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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

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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

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

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

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

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

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

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

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

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

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

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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

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

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

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

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

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

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

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

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