def test_construct_dagster_k8s_job_with_sidecar_container():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="test",
)
job = construct_dagster_k8s_job(cfg, [], "job123").to_dict()
assert job["spec"][
"ttl_seconds_after_finished"] == DEFAULT_K8S_JOB_TTL_SECONDS_AFTER_FINISHED
user_defined_cfg = UserDefinedDagsterK8sConfig(pod_spec_config={
"containers": [{
"command": ["echo", "HI"],
"image": "sidecar:bar",
"name": "sidecar"
}]
}, )
job = construct_dagster_k8s_job(
cfg, [], "job123", user_defined_k8s_config=user_defined_cfg).to_dict()
containers = job["spec"]["template"]["spec"]["containers"]
assert len(containers) == 2
assert containers[0]["image"] == "test/foo:latest"
assert containers[1]["image"] == "sidecar:bar"
assert containers[1]["command"] == ["echo", "HI"]
assert containers[1]["name"] == "sidecar"
def test_construct_dagster_k8s_job_with_job_op_labels():
common_labels = {
"app.kubernetes.io/name": "dagster",
"app.kubernetes.io/instance": "dagster",
"app.kubernetes.io/version": dagster_version,
"app.kubernetes.io/part-of": "dagster",
}
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="test",
)
job1 = construct_dagster_k8s_job(
cfg,
[],
"job123",
labels={
"dagster/job": "some_job",
"dagster/op": "some_op",
},
).to_dict()
expected_labels1 = dict(
**common_labels,
**{
"dagster/job": "some_job",
"dagster/op": "some_op",
},
)
assert job1["metadata"]["labels"] == expected_labels1
assert job1["spec"]["template"]["metadata"]["labels"] == expected_labels1
job2 = construct_dagster_k8s_job(
cfg,
[],
"job456",
labels={
"dagster/job":
"long_job_name_64____01234567890123456789012345678901234567890123",
"dagster/op":
"long_op_name_64_____01234567890123456789012345678901234567890123",
},
).to_dict()
expected_labels2 = dict(
**common_labels,
**{
# The last character should be truncated.
"dagster/job":
"long_job_name_64____0123456789012345678901234567890123456789012",
"dagster/op":
"long_op_name_64_____0123456789012345678901234567890123456789012",
},
)
assert job2["metadata"]["labels"] == expected_labels2
assert job2["spec"]["template"]["metadata"]["labels"] == expected_labels2
def test_construct_dagster_k8s_job_with_ttl():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="test",
)
job = construct_dagster_k8s_job(cfg, [], "job123").to_dict()
assert job["spec"][
"ttl_seconds_after_finished"] == DEFAULT_K8S_JOB_TTL_SECONDS_AFTER_FINISHED
user_defined_cfg = UserDefinedDagsterK8sConfig(
job_spec_config={"ttl_seconds_after_finished": 0}, )
job = construct_dagster_k8s_job(
cfg, [], "job123", user_defined_k8s_config=user_defined_cfg).to_dict()
assert job["spec"]["ttl_seconds_after_finished"] == 0
def test_construct_dagster_k8s_job_with_user_defined_env_from():
@graph
def user_defined_k8s_env_from_tags_graph():
pass
# These fields still work even when using underscore keys
user_defined_k8s_config = get_user_defined_k8s_config(
user_defined_k8s_env_from_tags_graph.to_job(
tags={
USER_DEFINED_K8S_CONFIG_KEY: {
"container_config": {
"envFrom": [
{
"configMapRef": {
"name": "user_config_map_ref",
"optional": "True",
}
},
{
"secretRef": {
"name": "user_secret_ref_one",
"optional": "True"
}
},
{
"secretRef": {
"name": "user_secret_ref_two",
"optional": "False",
},
"prefix": "with_prefix",
},
]
}
}
}).tags)
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="some-instance-configmap",
env_config_maps=["config_map"],
env_secrets=["secret"],
)
job = construct_dagster_k8s_job(
cfg, ["foo", "bar"],
"job",
user_defined_k8s_config=user_defined_k8s_config).to_dict()
env_from = job["spec"]["template"]["spec"]["containers"][0]["env_from"]
env_from_mapping = {(env_var.get("config_map_ref")
or env_var.get("secret_ref")).get("name"): env_var
for env_var in env_from}
assert len(env_from_mapping) == 5
assert env_from_mapping["config_map"]
assert env_from_mapping["user_config_map_ref"]
assert env_from_mapping["secret"]
assert env_from_mapping["user_secret_ref_one"]
assert env_from_mapping["user_secret_ref_two"]
def test_valid_job_format(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), 'env.yaml'))
pipeline_name = 'demo_pipeline'
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
job_name = 'dagster-run-%s' % run.run_id
pod_name = 'dagster-run-%s' % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=['dagster-graphql'],
args=[
'-p',
'executeRunInProcess',
'-v',
seven.json.dumps({'runId': run.run_id}),
],
job_name=job_name,
pod_name=pod_name,
component='runmaster',
)
assert (yaml.dump(
remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() == EXPECTED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
