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

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.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

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

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.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...