OpenTelemetry vs OpenTracing - Key Differences and Migration Path
OpenTelemetry and OpenTracing are two closely connected open-source projects that enhance observability in modern distributed systems. They are designed to instrument application code for generating telemetry data.
OpenTelemetry is a comprehensive, vendor-neutral framework that helps capture various types of telemetry data, while OpenTracing focuses specifically on tracing and provides a way to instrument applications for that purpose.
In this blog, we’ll compare OpenTelemetry and OpenTracing, focusing on their features, evolution, and migration process. We’ll also look at benefits of transitioning from OpenTracing to OpenTelemetry to help you make an informed decision.
This blog highlights,
- What is OpenTelemetry?
- What is OpenTracing?
- OpenTelemetry vs OpenTracing Comparison
- Limitations of OpenTracing
- Why Choose OpenTelemetry Over OpenTracing
- Migrating from OpenTracing to OpenTelemetry
What is OpenTelemetry?
OpenTelemetry (OTel) is an open-source, vendor-neutral framework designed for Observability. It provides a collection of APIs, SDKs, and tools that allow you to instrument, generate, collect, and export telemetry data such as traces, metrics, and logs.
This data helps you analyse your software's performance and behavior, making it easier to monitor and troubleshoot systems.
This toolkit is vendor-agnostic, meaning it works with various Observability backends, including both open-source tools like Jaeger and Prometheus and commercial solutions.
OpenTelemetry's primary goal is to make it simple to instrument applications and systems, regardless of the programming language, infrastructure, or runtime environment.
For more detailed information on OpenTelemetry, check out this guide: OpenTelemetry Guide.
What is OpenTracing?
OpenTracing is an open-source project and vendor-neutral API specification for distributed tracing in microservices and cloud-native applications.
It aims to provide a unified approach for instrumenting applications for tracing across various languages and platforms. The API supports multiple languages, including Java, JavaScript, and Python.
OpenTracing is not a standalone tool but a standard framework that works with multiple tracing tools, allowing developers flexibility in tool selection.
OpenTracing, started in 2016, aimed to create a vendor-neutral tracing API. Google introduced OpenCensus in 2018 for metrics and tracing. The overlap led to confusion within the ecosystem.
In 2019, to reduce confusion and combine strengths, the two projects merged to form OpenTelemetry. This new project, under the CNCF, expanded to cover tracing, metrics, and logs. OpenTracing and OpenCensus entered maintenance mode, with efforts focused on migrating users to OpenTelemetry.
OpenTelemetry vs OpenTracing Comparison
| Aspect | OpenTelemetry | OpenTracing |
|---|---|---|
| Scope | Supports metrics, logs, and traces. | Primarily focused on tracing only. |
| Vendor Support | Offers wide vendor support. | Provides limited vendor support. |
| API | Features a unified API. | Utilizes separate APIs for different telemetry types. |
| Future Development | Actively under development. | Deprecated and replaced by OpenTelemetry. |
| Community | Large and growing community. | Smaller but stable community. |
| Instrumentation | Supports both auto and manual instrumentation. | Primarily manual instrumentation. |
| Active Development | Yes, continuously evolving. | In maintenance mode. |
| Language Support | Extensive support across many languages. | Limited language support. |
| Auto-instrumentation | Yes, provides auto-instrumentation capabilities. | Limited auto-instrumentation features. |
| Future-proofing | High potential for adaptability and growth. | Low potential for future developments. |
| Context Propagation | Advanced context propagation mechanisms. | Basic context propagation capabilities. |
| Performance Overhead | Low performance overhead. | Varies based on implementation. |
| Cloud-Native Integration | Strong integration with cloud-native technologies. | Limited cloud-native integration. |
| Community Support | Large and growing support base. | Diminishing community support. |
| Standardization | A graduated project under CNCF. | An archived project within CNCF. |
If you are choosing between OpenTelemetry and OpenTracing, it is recommended to choose OpenTelemetry, as OpenTracing is now deprecated.
Limitations of OpenTracing
- OpenTracing primarily focuses on distributed tracing while neglecting the collection and management of metrics and logs.
- OpenTracing offers only an API, leaving the implementation of the SDK to third-party developers.
- Integrating OpenTracing into large systems with multiple services can be complex and challenging.
- Users must implement a separate tracing system that supports the OpenTracing API, adding complexity to both the setup and operational aspects of monitoring.
- The API has limited capabilities, often requiring developers to write additional code or rely on third-party libraries.
- With OpenTracing deprecated, migrating to OpenTelemetry is the logical next step to benefit from better support and enhanced features.
- OpenTracing does not provide a standard framework for collecting and managing telemetry data.
- OpenTracing lacks a standardized approach for integrating with various backends.
Why Choose OpenTelemetry Over OpenTracing
- OpenTelemetry supports traces, metrics, and logs, giving you a complete view of your system’s performance, unlike OpenTracing, which focuses only on tracing.
- As the successor to OpenTracing, OpenTelemetry benefits from ongoing development and community support, making it a more sustainable choice.
- OpenTelemetry is widely adopted, providing better integration with cloud-native tools and services.
- OpenTelemetry offers automatic instrumentation, reducing the manual effort required.
- Unlike OpenTracing, where separate APIs were needed for traces, metrics, and logs, OpenTelemetry provides a single set of APIs for all.
