APM and Observability: Cutting Through the Confusion — Part 11

Pete Goldin
APMdigest

What's in the future for APM and Observability?

Start with: APM and Observability - Cutting Through the Confusion - Part 10

"Things are now changing in three-month intervals, so the only thing to know is that it will be different," Sven Delmas, VP of Research at Mezmo, responds.

But the experts do have some ideas, and some of them even contradict each other. In the final installments of this series, the experts present their visions of the future for APM, Observability and beyond.

CONSOLIDATION OF APM AND OBSERVABILITY

The lines between APM and observability will continue to blur, as organizations seek more integrated and intelligent solutions.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

The convergence of APM and observability, bolstered by AI and open-source tools, will fundamentally reshape IT strategies across the globe. Organizations will shift towards holistic, integrated monitoring solutions, prioritizing flexibility, automation and comprehensive visibility.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

The lines between observability, monitoring and APM will continue to blur as enterprises expand their data collection sources and analysis to make application management more effective and to extract more value from their end user computing investment. Driving this trend is the continued proliferation of devices and applications in use, including SaaS and emerging AI applications, which has already created an almost unmanageable workload for IT teams. The lines will blur as enterprises will be looking for ways to consolidate APM, monitoring and observability functions for better manageability, streamlined data collection and more up-to-date insights that can be acted upon.
Simon Townsend
Head of the Office of the CTO, ControlUp

NEED FOR BOTH APM AND OBSERVABILITY

Organizations with mixed architectures will require both APM and observability tools for the foreseeable future. Transitioning to solely containerized environments is a gradual process, so older APM tools will still be necessary for legacy systems.
Jeff Cobb
Global Head of Product & Design, Chronosphere

UNIFIED PLATFORM

There will be a shift toward platform-based approaches that provide a single source of truth for teams across enterprises.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

Looking ahead, I reckon we can expect APM and observability to continue converging into unified, intelligent platforms that deliver comprehensive, full-stack visibility. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

COMPOSABLE PLATFORM

Instead of one massive platform, we'll see composable architectures where different teams use different tools, but all pull from a shared, optimized telemetry stream.
Gurjeet Arora
CEO and Co-Founder, Observo AI

A primary focus item for observability will be: Expanding observability into an open composable platform that allows customers to integrate and expand existing information and provide even better and faster insights.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

MORE ACCURATE TERMINOLOGY

I think the APM, observability and AIOps markets will all continue to transform. I'm hopeful that we will develop more accurate terminology that better reflects the sophistication and capabilities of this whole market and the tools/technologies that deliver amazing capabilities and insights.
Carlos Casanova
Principal Analyst, Forrester

MORE CONFUSING TERMINOLOGY

Market definitions of APM and observability will remain fluid and driven by vendor self-interest. Companies will continue to redefine terms to position themselves advantageously, leading to ongoing market confusion.
Jeff Cobb
Global Head of Product & Design, Chronosphere

REACTIVE TO PROACTIVE

Ultimately, observability and APM will both shift from being a reactive discipline to a proactive enabler of high reliability, security, and performance. Observability is going to expand and provide more answers to more problems across the business. 
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

Observability is poised to evolve from passive insight to active intelligence. We anticipate systems that not only detect anomalies but also initiate automated responses. As environments become increasingly dynamic, observability will transition from merely understanding current states to actively shaping and influencing future outcomes, driving innovation and resilience in unprecedented ways. The future will likely include a robust telemetry pipeline that dynamically decides which signals to store and send to higher-cost tools for analysis, potentially using GenAI to orchestrate the entire process of IT operations.
Gab Menachem
VP ITOM, ServiceNow

OPEN SOURCE

Open data protocols and acquisition methods will become increasingly important. Vendors will move away from proprietary data collection, and open protocols like OpenTelemetry and Prometheus will be favored to avoid vendor lock-in.
Jeff Cobb
Global Head of Product & Design, Chronosphere

OPENTELEMETRY

The future of Application Performance Monitoring (APM) is being reshaped by OpenTelemetry (OTel), which standardizes the semantics and collection of metrics, logs, and traces. This eliminates the limitations of traditional APM tools that rely on proprietary agents and formats, enabling developers to instrument once and analyze anywhere. As OTel adoption grows, its ecosystem of libraries is rapidly expanding to support diverse technologies such as LLMs, databases, messaging systems, CI/CD pipelines, and more. This evolution doesn't replace APM but enhances it, allowing vendors to focus on advanced features like AI-powered analytics rather than maintaining instrumentation layers.
Bahubali Shetti
Senior Director, Product Marketing, Elastic

