Adding Sagemaker pipeline sample (#272)

Issue #, if available:

Description of changes: Adding a Sagemaker pipeline example for creating and executing a pipeline run.

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

samples/pipeline/README.md

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+# Pipeline Sample
+
+This sample demonstrates how to submit a pipeline to Sagemaker for execution using your own JSON pipeline definition, using the AWS Controllers for Kubernetes (ACK) service controller for Amazon SageMaker.   
+
+## Prerequisites
+
+This sample assumes that you have completed the [common prerequisites](/samples/README.md).
+
+### Updating the Pipeline Specification
+
+In the `pipeline.yaml` file, modify the placeholder values with those associated with your account. 
+
+## Submitting your Pipeline Specification
+
+### Modify/Create a JSON pipeline definition
+
+Create the JSON pipeline definition using the JSON schema documented at https://aws-sagemaker-mlops.github.io/sagemaker-model-building-pipeline-definition-JSON-schema/. In this sample, you are provided a sample pipeline definition with one Training step.
+
+There are two ways to modify the *.spec.pipelineDefinition* key in the Kubernetes YAML spec. Choose one:
+
+Option 1: You can pass JSON pipeline definition inline as a JSON object. Example of this option is included in the `pipeline.yaml` file.
+
+Option 2: You can convert your JSON pipeline definition into String format. You may use online third-party tools to convert from JSON to String format.
+
+### Submit pipeline to Sagemaker and start an execution
+
+To submit your prepared pipeline specification, apply the specification to your Kubernetes cluster as such:
+```
+$ kubectl apply -f my-pipeline.yaml
+pipeline.sagemaker.services.k8s.aws/my-kubernetes-pipeline created
+```
+To start an execution run of the pipeline:
+```
+$ kubectl apply -f pipeline-execution.yaml
+pipelineexecution.sagemaker.services.k8s.aws/my-kubernetes-pipeline-execution created
+```
+
+### List pipelines and pipeline executions
+
+To list all pipelines created using the ACK controller use the following command:
+```
+$ kubectl get pipeline
+```
+If it is a pipeline executions it is endpointsconfigs.sagemaker.services.k8s.aws  
+```
+$ kubectl get pipelineexecution
+```
+
+### Describe a pipeline and pipeline execution
+
+To get more details about the pipeline once it's submitted, like checking the status, errors or parameters of the pipeline, use the following command:
+```
+$ kubectl describe pipeline my-kubernetes-pipeline
+```
+
+If it is a endpoint config it is endpointsconfigs.sagemaker.services.k8s.aws  
+```
+$ kubectl describe pipelineexecution my-kubernetes-pipeline-execution
+```
+
+### Delete a pipeline and a pipeline execution
+
+To delete the pipeline, use the following command:
+```
+$ kubectl delete pipeline my-kubernetes-pipeline
+```
+
+If it is a endpoint config it is endpointsconfigs.sagemaker.services.k8s.aws  
+```
+$ kubectl delete pipelineexecution my-kubernetes-pipeline-execution
+```

samples/pipeline/my-pipeline.json

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+{
+    "Version": "2020-12-01",
+    "Steps": [
+        {
+            "Name": "AbaloneTrain",
+            "Type": "Training",
+            "Arguments": {
+                "RoleArn": "<YOUR_SAGEMAKER_ROLE_ARN>",
+                "HyperParameters": {
+                    "max_depth": "5",
+                    "gamma": "4",
+                    "eta": "0.2",
+                    "min_child_weight": "6",
+                    "objective": "multi:softmax",
+                    "num_class": "10",
+                    "num_round": "10"
+                },
+                "AlgorithmSpecification": {
+                    "TrainingImage": "683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:1.7-1",
+                    "TrainingInputMode": "File"
+                },
+                "OutputDataConfig": {
+                    "S3OutputPath": "s3://<YOUR_BUCKET_NAME>/sagemaker/"
+                },
+                "ResourceConfig": {
+                    "InstanceCount": 1,
+                    "InstanceType": "ml.m4.xlarge",
+                    "VolumeSizeInGB": 5
+                },
+                "StoppingCondition": {
+                    "MaxRuntimeInSeconds": 86400
+                },
+                "InputDataConfig": [
+                    {
+                        "ChannelName": "train",
+                        "DataSource": {
+                            "S3DataSource": {
+                                "S3DataType": "S3Prefix",
+                                "S3Uri": "s3://<YOUR_BUCKET_NAME>/sagemaker/xgboost/train/",
+                                "S3DataDistributionType": "FullyReplicated"
+                            }
+                        },
+                        "ContentType": "text/libsvm"
+                    },
+                    {
+                        "ChannelName": "validation",
+                        "DataSource": {
+                            "S3DataSource": {
+                                "S3DataType": "S3Prefix",
+                                "S3Uri": "s3://<YOUR_BUCKET_NAME>/sagemaker/xgboost/validation/",
+                                "S3DataDistributionType": "FullyReplicated"
+                            }
+                        },
+                        "ContentType": "text/libsvm"
+                    }
+                ]
+            }
+        }
+    ]
+}