resources='',
).strip())
def test_construct_dagster_k8s_job_with_user_defined_service_account_name():
@graph
def user_defined_k8s_service_account_name_tags_graph():
pass
user_defined_k8s_config = get_user_defined_k8s_config(
user_defined_k8s_service_account_name_tags_graph.to_job(tags={
USER_DEFINED_K8S_CONFIG_KEY: {
"pod_spec_config": {
"service_account_name": "this-should-take-precedence",
},
},
}, ).tags)
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="some-instance-configmap",
service_account_name="this-should-be-overriden",
)
job = construct_dagster_k8s_job(
cfg, ["foo", "bar"],
"job",
user_defined_k8s_config=user_defined_k8s_config).to_dict()
service_account_name = job["spec"]["template"]["spec"][
"service_account_name"]
assert service_account_name == "this-should-take-precedence"
def test_valid_job_format(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), "env.yaml"))
pipeline_name = "demo_pipeline"
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
job_name = "dagster-run-%s" % run.run_id
pod_name = "dagster-run-%s" % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=["dagster"],
args=["api", "execute_run_with_structured_logs"],
job_name=job_name,
pod_name=pod_name,
component="run_coordinator",
)
assert (yaml.dump(
remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() == EXPECTED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
resources="",
).strip())
def test_construct_dagster_k8s_job_with_mounts():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{"name": "my_secret"}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
volume_mounts=[
{"name": "foo", "path": "biz/buz", "sub_path": "file.txt", "configmap": "settings-cm"}
],
)
job = construct_dagster_k8s_job(cfg, ["foo", "bar"], "job123").to_dict()
assert len(job["spec"]["template"]["spec"]["volumes"]) == 2
foo_volumes = [
volume for volume in job["spec"]["template"]["spec"]["volumes"] if volume["name"] == "foo"
]
assert len(foo_volumes) == 1
assert len(job["spec"]["template"]["spec"]["containers"][0]["volume_mounts"]) == 2
foo_volumes_mounts = [
volume
for volume in job["spec"]["template"]["spec"]["containers"][0]["volume_mounts"]
if volume["name"] == "foo"
]
assert len(foo_volumes_mounts) == 1
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{"name": "my_secret"}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
volume_mounts=[
{"name": "foo", "path": "biz/buz", "sub_path": "file.txt", "secret": "settings-secret"}
],
)
construct_dagster_k8s_job(cfg, ["foo", "bar"], "job123").to_dict()
def test_construct_dagster_k8s_job_with_user_defined_env():
@graph
def user_defined_k8s_env_tags_graph():
pass
user_defined_k8s_config = get_user_defined_k8s_config(
user_defined_k8s_env_tags_graph.to_job(
tags={
USER_DEFINED_K8S_CONFIG_KEY: {
"container_config": {
"env": [
{
"name": "ENV_VAR_1",
"value": "one"
},
{
"name": "ENV_VAR_2",
"value": "two"
},
{
"name": "DD_AGENT_HOST",
"valueFrom": {
"fieldRef": {
"fieldPath": "status.hostIP"
}
},
},
]
}
}
}).tags)
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="some-instance-configmap",
)
job = construct_dagster_k8s_job(
cfg, ["foo", "bar"],
"job",
user_defined_k8s_config=user_defined_k8s_config).to_dict()
env = job["spec"]["template"]["spec"]["containers"][0]["env"]
env_mapping = remove_none_recursively(
{env_var["name"]: env_var
for env_var in env})
# Has DAGSTER_HOME and three additional env vars
assert len(env_mapping) == 4
assert env_mapping["ENV_VAR_1"]["value"] == "one"
assert env_mapping["ENV_VAR_2"]["value"] == "two"
assert env_mapping["DD_AGENT_HOST"]["value_from"] == {
"field_ref": {
"field_path": "status.hostIP"
}
}
def test_valid_job_format_with_backcompat_resources(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), "env.yaml"))
pipeline_name = "demo_pipeline"
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
tags = validate_tags({
K8S_RESOURCE_REQUIREMENTS_KEY: ({
"requests": {
"cpu": "250m",
"memory": "64Mi"
},
"limits": {
"cpu": "500m",
"memory": "2560Mi"
},
})
})
user_defined_k8s_config = get_user_defined_k8s_config(tags)
job_name = "dagster-run-%s" % run.run_id
pod_name = "dagster-run-%s" % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=["dagster-graphql"],
args=[
"-p",
"executeRunInProcess",
"-v",
seven.json.dumps({"runId": run.run_id}),
],
job_name=job_name,
user_defined_k8s_config=user_defined_k8s_config,
pod_name=pod_name,
component="run_coordinator",
)
assert (yaml.dump(
remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() == EXPECTED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
