---
title: Migrating from OpenTracing
linkTitle: OpenTracing
aliases: [/docs/migration/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 |
| -------------- | --------------- | ----------------- |
| [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                |

Note that the OpenTelemetry API and SDKs generally have higher language version
requirements than their OpenTracing counterparts.

## Migration overview

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:

1. Install OpenTelemetry SDK(s), and remove the current OpenTracing
   implementation -- for example, a Jaeger client.
2. Install the OpenTelemetry instrumentation libraries, and remove the
   OpenTracing equivalents.
3. Update your dashboards, alerts, etc., to consume the new OpenTelemetry data.
4. When writing new application code, write all new instrumentation using the
   OpenTelemetry API.
5. 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.

1. 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.
2. Install the OpenTracing Shim. This shim allows the OpenTelemetry SDK to
   consume OpenTracing instrumentation.
3. 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.
4. 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](#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:

1. Replace one piece of OpenTracing instrumentation with its OpenTelemetry
   equivalent.
2. Observe how this changes the telemetry which your application produces.
3. Create new dashboards, alerts, etc which consume this new telemetry. Set up
   these dashboards before deploying the new OpenTelemetry library to
   production.
4. 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](#language-version-support) mentioned earlier.

### Semantic conventions

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.

### Baggage

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.

### Context management in JavaScript

In JavaScript, the OpenTelemetry API makes use of commonly available context
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 be traced.

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][ot_spec].

[.net]: /docs/languages/dotnet/shim/
[go]: https://pkg.go.dev/go.opentelemetry.io/otel/bridge/opentracing
[java]:
  https://github.com/open-telemetry/opentelemetry-java/tree/main/opentracing-shim
[javascript]: https://www.npmjs.com/package/@opentelemetry/shim-opentracing
[opentracing]: https://opentracing.io
[ot_spec]: /docs/specs/otel/compatibility/opentracing/
[python]:
  https://opentelemetry-python.readthedocs.io/en/stable/shim/opentracing_shim/opentracing_shim.html
[c++]:
  https://github.com/open-telemetry/opentelemetry-cpp/tree/main/opentracing-shim
