Tracing and Monitoring Local Models
Integration
Graphsignal tracer can be used in model applications that run models locally. See Quick Start guide on how to install and configure the Graphsignal tracer.
Model deployments, versions or environments can be tracked separately. Simply set a different name to deployment
in configure
method.
import graphsignal
graphsignal.configure(api_key='my-api-key', deployment='my-app-prod')
def predict(x):
with graphsignal.start_trace('predict'):
# model inference here
or using decorator:
@trace_function
def predict(x):
# model inference here
To record additional information with traced inferences, provide tags
to graphsignal.start_trace()
method or use Trace.set_tag
method.
To track data metrics and record per-inference data samples, Trace.set_data()
method can be used.
with graphsignal.start_trace('predict') as span:
span.set_data('input', input_data)
For model servers that only accept model files and expose them via REST API, see Local Models guide.