Migrating from OpenTracing
Backward compatibility with OpenTracing has been a priority for the OpenTelemetry project from the start. To ease migration, OpenTelemetry supports the use of both the OpenTelemetry and OpenTracing APIs in the same codebase. This allows OpenTracing instrumentation to be recorded using OpenTelemetry SDKs.
To accomplish this, each OpenTelemetry SDK provides an OpenTracing shim, which acts as a bridge between the OpenTracing API and the OpenTelemetry SDK. Note that OpenTracing shims are disabled by default.
Language version support
Before using an OpenTracing shim, check your project’s language and runtime component versions, and update if necessary. The minimum language versions of the OpenTracing and OpenTelemetry APIs are listed in the table below.
|Language||OpenTracing API||OpenTelemetry API|
Note that the OpenTelemetry API and SDKs generally have higher language version requirements than their OpenTracing counterparts.
Many codebases are currently instrumented with OpenTracing. These codebases use the OpenTracing API to instrument their application code and/or install OpenTracing plugins to instrument their libraries and frameworks.
A general approach to migrating to OpenTelemetry can be summarized as follows:
- Install OpenTelemetry SDK(s), and remove the current OpenTracing implementation – for example, a Jaeger client.
- Install the OpenTelemetry instrumentation libraries, and remove the OpenTracing equivalents.
- Update your dashboards, alerts, etc., to consume the new OpenTelemetry data.
- When writing new application code, write all new instrumentation using the OpenTelemetry API.
- Progressively re-instrument your application using the OpenTelemetry API. There is no hard requirement to remove existing OpenTracing API calls from your application, they will continue to work.
While migrating a sizable application can require significant effort, as suggested above, we recommend that OpenTracing users progressively migrate their application code. This will ease the burden of migration and help avoid breaks in observability.
The steps below present a careful, incremental approach to transitioning to OpenTelemetry.
Step 1: Install the OpenTelemetry SDK
Before changing any instrumentation, ensure that you can switch to the OpenTelemetry SDK without causing any break in the telemetry the application currently emits. Doing this step on its own – without simultaneously introducing any new instrumentation – is recommended, as it makes it easier to determine whether there is any kind of break in instrumentation.
- Replace the OpenTracing Tracer implementation you are currently using with the OpenTelemetry SDK. For example, if you are using the Jaeger, remove the Jaeger client and install the equivalent OpenTelemetry client.
- Install the OpenTracing Shim. This shim allows the OpenTelemetry SDK to consume OpenTracing instrumentation.
- Configure the OpenTelemetry SDK to export data using the same protocol and format that the OpenTracing client was using. For example, if you were using an OpenTracing client that exported tracing data in Zipkin format, configure the OpenTelemetry client to do the same.
- Alternatively, configure the OpenTelemetry SDK to emit OTLP, and send the data to a Collector, where you can manage exporting data in multiple formats.
Once you have the OpenTelemetry SDK installed, confirm that you can deploy your application and still receive the same OpenTracing-based telemetry. In other words, confirm that your dashboards, alerts, and other tracing-based analysis tools are still working.
Step 2: Progressively replace instrumentation
Once the OpenTelemetry SDK is installed, all new instrumentation can now be written using the OpenTelemetry API. With few exceptions, OpenTelemetry and OpenTracing instrumentation will work together seamlessly (see limits on compatibility below).
What about existing instrumentation? There is no hard requirement to migrate existing application code to OpenTelemetry. However, we do recommend migrating from any OpenTracing instrumentation libraries – libraries used to instrument web frameworks, HTTP clients, database clients, etc. – to their OpenTelemetry equivalents. This will improve support, as many OpenTracing libraries will be retired and may no longer be updated.
It is important to note that when switching to an OpenTelemetry instrumentation library, the data which is produced will change. OpenTelemetry has an improved model for how we instrument software (what we refer to as our “semantic conventions”). In many cases, OpenTelemetry produces better, more comprehensive tracing data. However, “better” also means “different.” This means that existing dashboards, alerts, etc. based on older OpenTracing instrumentation libraries may no longer work when those libraries are replaced.
For existing instrumentation, it is recommended to:
- Replace one piece of OpenTracing instrumentation with its OpenTelemetry equivalent.
- Observe how this changes the telemetry which your application produces.
- Create new dashboards, alerts, etc which consume this new telemetry. Set up these dashboards before deploying the new OpenTelemetry library to production.
- Optionally, add processing rules to the Collector which converts the new telemetry back into the old telemetry. The Collector can then be configured to emit both versions of the same telemetry, creating a data overlap. This allows new dashboards to populate themselves while you continue to use the old dashboards.
Limits on compatibility
In this section, we describe limits on compatibility other than the language version constraints mentioned earlier.
As mentioned above, OpenTelemetry has an improved model for instrumenting software. This means that the “tags” which are set by OpenTracing instrumentation may be different from the “attributes” which are set by OpenTelemetry. In other words, when replacing existing instrumentation, the data OpenTelemetry produces may be different from the data OpenTracing produces.
Again, for clarity: When changing instrumentation, be sure to also update any dashboards, alerts, etc. which relied on the old data.
In OpenTracing, baggage is carried with a SpanContext object associated with a Span. In OpenTelemetry, context and propagation are lower-level concepts – spans, baggage, metrics instruments, and other items are carried within a context object.
As a result of this change, baggage which is set using the OpenTracing API is not available to OpenTelemetry Propagators. As a result, mixing the OpenTelemetry and OpenTracing APIs is not recommended when using baggage.
Specifically, when baggage is set using the OpenTracing API:
- It is not accessible via the OpenTelemetry API.
- It is not injected by the OpenTelemetry propagators.
If you are using baggage, it is recommended that all baggage-related API calls be switched to OpenTelemetry at the same time. Be sure to check that any critical baggage items are still being propagated before rolling these changes into production.
managers, such as
async_hooks for Node.js and
Zones.js for the browser. These
context managers make tracing instrumentation a much less invasive and onerous
task, compared to adding a span as a parameter to every method which needs to
However, the OpenTracing API predates the common use of these context managers. OpenTracing code which passes the current active span as a parameter may create problems when mixed with OpenTelemetry code that stores the active span in a context manager. Using both methods within the same trace may create broken or mismatched spans, and is not recommended.
Instead of mixing the two APIs in the same trace, we recommend that you migrate complete code paths from OpenTracing to OpenTelemetry as a single unit, so that only one API is used at a time.
Specification and implementation details
For details on how each OpenTracing shim works, see the appropriate language-specific documentation. For details on the design of the OpenTracing shim, see OpenTracing Compatibility.