APM and Observability: Cutting Through the Confusion — Part 3

Pete Goldin
APMdigest

In Part 2 of this series, the experts outlined the many advantages of APM, however, most of them agree that APM has a range of limitations and is only one component of a broader Observability approach.

"While both aim to enhance system performance and reliability, observability offers a broader, more holistic approach and is designed for today's complex, distributed systems, as opposed to traditional, application-specific monitoring with APM," explains Varma Kunaparaju, SVP and GM for Cloud Platform and OpsRamp Software at HPE. "APM remains valuable for targeted application performance, but its limitations do not meet the needs of today's complex IT environments. Embracing observability is crucial for ensuring optimal performance, resilience, and scalability in modern IT landscapes."

APM Challenges and Limitations

The experts outlined some of the limitations and challenges faced by APM tools, compared to Observability. These limitations do not devalue APM but merely show that APM is not an all-encompassing solution but rather one part of the whole.

Only Provides Application-Level Visibility

APM tools watch over an organization's applications and infrastructure on which they run and can alert teams to changes in performance. While this information can help IT specialists identify issues, analyze root cause, and resolve problems, it is an incomplete picture since it only looks at the application level.
Douglas James
VP, Solutions & Ecosystem, ScienceLogic

Unable to Catch Unknown or Unexpected Issues

Most APM tools today do provide a huge range of capabilities out of the box, offering a host of dashboards, alerts for expected failures, and easy routes to identifying aggregate issues like high-traffic bottlenecks. However, they can struggle to uncover granular, unknown, unexpected issues, or issues that arise from complex subsystem interactions. The key difference to me is that a classic APM tool supports investigating a finite list of specific issues and failure modes, whereas observability allows you to ask and answer arbitrary questions about your system. You don't need to have imagined a particular system failure mode or issue ahead of time to understand it via observability tooling.
Emily Nakashima
VP of Engineering, Honeycomb

Not Built for Distributed Systems

APM, as it's traditionally defined, is no longer sufficient. The world of apps has changed from the time APM became a category on the Gartner Magic Quadrant list. Applications (whether web-based, on a phone, etc.) are now a collection of APIs, microservices, and systems separated not only by geography but by cloud platform. Many APM solutions don't have the range of tooling or depth of insight needed.
Leon Adato
Principal Technology Advocate, Catchpoint

Limited Extensibility

Some APM tools offer turnkey experiences with quick setup, curated insights, and integrations with compliance reporting or business analytics dashboards. These can be useful in well-defined environments. However, these benefits often come at the cost of transparency and extensibility. If your system evolves, or if you need to answer new performance questions, you may find yourself constrained by the limits of pre-baked tools.
Brian Douglas
Head of Ecosystem, Cloud Native Computing Foundation (CNCF)

APM: An Essential Component of Observability

Most of the experts see APM as one component of a broader Observability platform or tool set.

"We shouldn't be thinking about a question of APM or Observability, but instead looking at APM as a core piece of any Observability strategy," says Nic Benders, Chief Technical Strategist at New Relic.

Observability encompasses APM as one of its core components, according to Andreas Grabner, Fellow DevRel and CNCF Ambassador, Dynatrace. While APM traditionally focuses on the health and performance of applications, observability extends beyond applications to include infrastructure, networks, user experience, logs, metrics, traces, and more. Observability aims to provide a comprehensive understanding of system behavior across the entire software delivery lifecycle.

"APM is a vital component within the broader framework of observability," Gab Menachem, VP ITOM at ServiceNow, agrees. "Observability is like a tapestry woven from logs, metrics, traces, and dependencies, each thread contributing to the complete picture. APM provides a focused view on application performance, a crucial chapter in the comprehensive story that observability tells. By expanding to more assets and signals, observability integrates APM into a larger narrative that includes business context, creating a holistic system of record for IT."

"From my perspective, it's helpful to view APM as a specific cultivation practice within the broader landscape of observability," Juraci Paixão Kröhling, Software Engineer at OllyGarden, elaborates. "Observability represents the capability to understand a system's internal state based on the data it emits (telemetry), allowing for exploration and the answering of novel questions. APM uses this same telemetry but focuses specifically on answering a predefined set of questions related to application performance, often through specialized tooling. In this sense, APM is a vital, focused application built upon the foundational principles and data streams that observability encompasses."

Kunaparaju from HPE explains that it's easy and often fair to view APM as a specialized component within the broader observability framework. Observability has four pillars — metrics, events, logs, and traces — to provide a holistic view of a system's behavior, particularly in distributed environments. APM focuses on metrics and traces for specific applications, providing deep insights into application performance but with less emphasis on logs or cross-system interactions.

While some might argue APM stands apart due to its application-specific focus, observability encompasses APM's capabilities plus additional visibility into logs and distributed system interactions, Kunaparaju continues. These comprehensive insights are needed to navigate the complexities of modern, distributed systems while ensuring resilience and scalability. This is why observability is the present and future of IT operations.

