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New OpenTelemetry Network Protocol OpAMP - Game Changer for DevOps and Observability

Paul Stefanski
observIQ

Observability is one of the fastest growing industries in the world today — by both market size and data volume. Since the 90s, cloud monitoring has become a must-have for businesses in nearly every sector, not just technology. The exponentially increasing size of cloud infrastructures and data volume is creating two bubbles for customers seeking to collect and generate value from their data. Both are ready to burst. Both of these problems relate to how data collection agents are configured and managed, and new open source technologies by industry leaders are seeking to change the paradigm.

OpenTelemetry, a collaborative open source observability project, has introduced a new network protocol that addresses the infrastructure management headache, coupled with collector configuration options to filter and reduce data volume. Open Agent Management Protocol (OpAmp) is a new network protocol by the OpenTelemetry project that enables remote management of OpenTelemetry collectors (agents). In simple terms, it's a free and open source technology that dramatically reduces the effort and complexity of deploying and managing agents and data pipelines for DevOps teams.

Why is OpenTelemetry's OpAmp special?

It offers a simple and versatile method for remotely configuring and maintaining telemetry agents across massive environments with very little overhead. This is particularly useful for large cloud environments, and headless environments, where agent management would otherwise require manual management of every agent on every server.

OpAMP also enables agents to report information to multiple remote management destinations simultaneously, such as their status, properties, connections, configuration, operating system, version, agent CPU and RAM usage, data collection rate, and more. OpAMP can integrate with access credential management systems to keep environments secure. It also has a secure auto-update capability that makes maintaining large environments easy.

Similar technology is available through a handful of proprietary technologies, but the addition of OpAMP to OpenTelemetry is the launch point for industry-wide, vendor-agnostic adoption of the technology. Keeping with the open source mission, observability vendors collaborate on overarching technologies that benefit the whole industry, and focus independently on servicing specific niches.

That's what makes OpAMP so unique — as an open source technology built by experts from every major telemetry organization, it's completely vendor agnostic. It's available now as part of OpenTelemetry, but it's not dependent on OpenTelemetry as a whole.

OpAMP can be used to manage many agent types. Agents can collect data from any platform in any environment, and ship data to any, or multiple, data management or analysis platforms. Say you prefer a specific tool for data analysis, but another unrelated tool for data storage, and you also maintain an environment with servers across multiple cloud platforms; with OpAMP, you can manage different agent types across multiple environments through one place. Some agents, like OpenTelemetry agents, can ship to many analysis and storage tools simultaneously, and filter where specific data goes based on your configuration. With OpAMP, those agents and configurations are easily and remotely manageable at any scale, from source to destination.

OpenTelemetry is not meant to overrule or undercut any existing telemetry solutions. In fact it's exactly the opposite — it gives end users the freedom to use exactly the tools they want for their specific needs in conjunction with each other. As the observability industry continues to grow, and data volume swells, foundational technologies like OpAMP are critical to maintaining manageable technology infrastructures for both vendors and customers alike.

Paul Stefanski is Product Marketing Manager at observIQ

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

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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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 ...

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 ...

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 ...

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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.

New OpenTelemetry Network Protocol OpAMP - Game Changer for DevOps and Observability

Paul Stefanski
observIQ

Observability is one of the fastest growing industries in the world today — by both market size and data volume. Since the 90s, cloud monitoring has become a must-have for businesses in nearly every sector, not just technology. The exponentially increasing size of cloud infrastructures and data volume is creating two bubbles for customers seeking to collect and generate value from their data. Both are ready to burst. Both of these problems relate to how data collection agents are configured and managed, and new open source technologies by industry leaders are seeking to change the paradigm.

OpenTelemetry, a collaborative open source observability project, has introduced a new network protocol that addresses the infrastructure management headache, coupled with collector configuration options to filter and reduce data volume. Open Agent Management Protocol (OpAmp) is a new network protocol by the OpenTelemetry project that enables remote management of OpenTelemetry collectors (agents). In simple terms, it's a free and open source technology that dramatically reduces the effort and complexity of deploying and managing agents and data pipelines for DevOps teams.

Why is OpenTelemetry's OpAmp special?

It offers a simple and versatile method for remotely configuring and maintaining telemetry agents across massive environments with very little overhead. This is particularly useful for large cloud environments, and headless environments, where agent management would otherwise require manual management of every agent on every server.

OpAMP also enables agents to report information to multiple remote management destinations simultaneously, such as their status, properties, connections, configuration, operating system, version, agent CPU and RAM usage, data collection rate, and more. OpAMP can integrate with access credential management systems to keep environments secure. It also has a secure auto-update capability that makes maintaining large environments easy.

Similar technology is available through a handful of proprietary technologies, but the addition of OpAMP to OpenTelemetry is the launch point for industry-wide, vendor-agnostic adoption of the technology. Keeping with the open source mission, observability vendors collaborate on overarching technologies that benefit the whole industry, and focus independently on servicing specific niches.

That's what makes OpAMP so unique — as an open source technology built by experts from every major telemetry organization, it's completely vendor agnostic. It's available now as part of OpenTelemetry, but it's not dependent on OpenTelemetry as a whole.

OpAMP can be used to manage many agent types. Agents can collect data from any platform in any environment, and ship data to any, or multiple, data management or analysis platforms. Say you prefer a specific tool for data analysis, but another unrelated tool for data storage, and you also maintain an environment with servers across multiple cloud platforms; with OpAMP, you can manage different agent types across multiple environments through one place. Some agents, like OpenTelemetry agents, can ship to many analysis and storage tools simultaneously, and filter where specific data goes based on your configuration. With OpAMP, those agents and configurations are easily and remotely manageable at any scale, from source to destination.

OpenTelemetry is not meant to overrule or undercut any existing telemetry solutions. In fact it's exactly the opposite — it gives end users the freedom to use exactly the tools they want for their specific needs in conjunction with each other. As the observability industry continues to grow, and data volume swells, foundational technologies like OpAMP are critical to maintaining manageable technology infrastructures for both vendors and customers alike.

Paul Stefanski is Product Marketing Manager at observIQ

Hot Topics

The Latest

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

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.