resources="""
resources:
limits:
cpu: 500m
memory: 2560Mi
requests:
cpu: 250m
memory: 64Mi""",
).strip())
def test_construct_dagster_k8s_job_with_user_defined_volume_mounts_snake_case(
):
@graph
def user_defined_k8s_volume_mounts_tags_graph():
pass
# volume_mounts still work even when using underscore keys
user_defined_k8s_config = get_user_defined_k8s_config(
user_defined_k8s_volume_mounts_tags_graph.to_job(
tags={
USER_DEFINED_K8S_CONFIG_KEY: {
"container_config": {
"volume_mounts": [
{
"mountPath": "mount_path",
"mountPropagation": "mount_propagation",
"name": "a_volume_mount_one",
"readOnly": "False",
"subPath": "path/",
},
{
"mountPath": "mount_path",
"mountPropagation": "mount_propagation",
"name": "a_volume_mount_two",
"readOnly": "False",
"subPathExpr": "path/",
},
]
}
}
}).tags)
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="some-instance-configmap",
)
job = construct_dagster_k8s_job(
cfg, ["foo", "bar"],
"job",
user_defined_k8s_config=user_defined_k8s_config).to_dict()
volume_mounts = job["spec"]["template"]["spec"]["containers"][0][
"volume_mounts"]
volume_mounts_mapping = {
volume_mount["name"]: volume_mount
for volume_mount in volume_mounts
}
assert len(volume_mounts_mapping) == 3
assert volume_mounts_mapping["dagster-instance"]
assert volume_mounts_mapping["a_volume_mount_one"]
assert volume_mounts_mapping["a_volume_mount_two"]
def test_valid_job_format_with_resources(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), 'env.yaml'))
pipeline_name = 'demo_pipeline'
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
tags = validate_tags({
K8S_RESOURCE_REQUIREMENTS_KEY: ({
'requests': {
'cpu': '250m',
'memory': '64Mi'
},
'limits': {
'cpu': '500m',
'memory': '2560Mi'
},
})
})
resources = get_k8s_resource_requirements(tags)
job_name = 'dagster-run-%s' % run.run_id
pod_name = 'dagster-run-%s' % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=['dagster-graphql'],
args=[
'-p',
'executeRunInProcess',
'-v',
seven.json.dumps({'runId': run.run_id}),
],
job_name=job_name,
resources=resources,
pod_name=pod_name,
component='runmaster',
)
assert (yaml.dump(
remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() == EXPECTED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
resources='''
resources:
limits:
cpu: 500m
memory: 2560Mi
requests:
cpu: 250m
memory: 64Mi''',
).strip())
def test_construct_dagster_k8s_job_with_env():
with environ({"ENV_VAR_1": "one", "ENV_VAR_2": "two"}):
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="some-instance-configmap",
env_vars=["ENV_VAR_1", "ENV_VAR_2"],
)
job = construct_dagster_k8s_job(cfg, ["foo", "bar"], "job").to_dict()
env = job["spec"]["template"]["spec"]["containers"][0]["env"]
env_mapping = {env_var["name"]: env_var for env_var in env}
# Has DAGSTER_HOME and two additional env vars
assert len(env_mapping) == 3
assert env_mapping["ENV_VAR_1"]["value"] == "one"
assert env_mapping["ENV_VAR_2"]["value"] == "two"
def test_construct_dagster_k8s_job_no_postgres():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{"name": "my_secret"}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
)
job = construct_dagster_k8s_job(cfg, ["foo", "bar"], "job123").to_dict()
assert job["kind"] == "Job"
assert job["metadata"]["name"] == "job123"
assert job["spec"]["template"]["spec"]["containers"][0]["image"] == "test/foo:latest"
assert DAGSTER_PG_PASSWORD_ENV_VAR not in [
env["name"] for env in job["spec"]["template"]["spec"]["containers"][0]["env"]
]
def test_sanitize_labels():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="test",
)
job = construct_dagster_k8s_job(
cfg,
[],
"job456",
labels={
"dagster/op": "-get_f\o.o[bar-0]-", # pylint: disable=anomalous-backslash-in-string
"my_label": "_WhatsUP",
},
).to_dict()
assert job["metadata"]["labels"]["dagster/op"] == "get_f-o.o-bar-0"
assert job["metadata"]["labels"]["my_label"] == "WhatsUP"
def test_k8s_tag_op():
assert my_op
user_defined_cfg = get_user_defined_k8s_config(my_op.tags)
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
instance_config_map="test",
)
job = construct_dagster_k8s_job(cfg, [],
"job123",
user_defined_k8s_config=user_defined_cfg)
assert job.to_dict(
)["spec"]["template"]["spec"]["containers"][0]["resources"] == {
"requests": {
"cpu": "200m",
"memory": "32Mi"
},
"limits": None,
}
def _execute_step_k8s_job(
self,
execute_step_args_packed,
job_config_dict,
job_namespace,
load_incluster_config,
user_defined_k8s_config_dict=None,
kubeconfig_file=None,
):
"""Run step execution in a K8s job pod."""
