Create a Ray Cluster SDK upgrade scenarios

Author: Srihari1192

.github/workflows/olm_tests.yaml

@@ -122,12 +122,12 @@ jobs:
           BUNDLE_PUSH_OPT: "--tls-verify=false"
           CATALOG_PUSH_OPT: "--tls-verify=false"
 
-      - name: Run OLM Upgrade e2e AppWrapper creation test
+      - name: Run OLM Pre Upgrade test scenarios
         run: |
           export CODEFLARE_TEST_OUTPUT_DIR=${{ env.TEMP_DIR }}
           echo "CODEFLARE_TEST_OUTPUT_DIR=${CODEFLARE_TEST_OUTPUT_DIR}" >> $GITHUB_ENV
           set -euo pipefail
-          go test -timeout 30m -v ./test/upgrade -run TestMNISTCreateAppWrapper -json 2>&1 | tee ${CODEFLARE_TEST_OUTPUT_DIR}/gotest.log | gotestfmt
+          go test -timeout 30m -v ./test/upgrade -run 'TestMNISTCreateAppWrapper|TestMNISTRayClusterUp' -json 2>&1 | tee ${CODEFLARE_TEST_OUTPUT_DIR}/gotest.log | gotestfmt
 
       - name: Update Operator to the built version
         run: |
@@ -158,12 +158,12 @@ jobs:
           SUBSCRIPTION_NAME: "codeflare-operator"
           SUBSCRIPTION_NAMESPACE: "openshift-operators"
 
-      - name: Run OLM Upgrade e2e Appwrapper Job status test to monitor training
+      - name: Run OLM Post Upgrade test scenarios
         run: |
           export CODEFLARE_TEST_OUTPUT_DIR=${{ env.TEMP_DIR }}
           echo "CODEFLARE_TEST_OUTPUT_DIR=${CODEFLARE_TEST_OUTPUT_DIR}" >> $GITHUB_ENV
           set -euo pipefail
-          go test -timeout 30m -v ./test/upgrade -run TestMNISTCheckAppWrapperStatus -json 2>&1 | tee ${CODEFLARE_TEST_OUTPUT_DIR}/gotest.log | gotestfmt
+          go test -timeout 30m -v ./test/upgrade -run 'TestMNISTCheckAppWrapperStatus|TestMnistJobSubmit' -json 2>&1 | tee ${CODEFLARE_TEST_OUTPUT_DIR}/gotest.log | gotestfmt
 
       - name: Run e2e tests against built operator
         run: |

test/e2e/mnist_rayjob.py

@@ -0,0 +1,66 @@
+import sys
+import os
+
+from time import sleep
+
+from torchx.specs.api import AppState, is_terminal
+
+from codeflare_sdk.cluster.cluster import Cluster, ClusterConfiguration
+from codeflare_sdk.job.jobs import DDPJobDefinition
+
+namespace = sys.argv[1]
+ray_image = os.getenv('RAY_IMAGE')
+host = os.getenv('CLUSTER_HOSTNAME')
+
+ingress_options = {}
+if host is not None:
+    ingress_options = {
+        "ingresses": [
+            {
+                "ingressName": "ray-dashboard",
+                "port": 8265,
+                "pathType": "Prefix",
+                "path": "/",
+                "host": host,
+            },
+        ]
+    }
+
+# cluster = get_cluster('mnist',namespace)
+
+cluster = Cluster(ClusterConfiguration('mnist',namespace,image=ray_image,
+    ingress_options=ingress_options))
+
+print(cluster.details())
+
+jobdef = DDPJobDefinition(
+    name="mnist",
+    script="mnist.py",
+    scheduler_args={"requirements": "requirements.txt"},
+)
+job = jobdef.submit(cluster)
+
+done = False
+time = 0
+timeout = 300
+while not done:
+    status = job.status()
+    if is_terminal(status.state):
+        break
+    if not done:
+        print(status)
+        if timeout and time >= timeout:
+            raise TimeoutError(f"job has timed out after waiting {timeout}s")
+        sleep(5)
+        time += 5
+
+print(f"Job has completed: {status.state}")
+
+print(job.logs())
+
+cluster.down()
+
+if not status.state == AppState.SUCCEEDED:
+    exit(1)
+else:
+    exit(0)

test/e2e/start_ray_cluster.py

@@ -0,0 +1,51 @@
+import sys
+import os
+
+from time import sleep
+from torchx.specs.api import AppState, is_terminal
+
+from codeflare_sdk.cluster.cluster import Cluster, ClusterConfiguration
+
+namespace = sys.argv[1]
+ray_image = os.getenv('RAY_IMAGE')
+host = os.getenv('CLUSTER_HOSTNAME')
+
+ingress_options = {}
+if host is not None:
+    ingress_options = {
+        "ingresses": [
+            {
+                "ingressName": "ray-dashboard",
+                "port": 8265,
+                "pathType": "Prefix",
+                "path": "/",
+                "host": host,
+            },
+        ]
+    }
+
+cluster = Cluster(ClusterConfiguration(
+    name='mnist',
+    namespace=namespace,
+    num_workers=1,
+    head_cpus='500m',
+    head_memory=2,
+    min_cpus='500m',
+    max_cpus=1,
+    min_memory=1,
+    max_memory=2,
+    num_gpus=0,
+    instascale=False,
+    image=ray_image,
+    ingress_options=ingress_options,
+))
+
+cluster.up()
+
+cluster.status()
+
+cluster.wait_ready()
+
+cluster.status()
+
+cluster.details()