APM and Observability: Cutting Through the Confusion — Part 7

Pete Goldin
APMdigest

APM and Observability are often utilized by different teams within an organization, though there is considerable overlap, according to Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions.

Start with: APM and Observability - Cutting Through the Confusion - Part 6

In Part 7, the experts examine the different roles in IT and how they use either APM and Observability, or both:

APPLICATION OWNERS: DEV AND ITOPS

APM tools, with their guided interfaces and focus on specific application metrics, are often used directly by application developers, operations teams, and sometimes even product managers to understand application health and user experience.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

APM is owned primarily by the application owners and developers, who typically have some latitude over how to monitor their specific applications.
Paul Appleby
CEO, Virtana

APM tools are usually used by teams responsible for developing, deploying, and maintaining software applications. This typically entails software developers, SREs, and QA and performance testing teams.
Douglas James
VP, Solutions & Ecosystem, ScienceLogic

DEVELOPERS

APM tends to be the go-to for developers, application support, and QA professionals focused on application performance and behavior. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM is a more focused tool for application developers, and while application developers also use observability, other roles also make use of observability. 
Chrystal Taylor
Tech Evangelist, SolarWinds

APM offers granular insights at the code level, such as transaction tracing and end-user monitoring, which are indispensable for developers tackling application-specific challenges. These capabilities are foundational for diagnosing and resolving issues within the application layer.
Gab Menachem
VP ITOM, ServiceNow

The Tech Radar 2025 notes how developers experimenting with observability feel more empowered because it gives them the insight and autonomy to debug and optimize systems independently, not just escalate tickets.
Brian Douglas
Head of Ecosystem, Cloud Native Computing Foundation (CNCF)

DEVOPS

Observability is more commonly in the hands of site reliability engineers, DevOps, and platform teams who oversee the overall health and stability of complex, distributed systems. As DevOps practices continue to mature and responsibilities shift further left, these roles are increasingly converging. Today, it's common for engineers across these functions to leverage both APM and observability tools to ensure seamless deployment and smooth operations.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

Historically, APM and observability have been used in different roles. APM was used more by operations/monitoring teams, while observability was used more by developers/DevOps. However, this division is eroding as DevOps practices take hold and operational complexity increases. The shift from segregated to unified operational responsibility mirrors the broader IT evolution.
Jeff Cobb
Global Head of Product & Design, Chronosphere

SITE RELIABILITY ENGINEERS AND PLATFORM ENGINEERS

Observability practices, requiring deeper interaction with raw data, query languages, and system-wide context, tend to be the domain of more specialized roles like Site Reliability Engineers (SREs) or dedicated observability platform teams who need to perform deeper, more exploratory investigations.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

SREs and platform engineers harness observability for cross-system visibility. Observability's holistic view is a game-changer for managing modern, distributed systems ensuring everything runs smoothly and efficiently.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

Observability tools are designed to support SRE-based management objectives focused on error budgets as opposed to generating unneeded alerts. As an example, if a cluster is nearing capacity, should an alert be generated? For traditional IT Ops, this would be a typical alert. However, for SREs and developers already struggling with alert fatigue, there should not be an alert created as the Kubernetes pod should auto scale. The SRE and developer focus should be on what is occurring if this autoscaling is failing when the application error budget is consumed.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

ITOPS

APM is typically used by the business and infrastructure monitoring teams. However, the utilization of more user-friendly observability tools with OpenTelemetry allows the ITOps teams to use the same data with the correlated logs and metrics aligned to traces to triage issues and route appropriately (is it a code issue or a 3rd party latency?) and still allows developers and SREs to use existing toolsets where they have experience.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

CROSS-FUNCTIONAL

The roles in these spaces are fluid to begin with. I have yet to see two SREs in two different organizations with the same job description. Different organizations will have different operational models due to different team structures, team resourcing, tech stacks, etc.
Sven Delmas
VP of Research, Mezmo

Developers have gravitated towards APM, while operations and site reliability engineers (SREs) have focused on observability. However, as collaboration becomes more critical and systems grow increasingly interconnected, these roles are converging. Teams now require tools that foster a shared understanding and provide insights that transcend individual roles, enhancing collective efficacy. Observability's integration with GenAI further supports this convergence by providing a shared language and insights across roles.
Gab Menachem
VP ITOM, ServiceNow

A lot depends on your team's maturity, scale, personnel and organization. You might have a very large and clearly-delineated team, whereby the microservices team running a D-APM tool, is somewhat removed or walled-off from the database team that's running a database observability tool. Or the mobile client applications team might be far removed from the networking observability team. But in smaller organizations you might need to be a "jack-of-all-trades." Or at a larger organization you might be at that senior role and when those escalations occur, you need to be familiar with drilling down into any system across your organization, using whatever APM or observability tools your team has to troubleshoot, diagnose and resolve the most complex, urgent, bottom-line-impacting and pernicious of problems.
Peter Corless
Director, Product Marketing, StarTree

Platforms that unify telemetry data enable any team member to investigate issues without requiring specialized expertise in multiple tools.
Rakesh Gupta
Head of Product Management, Observe

Go to: APM and Observability: Cutting Through the Confusion — Part 8, exploring whether you need APM, Observability or both.

