Model Serving Monitoring
Integration
Graphsignal agent can be used in model servers that run custom Python inference code. See Quick Start guide on how to install and configure the Graphsignal agent.
Model deployments, versions or environments should be tracked separately. Simply set a different name to deployment
in configure
method.
import graphsignal
graphsignal.configure(api_key='my-api-key', deployment='my-model-v1-prod')
def predict(x):
with graphsignal.start_trace(endpoint='predict'):
# any function or code segment
To record additional information with traced inferences, provide tags
to start_trace
method or use EndpointTrace.set_tag
method.
To track data metrics and record per-inference data profiles, EndpointTrace.set_data
method can be used.
with graphsignal.start_trace(endpoint='predict') as trace:
trace.set_data('input', input_data)
For model servers that only accept model files and expose them via REST API, client-side integration can be used.
Examples
This FastAPI example illustrates how to integrate Graphsignal.