Added load-balancer option for clone juyterlab function

Author: sufianNetApp

netapp_dataops_k8s/README.md

@@ -129,14 +129,15 @@ The following options/arguments are optional:
     -n, --namespace=                Kubernetes namespace that source workspace is located in. If not specified, namespace "default" will be used.
     -p, --cpu=                      Number of CPUs to reserve for new JupyterLab workspace. Format: '0.5', '1', etc. If not specified, no CPUs will be reserved.
     -s, --source-snapshot-name=     Name of Kubernetes VolumeSnapshot to use as source for clone. Either -s/--source-snapshot-name or -j/--source-workspace-name must be specified.
+    -b, --load-balancer     Option to choose a LoadBalancer service instead of using NodePort service. If not specified, NodePort service will be utilized.
 ```
 
 ##### Example Usage
 
-Near-instantaneously create a new JupyterLab workspace, named 'project1-experiment3', that is an exact copy of the current contents of existing JupyterLab workspace 'project1' in namespace 'default'. Allocate 2 NVIDIA GPUs to the new workspace.
+Near-instantaneously create a new JupyterLab workspace, named 'project1-experiment3', that is an exact copy of the current contents of existing JupyterLab workspace 'project1' in namespace 'default'. Allocate 2 NVIDIA GPUs to the new workspace and use LoadBalancer service instead of NodePort.
 
 ```sh
-netapp_dataops_k8s_cli.py clone jupyterlab --new-workspace-name=project1-experiment3 --source-workspace-name=project1 --nvidia-gpu=2
+netapp_dataops_k8s_cli.py clone jupyterlab --new-workspace-name=project1-experiment3 --source-workspace-name=project1 --nvidia-gpu=2 --load-balancer
 Creating new JupyterLab workspace 'project1-experiment3' from source workspace 'project1' in namespace 'default'...
 
 Creating new VolumeSnapshot 'ntap-dsutil.for-clone.20210315185504' for source PVC 'ntap-dsutil-jupyterlab-project1' in namespace 'default' to use as source for clone...
@@ -161,7 +162,7 @@ Waiting for Deployment 'ntap-dsutil-jupyterlab-project1-experiment3' to reach Re
 Deployment successfully created.
 