samples/pipeline/pipeline-execution.yaml

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+apiVersion: sagemaker.services.k8s.aws/v1alpha1
+kind: PipelineExecution
+metadata:
+  name: my-kubernetes-pipeline-execution
+spec:
+  parallelismConfiguration:
+    maxParallelExecutionSteps: 2
+  pipelineExecutionDescription: "My first pipeline execution via Amazon EKS cluster."
+  pipelineName: my-kubernetes-pipeline
+

samples/pipeline/pipeline.yaml

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+apiVersion: sagemaker.services.k8s.aws/v1alpha1
+kind: Pipeline
+metadata:
+  name: my-kubernetes-pipeline
+spec:
+  parallelismConfiguration:
+    maxParallelExecutionSteps: 2
+  pipelineName: my-kubernetes-pipeline
+  pipelineDefinition: |
+    {
+      "Version": "2020-12-01",
+      "Steps": [
+          {
+              "Name": "AbaloneTrain",
+              "Type": "Training",
+              "Arguments": {
+                  "RoleArn": "<YOUR_SAGEMAKER_ROLE_ARN>",
+                  "HyperParameters": {
+                      "max_depth": "5",
+                      "gamma": "4",
+                      "eta": "0.2",
+                      "min_child_weight": "6",
+                      "objective": "multi:softmax",
+                      "num_class": "10",
+                      "num_round": "30"
+                  },
+                  "AlgorithmSpecification": {
+                      "TrainingImage": "683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:1.7-1",
+                      "TrainingInputMode": "File"
+                  },
+                  "OutputDataConfig": {
+                      "S3OutputPath": "s3://<YOUR_S3_BUCKET>/sagemaker/"
+                  },
+                  "ResourceConfig": {
+                      "InstanceCount": 1,
+                      "InstanceType": "ml.m4.xlarge",
+                      "VolumeSizeInGB": 5
+                  },
+                  "StoppingCondition": {
+                      "MaxRuntimeInSeconds": 86400
+                  },
+                  "InputDataConfig": [
+                      {
+                          "ChannelName": "train",
+                          "DataSource": {
+                              "S3DataSource": {
+                                  "S3DataType": "S3Prefix",
+                                  "S3Uri": "s3://<YOUR_S3_BUCKET>/sagemaker/xgboost/train/",
+                                  "S3DataDistributionType": "FullyReplicated"
+                              }
+                          },
+                          "ContentType": "text/libsvm"
+                      },
+                      {
+                          "ChannelName": "validation",
+                          "DataSource": {
+                              "S3DataSource": {
+                                  "S3DataType": "S3Prefix",
+                                  "S3Uri": "s3://<YOUR_S3_BUCKET>/sagemaker/xgboost/validation/",
+                                  "S3DataDistributionType": "FullyReplicated"
+                              }
+                          },
+                          "ContentType": "text/libsvm"
+                      }
+                  ]
+              }
+          }
+      ]
+    }
+  pipelineDisplayName: my-kubernetes-pipeline
+  roleARN: <YOUR_SAGEMAKER_ROLE_ARN>