execute_step_args = unpack_value(
check.dict_param(
execute_step_args_packed,
"execute_step_args_packed",
))
check.inst_param(execute_step_args, "execute_step_args",
ExecuteStepArgs)
check.invariant(
len(execute_step_args.step_keys_to_execute) == 1,
"Celery K8s task executor can only execute 1 step at a time",
)
# Celery will serialize this as a list
job_config = DagsterK8sJobConfig.from_dict(job_config_dict)
check.inst_param(job_config, "job_config", DagsterK8sJobConfig)
check.str_param(job_namespace, "job_namespace")
check.bool_param(load_incluster_config, "load_incluster_config")
user_defined_k8s_config = UserDefinedDagsterK8sConfig.from_dict(
user_defined_k8s_config_dict)
check.opt_inst_param(
user_defined_k8s_config,
"user_defined_k8s_config",
UserDefinedDagsterK8sConfig,
)
check.opt_str_param(kubeconfig_file, "kubeconfig_file")
# For when launched via DinD or running the cluster
if load_incluster_config:
kubernetes.config.load_incluster_config()
else:
kubernetes.config.load_kube_config(kubeconfig_file)
instance = DagsterInstance.from_ref(execute_step_args.instance_ref)
pipeline_run = instance.get_run_by_id(
execute_step_args.pipeline_run_id)
check.inst(
pipeline_run,
PipelineRun,
"Could not load run {}".format(execute_step_args.pipeline_run_id),
)
step_key = execute_step_args.step_keys_to_execute[0]
celery_worker_name = self.request.hostname
celery_pod_name = os.environ.get("HOSTNAME")
instance.report_engine_event(
"Task for step {step_key} picked up by Celery".format(
step_key=step_key),
pipeline_run,
EngineEventData([
EventMetadataEntry.text(celery_worker_name,
"Celery worker name"),
EventMetadataEntry.text(celery_pod_name,
"Celery worker Kubernetes Pod name"),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
if pipeline_run.status != PipelineRunStatus.STARTED:
instance.report_engine_event(
"Not scheduling step because pipeline run status is not STARTED",
pipeline_run,
EngineEventData([
EventMetadataEntry.text(step_key, "Step key"),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
return []
# Ensure we stay below k8s name length limits
k8s_name_key = get_k8s_job_name(execute_step_args.pipeline_run_id,
step_key)
retry_state = execute_step_args.known_state.get_retry_state()
if retry_state.get_attempt_count(step_key):
attempt_number = retry_state.get_attempt_count(step_key)
job_name = "dagster-job-%s-%d" % (k8s_name_key, attempt_number)
pod_name = "dagster-job-%s-%d" % (k8s_name_key, attempt_number)
else:
job_name = "dagster-job-%s" % (k8s_name_key)
pod_name = "dagster-job-%s" % (k8s_name_key)
input_json = serialize_dagster_namedtuple(execute_step_args)
args = ["dagster", "api", "execute_step", input_json]
job = construct_dagster_k8s_job(job_config, args, job_name,
user_defined_k8s_config, pod_name)
# Running list of events generated from this task execution
events = []
# Post event for starting execution
job_name = job.metadata.name
engine_event = instance.report_engine_event(
"Executing step {} in Kubernetes job {}".format(
step_key, job_name),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
EventMetadataEntry.text(job_name, "Kubernetes Job name"),
EventMetadataEntry.text(job_config.job_image, "Job image"),
EventMetadataEntry.text(job_config.image_pull_policy,
"Image pull policy"),
EventMetadataEntry.text(str(job_config.image_pull_secrets),
"Image pull secrets"),
EventMetadataEntry.text(
str(job_config.service_account_name),
"Service account name"),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
# validated above that step_keys is length 1, and it is not possible to use ETH or
# execution plan in this function (Celery K8s workers should not access to user code)
step_key=step_key,
)
events.append(engine_event)
try:
kubernetes.client.BatchV1Api().create_namespaced_job(
body=job, namespace=job_namespace)
except kubernetes.client.rest.ApiException as e:
if e.reason == "Conflict":
# There is an existing job with the same name so proceed and see if the existing job succeeded
instance.report_engine_event(
"Did not create Kubernetes job {} for step {} since job name already "
"exists, proceeding with existing job.".format(
job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
EventMetadataEntry.text(job_name,
"Kubernetes Job name"),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
step_key=step_key,
)
else:
instance.report_engine_event(
"Encountered unexpected error while creating Kubernetes job {} for step {}, "
"exiting.".format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
],
error=serializable_error_info_from_exc_info(
sys.exc_info()),
),
CeleryK8sJobExecutor,
step_key=step_key,
)
return []
try:
wait_for_job_success(
job_name=job_name,
namespace=job_namespace,
instance=instance,
run_id=execute_step_args.pipeline_run_id,
)
except (DagsterK8sError, DagsterK8sTimeoutError) as err:
step_failure_event = construct_step_failure_event_and_handle(
pipeline_run, step_key, err, instance=instance)
events.append(step_failure_event)
except DagsterK8sPipelineStatusException:
instance.report_engine_event(
"Terminating Kubernetes Job because pipeline run status is not STARTED",
pipeline_run,
EngineEventData([
EventMetadataEntry.text(step_key, "Step key"),
EventMetadataEntry.text(job_name, "Kubernetes Job name"),
EventMetadataEntry.text(job_namespace,
"Kubernetes Job namespace"),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
delete_job(job_name=job_name, namespace=job_namespace)
return []
except (
DagsterK8sUnrecoverableAPIError,
DagsterK8sAPIRetryLimitExceeded,
# We shouldn't see unwrapped APIExceptions anymore, as they should all be wrapped in
# a retry boundary. We still catch it here just in case we missed one so that we can
# report it to the event log
kubernetes.client.rest.ApiException,
) as err:
instance.report_engine_event(
"Encountered unexpected error while waiting on Kubernetes job {} for step {}, "
"exiting.".format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
],
error=serializable_error_info_from_exc_info(
sys.exc_info()),
),
CeleryK8sJobExecutor,
step_key=step_key,
)
return []
try:
pod_names = get_pod_names_in_job(job_name, namespace=job_namespace)
except kubernetes.client.rest.ApiException as e:
instance.report_engine_event(
"Encountered unexpected error retreiving Pods for Kubernetes job {} for step {}, "
"exiting.".format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
],
error=serializable_error_info_from_exc_info(
sys.exc_info()),
),
CeleryK8sJobExecutor,
step_key=step_key,
)
return []
# Post engine event for log retrieval
engine_event = instance.report_engine_event(
"Retrieving logs from Kubernetes Job pods",
pipeline_run,
EngineEventData(
[EventMetadataEntry.text("\n".join(pod_names), "Pod names")]),
CeleryK8sJobExecutor,
step_key=step_key,
)
events.append(engine_event)
logs = []
for pod_name in pod_names:
try:
raw_logs = retrieve_pod_logs(pod_name, namespace=job_namespace)
logs += raw_logs.split("\n")
except kubernetes.client.rest.ApiException as e:
instance.report_engine_event(
"Encountered unexpected error while fetching pod logs for Kubernetes job {}, "
"Pod name {} for step {}. Will attempt to continue with other pods."
