Update samples yaml (#102)

* Update samples yaml

* Remove configmap volumn part to keep the mini one clean

ray-operator/config/samples/config-map-ray-code.yaml

@@ -3,10 +3,8 @@ kind: ConfigMap
 metadata:
   name: ray-code
 data: 
-# note: /var  should be writable to write to /var/ray_nodes.txt
-  code.py: |
+  sample_code.py: |
     import ray
-    from ray import services
     from os import environ
     redis_pass = environ.get("REDIS_PASSWORD") 
     print("trying to connect to Ray!")
@@ -17,10 +15,10 @@ data:
     @ray.remote
     def f():
       time.sleep(0.01)
-      return ray.services.get_node_ip_address()
+      return ray._private.services.get_node_ip_address()
     values=set(ray.get([f.remote() for _ in range(1000)]))
     print("Ray Nodes: ",str(values))
-    file = open("/var/ray_nodes.txt","a")
+    file = open("/tmp/ray_nodes.txt","a")
     file.write("available nodes: %s\n" % str(values))
     file.close()
     end = time.time()

ray-operator/config/samples/ray-cluster.complete.yaml

@@ -6,7 +6,7 @@ metadata:
     # An unique identifier for the head node and workers of this cluster.
   name: raycluster-complete
 spec:
-  rayVersion: '1.0.1'
+  rayVersion: '1.8.0'
   ######################headGroupSpecs#################################
   # head group template and specs, (perhaps 'group' is not needed in the name)
   headGroupSpec:
@@ -42,12 +42,12 @@ spec:
       spec:
         containers:
         - name: ray-head
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # you can have any command and args here to run your code. 
           # the below command/args will be appended after the Ray start command and it args, and executed after Ray start.
           command: ["python3"]
           args:
-          - '/opt/code.py'
+          - '/opt/sample_code.py'
           env:
           - name: CPU_REQUEST
             valueFrom:
@@ -97,8 +97,8 @@ spec:
             name: ray-code
             # An array of keys from the ConfigMap to create as files
             items:
-            - key: code.py
-              path: code.py
+            - key: sample_code.py
+              path: sample_code.py
   workerGroupSpecs:
   # the pod replicas in this group typed worker
   - replicas: 1
@@ -134,10 +134,11 @@ spec:
         # the env var $RAY_IP is set by the operator if missing, with the value of the head service name
         - name: init-myservice
           image: busybox:1.28
+          # Change the cluster postfix if you don't have a default setting
           command: ['sh', '-c', "until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for myservice; sleep 2; done"]   
         containers:
         - name: machine-learning # must consist of lower case alphanumeric characters or '-', and must start and end with an alphanumeric character (e.g. 'my-name',  or '123-abc'
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # environment variables to set in the container.Optional.
           # Refer to https://kubernetes.io/docs/tasks/inject-data-application/define-environment-variable-container/
           env:

ray-operator/config/samples/ray-cluster.getting-started.yaml

@@ -6,7 +6,7 @@ metadata:
     # An unique identifier for the head node and workers of this cluster.
   name: raycluster-getting-started
 spec:
-  rayVersion: '0.8.6' # should match the Ray version in the image of the containers
+  rayVersion: '1.8.0' # should match the Ray version in the image of the containers
   ######################headGroupSpecs#################################
   # head group template and specs, (perhaps 'group' is not needed in the name)
   headGroupSpec:
@@ -42,12 +42,12 @@ spec:
       spec:
         containers:
         - name: ray-head
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # you can have any command and args here to run your code. 
           # the below command/args will be appended after the Ray start command and it args, and executed after Ray start.
           command: ["python"]
           args:
-          - '/opt/code.py'
+          - '/opt/sample_code.py'
           env:
           - name: MY_POD_IP
             valueFrom:
@@ -66,8 +66,8 @@ spec:
             name: ray-code-single
             # An array of keys from the ConfigMap to create as files
             items:
-            - key: code.py
-              path: code.py
+            - key: sample_code.py
+              path: sample_code.py
 ######################Ray code sample#################################
 # this is only an example code that is mounted into the container and executed to show the Ray cluster at work
 ---
@@ -76,9 +76,8 @@ kind: ConfigMap
 metadata:
   name: ray-code-single
 data: 
-  code.py: |
+  sample_code.py: |
     import ray
-    from ray import services
     from os import environ
     redis_pass = environ.get("REDIS_PASSWORD") 
     print("trying to connect to Ray!")
@@ -89,11 +88,11 @@ data:
     @ray.remote
     def f():
       time.sleep(0.01)
-      return ray.services.get_node_ip_address()
+      return ray._private.services.get_node_ip_address()
     values=set(ray.get([f.remote() for _ in range(1000)]))
     print("Ray Nodes: ",str(values))
-    f = open("/var/ray_nodes.txt","a")
-    f.write("available nodes: %s\n" % str(values))
-    f.close()
+    file = open("/tmp/ray_nodes.txt","a")
+    file.write("available nodes: %s\n" % str(values))
+    file.close()
     end = time.time()
     print("Execution time = ",end - start)

