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Version: v0.64.0

Deployment environment variables

This page describes how to manage custom environment variables in the scoring runtime.

Connect to H2O MLOps​

import h2o_mlops
import time


mlops = h2o_mlops.Client()

New deployment​

  1. Prepare everything you need to create a deployment.
project = mlops.projects.create(name="demo")

experiment = project.experiments.create(
   data="/Users/jgranados/Downloads/GBM_model_python_1649367037255_1.zip",
   name="experiment-from-client"
)
model = project.models.create(name="model-from-client")
model.register(experiment=experiment)

environment = project.environments.list(name="DEV")[0]

scoring_runtime = mlops.runtimes.scoring.list(
   artifact_type=model.get_experiment().scoring_artifact_types[0]
)[0]
  1. Define a few environment variables to add to the scoring runtime.
environment_variables = {"MY_CUSTOM_VAR_1": "abc", "MY_CUSTOM_VAR_2": "xyz"}
  1. Deploy using the environment variables argument.
deployment = environment.deployments.create_single(
   name="deployment-from-client",
   model=model,
   scoring_runtime=scoring_runtime,
   environment_variables=environment_variables,
)

while not deployment.is_healthy():
   deployment.raise_for_failure()
   time.sleep(5)

deployment.environment_variables

Output:

{'MY_CUSTOM_VAR_1': 'abc', 'MY_CUSTOM_VAR_2': 'xyz'}

Existing deployment​

You can also set environment variables in an existing deployment. Note that this removes all environment variables that were previously set.

deployment.set_environment_variables({"MY_OTHER_CUSTOM_VAR": "123"})

while not deployment.is_healthy():
   deployment.raise_for_failure()
   time.sleep(5)

deployment.environment_variables

Output:

{'MY_OTHER_CUSTOM_VAR': '123'}
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