.format(job_name, pod_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step key"),
],
error=serializable_error_info_from_exc_info(
sys.exc_info()),
),
CeleryK8sJobExecutor,
step_key=step_key,
)
events += filter_dagster_events_from_pod_logs(logs)
serialized_events = [
serialize_dagster_namedtuple(event) for event in events
]
return serialized_events
def test_valid_job_format_with_user_defined_k8s_config(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), "env.yaml"))
pipeline_name = "demo_pipeline"
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
tags = validate_tags({
USER_DEFINED_K8S_CONFIG_KEY: ({
"container_config": {
"resources": {
"requests": {
"cpu": "250m",
"memory": "64Mi"
},
"limits": {
"cpu": "500m",
"memory": "2560Mi"
},
}
},
"pod_template_spec_metadata": {
"annotations": {
"cluster-autoscaler.kubernetes.io/safe-to-evict": "true"
},
"labels": {
"spotinst.io/restrict-scale-down": "true"
},
},
"pod_spec_config": {
"affinity": {
"nodeAffinity": {
"requiredDuringSchedulingIgnoredDuringExecution": {
"nodeSelectorTerms": [{
"matchExpressions": [{
"key":
"kubernetes.io/e2e-az-name",
"operator":
"In",
"values": ["e2e-az1", "e2e-az2"],
}]
}]
}
}
}
},
})
})
user_defined_k8s_config = get_user_defined_k8s_config(tags)
job_name = "dagster-run-%s" % run.run_id
pod_name = "dagster-run-%s" % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=["dagster"],
args=["api", "execute_run_with_structured_logs"],
job_name=job_name,
user_defined_k8s_config=user_defined_k8s_config,
pod_name=pod_name,
component="run_coordinator",
)
assert (yaml.dump(remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() ==
EXPECTED_CONFIGURED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
labels="spotinst.io/restrict-scale-down: 'true'",
resources="""
resources:
limits:
cpu: 500m
memory: 2560Mi
requests:
cpu: 250m
memory: 64Mi""",
annotations="""annotations:
cluster-autoscaler.kubernetes.io/safe-to-evict: \'true\'""",
affinity="""affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: kubernetes.io/e2e-az-name
operator: In
values:
- e2e-az1
- e2e-az2""",
).strip())
def test_construct_dagster_k8s_job_with_mounts():
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{
"name": "my_secret"
}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
volume_mounts=[{
"name": "foo",
"mountPath": "biz/buz",
"subPath": "file.txt"
}],
volumes=[
{
"name": "foo",
"configMap": {
"name": "settings-cm"
}
},
],
)
job = construct_dagster_k8s_job(cfg, ["foo", "bar"], "job123").to_dict()
assert len(job["spec"]["template"]["spec"]["volumes"]) == 2
foo_volumes = [
volume for volume in job["spec"]["template"]["spec"]["volumes"]
if volume["name"] == "foo"
]
assert len(foo_volumes) == 1
assert foo_volumes[0]["config_map"]["name"] == "settings-cm"
assert len(
job["spec"]["template"]["spec"]["containers"][0]["volume_mounts"]) == 2
foo_volumes_mounts = [
volume for volume in job["spec"]["template"]["spec"]["containers"][0]
["volume_mounts"] if volume["name"] == "foo"
]
assert len(foo_volumes_mounts) == 1
cfg = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{
"name": "my_secret"
}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
volume_mounts=[{
"name": "foo",
"mountPath": "biz/buz",
"subPath": "file.txt"
}],
volumes=[
{
"name": "foo",
"secret": {
"secretName": "settings-secret"
}
},
],
)
job = construct_dagster_k8s_job(cfg, ["foo", "bar"], "job123").to_dict()
assert len(job["spec"]["template"]["spec"]["volumes"]) == 2
foo_volumes = [
volume for volume in job["spec"]["template"]["spec"]["volumes"]
if volume["name"] == "foo"
]
assert len(foo_volumes) == 1
assert foo_volumes[0]["secret"]["secret_name"] == "settings-secret"
cfg_with_invalid_volume_key = DagsterK8sJobConfig(
job_image="test/foo:latest",
dagster_home="/opt/dagster/dagster_home",
image_pull_policy="Always",
image_pull_secrets=[{
"name": "my_secret"
}],
service_account_name=None,
instance_config_map="some-instance-configmap",
postgres_password_secret=None,
env_config_maps=None,
env_secrets=None,
volume_mounts=[{
"name": "foo",
"mountPath": "biz/buz",
"subPath": "file.txt"
}],
volumes=[
{
"name": "foo",
"invalidKey": "settings-secret"
},
],
)
with pytest.raises(
Exception,
match="Unexpected keys in model class V1Volume: {'invalidKey'}"):
construct_dagster_k8s_job(cfg_with_invalid_volume_key, ["foo", "bar"],
"job123").to_dict()
def _execute_step_k8s_job(
self,
instance_ref_dict,
step_keys,
run_config,
mode,
repo_name,
repo_location_name,
run_id,
job_config_dict,
job_namespace,
load_incluster_config,
retries_dict,
pipeline_origin_packed,
user_defined_k8s_config_dict=None,
kubeconfig_file=None,
):
"""Run step execution in a K8s job pod.
