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Embrace Contributes Kotlin Implementation and SDK to OpenTelemetry

Contribution continues Embrace’s investment in vendor-agnostic, open-source instrumentation in frontend and mobile by extending support to Kotlin and Kotlin Multiplatform

Embrace announced that the donation of its Kotlin implementation and SDK to OpenTelemetry has been accepted. 

This contribution expands vendor-neutral observability support across client and server-side applications written in Kotlin.

OpenTelemetry is an incubating Cloud Native Computing Foundation (CNCF) project developed by end users, open source contributors, and vendors to advance interoperable, portable observability standards. Kotlin is the default language for modern Android development, and Kotlin Multiplatform (KMP) is increasingly used to share code across Android, iOS, web, and server-side applications. This contribution enhances OpenTelemetry’s reach to Kotlin and KMP use cases, enabling teams to capture telemetry in a way that better aligns with user-facing applications.

“OpenTelemetry is becoming the global foundation for observability, and meaningful contributions to that foundation matter,” said Andrew Tunall, President and Chief Product Officer at Embrace. “With Kotlin now central to mobile, frontend, and backend development, and with growing community investment in client-side observability, this is an exciting moment for the ecosystem. We’re proud to donate a Kotlin Multiplatform implementation that supports production-ready, real-world engineering workflows.”

Enabling client-side observability for Kotlin and KMP

The implementation can be used for backend development needs, and it also introduces new support for client-side environments like mobile and web. Client-side environments present unique observability challenges, requiring teams to understand not just whether an application is functioning, but how end-users experience workflows and why outcomes change in production.

While Kotlin applications running on the Java Virtual Machine (JVM) can use OpenTelemetry through Java interoperability, teams building shared logic with Kotlin Multiplatform often require a solution that operates without JVM dependencies. The contributed implementation addresses these needs while remaining aligned with OpenTelemetry’s specification-driven approach. It supports two modes of operation:

  • Compatibility mode, which interoperates with the OpenTelemetry Java SDK for Android and JVM targets. This enables engineering teams to leverage existing instrumentation built by the JVM community.
  • Regular mode, which is a re-write of the OTel spec in Kotlin. This can be used for both JVM and non-JVM targets.

At the time of contribution, the project includes tracing and logging APIs, providing a foundation for modeling user workflows and correlating events across platforms.

Community stewardship and ecosystem impact

Embrace will continue to contribute and maintain the implementation alongside the broader OpenTelemetry community and encourages additional contributors to participate.

“The real power of OpenTelemetry is the standard itself – a shared contract that allows many implementations to evolve and serve different environments,” said Jamie Lynch, Senior  Software Engineer at Embrace and a Maintainer of the OpenTelemetry Kotlin project. “By contributing a Kotlin Multiplatform implementation, we’re investing in a future where frontend teams can build observability on the same open foundations as the backend, while meeting the realities of modern app development.”

Developers interested in using or contributing to the OpenTelemetry Kotlin Multiplatform implementation can:

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Embrace Contributes Kotlin Implementation and SDK to OpenTelemetry

Contribution continues Embrace’s investment in vendor-agnostic, open-source instrumentation in frontend and mobile by extending support to Kotlin and Kotlin Multiplatform

Embrace announced that the donation of its Kotlin implementation and SDK to OpenTelemetry has been accepted. 

This contribution expands vendor-neutral observability support across client and server-side applications written in Kotlin.

OpenTelemetry is an incubating Cloud Native Computing Foundation (CNCF) project developed by end users, open source contributors, and vendors to advance interoperable, portable observability standards. Kotlin is the default language for modern Android development, and Kotlin Multiplatform (KMP) is increasingly used to share code across Android, iOS, web, and server-side applications. This contribution enhances OpenTelemetry’s reach to Kotlin and KMP use cases, enabling teams to capture telemetry in a way that better aligns with user-facing applications.

“OpenTelemetry is becoming the global foundation for observability, and meaningful contributions to that foundation matter,” said Andrew Tunall, President and Chief Product Officer at Embrace. “With Kotlin now central to mobile, frontend, and backend development, and with growing community investment in client-side observability, this is an exciting moment for the ecosystem. We’re proud to donate a Kotlin Multiplatform implementation that supports production-ready, real-world engineering workflows.”

Enabling client-side observability for Kotlin and KMP

The implementation can be used for backend development needs, and it also introduces new support for client-side environments like mobile and web. Client-side environments present unique observability challenges, requiring teams to understand not just whether an application is functioning, but how end-users experience workflows and why outcomes change in production.

While Kotlin applications running on the Java Virtual Machine (JVM) can use OpenTelemetry through Java interoperability, teams building shared logic with Kotlin Multiplatform often require a solution that operates without JVM dependencies. The contributed implementation addresses these needs while remaining aligned with OpenTelemetry’s specification-driven approach. It supports two modes of operation:

  • Compatibility mode, which interoperates with the OpenTelemetry Java SDK for Android and JVM targets. This enables engineering teams to leverage existing instrumentation built by the JVM community.
  • Regular mode, which is a re-write of the OTel spec in Kotlin. This can be used for both JVM and non-JVM targets.

At the time of contribution, the project includes tracing and logging APIs, providing a foundation for modeling user workflows and correlating events across platforms.

Community stewardship and ecosystem impact

Embrace will continue to contribute and maintain the implementation alongside the broader OpenTelemetry community and encourages additional contributors to participate.

“The real power of OpenTelemetry is the standard itself – a shared contract that allows many implementations to evolve and serve different environments,” said Jamie Lynch, Senior  Software Engineer at Embrace and a Maintainer of the OpenTelemetry Kotlin project. “By contributing a Kotlin Multiplatform implementation, we’re investing in a future where frontend teams can build observability on the same open foundations as the backend, while meeting the realities of modern app development.”

Developers interested in using or contributing to the OpenTelemetry Kotlin Multiplatform implementation can:

Hot Topic

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 ...