APM within Observability Platforms

Ariel Assaraf, CEO of Coralogix, points out that in a mature observability platform, you get APM built-in. You don't lose APM — you level it up with business context and analytics.

"What we're seeing now is an increased adoption — APM is increasingly being integrated into broader observability platforms," Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions, agrees, "allowing teams to combine real-time performance insights with deeper, system-wide understanding. In many ways, observability builds on the strengths of APM."

Balachandran continues, "While APM is excellent at surfacing known performance issues within the application layer, observability gives teams the flexibility to investigate both known and unknown problems across the entire stack. In that sense, APM fits naturally within the larger scope of observability. It addresses a critical piece of the puzzle, complementing the more exploratory and system-wide capabilities that observability offers. In conclusion, observability cannot exist without APM."

COUNTERPOINT: APM Is Not a Subset of Observability

Some of the experts dispute whether APM is technically a subset or component within Observability, so I am including that perspective here as well:

APM Is a Specialization

APM is not a form of observability, but more like a specialization. Observability captures performance (and all the other system behaviors) through multiple types of telemetry, while APM is specifically about application performance metrics and user experience factors, which is an area of specialization. This can be thought of as similar to medicine (e.g,. internal medicine), where specialists know more about a small area than a person practicing medicine. Both are needed in some capacity, and APM provides detail and depth about application performance while observability provides breadth into all systems.
Sam Suthar
Founding Director, Middleware

APM and Observability Solve Different Problems

APM is not a subset of observability. They represent solutions for different generational problems, not a hierarchical or nested relationship. I view the evolution of these technologies through distinct generational shifts, driven by changes in the underlying infrastructure being managed (Gen 1. hardware/network, Gen 2. software, Gen 3. VMs/cloud, Gen 4. containers). APM (particularly "Gen 3 APM," which most people refer to) was developed to solve the problems that arose with virtualization and cloud environments. Observability (Gen 4) is a response to the complexities and economic challenges introduced by containerization and microservices.

It's not a matter of observability being a broader category that simply includes APM. Or that observability has more capabilities than APM. It's about them each addressing a fundamentally different problem. Observability addresses new complexities, especially the scale and economics of data volume/telemetry, which didn't exist for APM.
Jeff Cobb
Global Head of Product & Design, Chronosphere

Go to: APM and Observability - Cutting Through the Confusion - Part 4

Pete Goldin is Editor and Publisher of APMdigest

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APM and Observability: Cutting Through the Confusion — Part 3

Pete Goldin
APMdigest

In Part 2 of this series, the experts outlined the many advantages of APM, however, most of them agree that APM has a range of limitations and is only one component of a broader Observability approach.

"While both aim to enhance system performance and reliability, observability offers a broader, more holistic approach and is designed for today's complex, distributed systems, as opposed to traditional, application-specific monitoring with APM," explains Varma Kunaparaju, SVP and GM for Cloud Platform and OpsRamp Software at HPE. "APM remains valuable for targeted application performance, but its limitations do not meet the needs of today's complex IT environments. Embracing observability is crucial for ensuring optimal performance, resilience, and scalability in modern IT landscapes."

APM Challenges and Limitations

The experts outlined some of the limitations and challenges faced by APM tools, compared to Observability. These limitations do not devalue APM but merely show that APM is not an all-encompassing solution but rather one part of the whole.

Only Provides Application-Level Visibility

APM tools watch over an organization's applications and infrastructure on which they run and can alert teams to changes in performance. While this information can help IT specialists identify issues, analyze root cause, and resolve problems, it is an incomplete picture since it only looks at the application level.
Douglas James
VP, Solutions & Ecosystem, ScienceLogic

Unable to Catch Unknown or Unexpected Issues

Most APM tools today do provide a huge range of capabilities out of the box, offering a host of dashboards, alerts for expected failures, and easy routes to identifying aggregate issues like high-traffic bottlenecks. However, they can struggle to uncover granular, unknown, unexpected issues, or issues that arise from complex subsystem interactions. The key difference to me is that a classic APM tool supports investigating a finite list of specific issues and failure modes, whereas observability allows you to ask and answer arbitrary questions about your system. You don't need to have imagined a particular system failure mode or issue ahead of time to understand it via observability tooling.
Emily Nakashima
VP of Engineering, Honeycomb

Not Built for Distributed Systems

APM, as it's traditionally defined, is no longer sufficient. The world of apps has changed from the time APM became a category on the Gartner Magic Quadrant list. Applications (whether web-based, on a phone, etc.) are now a collection of APIs, microservices, and systems separated not only by geography but by cloud platform. Many APM solutions don't have the range of tooling or depth of insight needed.
Leon Adato
Principal Technology Advocate, Catchpoint

Limited Extensibility

Some APM tools offer turnkey experiences with quick setup, curated insights, and integrations with compliance reporting or business analytics dashboards. These can be useful in well-defined environments. However, these benefits often come at the cost of transparency and extensibility. If your system evolves, or if you need to answer new performance questions, you may find yourself constrained by the limits of pre-baked tools.
Brian Douglas
Head of Ecosystem, Cloud Native Computing Foundation (CNCF)

APM: An Essential Component of Observability

Most of the experts see APM as one component of a broader Observability platform or tool set.