 Workspace successfully created.
-To access workspace, navigate to http://10.61.188.112:30993
+To access workspace, navigate to http://10.61.188.110
 JupyterLab workspace successfully cloned.
 ```
 
@@ -832,6 +833,7 @@ def clone_jupyter_lab(
     new_workspace_name: str,                          # Name of new workspace (name to be applied to new JupyterLab workspace) (required).
     source_workspace_name: str,                       # Name of JupyterLab workspace to use as source for clone. (required).
     source_snapshot_name: str = None,                 # Name of Kubernetes VolumeSnapshot to use as source for clone.
+    load_balancer_service: bool = False,              # Option to use a LoadBalancer instead of using NodePort service. If not specified, NodePort service will be utilized.
     new_workspace_password: str = None,               # Workspace password (this password will be required in order to access the workspace). If not specified, you will be prompted to enter a password via the console.
     volume_snapshot_class: str = "csi-snapclass",     # Kubernetes VolumeSnapshotClass to use when creating clone. If not specified, "csi-snapclass" will be used. Note: VolumeSnapshotClass must be configured to use Trident.
     namespace: str = "default",                      # Kubernetes namespace that source workspace is located in. If not specified, namespace "default" will be used.

netapp_dataops_k8s/netapp_dataops/k8s.py

@@ -331,7 +331,7 @@ def _wait_for_jupyter_lab_deployment_ready(workspaceName: str, namespace: str =
 
 
 def clone_jupyter_lab(new_workspace_name: str, source_workspace_name: str, source_snapshot_name: str = None,
-                      new_workspace_password: str = None, volume_snapshot_class: str = "csi-snapclass",
+                      load_balancer_service: bool = False, new_workspace_password: str = None, volume_snapshot_class: str = "csi-snapclass",
                       namespace: str = "default", request_cpu: str = None, request_memory: str = None,
                       request_nvidia_gpu: str = None, print_output: bool = False):
     # Determine source PVC details
@@ -374,7 +374,7 @@ def clone_jupyter_lab(new_workspace_name: str, source_workspace_name: str, sourc
     print()
     create_jupyter_lab(workspace_name=new_workspace_name, workspace_size=workspaceSize, namespace=namespace,
                        workspace_password=new_workspace_password, workspace_image=sourceWorkspaceImage, request_cpu=request_cpu,
-                       request_memory=request_memory, request_nvidia_gpu=request_nvidia_gpu, print_output=print_output,
+                       load_balancer_service=load_balancer_service, request_memory=request_memory, request_nvidia_gpu=request_nvidia_gpu, print_output=print_output,
                        pvc_already_exists=True, labels=labels)
 
     if print_output:

netapp_dataops_k8s/netapp_dataops/netapp_dataops_k8s_cli.py

@@ -73,10 +73,12 @@
 \t-n, --namespace=\t\tKubernetes namespace that source workspace is located in. If not specified, namespace "default" will be used.
 \t-p, --cpu=\t\t\tNumber of CPUs to reserve for new JupyterLab workspace. Format: '0.5', '1', etc. If not specified, no CPUs will be reserved.
 \t-s, --source-snapshot-name=\tName of Kubernetes VolumeSnapshot to use as source for clone. Either -s/--source-snapshot-name or -j/--source-workspace-name must be specified.
+\t-b, --source-snapshot-name=\tName of Kubernetes VolumeSnapshot to use as source for clone. Either -s/--source-snapshot-name or -j/--source-workspace-name must be specified.
+\t-b, --load-balancer\tOption to use a LoadBalancer instead of using NodePort service. If not specified, NodePort service will be utilized.
 
 Examples:
-\tnetapp_dataops_k8s_cli.py clone jupyterlab --new-workspace-name=project1-experiment1 --source-workspace-name=project1 --nvidia-gpu=1
-\tnetapp_dataops_k8s_cli.py clone jupyterlab -w project2-mike -s project2-snap1 -n team1 -g 1 -p 0.5 -m 1Gi
+\tnetapp_dataops_k8s_cli.py clone jupyterlab --new-workspace-name=project1-experiment1 --source-workspace-name=project1 --nvidia-gpu=1 
+\tnetapp_dataops_k8s_cli.py clone jupyterlab -w project2-mike -s project2-snap1 -n team1 -g 1 -p 0.5 -m 1Gi -b
 '''
 helpTextCloneVolume = '''
 Command: clone volume
@@ -438,13 +440,14 @@ def getTarget(args: list) -> str:
             requestNvidiaGpu = None
             requestMemory = None
             requestCpu = None
+            load_balancer_service= False
 
             # Get command line options
             try:
-                opts, args = getopt.getopt(sys.argv[3:], "hw:c:n:s:j:g:m:p:",
+                opts, args = getopt.getopt(sys.argv[3:], "hw:c:n:s:j:g:m:p:b",
                                            ["help", "new-workspace-name=", "volume-snapshot-class=", "namespace=",
                                             "source-snapshot-name=", "source-workspace-name=", "nvidia-gpu=", "memory=",
-                                            "cpu="])
+                                            "cpu=", "load-balancer"])
             except:
                 handleInvalidCommand(helpText=helpTextCloneJupyterLab, invalidOptArg=True)
 
@@ -469,6 +472,8 @@ def getTarget(args: list) -> str:
                     requestMemory = arg
                 elif opt in ("-p", "--cpu"):
                     requestCpu = arg
+                elif opt in ("-b", "--load-balancer"):
+                    load_balancer_service = True
 
             # Check for required options
             if not newWorkspaceName or (not sourceSnapshotName and not sourceWorkspaceName):
@@ -480,7 +485,7 @@ def getTarget(args: list) -> str:
 
             # Clone volume
             try:
-                clone_jupyter_lab(new_workspace_name=newWorkspaceName, source_workspace_name=sourceWorkspaceName,
+                clone_jupyter_lab(new_workspace_name=newWorkspaceName, source_workspace_name=sourceWorkspaceName, load_balancer_service=load_balancer_service,
                                   source_snapshot_name=sourceSnapshotName, volume_snapshot_class=volumeSnapshotClass,
                                   namespace=namespace, request_cpu=requestCpu, request_memory=requestMemory,
                                   request_nvidia_gpu=requestNvidiaGpu, print_output=True)