Sending OpenTelemetry Trace Data to Your Phoenix Project: A Guide

rithwhick p. · 2025-03-18T08:22:45.377Z

Hi! I have OpenTelemetry trace data that I want to send to my Phoenix project. Is it possible to send it directly without transformations? If yes, could you share resource links and example code? If not, what's the minimal transformation needed and what's the process? Any help would be appreciated! Schema of the data i had : { "resourceSpans": [ { "resource": { "attributes": [ { "key": string, "value": { "stringValue": string } } ] }, "instrumentationLibrarySpans": [ { "instrumentationLibrary": { "name": string, "version": string }, "spans": [ { "traceId": string, "spanId": string, "name": string, "kind": string, "startTimeUnixNano": string, "endTimeUnixNano": string, "attributes": [ { "key": string, "value": { "stringValue": string } } ] } ] } ] } ] }

7 comments

· Sorted by Oldest

RunLLM
APP
·
Yes, you can send OpenTelemetry trace data directly to Phoenix without transformations, as Phoenix supports OTLP (OpenTelemetry Protocol) for receiving traces. You need to ensure that your trace data is formatted according to the OpenTelemetry specifications, which your schema seems to comply with. You can use the OTLP HTTP or gRPC endpoint provided by Phoenix to send your trace data.To send the data, you can use the OTLPSpanExporter from the OpenTelemetry SDK. Here's an example of how you can configure the exporter in Python: LBKSfrom opentelemetry import trace from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessorLBKS# Set up the tracer provider tracer_provider = TracerProvider() trace.set_tracer_provider(tracer_provider)LBKS# Configure the OTLP exporter span_exporter = OTLPSpanExporter(endpoint="http://localhost:6006/v1/traces") span_processor = SimpleSpanProcessor(span_exporter) tracer_provider.add_span_processor(span_processor)LBKSThis setup will send your trace data to the Phoenix server running at http://localhost:6006/v1/traces. Make sure to replace the endpoint with your actual Phoenix server endpoint if it's different.Would you like more details on any specific part of this setup?Sources: - Setup Tracing: Python
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rithwhick p.
·
RunLLM I have couple of questions :
1.
here there is no project name mentioned right?how does the tracer export to certain project?
2.
here we are setting up the tracer to catch the tracing data but my use case was that i will get this data from other platform i need to inject this directly to see in my project in Phoenix?
RunLLM
APP
·
1. Project Name Configuration: To export traces to a specific project in Phoenix, you need to set the project name in the resource attributes of the TracerProvider. This can be done by adding the project name to the resource attributes when setting up the tracer. Here's how you can do it:
from openinference.semconv.resource import ResourceAttributesLBKS resource = Resource(attributes={ ResourceAttributes.PROJECT_NAME: '<your-project-name> ' }) tracer_provider = TracerProvider(resource=resource) ```LBKSLBKS This ensures that all traces are associated with the specified project in Phoenix.LBKS2. **Injecting External Trace Data**: If you have trace data from another platform and want to inject it directly into Phoenix, you can use the Phoenix API to log traces. You would need to convert your trace data into the format expected by Phoenix and use the `log_traces` method of the Phoenix client. Here's a basic example of how you might do this: LBKS ```LBKS import phoenix as pxLBKS client = px.Client() # Assuming `trace_data` is your external trace data formatted correctly client.log_traces(trace_data) ```LBKSLBKS Ensure that your trace data is formatted according to the OpenTelemetry specifications and includes the necessary project information.LBKSWould you like more details on any specific part of this process?LBKSSources: - [Setup Tracing: Python](https://github.com/Arize-ai/phoenix/blob/main/docs/tracing/how-to-tracing/setup-tracing-python.md) - [GitHub Issue #3531](https://github.com/Arize-ai/phoenix/issues/3531)
