Move TF Operator e2e tests to AWS Prow (kubeflow#1204)

Author: ChanYiLin

manifests/crd.yaml

@@ -0,0 +1,47 @@
+apiVersion: apiextensions.k8s.io/v1beta1
+kind: CustomResourceDefinition
+metadata:
+  name: tfjobs.kubeflow.org
+spec:
+  group: kubeflow.org
+  scope: Namespaced
+  names:
+    kind: TFJob
+    singular: tfjob
+    plural: tfjobs
+  versions:
+  - name: v1
+    served: true
+    storage: true
+  subresources:
+    status: {}
+  validation:
+    openAPIV3Schema:
+      properties:
+        spec:
+          properties:
+            tfReplicaSpecs:
+              properties:
+                # The validation works when the configuration contains
+                # `Worker`, `PS` , `Chief` or `Evaluator`. Otherwise it will not be validated.
+                Worker:
+                  properties:
+                    replicas:
+                      type: integer
+                      minimum: 1
+                PS:
+                  properties:
+                    replicas:
+                      type: integer
+                      minimum: 1
+                Chief:
+                  properties:
+                    replicas:
+                      type: integer
+                      minimum: 1
+                      maximum: 1
+                Evaluator:
+                  properties:
+                    replicas:
+                      type: integer
+                      minimum: 0

manifests/deployment.yaml

@@ -0,0 +1,30 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: tf-job-operator
+  namespace: kubeflow
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      name: tf-job-operator
+  template:
+    metadata:
+      labels:
+        name: tf-job-operator
+    spec:
+      containers:
+      - args:
+        - --monitoring-port=8443
+        env:
+        - name: MY_POD_NAMESPACE
+          valueFrom:
+            fieldRef:
+              fieldPath: metadata.namespace
+        - name: MY_POD_NAME
+          valueFrom:
+            fieldRef:
+              fieldPath: metadata.name
+        image: gcr.io/kubeflow-images-public/tf-operator:v0.6.0
+        name: tf-job-operator
+      serviceAccountName: tf-job-operator

manifests/kustomization.yaml

@@ -0,0 +1,15 @@
+apiVersion: kustomize.config.k8s.io/v1beta1
+kind: Kustomization
+namespace: kubeflow
+resources:
+- crd.yaml
+- namespace.yaml
+- rbac.yaml
+- deployment.yaml
+- service.yaml
+commonLabels:
+  kustomize.component: tf-job-operator
+images:
+- name: gcr.io/kubeflow-images-public/tf-operator
+  newName: 809251082950.dkr.ecr.us-west-2.amazonaws.com/tf-operator
+  newTag: "0.1"

manifests/namespace.yaml

@@ -0,0 +1,4 @@
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: kubeflow

manifests/podgroup.yaml

@@ -0,0 +1,39 @@
+apiVersion: apiextensions.k8s.io/v1beta1
+kind: CustomResourceDefinition
+metadata:
+  name: podgroups.scheduling.incubator.k8s.io
+spec:
+  group: scheduling.incubator.k8s.io
+  names:
+    kind: PodGroup
+    plural: podgroups
+  scope: Namespaced
+  validation:
+    openAPIV3Schema:
+      properties:
+        apiVersion:
+          type: string
+        kind:
+          type: string
+        metadata:
+          type: object
+        spec:
+          properties:
+            minMember:
+              format: int32
+              type: integer
+          type: object
+        status:
+          properties:
+            succeeded:
+              format: int32
+              type: integer
+            failed:
+              format: int32
+              type: integer
+            running:
+              format: int32
+              type: integer
+          type: object
+      type: object
+  version: v1alpha1

