awesome-copilot/plugins/phoenix/skills/phoenix-tracing/references/production-python.md

Phoenix Tracing: Production Guide (Python)

CRITICAL: Configure batching, data masking, and span filtering for production deployment.

Metadata

Attribute	Value
Priority	Critical - production readiness
Impact	Security, Performance
Setup Time	5-15 min

Batch Processing

Enable batch processing for production efficiency. Batching reduces network overhead by sending spans in groups rather than individually.

Data Masking (PII Protection)

Environment variables:

export OPENINFERENCE_HIDE_INPUTS=true          # Hide input.value
export OPENINFERENCE_HIDE_OUTPUTS=true         # Hide output.value
export OPENINFERENCE_HIDE_INPUT_MESSAGES=true  # Hide LLM input messages
export OPENINFERENCE_HIDE_OUTPUT_MESSAGES=true # Hide LLM output messages
export OPENINFERENCE_HIDE_INPUT_IMAGES=true    # Hide image content
export OPENINFERENCE_HIDE_INPUT_TEXT=true      # Hide embedding text
export OPENINFERENCE_BASE64_IMAGE_MAX_LENGTH=10000  # Limit image size

Python TraceConfig:

from phoenix.otel import register
from openinference.instrumentation import TraceConfig

config = TraceConfig(
    hide_inputs=True,
    hide_outputs=True,
    hide_input_messages=True
)
register(trace_config=config)

Precedence: Code > Environment variables > Defaults

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Span Filtering

Suppress specific code blocks:

from phoenix.otel import suppress_tracing

with suppress_tracing():
    internal_logging()  # No spans generated