2026 Observability Predictions - Part 6

In APMdigest's 2026 Observability Predictions Series, industry experts — from analysts and consultants to the top vendors — offer predictions on how Observability and related technologies will evolve and impact business in 2026. Part 6 covers OpenTelemetry.

OPENTELEMETRY DOMINATION

OpenTelemetry (OTel) has been increasingly adopted in the last five years, and it is on its way to become the dominant data standard in observability in 2026 and beyond. Cloud-native organizations will adopt OTel methods to collect logs, metrics, and traces in a vendor-neutral manner, and dedicated observability solutions will add rigor to the practice. Enhanced SDKs and collectors will enable seamless auto-instrumentation across programming languages and platforms, thereby reducing vendor lock-in and elevating data quality across the board. OTel's global adoption will also simplify and accelerate the adoption of unified observability, which will in turn fuel more accurate AIOps analytics and automation.
Srinivasa Raghavan Santhanam
Director of Product Management, ManageEngine

ANALYST REPORT: 2025 Gartner® Magic Quadrant™ for Digital Experience Monitoring

OpenTelemetry starts getting wide adoption. The largest enterprises start shifting from an array of proprietary data collection and vendor-specific formats toward OpenTelemetry to simplify their observability and analytics stacks, across both their backend o11y but also every digital property.
Andrew Tunall
President and CPO, Embrace

OpenTelemetry becomes the default: 2026 will be the year observability teams stop asking if they should use OpenTelemetry – and start asking why they haven't yet. In 2025, OTel crossed the tipping point. Every major language, framework, and cloud provider now supports OTel natively. Vendors, open source projects, and even internal tools are aligning around OTel because it removes the worst kind of work: duplicate instrumentation, custom agents, and vendor-specific SDKs. When everything speaks the same telemetry language, you can focus on what really matters — the insights, not the ingestion. OpenTelemetry didn't just unify formats, it unified the community. We're all solving problems together now instead of reinventing the same instrumentations.
Marylia Gutierrrez
Principal Software Engineer, Grafana Labs
OpenTelemetry Governance Committee Member

OTEL FOR AI AGENTS

As OpenTelemetry approaches its 10-year mark, we're entering a new era where observability isn't just an add-on, it's foundational. The next phase is about making observability truly built-in, so teams don't have to think about whether they have visibility, they just do. You can't look at synthetic metrics or workflows to understand user experiences with AI; you need to look at the actual interactions. I expect to see more investment and exploration around open standards for agent communication and transparency, as well as more tools designed to give operators visibility into what's happening with their agentic deployments. OpenTelemetry has always been about giving teams the tools to see clearly, and that's never been more critical than in this new AI-driven world.
Austin Parker
Director of Open Source, Honeycomb

OTEL AS GOVERNANCE FRAMEWORK

In 2026, OpenTelemetry is poised to become the default data layer for enterprise observability and AIOps. Widespread adoption will unify how we capture, structure, and share telemetry across applications, clouds, and vendors. The real breakthrough, however, will be OpenTelemetry's interoperability, unlocking the ability to process metrics, traces, and logs in multiple analytics back ends simultaneously without vendor lock-in. With this evolution, OpenTelemetry will transform into a governance framework as much as a standard, defining how telemetry data should be enriched, secured, and optimized for cost. This evolution will finally enable organizations to seamlessly connect infrastructure signals to business intelligence, allowing AI systems to understand not just what's happening, but why — and at what cost. 
Priyanka Kharat
VP, Product Engineering, ScienceLogic

OTEL AS COST CONTROL CHOKEPOINT

OpenTelemetry — From Standard to Cost-Control Chokepoint: By 2026, OpenTelemetry will reach ~95% adoption for new cloud-native instrumentation, completing its role as the standard for data collection and evolving into a cost-control chokepoint. Vendor competition will pivot to Collector-based Data Optimization as a Service, with advanced OTel Collector pipelines becoming critical for sampling, filtering, enriching, and modifying telemetry at the source. This allows organizations to enforce compliance, implement data contracts, and dramatically reduce ingestion costs — making the Collector the central lever for controlling observability spend across the entire stack.
Sebastian Krahe
VP Product, Checkmk

SEMANTIC CONVENTIONS

Semantic conventions, especially in non-traditional use cases like end-user facing apps like mobile and web, are going to take off and give the ecosystem a more specific vocabulary when it comes to modeling specialized domains. With improved tooling like Weaver and a more federated organization to handle the incoming PRs, something we've always wanted — more and better semconv — will happen at a greater pace.
Hanson Ho
Android Architect, Embrace

SWIFT-NATIVE LIBRARIES

OpenTelemetry is becoming a first-class citizen with Swift-native libraries finally being available. This will unlock the ability for tool providers to stream standard traces back to IT services, promoting new levels of visibility and analytics for Ops and IT.
Chris Chapman
CTO, MacStadium