💡 Hint: Mention RunLLM in the thread for followups.
rithwhick p.
·
RunLLM Trace json data will be converted to TraceDataset right? when i do this it says that data schema is wrong change it to dataframe and then when i change it , it will come again to start that give the data with trace id, parent id, span id etc but not the above format i was giving. can you please confirm!
RunLLM
APP
·
Yes, to convert trace JSON data into a TraceDataset in Phoenix, the data must be structured as a pandas DataFrame with specific required columns. The TraceDataset expects a flattened representation of spans, which includes columns like trace_id, span_id, parent_id, start_time, end_time, and other attributes.If you encounter schema errors, it likely means that the JSON data needs to be transformed into a DataFrame with the required columns. Here's a basic example of how you can convert JSON data to a TraceDataset: LBKSimport pandas as pd from phoenix.trace.trace_dataset import TraceDatasetLBKS# Example JSON data json_data = [ { "trace_id": "trace1", "span_id": "span1", "parent_id": None, "name": "example-span", "start_time": "2023-09-07T12:54:47.293922-06:00", "end_time": "2023-09-07T12:54:49.322066-06:00", "attributes": {"key": "value"} } ]LBKS# Convert JSON to DataFrame df = pd.json_normalize(json_data)LBKS# Create TraceDataset trace_ds = TraceDataset(dataframe=df)LBKSEnsure that your DataFrame includes all required columns as specified in the Phoenix documentation. If your JSON data is not in this format, you will need to transform it accordingly.Would you like more details on any specific part of this process?Sources: - TraceDataset Class
💡 Hint: Mention RunLLM in the thread for followups.
rithwhick p.
·
RunLLM but i dont want to transform i will get data from other service and i want to directly inject it without any transformation . how can i do that?
RunLLM
APP
·
To directly inject trace data from another service into Phoenix without transformation, you need to ensure that the data is already in a format compatible with the OpenTelemetry Protocol (OTLP) that Phoenix supports. Phoenix acts as an OTLP collector, so it can receive data directly if it adheres to the OTLP specifications.Here’s how you can send your trace data directly to Phoenix: 1. Ensure OTLP Compatibility: Make sure your trace data is formatted according to the OTLP specifications. This includes having the correct structure for resourceSpans, instrumentationLibrarySpans, and spans.2. Send Data to Phoenix: Use an OTLP exporter to send the data to Phoenix. If your data is already in OTLP format, you can use an HTTP or gRPC client to send it to the Phoenix endpoint. Example using Python and OTLP HTTP exporter:
from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessorLBKS # Set up the tracer provider tracer_provider = TracerProvider() span_exporter = OTLPSpanExporter(endpoint="http://localhost:6006/v1/traces") span_processor = SimpleSpanProcessor(span_exporter) tracer_provider.add_span_processor(span_processor) ```LBKSLBKS3. **Configure Endpoint**: Ensure that the endpoint in the exporter matches the Phoenix server's endpoint where it is listening for OTLP data.LBKSBy following these steps, you can send your trace data directly to Phoenix without needing to transform it into a `TraceDataset` or any other intermediate format.LBKSWould you like more details on any specific part of this setup?LBKSSources: - [https://github.com/Arize-ai/phoenix/issues/3531](https://github.com/Arize-ai/phoenix/issues/3531)
💡 Hint: Mention RunLLM in the thread for followups.