"""
check.dict_param(instance_ref_dict, "instance_ref_dict")
check.list_param(step_keys, "step_keys", of_type=str)
check.invariant(
len(step_keys) == 1, "Celery K8s task executor can only execute 1 step at a time"
)
check.dict_param(run_config, "run_config")
check.str_param(mode, "mode")
check.str_param(repo_name, "repo_name")
check.str_param(repo_location_name, "repo_location_name")
check.str_param(run_id, "run_id")
# Celery will serialize this as a list
job_config = DagsterK8sJobConfig.from_dict(job_config_dict)
check.inst_param(job_config, "job_config", DagsterK8sJobConfig)
check.str_param(job_namespace, "job_namespace")
check.bool_param(load_incluster_config, "load_incluster_config")
check.dict_param(retries_dict, "retries_dict")
pipeline_origin = unpack_value(
check.dict_param(
pipeline_origin_packed, "pipeline_origin_packed"
) # TODO: make part of args
)
check.inst(pipeline_origin, PipelineOrigin)
user_defined_k8s_config = UserDefinedDagsterK8sConfig.from_dict(
user_defined_k8s_config_dict
)
check.opt_inst_param(
user_defined_k8s_config, "user_defined_k8s_config", UserDefinedDagsterK8sConfig,
)
check.opt_str_param(kubeconfig_file, "kubeconfig_file")
# For when launched via DinD or running the cluster
if load_incluster_config:
kubernetes.config.load_incluster_config()
else:
kubernetes.config.load_kube_config(kubeconfig_file)
instance_ref = InstanceRef.from_dict(instance_ref_dict)
instance = DagsterInstance.from_ref(instance_ref)
pipeline_run = instance.get_run_by_id(run_id)
check.invariant(pipeline_run, "Could not load run {}".format(run_id))
step_key = step_keys[0]
celery_worker_name = self.request.hostname
celery_pod_name = os.environ.get("HOSTNAME")
instance.report_engine_event(
"Task for step {step_key} picked up by Celery".format(step_key=step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(celery_worker_name, "Celery worker name"),
EventMetadataEntry.text(celery_pod_name, "Celery worker Kubernetes Pod name"),
]
),
CeleryK8sJobExecutor,
step_key=step_key,
)
if pipeline_run.status != PipelineRunStatus.STARTED:
instance.report_engine_event(
"Not scheduling step because pipeline run status is not STARTED",
pipeline_run,
EngineEventData([EventMetadataEntry.text(step_key, "Step keys"),]),
CeleryK8sJobExecutor,
step_key=step_key,
)
return
# Ensure we stay below k8s name length limits
k8s_name_key = get_k8s_job_name(run_id, step_key)
retries = Retries.from_config(retries_dict)
if retries.get_attempt_count(step_key):
attempt_number = retries.get_attempt_count(step_key)
job_name = "dagster-job-%s-%d" % (k8s_name_key, attempt_number)
pod_name = "dagster-job-%s-%d" % (k8s_name_key, attempt_number)
else:
job_name = "dagster-job-%s" % (k8s_name_key)
pod_name = "dagster-job-%s" % (k8s_name_key)
input_json = serialize_dagster_namedtuple(
ExecuteStepArgs(
pipeline_origin=pipeline_origin,
pipeline_run_id=run_id,
instance_ref=None,
mode=mode,
step_keys_to_execute=step_keys,
run_config=run_config,
retries_dict=retries_dict,
)
)
command = ["dagster"]
args = ["api", "execute_step_with_structured_logs", input_json]
job = construct_dagster_k8s_job(
job_config, command, args, job_name, user_defined_k8s_config, pod_name
)
# Running list of events generated from this task execution
events = []
# Post event for starting execution
job_name = job.metadata.name
engine_event = instance.report_engine_event(
"Executing step {} in Kubernetes job {}".format(step_key, job_name),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step keys"),
EventMetadataEntry.text(job_name, "Kubernetes Job name"),
EventMetadataEntry.text(pod_name, "Kubernetes Pod name"),
EventMetadataEntry.text(job_config.job_image, "Job image"),
EventMetadataEntry.text(job_config.image_pull_policy, "Image pull policy"),
EventMetadataEntry.text(
str(job_config.image_pull_secrets), "Image pull secrets"
),
EventMetadataEntry.text(
str(job_config.service_account_name), "Service account name"
),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
# validated above that step_keys is length 1, and it is not possible to use ETH or
# execution plan in this function (Celery K8s workers should not access to user code)
step_key=step_key,
)
events.append(engine_event)
try:
kubernetes.client.BatchV1Api().create_namespaced_job(body=job, namespace=job_namespace)
except kubernetes.client.rest.ApiException as e:
if e.reason == "Conflict":