VENDOR-AGNOSTIC INSIGHTS

The promise of OTel is finally felt in the market. Combined with agent-driven analysis, OTel breaks the proprietary formats that once locked companies into vendors. This combination reduces dependency on incumbents, giving enterprises true control over their observability data and enabling more flexible, vendor-agnostic insights. 
Tucker Callaway
CEO, Mezmo

UNIFYING OBSERVABILITY, APM AND DEVOPS

In 2026, I see observability, APM, and DevOps finally coming together in a much more practical and integrated way. OpenTelemetry will solidify itself as the standard plumbing for enterprise telemetry, and the real differentiation will shift to how well platforms use that data to anticipate issues and automate the messy parts of operations. AIOps won't just be about noise reduction anymore, it will start handling full incident lifecycles, from detection to remediation, often before the user feels anything. This tighter connection between backend telemetry, digital experience, and cloud operations will give teams a clearer, more actionable view of reliability and performance across their environments.
Renato Sugano
Cloud Matching Specialist, Andela

End-to-End Observability will benefit from open standards such as OpenTelemetry: Traditional APM is evolving into end-to-end observability, and open standards are at the heart of this transition. OpenTelemetry (OTel), an open-source telemetry standard, is rapidly becoming the pillar of how teams collect and unify metrics, logs and traces across distributed systems. In 2026, OpenTelemetry is poised to cement its place as the global standard for instrumentation, embraced by both open-source communities and major vendors alike. This widespread adoption will drastically simplify the integration of monitoring tools and break down data silos. Using vendor-neutral OTel agents, teams can capture telemetry from every component (cloud services, microservices, serverless functions, etc.) and correlate them seamlessly. The result is true end-to-end visibility — from user experience to backend infrastructure — without the need for proprietary agents in each layer. OpenTelemetry's unified approach lowers the barrier to observability by making it easier to implement and standardize across the stack. Ultimately, embracing open standards like OTel means faster troubleshooting (since metrics, logs and traces can be analyzed in context) and a more proactive, data-driven APM strategy that benefits the entire organization.
Sam Suthar
Founding Director, Middleware

Got to: 2026 Observability Predictions - Part 7, covering Observability data

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Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

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Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

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Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

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Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Reliability Is the New Bottleneck of Innovation

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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2026 Observability Predictions - Part 6

In APMdigest's 2026 Observability Predictions Series, industry experts — from analysts and consultants to the top vendors — offer predictions on how Observability and related technologies will evolve and impact business in 2026. Part 6 covers OpenTelemetry.

OPENTELEMETRY DOMINATION

OpenTelemetry (OTel) has been increasingly adopted in the last five years, and it is on its way to become the dominant data standard in observability in 2026 and beyond. Cloud-native organizations will adopt OTel methods to collect logs, metrics, and traces in a vendor-neutral manner, and dedicated observability solutions will add rigor to the practice. Enhanced SDKs and collectors will enable seamless auto-instrumentation across programming languages and platforms, thereby reducing vendor lock-in and elevating data quality across the board. OTel's global adoption will also simplify and accelerate the adoption of unified observability, which will in turn fuel more accurate AIOps analytics and automation.
Srinivasa Raghavan Santhanam
Director of Product Management, ManageEngine

ANALYST REPORT: 2025 Gartner® Magic Quadrant™ for Digital Experience Monitoring

OpenTelemetry starts getting wide adoption. The largest enterprises start shifting from an array of proprietary data collection and vendor-specific formats toward OpenTelemetry to simplify their observability and analytics stacks, across both their backend o11y but also every digital property.
Andrew Tunall
President and CPO, Embrace

OpenTelemetry becomes the default: 2026 will be the year observability teams stop asking if they should use OpenTelemetry – and start asking why they haven't yet. In 2025, OTel crossed the tipping point. Every major language, framework, and cloud provider now supports OTel natively. Vendors, open source projects, and even internal tools are aligning around OTel because it removes the worst kind of work: duplicate instrumentation, custom agents, and vendor-specific SDKs. When everything speaks the same telemetry language, you can focus on what really matters — the insights, not the ingestion. OpenTelemetry didn't just unify formats, it unified the community. We're all solving problems together now instead of reinventing the same instrumentations.
Marylia Gutierrrez
Principal Software Engineer, Grafana Labs
OpenTelemetry Governance Committee Member

OTEL FOR AI AGENTS

As OpenTelemetry approaches its 10-year mark, we're entering a new era where observability isn't just an add-on, it's foundational. The next phase is about making observability truly built-in, so teams don't have to think about whether they have visibility, they just do. You can't look at synthetic metrics or workflows to understand user experiences with AI; you need to look at the actual interactions. I expect to see more investment and exploration around open standards for agent communication and transparency, as well as more tools designed to give operators visibility into what's happening with their agentic deployments. OpenTelemetry has always been about giving teams the tools to see clearly, and that's never been more critical than in this new AI-driven world.
Austin Parker
Director of Open Source, Honeycomb

