NashTech Insights

Bridging the Gap: Integrating Jaeger with Open Tracing for Seamless Interoperability

Rahul Miglani
Rahul Miglani
Table of Contents

In the dynamic world of distributed systems, tracing requests across microservices is essential for understanding interactions, bottlenecks, and performance issues. Jaeger, a powerful distributed tracing system, is a game-changer in this regard. But what about cross-platform compatibility and standardization? That’s where Open Tracing comes into play. In this blog, we’ll explore how Jaeger and OpenTracing intertwine, highlighting the significance of their integration in achieving seamless trace instrumentation and analysis across different services and frameworks.

Understanding OpenTracing

Open Tracing is an open standard that provides a consistent API for instrumenting code to capture traces. It allows you to add trace information to your applications without being tied to a specific tracing implementation. This empowers developers to switch between different tracing systems without rewriting the instrumentation code.

The Relationship Between Jaeger and OpenTracing

Jaeger and OpenTracing share a symbiotic relationship. Jaeger is a fully-fledged distributed tracing system, while OpenTracing defines a set of APIs for instrumenting applications. Jaeger’s client libraries implement the OpenTracing API, enabling applications instrumented with OpenTracing to seamlessly integrate with the Jaeger tracing backend.

Benefits of Integrating Jaeger with OpenTracing

1. Cross-Platform Compatibility

By adhering to the OpenTracing API, Jaeger ensures compatibility with applications written in various programming languages and frameworks. This compatibility facilitates consistent trace instrumentation regardless of the underlying technologies.

2. Vendor-Neutral Instrumentation

OpenTracing’s vendor-neutral approach allows you to instrument your code without being tied to a specific tracing provider. This means you can switch to different tracing solutions like Zipkin or LightStep without changing your codebase.

3. Smooth Migration and Switching

Integrating Jaeger with OpenTracing future-proofs your tracing instrumentation. If you decide to move away from Jaeger in the future, your instrumentation efforts remain intact, making migration or experimentation with other systems straightforward.

How to Integrate Jaeger with OpenTracing

1. Choose Your Platform

Select the programming language and framework you’re using for your application. Check if there’s an OpenTracing-compatible library available for that platform.

2. Install the OpenTracing Library

Install the OpenTracing library for your chosen language. Libraries are available for various languages, including Java, Go, Python, and more.

3. Instrument Your Code

Use the OpenTracing API to add trace information to your code. This involves creating spans to mark the beginning and end of operations.

4. Choose Jaeger as a Backend

Configure your OpenTracing-compatible library to use Jaeger as the tracing backend. This might involve setting the Jaeger agent’s address and port.

5. Visualize Traces in Jaeger

Access the Jaeger UI to visualize and analyze the traces captured by your instrumented application.


The integration of Jaeger with OpenTracing bridges the gap between tracing systems and applications, offering a standardized approach to trace instrumentation. This harmonious relationship ensures cross-platform compatibility, vendor-neutral instrumentation, and smooth migration options. By embracing this integration, you lay the foundation for robust trace collection, enabling you to understand the intricacies of your microservices architecture and optimize performance with ease. OpenTracing and Jaeger’s partnership is a testament to the power of standardization in enhancing the observability and performance of modern distributed systems.

Rahul Miglani

Rahul Miglani

Rahul Miglani is Vice President at NashTech and Heads the DevOps Competency and also Heads the Cloud Engineering Practice. He is a DevOps evangelist with a keen focus to build deep relationships with senior technical individuals as well as pre-sales from customers all over the globe to enable them to be DevOps and cloud advocates and help them achieve their automation journey. He also acts as a technical liaison between customers, service engineering teams, and the DevOps community as a whole. Rahul works with customers with the goal of making them solid references on the Cloud container services platforms and also participates as a thought leader in the docker, Kubernetes, container, cloud, and DevOps community. His proficiency includes rich experience in highly optimized, highly available architectural decision-making with an inclination towards logging, monitoring, security, governance, and visualization.

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