# There is an existing job with the same name so do not procede.
instance.report_engine_event(
"Did not create Kubernetes job {} for step {} since job name already "
"exists, exiting.".format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step keys"),
EventMetadataEntry.text(job_name, "Kubernetes Job name"),
EventMetadataEntry.text(pod_name, "Kubernetes Pod name"),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
step_key=step_key,
)
else:
instance.report_engine_event(
"Encountered unexpected error while creating Kubernetes job {} for step {}, "
"exiting.".format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step keys"),
EventMetadataEntry.text(e, "Error"),
]
),
CeleryK8sJobExecutor,
step_key=step_key,
)
return
try:
wait_for_job_success(
job_name=job_name, namespace=job_namespace, instance=instance, run_id=run_id,
)
except DagsterK8sPipelineStatusException:
instance.report_engine_event(
"Terminating Kubernetes Job because pipeline run status is not STARTED",
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, "Step keys"),
EventMetadataEntry.text(job_name, "Kubernetes Job name"),
EventMetadataEntry.text(job_namespace, "Kubernetes Job namespace"),
]
),
CeleryK8sJobExecutor,
step_key=step_key,
)
delete_job(job_name=job_name, namespace=job_namespace)
return
pod_names = get_pod_names_in_job(job_name, namespace=job_namespace)
# Post engine event for log retrieval
engine_event = instance.report_engine_event(
"Retrieving logs from Kubernetes Job pods",
pipeline_run,
EngineEventData([EventMetadataEntry.text("\n".join(pod_names), "Pod names")]),
CeleryK8sJobExecutor,
step_key=step_key,
)
events.append(engine_event)
logs = []
for pod_name in pod_names:
raw_logs = retrieve_pod_logs(pod_name, namespace=job_namespace)
logs += raw_logs.split("\n")
events += filter_dagster_events_from_pod_logs(logs)
serialized_events = [serialize_dagster_namedtuple(event) for event in events]
return serialized_events
def _execute_step_k8s_job(
_self,
instance_ref_dict,
step_keys,
run_config,
mode,
repo_name,
repo_location_name,
run_id,
job_config_dict,
job_namespace,
load_incluster_config,
retries_dict,
pipeline_origin_packed,
resources=None,
kubeconfig_file=None,
):
'''Run step execution in a K8s job pod.
'''
check.dict_param(instance_ref_dict, 'instance_ref_dict')
check.list_param(step_keys, 'step_keys', of_type=str)
check.invariant(
len(step_keys) == 1,
'Celery K8s task executor can only execute 1 step at a time')
check.dict_param(run_config, 'run_config')
check.str_param(mode, 'mode')
check.str_param(repo_name, 'repo_name')
check.str_param(repo_location_name, 'repo_location_name')
check.str_param(run_id, 'run_id')
# Celery will serialize this as a list
job_config = DagsterK8sJobConfig.from_dict(job_config_dict)
check.inst_param(job_config, 'job_config', DagsterK8sJobConfig)
check.str_param(job_namespace, 'job_namespace')
check.bool_param(load_incluster_config, 'load_incluster_config')
check.dict_param(retries_dict, 'retries_dict')
pipeline_origin = unpack_value(
check.dict_param(
pipeline_origin_packed,
'pipeline_origin_packed') # TODO: make part of args
)
check.inst(pipeline_origin, PipelineOrigin)
check.opt_dict_param(resources,
'resources',
key_type=str,
value_type=dict)
check.opt_str_param(kubeconfig_file, 'kubeconfig_file')
# For when launched via DinD or running the cluster
if load_incluster_config:
kubernetes.config.load_incluster_config()
else:
kubernetes.config.load_kube_config(kubeconfig_file)
instance_ref = InstanceRef.from_dict(instance_ref_dict)
instance = DagsterInstance.from_ref(instance_ref)
pipeline_run = instance.get_run_by_id(run_id)
check.invariant(pipeline_run, 'Could not load run {}'.format(run_id))
step_key = step_keys[0]
if pipeline_run.status != PipelineRunStatus.STARTED:
instance.report_engine_event(
'Not scheduling step because pipeline run status is not STARTED',
pipeline_run,
EngineEventData([
EventMetadataEntry.text(step_key, 'Step keys'),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
return
# Ensure we stay below k8s name length limits
k8s_name_key = get_k8s_job_name(run_id, step_key)
retries = Retries.from_config(retries_dict)
if retries.get_attempt_count(step_key):
attempt_number = retries.get_attempt_count(step_key)
job_name = 'dagster-job-%s-%d' % (k8s_name_key, attempt_number)
pod_name = 'dagster-job-%s-%d' % (k8s_name_key, attempt_number)
else:
job_name = 'dagster-job-%s' % (k8s_name_key)
pod_name = 'dagster-job-%s' % (k8s_name_key)
input_json = serialize_dagster_namedtuple(
ExecuteStepArgs(
pipeline_origin=pipeline_origin,
pipeline_run_id=run_id,
instance_ref=None,
mode=mode,
step_keys_to_execute=step_keys,
run_config=run_config,
retries_dict=retries_dict,
))
command = ['dagster']
args = ['api', 'execute_step_with_structured_logs', input_json]
job = construct_dagster_k8s_job(job_config, command, args, job_name,
resources, pod_name)
# Running list of events generated from this task execution
events = []
# Post event for starting execution
job_name = job.metadata.name
engine_event = instance.report_engine_event(
'Executing step {} in Kubernetes job {}'.format(
step_key, job_name),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, 'Step keys'),
EventMetadataEntry.text(job_name, 'Kubernetes Job name'),
EventMetadataEntry.text(pod_name, 'Kubernetes Pod name'),
EventMetadataEntry.text(job_config.job_image, 'Job image'),
EventMetadataEntry.text(job_config.image_pull_policy,
'Image pull policy'),
EventMetadataEntry.text(str(job_config.image_pull_secrets),
'Image pull secrets'),
EventMetadataEntry.text(
str(job_config.service_account_name),
'Service account name'),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
# validated above that step_keys is length 1, and it is not possible to use ETH or
# execution plan in this function (Celery K8s workers should not access to user code)
step_key=step_key,
)
events.append(engine_event)
try:
kubernetes.client.BatchV1Api().create_namespaced_job(
body=job, namespace=job_namespace)
except kubernetes.client.rest.ApiException as e:
if e.reason == 'Conflict':
