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"APM remains a vital tool in the shed; it hasn't been replaced by observability, but rather complemented by it," adds Juraci Paixão Kröhling, Software Engineer at OllyGarden.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ManageEngine APM Solutions, agrees, "APM continues to be a vital part of the modern monitoring stack — it hasn't been replaced by observability, and that's for good reason.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

Related Links

Hot Topics

The Latest

The Real Enterprise AI Risk Isn't Hallucinations

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

IT Leaders Must Establish a Network Data Architecture Practice

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

Data Center Outages Are Decreasing but More Costly

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

Observability Has a Physical Layer Now: What AI Infrastructure Teaches IT Operations

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

TLS Certificate Expiration Is Becoming an Observability Problem

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprise Cloud Observability: Choosing the Right Starting Point

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

AI Is Making Incident Management More Complex - Bad Data Makes It Harder

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

MEAN TIME TO INSIGHT Podcast - Episode 26: Network Compliance

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

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

Related Links

Hot Topics

The Latest

The Real Enterprise AI Risk Isn't Hallucinations

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

IT Leaders Must Establish a Network Data Architecture Practice

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

Data Center Outages Are Decreasing but More Costly

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

Observability Has a Physical Layer Now: What AI Infrastructure Teaches IT Operations

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

TLS Certificate Expiration Is Becoming an Observability Problem

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprise Cloud Observability: Choosing the Right Starting Point

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

AI Is Making Incident Management More Complex - Bad Data Makes It Harder

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

MEAN TIME TO INSIGHT Podcast - Episode 26: Network Compliance

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...