Download the EMA Report: Taking Observability to the Next Level - OpenTelemetry’s Emerging Role in IT Performance and Reliability

The continued adoption of open standards like OpenTelemetry is driving industry wide consistency and enabling true interoperability across diverse environments. As data collection becomes standardized, the value shifts from simply getting data in, to how effectively APM vendors can analyze and operationalize that data. This shift will push vendors to compete on architectural excellence, data correlation, and the quality of insights delivered through AI rather than on proprietary data ingestion methods.
Mimi Shalash
Observability Advisor at Splunk, a Cisco Company

I anticipate a continued flourishing of observability practices, driven by increasing system complexity. We'll see a greater emphasis on telemetry quality and efficiency — what I call "purposeful instrumentation" — moving away from merely collecting vast amounts of data towards cultivating the right data needed for insight, partly driven by cost pressures. AI/ML will become more deeply integrated, providing smarter insights. Managing the telemetry pipeline itself will become a critical focus area, with solutions emerging to handle the complexity of collecting, processing, and routing telemetry data effectively at scale. Through all this, I believe the open standard of OpenTelemetry will become even more foundational, providing the bedrock upon which much of this evolution rests.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

Open standards like OpenTelemetry will see broader adoption, helping to ensure interoperability and consistency across diverse toolsets. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM solutions

NETOPS

The future is convergent and AI-driven. We predict APM, network observability, and infrastructure monitoring will increasingly be integrated through shared data models and intelligent automation. NetOps platforms will play a central role in providing full-stack visibility across hybrid environments. As networks become more complex, the ability to automate diagnostics, enforce compliance, and prevent outages will become non-negotiable — placing NetOps platforms at the center of the observability stack.
Nigel Hickey
Senior Technical Marketing Manager, NetBrain

SHIFT TO DEVOPS

The shift towards DevOps will continue, blurring the lines between traditional operations and development roles. Developers will increasingly be responsible for operating and monitoring systems.
Jeff Cobb
Global Head of Product & Design, Chronosphere

We expect the future to be more automated, AI-driven, and developer-centric. Observability will be embedded earlier in the development lifecycle, and used more proactively, not just during production incidents. It will also allow for more actions being taken to close the loop in cases of deployment rollbacks, autoscaling, and more.
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

CONVERGENCE OF OBSERVABILITY AND SECURITY

The trend of integrating security and observability practices early in the development lifecycle ("shift left") can regain momentum, despite developer skepticism in some quarters, with better tooling and automation. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

We'll likely see vendors continue to push convergence between APM, observability, and security analytics to deliver unified views of performance, availability, and threat detection — something already reflected in the wave of acquisitions by larger platforms aiming to expand their capabilities across the APM and observability space.
Gurjeet Arora
CEO and Co-Founder, Observo AI

REDUCING OBSERVABILITY COSTS

A primary focus item for observability will be: Reducing the (sometimes massive) costs associated with observability data collection, and using those cost reductions to extend the usage of observability tools to more applications and users.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

CONSOLIDATION OF MULTIPLE TOOLS

We expect to see more consolidation of tools (including M&As) and use cases from adjacent areas into Observability, such as developer portals, feature flagging and experimentation, cloud cost management, LLM observability, and data observability — breaking down all silos within an organization and creating a single source of truth to understand the true state of the business.
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

BUSINESS-LEVEL INSIGHTS

Importantly, we'll also see a growing emphasis on connecting technical signals to business outcomes — enabling observability platforms to inform not just engineering decisions, but strategic ones at the executive level as well.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

Observability will be the data platform for org health. The tools will blur, and what matters is: can you tie telemetry to business and impact? That's the future, and it's already here for the mature teams.
Ariel Assaraf
CEO, Coralogix

Go to: APM and Observability - Cutting Through the Confusion - Part 12, the final installment, covering APM and Observability predictions related to AI.

Pete Goldin is Editor and Publisher of APMdigest

Related Links

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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

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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 ...

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APM and Observability: Cutting Through the Confusion — Part 11

Pete Goldin
APMdigest

What's in the future for APM and Observability?

