler applications or needs, most APM tools can provide value immediately with targeted metrics and easy visualization. On the other hand, observability provides comprehensive system understanding through logs, metrics, and traces.
Sam Suthar
Founding Director, Middleware

Lower Cost

There is still broad usage of traditional APM tools, and they are absolutely appropriate because they do not carry the cost of observability tools with the massive data associated with traces and logs.
Harald Burose
Director, Product Management, Research & Development, OpenText

Go to: APM and Observability: Cutting Through the Confusion - Part 3, covering the limitations of APM and it's position as a component of Observability.

Pete Goldin is Editor and Publisher of APMdigest

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...