apiVersion: v1
kind: ConfigMap
metadata:
  labels:
    app: ml-pipeline
  name: ml-pipeline-config
data:
  config.json: |
    {
      "DBConfig": {
        "Host": "$(DBSERVICE_HOST)",
        "Port": "3306",
        "DriverName": "mysql",
        "DataSourceName": "",
        "DBName": "$(DBNAME_PIPELINE)",
        "GroupConcatMaxLen": "$(groupConcatMaxLen)"
      },
      "ObjectStoreConfig": {
        "Host": "s3.amazonaws.com",
        "Region": "$(awsRegion)",
        "Secure": true,
        "BucketName": "$(pipelineBucket)",
        "PipelineFolder": "$(pipelinePath)",
        "PipelinePath": "$(pipelinePath)"
      },
      "InitConnectionTimeout": "6m",
      "DefaultPipelineRunnerServiceAccount": "pipeline-runner"
    }
  sample_config.json: |
    [
      {
        "name": "[Demo] XGBoost - Training with Confusion Matrix",
        "description": "[source code](https://github.com/kubeflow/pipelines/blob/master/samples/core/xgboost_training_cm) [GCP Permission requirements](https://github.com/kubeflow/pipelines/blob/master/samples/core/xgboost_training_cm#requirements). A trainer that does end-to-end distributed training for XGBoost models.",
        "file": "/samples/core/xgboost_training_cm/xgboost_training_cm.py.yaml"
      },
      {
        "name": "[Demo] TFX - Taxi Tip Prediction Model Trainer",
        "description": "[source code](https://console.cloud.google.com/mlengine/notebooks/deploy-notebook?q=download_url%3Dhttps%253A%252F%252Fraw.githubusercontent.com%252Fkubeflow%252Fpipelines%252Fmaster%252Fsamples%252Fcore%252Fparameterized_tfx_oss%252Ftaxi_pipeline_notebook.ipynb) [GCP Permission requirements](https://github.com/kubeflow/pipelines/blob/master/samples/contrib/parameterized_tfx_oss#permission). Example pipeline that does classification with model analysis based on a public tax cab dataset.",
        "file": "/samples/core/parameterized_tfx_oss/parameterized_tfx_oss.py.yaml"
      },
      {
        "name": "[Tutorial] Data passing in python components",
        "description": "[source code](https://github.com/kubeflow/pipelines/tree/master/samples/tutorials/Data%20passing%20in%20python%20components) Shows how to pass data between python components.",
        "file": "/samples/tutorials/Data passing in python components/Data passing in python components - Files.py.yaml"
      },
      {
        "name": "[Tutorial] DSL - Control structures",
        "description": "[source code](https://github.com/kubeflow/pipelines/tree/master/samples/tutorials/DSL%20-%20Control%20structures) Shows how to use conditional execution and exit handlers. This pipeline will randomly fail to demonstrate that the exit handler gets executed even in case of failure.",
        "file": "/samples/tutorials/DSL - Control structures/DSL - Control structures.py.yaml"
      }
    ]