async def start_scheduler(self):
self.cluster._log(
f"Launching cluster with the following configuration: "
f"\n Source Image: {self.source_image} "
f"\n Docker Image: {self.docker_image} "
f"\n Machine Type: {self.machine_type} "
f"\n Filesytsem Size: {self.filesystem_size} "
f"\n N-GPU Type: {self.ngpus} {self.gpu_type}"
f"\n Zone: {self.zone} ")
self.cluster._log("Creating scheduler instance")
self.internal_ip, self.external_ip = await self.create_vm()
if self.config.get("public_ingress", True) and not is_inside_gce():
# scheduler must be publicly available, and firewall
# needs to be in place to allow access to 8786 on
# the external IP
self.address = f"{self.cluster.protocol}://{self.external_ip}:8786"
else:
# if the client is running inside GCE environment
# it's better to use internal IP, which doesn't
# require firewall setup
self.address = f"{self.cluster.protocol}://{self.internal_ip}:8786"
await self.wait_for_scheduler()
# need to reserve internal IP for workers
# gcp docker containers can't see resolve ip address
self.cluster.scheduler_internal_ip = self.internal_ip
self.cluster.scheduler_external_ip = self.external_ip
def test_is_gce_env():
# Note: this test isn't super valuable, but at least we run the code
assert is_inside_gce() is False
import pytest
from dask_cloudprovider.gcp.utils import build_request, is_inside_gce
def test_build_request():
assert build_request()(None, lambda x: x, "https://example.com")
@pytest.mark.xfail(is_inside_gce(),
reason="Fails if you run this test on GCE environment")
def test_is_gce_env():
# Note: this test isn't super valuable, but at least we run the code
assert is_inside_gce() is False