ray-operator/config/samples/ray-cluster.heterogeneous.yaml

@@ -6,7 +6,7 @@ metadata:
     # An unique identifier for the head node and workers of this cluster.
   name: raycluster-heterogeneous
 spec:
-  rayVersion: '1.0.1'
+  rayVersion: '1.8.0'
   ######################headGroupSpecs#################################
   # head group template and specs, (perhaps 'group' is not needed in the name)
   headGroupSpec:
@@ -40,15 +40,14 @@ spec:
         annotations:
           key: value
       spec:
-#        initContainers: # to avoid worker crashing before head service is created
         containers:
         - name: ray-head
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # you can have any command and args here to run your code. 
           # the below command/args will be appended after the Ray start command and it args, and executed after Ray start.
           command: ["sleep"]
           args:
-          - 'infinity'
+          - "infinity"
           env:
           - name: MY_POD_IP
             valueFrom:
@@ -72,8 +71,8 @@ spec:
             name: ray-code
             # An array of keys from the ConfigMap to create as files
             items:
-            - key: code.py
-              path: code.py
+            - key: sample_code.py
+              path: sample_code.py
   workerGroupSpecs:
   # the pod replicas in this group typed worker
   - replicas: 3
@@ -107,10 +106,11 @@ spec:
         # the env var $RAY_IP is set by the operator if missing, with the value of the head service name
         - name: init-myservice
           image: busybox:1.28
+          # Change the cluster postfix if you don't have a default setting
           command: ['sh', '-c', "until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for myservice; sleep 2; done"]   
         containers:
         - name: machine-learning # must consist of lower case alphanumeric characters or '-', and must start and end with an alphanumeric character (e.g. 'my-name',  or '123-abc'
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # environment variables to set in the container.Optional.
           # Refer to https://kubernetes.io/docs/tasks/inject-data-application/define-environment-variable-container/
           env:
@@ -178,10 +178,11 @@ spec:
         initContainers:
         - name: init-myservice
           image: busybox:1.28
+          # Change the cluster postfix if you don't have a default setting
           command: ['sh', '-c', "until nslookup raycluster-heterogeneous-head-svc.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for myservice; sleep 2; done"]
         containers:
         - name: machine-learning # must consist of lower case alphanumeric characters or '-', and must start and end with an alphanumeric character (e.g. 'my-name',  or '123-abc'
-          image: rayproject/autoscaler
+          image: rayproject/ray:1.8.0
           # environment variables to set in the container.Optional.
           # Refer to https://kubernetes.io/docs/tasks/inject-data-application/define-environment-variable-container/
           env:

ray-operator/config/samples/ray-cluster.mini.yaml

@@ -6,7 +6,7 @@ metadata:
     # An unique identifier for the head node and workers of this cluster.
   name: raycluster-mini
 spec:
-  rayVersion: '0.8.6' # should match the Ray version in the image of the containers
+  rayVersion: '1.8.0' # should match the Ray version in the image of the containers
   ######################headGroupSpecs#################################
   # head group template and specs, (perhaps 'group' is not needed in the name)
   headGroupSpec:
@@ -44,14 +44,14 @@ spec:
       spec:
         containers:
         - name: ray-head
-          image: rayproject/ray:1.6.0
+          image: rayproject/ray:1.8.0
           #image: rayproject/ray:nightly
           #image: bonsaidev.azurecr.io/bonsai/lazer-0-9-0-cpu:dev
           # you can have any command and args here to run your code. 
           # the below command/args will be appended after the Ray start command and it args, and executed after Ray start.
           command: ["sleep"]
           args:
-          - '10000'
+          - "infinity"
           env:
           - name: MY_POD_IP
             valueFrom:
@@ -64,6 +64,3 @@ spec:
             name: dashboard
           - containerPort: 10001
             name: client
-
-
-