def test_canary_update(self, client, created_endpoints, experiment_run,
model_for_deployment):
experiment_run.log_model(model_for_deployment['model'],
custom_modules=[])
experiment_run.log_requirements(['scikit-learn'])
path = verta._internal_utils._utils.generate_default_name()
endpoint = client.set_endpoint(path)
created_endpoints.append(endpoint)
original_status = endpoint.get_status()
original_build_ids = get_build_ids(original_status)
strategy = CanaryUpdateStrategy(interval=1, step=0.5)
with pytest.raises(RuntimeError) as excinfo:
endpoint.update(experiment_run, strategy)
assert "canary update strategy must have at least one rule" in str(
excinfo.value)
strategy.add_rule(MaximumAverageLatencyThresholdRule(0.8))
updated_status = endpoint.update(experiment_run, strategy)
# Check that a new build is added:
new_build_ids = get_build_ids(updated_status)
assert len(new_build_ids) - len(
new_build_ids.intersection(original_build_ids)) > 0
def test_update_with_parameters(self, client, created_endpoints,
experiment_run, model_for_deployment):
experiment_run.log_model(model_for_deployment['model'],
custom_modules=[])
experiment_run.log_requirements(['scikit-learn'])
path = verta._internal_utils._utils.generate_default_name()
endpoint = client.set_endpoint(path)
created_endpoints.append(endpoint)
original_status = endpoint.get_status()
original_build_ids = get_build_ids(original_status)
strategy = CanaryUpdateStrategy(interval=1, step=0.5)
strategy.add_rule(MaximumAverageLatencyThresholdRule(0.8))
updated_status = endpoint.update(experiment_run,
strategy,
resources=Resources(cpu=.25,
memory="512Mi"),
env_vars={
'CUDA_VISIBLE_DEVICES': "1,2",
"VERTA_HOST": "app.verta.ai"
})
# Check that a new build is added:
new_build_ids = get_build_ids(updated_status)
assert len(new_build_ids) - len(
new_build_ids.intersection(original_build_ids)) > 0
def test_download_manifest(self, client, in_tempdir):
download_to_path = "manifest.yaml"
path = verta._internal_utils._utils.generate_default_name()
name = verta._internal_utils._utils.generate_default_name()
strategy = CanaryUpdateStrategy(interval=10, step=0.1)
strategy.add_rule(MaximumAverageLatencyThresholdRule(0.1))
resources = Resources(cpu=.1, memory="128Mi")
autoscaling = Autoscaling(min_replicas=1,
max_replicas=10,
min_scale=0.1,
max_scale=2)
autoscaling.add_metric(CpuUtilizationTarget(0.75))
env_vars = {'env1': "var1", 'env2': "var2"}
filepath = client.download_endpoint_manifest(
download_to_path=download_to_path,
path=path,
name=name,
strategy=strategy,
autoscaling=autoscaling,
resources=resources,
env_vars=env_vars,
)
# can be loaded as YAML
with open(filepath, 'rb') as f:
manifest = yaml.safe_load(f)
assert manifest['kind'] == "Endpoint"
# check environment variables
containers = manifest['spec']['function']['spec']['templates'][
'deployment']['spec']['template']['spec']['containers']
retrieved_env_vars = {
env_var['name']: env_var['value']
for env_var in containers[0]['env']
}
assert retrieved_env_vars == env_vars