Start with: APM and Observability - Cutting Through the Confusion - Part 10

"Things are now changing in three-month intervals, so the only thing to know is that it will be different," Sven Delmas, VP of Research at Mezmo, responds.

But the experts do have some ideas, and some of them even contradict each other. In the final installments of this series, the experts present their visions of the future for APM, Observability and beyond.

CONSOLIDATION OF APM AND OBSERVABILITY

The lines between APM and observability will continue to blur, as organizations seek more integrated and intelligent solutions.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

The convergence of APM and observability, bolstered by AI and open-source tools, will fundamentally reshape IT strategies across the globe. Organizations will shift towards holistic, integrated monitoring solutions, prioritizing flexibility, automation and comprehensive visibility.
Varma Kunaparaju
SVP and GM for Cloud Platform and OpsRamp Software, HPE

The lines between observability, monitoring and APM will continue to blur as enterprises expand their data collection sources and analysis to make application management more effective and to extract more value from their end user computing investment. Driving this trend is the continued proliferation of devices and applications in use, including SaaS and emerging AI applications, which has already created an almost unmanageable workload for IT teams. The lines will blur as enterprises will be looking for ways to consolidate APM, monitoring and observability functions for better manageability, streamlined data collection and more up-to-date insights that can be acted upon.
Simon Townsend
Head of the Office of the CTO, ControlUp

NEED FOR BOTH APM AND OBSERVABILITY

Organizations with mixed architectures will require both APM and observability tools for the foreseeable future. Transitioning to solely containerized environments is a gradual process, so older APM tools will still be necessary for legacy systems.
Jeff Cobb
Global Head of Product & Design, Chronosphere

UNIFIED PLATFORM

There will be a shift toward platform-based approaches that provide a single source of truth for teams across enterprises.
Andreas Grabner
Fellow DevRel and CNCF Ambassador, Dynatrace

Looking ahead, I reckon we can expect APM and observability to continue converging into unified, intelligent platforms that deliver comprehensive, full-stack visibility. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

COMPOSABLE PLATFORM

Instead of one massive platform, we'll see composable architectures where different teams use different tools, but all pull from a shared, optimized telemetry stream.
Gurjeet Arora
CEO and Co-Founder, Observo AI

A primary focus item for observability will be: Expanding observability into an open composable platform that allows customers to integrate and expand existing information and provide even better and faster insights.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

MORE ACCURATE TERMINOLOGY

I think the APM, observability and AIOps markets will all continue to transform. I'm hopeful that we will develop more accurate terminology that better reflects the sophistication and capabilities of this whole market and the tools/technologies that deliver amazing capabilities and insights.
Carlos Casanova
Principal Analyst, Forrester

MORE CONFUSING TERMINOLOGY

Market definitions of APM and observability will remain fluid and driven by vendor self-interest. Companies will continue to redefine terms to position themselves advantageously, leading to ongoing market confusion.
Jeff Cobb
Global Head of Product & Design, Chronosphere

REACTIVE TO PROACTIVE

Ultimately, observability and APM will both shift from being a reactive discipline to a proactive enabler of high reliability, security, and performance. Observability is going to expand and provide more answers to more problems across the business. 
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

Observability is poised to evolve from passive insight to active intelligence. We anticipate systems that not only detect anomalies but also initiate automated responses. As environments become increasingly dynamic, observability will transition from merely understanding current states to actively shaping and influencing future outcomes, driving innovation and resilience in unprecedented ways. The future will likely include a robust telemetry pipeline that dynamically decides which signals to store and send to higher-cost tools for analysis, potentially using GenAI to orchestrate the entire process of IT operations.
Gab Menachem
VP ITOM, ServiceNow

OPEN SOURCE

Open data protocols and acquisition methods will become increasingly important. Vendors will move away from proprietary data collection, and open protocols like OpenTelemetry and Prometheus will be favored to avoid vendor lock-in.
Jeff Cobb
Global Head of Product & Design, Chronosphere

OPENTELEMETRY

The future of Application Performance Monitoring (APM) is being reshaped by OpenTelemetry (OTel), which standardizes the semantics and collection of metrics, logs, and traces. This eliminates the limitations of traditional APM tools that rely on proprietary agents and formats, enabling developers to instrument once and analyze anywhere. As OTel adoption grows, its ecosystem of libraries is rapidly expanding to support diverse technologies such as LLMs, databases, messaging systems, CI/CD pipelines, and more. This evolution doesn't replace APM but enhances it, allowing vendors to focus on advanced features like AI-powered analytics rather than maintaining instrumentation layers.
Bahubali Shetti
Senior Director, Product Marketing, Elastic