RunLLM
APP
·
Yes, you can send OpenTelemetry trace data directly to Phoenix without transformations, as Phoenix supports OTLP (OpenTelemetry Protocol) for receiving traces. You need to ensure that your trace data is formatted according to the OpenTelemetry specifications, which your schema seems to comply with. You can use the OTLP HTTP or gRPC endpoint provided by Phoenix to send your trace data.To send the data, you can use the OTLPSpanExporter from the OpenTelemetry SDK. Here's an example of how you can configure the exporter in Python: LBKSfrom opentelemetry import trace from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessorLBKS# Set up the tracer provider tracer_provider = TracerProvider() trace.set_tracer_provider(tracer_provider)LBKS# Configure the OTLP exporter span_exporter = OTLPSpanExporter(endpoint="http://localhost:6006/v1/traces") span_processor = SimpleSpanProcessor(span_exporter) tracer_provider.add_span_processor(span_processor)LBKSThis setup will send your trace data to the Phoenix server running at http://localhost:6006/v1/traces. Make sure to replace the endpoint with your actual Phoenix server endpoint if it's different.Would you like more details on any specific part of this setup?Sources: - Setup Tracing: Python
💡 Hint: Mention RunLLM in the thread for followups.
rithwhick p.
·
RunLLM I have couple of questions :
1.
here there is no project name mentioned right?how does the tracer export to certain project?
2.
here we are setting up the tracer to catch the tracing data but my use case was that i will get this data from other platform i need to inject this directly to see in my project in Phoenix?
RunLLM
APP
·
1. Project Name Configuration: To export traces to a specific project in Phoenix, you need to set the project name in the resource attributes of the TracerProvider. This can be done by adding the project name to the resource attributes when setting up the tracer. Here's how you can do it:
from openinference.semconv.resource import ResourceAttributesLBKS resource = Resource(attributes={ ResourceAttributes.PROJECT_NAME: '<your-project-name> ' }) tracer_provider = TracerProvider(resource=resource) ```LBKSLBKS This ensures that all traces are associated with the specified project in Phoenix.LBKS2. **Injecting External Trace Data**: If you have trace data from another platform and want to inject it directly into Phoenix, you can use the Phoenix API to log traces. You would need to convert your trace data into the format expected by Phoenix and use the `log_traces` method of the Phoenix client. Here's a basic example of how you might do this: LBKS ```LBKS import phoenix as pxLBKS client = px.Client() # Assuming `trace_data` is your external trace data formatted correctly client.log_traces(trace_data) ```LBKSLBKS Ensure that your trace data is formatted according to the OpenTelemetry specifications and includes the necessary project information.LBKSWould you like more details on any specific part of this process?LBKSSources: - [Setup Tracing: Python](https://github.com/Arize-ai/phoenix/blob/main/docs/tracing/how-to-tracing/setup-tracing-python.md) - [GitHub Issue #3531](https://github.com/Arize-ai/phoenix/issues/3531)
💡 Hint: Mention RunLLM in the thread for followups.
rithwhick p.
·
RunLLM Trace json data will be converted to TraceDataset right? when i do this it says that data schema is wrong change it to dataframe and then when i change it , it will come again to start that give the data with trace id, parent id, span id etc but not the above format i was giving. can you please confirm!
RunLLM
APP
·
Yes, to convert trace JSON data into a TraceDataset in Phoenix, the data must be structured as a pandas DataFrame with specific required columns. The TraceDataset expects a flattened representation of spans, which includes columns like trace_id, span_id, parent_id, start_time, end_time, and other attributes.If you encounter schema errors, it likely means that the JSON data needs to be transformed into a DataFrame with the required columns. Here's a basic example of how you can convert JSON data to a TraceDataset: LBKSimport pandas as pd from phoenix.trace.trace_dataset import TraceDatasetLBKS# Example JSON data json_data = [ { "trace_id": "trace1", "span_id": "span1", "parent_id": None, "name": "example-span", "start_time": "2023-09-07T12:54:47.293922-06:00", "end_time": "2023-09-07T12:54:49.322066-06:00", "attributes": {"key": "value"} } ]LBKS# Convert JSON to DataFrame df = pd.json_normalize(json_data)LBKS# Create TraceDataset trace_ds = TraceDataset(dataframe=df)LBKSEnsure that your DataFrame includes all required columns as specified in the Phoenix documentation. If your JSON data is not in this format, you will need to transform it accordingly.Would you like more details on any specific part of this process?Sources: - TraceDataset Class
💡 Hint: Mention RunLLM in the thread for followups.
rithwhick p.
·
RunLLM but i dont want to transform i will get data from other service and i want to directly inject it without any transformation . how can i do that?
RunLLM
APP
·
To directly inject trace data from another service into Phoenix without transformation, you need to ensure that the data is already in a format compatible with the OpenTelemetry Protocol (OTLP) that Phoenix supports. Phoenix acts as an OTLP collector, so it can receive data directly if it adheres to the OTLP specifications.Here’s how you can send your trace data directly to Phoenix: 1. Ensure OTLP Compatibility: Make sure your trace data is formatted according to the OTLP specifications. This includes having the correct structure for resourceSpans, instrumentationLibrarySpans, and spans.2. Send Data to Phoenix: Use an OTLP exporter to send the data to Phoenix. If your data is already in OTLP format, you can use an HTTP or gRPC client to send it to the Phoenix endpoint. Example using Python and OTLP HTTP exporter:
from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import SimpleSpanProcessorLBKS # Set up the tracer provider tracer_provider = TracerProvider() span_exporter = OTLPSpanExporter(endpoint="http://localhost:6006/v1/traces") span_processor = SimpleSpanProcessor(span_exporter) tracer_provider.add_span_processor(span_processor) ```LBKSLBKS3. **Configure Endpoint**: Ensure that the endpoint in the exporter matches the Phoenix server's endpoint where it is listening for OTLP data.LBKSBy following these steps, you can send your trace data directly to Phoenix without needing to transform it into a `TraceDataset` or any other intermediate format.LBKSWould you like more details on any specific part of this setup?LBKSSources: - [https://github.com/Arize-ai/phoenix/issues/3531](https://github.com/Arize-ai/phoenix/issues/3531)
💡 Hint: Mention RunLLM in the thread for followups.