Databricks
GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #96
A Generative AI Engineer is tasked with deploying an application that takes advantage of a custom MLflow Pyfunc model to return some interim results. How should they configure the endpoint to pass the
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ML Model Deployment and MLOps
Question
A Generative AI Engineer is tasked with deploying an application that takes advantage of a custom MLflow Pyfunc model to return some interim results. How should they configure the endpoint to pass the secrets and credentials?
Options
- AUse spark.conf.set ()
- BPass variables using the Databricks Feature Store API
- CAdd credentials using environment variables
- DPass the secrets in plain text
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Topics
#MLflow Model Deployment#Secrets Management#Environment Variables#Endpoint Configuration