OTEL AS GOVERNANCE FRAMEWORK

In 2026, OpenTelemetry is poised to become the default data layer for enterprise observability and AIOps. Widespread adoption will unify how we capture, structure, and share telemetry across applications, clouds, and vendors. The real breakthrough, however, will be OpenTelemetry's interoperability, unlocking the ability to process metrics, traces, and logs in multiple analytics back ends simultaneously without vendor lock-in. With this evolution, OpenTelemetry will transform into a governance framework as much as a standard, defining how telemetry data should be enriched, secured, and optimized for cost. This evolution will finally enable organizations to seamlessly connect infrastructure signals to business intelligence, allowing AI systems to understand not just what's happening, but why — and at what cost. 
Priyanka Kharat
VP, Product Engineering, ScienceLogic

OTEL AS COST CONTROL CHOKEPOINT

OpenTelemetry — From Standard to Cost-Control Chokepoint: By 2026, OpenTelemetry will reach ~95% adoption for new cloud-native instrumentation, completing its role as the standard for data collection and evolving into a cost-control chokepoint. Vendor competition will pivot to Collector-based Data Optimization as a Service, with advanced OTel Collector pipelines becoming critical for sampling, filtering, enriching, and modifying telemetry at the source. This allows organizations to enforce compliance, implement data contracts, and dramatically reduce ingestion costs — making the Collector the central lever for controlling observability spend across the entire stack.
Sebastian Krahe
VP Product, Checkmk

SEMANTIC CONVENTIONS

Semantic conventions, especially in non-traditional use cases like end-user facing apps like mobile and web, are going to take off and give the ecosystem a more specific vocabulary when it comes to modeling specialized domains. With improved tooling like Weaver and a more federated organization to handle the incoming PRs, something we've always wanted — more and better semconv — will happen at a greater pace.
Hanson Ho
Android Architect, Embrace

SWIFT-NATIVE LIBRARIES

OpenTelemetry is becoming a first-class citizen with Swift-native libraries finally being available. This will unlock the ability for tool providers to stream standard traces back to IT services, promoting new levels of visibility and analytics for Ops and IT.
Chris Chapman
CTO, MacStadium

VENDOR-AGNOSTIC INSIGHTS

The promise of OTel is finally felt in the market. Combined with agent-driven analysis, OTel breaks the proprietary formats that once locked companies into vendors. This combination reduces dependency on incumbents, giving enterprises true control over their observability data and enabling more flexible, vendor-agnostic insights. 
Tucker Callaway
CEO, Mezmo

UNIFYING OBSERVABILITY, APM AND DEVOPS

In 2026, I see observability, APM, and DevOps finally coming together in a much more practical and integrated way. OpenTelemetry will solidify itself as the standard plumbing for enterprise telemetry, and the real differentiation will shift to how well platforms use that data to anticipate issues and automate the messy parts of operations. AIOps won't just be about noise reduction anymore, it will start handling full incident lifecycles, from detection to remediation, often before the user feels anything. This tighter connection between backend telemetry, digital experience, and cloud operations will give teams a clearer, more actionable view of reliability and performance across their environments.
Renato Sugano
Cloud Matching Specialist, Andela

End-to-End Observability will benefit from open standards such as OpenTelemetry: Traditional APM is evolving into end-to-end observability, and open standards are at the heart of this transition. OpenTelemetry (OTel), an open-source telemetry standard, is rapidly becoming the pillar of how teams collect and unify metrics, logs and traces across distributed systems. In 2026, OpenTelemetry is poised to cement its place as the global standard for instrumentation, embraced by both open-source communities and major vendors alike. This widespread adoption will drastically simplify the integration of monitoring tools and break down data silos. Using vendor-neutral OTel agents, teams can capture telemetry from every component (cloud services, microservices, serverless functions, etc.) and correlate them seamlessly. The result is true end-to-end visibility — from user experience to backend infrastructure — without the need for proprietary agents in each layer. OpenTelemetry's unified approach lowers the barrier to observability by making it easier to implement and standardize across the stack. Ultimately, embracing open standards like OTel means faster troubleshooting (since metrics, logs and traces can be analyzed in context) and a more proactive, data-driven APM strategy that benefits the entire organization.
Sam Suthar
Founding Director, Middleware

Got to: 2026 Observability Predictions - Part 7, covering Observability data

Related Links

Hot Topics

The Latest

Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

Most Enterprises Think They Can Switch AI Vendors in a Month ... Most Who've Tried Couldn't

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

How Intelligent Orchestration Enables Enterprises to Move from AI POC to AI Production

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Reliability Is the New Bottleneck of Innovation

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

5 Takeaways from the Observability Forecast for Retail and eCommerce

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...