Pete Goldin is Editor and Publisher of APMdigest

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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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APM and Observability: Cutting Through the Confusion — Part 7

Pete Goldin
APMdigest

APM and Observability are often utilized by different teams within an organization, though there is considerable overlap, according to Arun Balachandran, Senior Product Marketing Manager, ManageEngine APM Solutions.

Start with: APM and Observability - Cutting Through the Confusion - Part 6

In Part 7, the experts examine the different roles in IT and how they use either APM and Observability, or both:

APPLICATION OWNERS: DEV AND ITOPS

APM tools, with their guided interfaces and focus on specific application metrics, are often used directly by application developers, operations teams, and sometimes even product managers to understand application health and user experience.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

APM is owned primarily by the application owners and developers, who typically have some latitude over how to monitor their specific applications.
Paul Appleby
CEO, Virtana

APM tools are usually used by teams responsible for developing, deploying, and maintaining software applications. This typically entails software developers, SREs, and QA and performance testing teams.
Douglas James
VP, Solutions & Ecosystem, ScienceLogic

DEVELOPERS

APM tends to be the go-to for developers, application support, and QA professionals focused on application performance and behavior. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

APM is a more focused tool for application developers, and while application developers also use observability, other roles also make use of observability. 
Chrystal Taylor
Tech Evangelist, SolarWinds

APM offers granular insights at the code level, such as transaction tracing and end-user monitoring, which are indispensable for developers tackling application-specific challenges. These capabilities are foundational for diagnosing and resolving issues within the application layer.
Gab Menachem
VP ITOM, ServiceNow

The Tech Radar 2025 notes how developers experimenting with observability feel more empowered because it gives them the insight and autonomy to debug and optimize systems independently, not just escalate tickets.
Brian Douglas
Head of Ecosystem, Cloud Native Computing Foundation (CNCF)

DEVOPS

Observability is more commonly in the hands of site reliability engineers, DevOps, and platform teams who oversee the overall health and stability of complex, distributed systems. As DevOps practices continue to mature and responsibilities shift further left, these roles are increasingly converging. Today, it's common for engineers across these functions to leverage both APM and observability tools to ensure seamless deployment and smooth operations.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

Historically, APM and observability have been used in different roles. APM was used more by operations/monitoring teams, while observability was used more by developers/DevOps. However, this division is eroding as DevOps practices take hold and operational complexity increases. The shift from segregated to unified operational responsibility mirrors the broader IT evolution.
Jeff Cobb
Global Head of Product & Design, Chronosphere

SITE RELIABILITY ENGINEERS AND PLATFORM ENGINEERS

Observability practices, requiring deeper interaction with raw data, query languages, and system-wide context, tend to be the domain of more specialized roles like Site Reliability Engineers (SREs) or dedicated observability platform teams who need to perform deeper, more exploratory investigations.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

SREs and platform engineers harness observability for cross-system visibility. Observability's holistic view is a game-changer for managing modern, distributed systems ensuring everything runs smoothly and efficiently.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

Observability tools are designed to support SRE-based management objectives focused on error budgets as opposed to generating unneeded alerts. As an example, if a cluster is nearing capacity, should an alert be generated? For traditional IT Ops, this would be a typical alert. However, for SREs and developers already struggling with alert fatigue, there should not be an alert created as the Kubernetes pod should auto scale. The SRE and developer focus should be on what is occurring if this autoscaling is failing when the application error budget is consumed.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

ITOPS

APM is typically used by the business and infrastructure monitoring teams. However, the utilization of more user-friendly observability tools with OpenTelemetry allows the ITOps teams to use the same data with the correlated logs and metrics aligned to traces to triage issues and route appropriately (is it a code issue or a 3rd party latency?) and still allows developers and SREs to use existing toolsets where they have experience.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

CROSS-FUNCTIONAL

The roles in these spaces are fluid to begin with. I have yet to see two SREs in two different organizations with the same job description. Different organizations will have different operational models due to different team structures, team resourcing, tech stacks, etc.
Sven Delmas
VP of Research, Mezmo

Developers have gravitated towards APM, while operations and site reliability engineers (SREs) have focused on observability. However, as collaboration becomes more critical and systems grow increasingly interconnected, these roles are converging. Teams now require tools that foster a shared understanding and provide insights that transcend individual roles, enhancing collective efficacy. Observability's integration with GenAI further supports this convergence by providing a shared language and insights across roles.
Gab Menachem
VP ITOM, ServiceNow

A lot depends on your team's maturity, scale, personnel and organization. You might have a very large and clearly-delineated team, whereby the microservices team running a D-APM tool, is somewhat removed or walled-off from the database team that's running a database observability tool. Or the mobile client applications team might be far removed from the networking observability team. But in smaller organizations you might need to be a "jack-of-all-trades." Or at a larger organization you might be at that senior role and when those escalations occur, you need to be familiar with drilling down into any system across your organization, using whatever APM or observability tools your team has to troubleshoot, diagnose and resolve the most complex, urgent, bottom-line-impacting and pernicious of problems.
Peter Corless
Director, Product Marketing, StarTree

Platforms that unify telemetry data enable any team member to investigate issues without requiring specialized expertise in multiple tools.
Rakesh Gupta
Head of Product Management, Observe

Go to: APM and Observability: Cutting Through the Confusion — Part 8, exploring whether you need APM, Observability or both.

Pete Goldin is Editor and Publisher of APMdigest

Related Links

Hot Topics

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Empowering the Human Side of the Autonomous IT Age

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

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.