manifests/rbac.yaml

@@ -0,0 +1,61 @@
+apiVersion: v1
+kind: ServiceAccount
+metadata:
+  labels:
+    app: tf-job-operator
+  name: tf-job-operator
+  namespace: kubeflow
+---
+apiVersion: rbac.authorization.k8s.io/v1beta1
+kind: ClusterRole
+metadata:
+  labels:
+    app: tf-job-operator
+  name: tf-job-operator
+rules:
+- apiGroups:
+  - kubeflow.org
+  resources:
+  - tfjobs
+  - tfjobs/status
+  - tfjobs/finalizers
+  verbs:
+  - '*'
+- apiGroups:
+  - apiextensions.k8s.io
+  resources:
+  - customresourcedefinitions
+  verbs:
+  - '*'
+- apiGroups:
+  - ""
+  resources:
+  - pods
+  - services
+  - endpoints
+  - events
+  verbs:
+  - '*'
+- apiGroups:
+  - apps
+  - extensions
+  resources:
+  - deployments
+  verbs:
+  - '*'
+---
+apiVersion: rbac.authorization.k8s.io/v1beta1
+kind: ClusterRoleBinding
+metadata:
+  labels:
+    app: tf-job-operator
+  name: tf-job-operator
+roleRef:
+  apiGroup: rbac.authorization.k8s.io
+  kind: ClusterRole
+  name: tf-job-operator
+subjects:
+- kind: ServiceAccount
+  name: tf-job-operator
+  namespace: kubeflow
+---

manifests/service.yaml

@@ -0,0 +1,19 @@
+apiVersion: v1
+kind: Service
+metadata:
+  annotations:
+    prometheus.io/path: /metrics
+    prometheus.io/scrape: "true"
+    prometheus.io/port: "8443"
+  labels:
+    app: tf-job-operator
+  name: tf-job-operator
+  namespace: kubeflow
+spec:
+  ports:
+  - name: monitoring-port
+    port: 8443
+    targetPort: 8443
+  selector:
+    name: tf-job-operator
+  type: ClusterIP

py/kubeflow/tf_operator/cleanpod_policy_tests.py

@@ -3,6 +3,7 @@
 
 from kubeflow.testing import ks_util, test_util, util
 from kubeflow.tf_operator import k8s_util, test_runner, tf_job_client
+from kubeflow.tf_operator import util as tf_operator_util
 from kubernetes import client as k8s_client
 
 CLEANPOD_ALL_COMPONENT_NAME = "clean_pod_all"
@@ -23,11 +24,12 @@ def __init__(self, args):
       class_name="CleanPodPolicyTests", name=name)
 
   def run_tfjob_with_cleanpod_policy(self, component, clean_pod_policy):
+    tf_operator_util.load_kube_config()
     api_client = k8s_client.ApiClient()
 
     # Setup the ksonnet app
     ks_cmd = ks_util.get_ksonnet_cmd(self.app_dir)
-    ks_util.setup_ks_app(self.app_dir, self.env, self.namespace, component,
+    tf_operator_util.setup_ks_app(self.app_dir, self.env, self.namespace, component,
                          self.params)
 
     # Create the TF job

py/kubeflow/tf_operator/deploy.py

@@ -90,7 +90,7 @@ def ks_deploy(app_dir, component, params, env=None, account=None):
     if not re.search(".*environment.*already exists.*", e.output):
       raise
 
-  for k, v in params.iteritems():
+  for k, v in params.items():
     util.run([ks_cmd, "param", "set", "--env=" + env, component, k, v],
              cwd=app_dir)
 

py/kubeflow/tf_operator/distributed_training_tests.py

@@ -3,6 +3,7 @@
 
 from kubeflow.testing import ks_util, test_util, util
 from kubeflow.tf_operator import test_runner, tf_job_client
+from kubeflow.tf_operator import util as tf_operator_util
 from kubernetes import client as k8s_client
 
 TFJOB_COMPONENT_NAME = "distributed_training"
@@ -23,10 +24,11 @@ def __init__(self, args):
   # Run a distributed training TFJob, wait for it to complete, and check for pod/service
   # creation errors.
   def run_distributed_training_job(self, component):
+    tf_operator_util.load_kube_config()
     api_client = k8s_client.ApiClient()
 
     # Setup the ksonnet app
-    ks_util.setup_ks_app(self.app_dir, self.env, self.namespace, component,
+    tf_operator_util.setup_ks_app(self.app_dir, self.env, self.namespace, component,
                          self.params)
 
     # Create the TF job