"We shouldn't be thinking about a question of APM or Observability, but instead looking at APM as a core piece of any Observability strategy," says Nic Benders, Chief Technical Strategist at New Relic.

Observability encompasses APM as one of its core components, according to Andreas Grabner, Fellow DevRel and CNCF Ambassador, Dynatrace. While APM traditionally focuses on the health and performance of applications, observability extends beyond applications to include infrastructure, networks, user experience, logs, metrics, traces, and more. Observability aims to provide a comprehensive understanding of system behavior across the entire software delivery lifecycle.

"APM is a vital component within the broader framework of observability," Gab Menachem, VP ITOM at ServiceNow, agrees. "Observability is like a tapestry woven from logs, metrics, traces, and dependencies, each thread contributing to the complete picture. APM provides a focused view on application performance, a crucial chapter in the comprehensive story that observability tells. By expanding to more assets and signals, observability integrates APM into a larger narrative that includes business context, creating a holistic system of record for IT."

"From my perspective, it's helpful to view APM as a specific cultivation practice within the broader landscape of observability," Juraci Paixão Kröhling, Software Engineer at OllyGarden, elaborates. "Observability represents the capability to understand a system's internal state based on the data it emits (telemetry), allowing for exploration and the answering of novel questions. APM uses this same telemetry but focuses specifically on answering a predefined set of questions related to application performance, often through specialized tooling. In this sense, APM is a vital, focused application built upon the foundational principles and data streams that observability encompasses."

Kunaparaju from HPE explains that it's easy and often fair to view APM as a specialized component within the broader observability framework. Observability has four pillars — metrics, events, logs, and traces — to provide a holistic view of a system's behavior, particularly in distributed environments. APM focuses on metrics and traces for specific applications, providing deep insights into application performance but with less emphasis on logs or cross-system interactions.

While some might argue APM stands apart due to its application-specific focus, observability encompasses APM's capabilities plus additional visibility into logs and distributed system interactions, Kunaparaju continues. These comprehensive insights are needed to navigate the complexities of modern, distributed systems while ensuring resilience and scalability. This is why observability is the present and future of IT operations.

APM within Observability Platforms

Ariel Assaraf, CEO of Coralogix, points out that in a mature observability platform, you get APM built-in. You don't lose APM — you level it up with business context and analytics.

"What we're seeing now is an increased adoption — APM is increasingly being integrated into broader observability platforms," Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions, agrees, "allowing teams to combine real-time performance insights with deeper, system-wide understanding. In many ways, observability builds on the strengths of APM."

Balachandran continues, "While APM is excellent at surfacing known performance issues within the application layer, observability gives teams the flexibility to investigate both known and unknown problems across the entire stack. In that sense, APM fits naturally within the larger scope of observability. It addresses a critical piece of the puzzle, complementing the more exploratory and system-wide capabilities that observability offers. In conclusion, observability cannot exist without APM."

COUNTERPOINT: APM Is Not a Subset of Observability

Some of the experts dispute whether APM is technically a subset or component within Observability, so I am including that perspective here as well:

APM Is a Specialization

APM is not a form of observability, but more like a specialization. Observability captures performance (and all the other system behaviors) through multiple types of telemetry, while APM is specifically about application performance metrics and user experience factors, which is an area of specialization. This can be thought of as similar to medicine (e.g,. internal medicine), where specialists know more about a small area than a person practicing medicine. Both are needed in some capacity, and APM provides detail and depth about application performance while observability provides breadth into all systems.
Sam Suthar
Founding Director, Middleware

APM and Observability Solve Different Problems

APM is not a subset of observability. They represent solutions for different generational problems, not a hierarchical or nested relationship. I view the evolution of these technologies through distinct generational shifts, driven by changes in the underlying infrastructure being managed (Gen 1. hardware/network, Gen 2. software, Gen 3. VMs/cloud, Gen 4. containers). APM (particularly "Gen 3 APM," which most people refer to) was developed to solve the problems that arose with virtualization and cloud environments. Observability (Gen 4) is a response to the complexities and economic challenges introduced by containerization and microservices.

It's not a matter of observability being a broader category that simply includes APM. Or that observability has more capabilities than APM. It's about them each addressing a fundamentally different problem. Observability addresses new complexities, especially the scale and economics of data volume/telemetry, which didn't exist for APM.
Jeff Cobb
Global Head of Product & Design, Chronosphere

Go to: APM and Observability - Cutting Through the Confusion - Part 4

Pete Goldin is Editor and Publisher of APMdigest

Related Links

Hot Topics

The Latest

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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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 ...

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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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

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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.

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