# There is an existing job with the same name so do not procede.
instance.report_engine_event(
'Did not create Kubernetes job {} for step {} since job name already '
'exists, exiting.'.format(job_name, step_key),
pipeline_run,
EngineEventData(
[
EventMetadataEntry.text(step_key, 'Step keys'),
EventMetadataEntry.text(job_name,
'Kubernetes Job name'),
EventMetadataEntry.text(pod_name,
'Kubernetes Pod name'),
],
marker_end=DELEGATE_MARKER,
),
CeleryK8sJobExecutor,
step_key=step_key,
)
else:
instance.report_engine_event(
'Encountered unexpected error while creating Kubernetes job {} for step {}, '
'exiting.'.format(job_name, step_key),
pipeline_run,
EngineEventData([
EventMetadataEntry.text(step_key, 'Step keys'),
EventMetadataEntry.text(e, 'Error'),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
return
try:
wait_for_job_success(
job_name=job_name,
namespace=job_namespace,
instance=instance,
run_id=run_id,
)
except DagsterK8sPipelineStatusException:
instance.report_engine_event(
'Terminating Kubernetes Job because pipeline run status is not STARTED',
pipeline_run,
EngineEventData([
EventMetadataEntry.text(step_key, 'Step keys'),
EventMetadataEntry.text(job_name, 'Kubernetes Job name'),
EventMetadataEntry.text(job_namespace,
'Kubernetes Job namespace'),
]),
CeleryK8sJobExecutor,
step_key=step_key,
)
delete_job(job_name=job_name, namespace=job_namespace)
return
pod_names = get_pod_names_in_job(job_name, namespace=job_namespace)
# Post engine event for log retrieval
engine_event = instance.report_engine_event(
'Retrieving logs from Kubernetes Job pods',
pipeline_run,
EngineEventData(
[EventMetadataEntry.text('\n'.join(pod_names), 'Pod names')]),
CeleryK8sJobExecutor,
step_key=step_key,
)
events.append(engine_event)
logs = []
for pod_name in pod_names:
raw_logs = retrieve_pod_logs(pod_name, namespace=job_namespace)
logs += raw_logs.split('\n')
events += filter_dagster_events_from_pod_logs(logs)
serialized_events = [
serialize_dagster_namedtuple(event) for event in events
]
return serialized_events
def test_valid_job_format_with_user_defined_k8s_config(run_launcher):
docker_image = test_project_docker_image()
run_config = load_yaml_from_path(
os.path.join(test_project_environments_path(), 'env.yaml'))
pipeline_name = 'demo_pipeline'
run = PipelineRun(pipeline_name=pipeline_name, run_config=run_config)
tags = validate_tags({
USER_DEFINED_K8S_CONFIG_KEY: ({
'container_config': {
'resources': {
'requests': {
'cpu': '250m',
'memory': '64Mi'
},
'limits': {
'cpu': '500m',
'memory': '2560Mi'
},
}
},
'pod_template_spec_metadata': {
'annotations': {
"cluster-autoscaler.kubernetes.io/safe-to-evict": "true"
}
},
'pod_spec_config': {
'affinity': {
'nodeAffinity': {
'requiredDuringSchedulingIgnoredDuringExecution': {
'nodeSelectorTerms': [{
'matchExpressions': [{
'key':
'kubernetes.io/e2e-az-name',
'operator':
'In',
'values': ['e2e-az1', 'e2e-az2'],
}]
}]
}
}
}
},
})
})
user_defined_k8s_config = get_user_defined_k8s_config(tags)
job_name = 'dagster-run-%s' % run.run_id
pod_name = 'dagster-run-%s' % run.run_id
job = construct_dagster_k8s_job(
job_config=run_launcher.job_config,
command=['dagster-graphql'],
args=[
'-p',
'executeRunInProcess',
'-v',
seven.json.dumps({'runId': run.run_id}),
],
job_name=job_name,
user_defined_k8s_config=user_defined_k8s_config,
pod_name=pod_name,
component='run_coordinator',
)
assert (yaml.dump(remove_none_recursively(job.to_dict()),
default_flow_style=False).strip() ==
EXPECTED_CONFIGURED_JOB_SPEC.format(
run_id=run.run_id,
job_image=docker_image,
image_pull_policy=image_pull_policy(),
dagster_version=dagster_version,
resources='''
resources:
limits:
cpu: 500m
memory: 2560Mi
requests:
cpu: 250m
memory: 64Mi''',
annotations='''annotations:
cluster-autoscaler.kubernetes.io/safe-to-evict: \'true\'''',
affinity='''affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: kubernetes.io/e2e-az-name
operator: In
values:
- e2e-az1
- e2e-az2''',
).strip())