- Backed by major companies like Google and Microsoft, OpenTelemetry has a large, active community, making it more reliable and future-proof than OpenTracing.
- OpenTelemetry offers a simpler and more streamlined setup process compared to OpenTracing, making it quicker to configure and use.
Migrating from OpenTracing to OpenTelemetry
From the start, the OpenTelemetry project has prioritized backward compatibility with OpenTracing to facilitate the migration of instrumented codebases. To simplify the migration process, OpenTelemetry enables the use of both OpenTelemetry and OpenTracing APIs within the same codebase. This allows OpenTracing instrumentation to be captured using OpenTelemetry SDKs.
To achieve this, each OpenTelemetry SDK includes an OpenTracing shim, which serves as a bridge between the OpenTracing API and the OpenTelemetry SDK. It’s important to note that these OpenTracing shims are disabled by default.
Language Version Support
Before utilizing an OpenTracing shim, ensure that your project’s language and runtime components meet the required versions, and update them if needed. The table below outlines the minimum language versions for the OpenTracing and OpenTelemetry APIs.
| Language | OpenTracing API | OpenTelemetry API |
|---|---|---|
| Go | 1.13 | 1.16 |
| Java | 7 | 8 |
| Python | 2.7 | 3.6 |
| JavaScript | 6 | 8.5 |
| .NET | 1.3 | 1.4 |
| C++ | 11 | 11 |
A General Approach to Migrate
Many codebases are currently instrumented using OpenTracing. These codebases utilize the OpenTracing API to instrument their application code and may also install OpenTracing plugins to instrument their libraries and frameworks.
- Install the necessary OpenTelemetry SDKs.
- Remove the existing OpenTracing implementation.
- Install the OpenTelemetry instrumentation libraries and remove the OpenTracing equivalents.
- Update your dashboards, alerts, and other monitoring tools to use the new OpenTelemetry data.
- Write all new application instrumentation using the OpenTelemetry API.
- Slowly update your application to utilize the OpenTelemetry API for instrumentation.
It is not mandatory to remove the existing OpenTracing API calls from your application, and they will continue to function as expected.
Migrating a large application can be challenging. OpenTracing users are suggested to gradually migrate their application code, as this can make the process easier and help prevent issues with observability, especially when dealing with a large application.
Incremental Approach
Step 1: Install the OpenTelemetry SDK
Before modifying any instrumentation, it is important to ensure that you can switch to the OpenTelemetry SDK without disrupting the telemetry data that your application currently generates.
It is advisable to do this step separately, rather than introducing a new instrumentation simultaneously. This way, you can clearly identify any kind of break in the existing instrumentation.
- Replace your current OpenTracing Tracer implementation with the OpenTelemetry SDK. For instance, if you are using Jaeger, uninstall the Jaeger client and install the corresponding OpenTelemetry client.
- Next, install the OpenTracing Shim, which enables the OpenTelemetry SDK to utilize OpenTracing instrumentation.
- Then, configure the OpenTelemetry SDK to export data using the same protocol and format as your previous OpenTracing client. For example, if your OpenTracing client was exporting tracing data in Zipkin format, set up the OpenTelemetry client to do the same.
- Alternatively, you can configure the OpenTelemetry SDK to emit OTLP and send the data to a Collector, where you can manage the export of data in various formats.
After installing the OpenTelemetry SDK, verify that you can deploy your application. Check that you are still receiving the same telemetry data from OpenTracing.
Make sure dashboards, alerts, and other tracing-based analysis tools continue to receive the expected telemetry data without interruptions. This will confirm that the transition to OpenTelemetry has not affected your application's observability.
Step 2: Progressively replace instrumentation
Once the OpenTelemetry SDK is installed, you can write all new instrumentation using the OpenTelemetry API. With a few exceptions, instrumentation from OpenTelemetry and OpenTracing will generally be compatible and function together smoothly.
It is not must to migrate existing application code to OpenTelemetry. However, it is recommended to migrate from any OpenTracing instrumentation libraries to their OpenTelemetry equivalents. This will enhance support, as many OpenTracing libraries will be retired and may no longer receive updates.
OpenTelemetry generates better and more comprehensive tracing data. It is important to note that when switching to an OpenTelemetry instrumentation library, the produced data will change. Also note that the existing dashboards, alerts, and other tools based on older OpenTracing instrumentation libraries may no longer function once those libraries are replaced.
Recommendations for Existing Instrumentation:
- Replace one piece of OpenTracing instrumentation with its OpenTelemetry equivalent.
- Observe how this affects the telemetry produced by your application.
- Create new dashboards, alerts, etc., that utilize the new telemetry. Set up these dashboards before deploying the new OpenTelemetry library to production.
- Optionally, you can add processing rules to the Collector to transform the new telemetry back into the old telemetry format. Configure the Collector to output both versions of the same telemetry, creating a data overlap. This enables new dashboards to populate while you continue to utilize the old dashboards.
Conclusion
Migrating from OpenTracing to OpenTelemetry offers numerous benefits, as OpenTelemetry provides a unified approach by handling not just tracing, but also metrics and logs. This helps simplify system monitoring and troubleshooting, especially for cloud-native applications that need efficient observability.
OpenTelemetry’s backward compatibility with OpenTracing makes the transition smoother, allowing existing OpenTracing setups to continue working while adopting the new features.
With continuous development and strong community support, OpenTelemetry offers a future-proof solution for scalable observability, ensuring better integration with new technologies.