Download the EMA Report: Taking Observability to the Next Level - OpenTelemetry’s Emerging Role in IT Performance and Reliability

The continued adoption of open standards like OpenTelemetry is driving industry wide consistency and enabling true interoperability across diverse environments. As data collection becomes standardized, the value shifts from simply getting data in, to how effectively APM vendors can analyze and operationalize that data. This shift will push vendors to compete on architectural excellence, data correlation, and the quality of insights delivered through AI rather than on proprietary data ingestion methods.
Mimi Shalash
Observability Advisor at Splunk, a Cisco Company

I anticipate a continued flourishing of observability practices, driven by increasing system complexity. We'll see a greater emphasis on telemetry quality and efficiency — what I call "purposeful instrumentation" — moving away from merely collecting vast amounts of data towards cultivating the right data needed for insight, partly driven by cost pressures. AI/ML will become more deeply integrated, providing smarter insights. Managing the telemetry pipeline itself will become a critical focus area, with solutions emerging to handle the complexity of collecting, processing, and routing telemetry data effectively at scale. Through all this, I believe the open standard of OpenTelemetry will become even more foundational, providing the bedrock upon which much of this evolution rests.
Juraci Paixão Kröhling
Software Engineer, OllyGarden

Open standards like OpenTelemetry will see broader adoption, helping to ensure interoperability and consistency across diverse toolsets. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM solutions

NETOPS

The future is convergent and AI-driven. We predict APM, network observability, and infrastructure monitoring will increasingly be integrated through shared data models and intelligent automation. NetOps platforms will play a central role in providing full-stack visibility across hybrid environments. As networks become more complex, the ability to automate diagnostics, enforce compliance, and prevent outages will become non-negotiable — placing NetOps platforms at the center of the observability stack.
Nigel Hickey
Senior Technical Marketing Manager, NetBrain

SHIFT TO DEVOPS

The shift towards DevOps will continue, blurring the lines between traditional operations and development roles. Developers will increasingly be responsible for operating and monitoring systems.
Jeff Cobb
Global Head of Product & Design, Chronosphere

We expect the future to be more automated, AI-driven, and developer-centric. Observability will be embedded earlier in the development lifecycle, and used more proactively, not just during production incidents. It will also allow for more actions being taken to close the loop in cases of deployment rollbacks, autoscaling, and more.
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

CONVERGENCE OF OBSERVABILITY AND SECURITY

The trend of integrating security and observability practices early in the development lifecycle ("shift left") can regain momentum, despite developer skepticism in some quarters, with better tooling and automation. 
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

We'll likely see vendors continue to push convergence between APM, observability, and security analytics to deliver unified views of performance, availability, and threat detection — something already reflected in the wave of acquisitions by larger platforms aiming to expand their capabilities across the APM and observability space.
Gurjeet Arora
CEO and Co-Founder, Observo AI

REDUCING OBSERVABILITY COSTS

A primary focus item for observability will be: Reducing the (sometimes massive) costs associated with observability data collection, and using those cost reductions to extend the usage of observability tools to more applications and users.
Harald Burose
Director, Product Management, Research & Development – Engineering, OpenText

CONSOLIDATION OF MULTIPLE TOOLS

We expect to see more consolidation of tools (including M&As) and use cases from adjacent areas into Observability, such as developer portals, feature flagging and experimentation, cloud cost management, LLM observability, and data observability — breaking down all silos within an organization and creating a single source of truth to understand the true state of the business.
Hugo Kaczmarek
Director of Product, APM Suite, Datadog

BUSINESS-LEVEL INSIGHTS

Importantly, we'll also see a growing emphasis on connecting technical signals to business outcomes — enabling observability platforms to inform not just engineering decisions, but strategic ones at the executive level as well.
Arun Balachandran
Senior Product Marketing Manager, ManageEngine APM Solutions

Observability will be the data platform for org health. The tools will blur, and what matters is: can you tie telemetry to business and impact? That's the future, and it's already here for the mature teams.
Ariel Assaraf
CEO, Coralogix

Go to: APM and Observability - Cutting Through the Confusion - Part 12, the final installment, covering APM and Observability predictions related to AI.

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 ...