Minor bug Fixes

databricks_template_schema.json

@@ -132,17 +132,82 @@
       "type": "string",
       "description": "\nWhether to use the Model Registry with Unity Catalog",
       "default": "no",
-      "enum": ["yes", "no"],
+      "enum": ["yes", "no"]
+    },
+    "input_staging_catalog_name": {
+      "order": 12,
+      "type": "string",
+      "description": "\nName of the catalog in Unity Catalog that will host the staging UC resources. \nThis catalog must already exist and service principals must have access to it.",
+      "default": "staging",
       "skip_prompt_if": {
-        "properties": {
-          "input_setup_cicd_and_project": {
-            "const": "CICD_Only"
+        "anyOf": [
+          {
+            "properties": {
+              "input_include_models_in_unity_catalog": {
+                "const": "no"
+              }
+            }
+          },
+          {
+            "properties": {
+              "input_setup_cicd_and_project": {
+                "const": "Project_Only"
+              }
+            }
           }
-        }
+        ]
+      }
+    },
+    "input_prod_catalog_name": {
+      "order": 13,
+      "type": "string",
+      "description": "\nName of the Prod Unity Catalog",
+      "default": "prod",
+      "skip_prompt_if": {
+        "anyOf": [
+          {
+            "properties": {
+              "input_include_models_in_unity_catalog": {
+                "const": "no"
+              }
+            }
+          },
+          {
+            "properties": {
+              "input_setup_cicd_and_project": {
+                "const": "Project_Only"
+              }
+            }
+          }
+        ]
+      }
+    },
+    "input_test_catalog_name": {
+      "order": 14,
+      "type": "string",
+      "description": "\nName of the catalog in Unity Catalog that will be used for integration tests",
+      "default": "test",
+      "skip_prompt_if": {
+        "anyOf": [
+          {
+            "properties": {
+              "input_include_models_in_unity_catalog": {
+                "const": "no"
+              }
+            }
+          },
+          {
+            "properties": {
+              "input_setup_cicd_and_project": {
+                "const": "Project_Only"
+              }
+            }
+          }
+        ]
       }
     },
     "input_schema_name": {
-      "order": 12,
+      "order": 15,
       "type": "string",
       "description": "\nName of schema to use when registering a model in Unity Catalog.\nThis schema must already exist and service principals must have access.\nWe recommend using the project name.\nDefault",
       "default": "{{if (eq .input_include_models_in_unity_catalog `no`)}}schema{{else}}{{ .input_project_name }}{{end}}",
@@ -168,7 +233,7 @@
       }
     },
     "input_unity_catalog_read_user_group": {
-      "order": 13,
+      "order": 16,
       "type": "string",
       "default": "account users",
       "description": "\nUser group name to give EXECUTE privileges to models in Unity Catalog (UC).\nIt must exist in UC with access granted to the staging and prod workspaces.\nDefault",
@@ -192,7 +257,7 @@
       }
     },
     "input_include_feature_store": {
-      "order": 14,
+      "order": 17,
       "type": "string",
       "description": "\nWhether to include Feature Store",
       "default": "no",
@@ -206,7 +271,7 @@
       }
     },
     "input_include_mlflow_recipes": {
-      "order": 15,
+      "order": 18,
       "type": "string",
       "description": "\nWhether to include MLflow Recipes",
       "default": "no",

template/{{.input_root_dir}}/.azure/devops-pipelines/deploy-cicd.yml.tmpl

@@ -59,7 +59,7 @@ jobs:
 
     # Update databricks.yml
     - script: |
-        echo -e "  staging:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}\n\n  prod:\n    workspace:\n      host: {{template `databricks_prod_workspace_host` .}}\n\n  test:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}" >> "$(PROJECT_NAME_ALPHA)/databricks.yml"
+        echo -e "  {{ .input_staging_catalog_name }}:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}\n\n  {{ .input_prod_catalog_name }}:\n    workspace:\n      host: {{template `databricks_prod_workspace_host` .}}\n\n  {{ .input_test_catalog_name }}:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}" >> "$(PROJECT_NAME_ALPHA)/databricks.yml"
       displayName: 'Update databricks.yml'
 
     # Initialize CICD Bundle

template/{{.input_root_dir}}/.github/workflows/deploy-cicd.yml.tmpl

@@ -23,6 +23,10 @@ jobs:
   cicd:
     runs-on: ubuntu-latest
     steps:
+      - name: Get current timestamp
+        id: timestamp
+        run: |
+          echo "timestamp=$(date +'%s')" >> "$GITHUB_ENV"
       - uses: actions/checkout@v3
         with:
           ref: {{`${{ github.event.pull_request.head.sha || github.sha }}`}}
@@ -49,7 +53,7 @@ jobs:
       - name: Update databricks.yml
         id: update
         run: |
-          echo -e "  staging:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}\n\n  prod:\n    workspace:\n      host: {{template `databricks_prod_workspace_host` .}}\n\n  test:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}" >> "$PROJECT_NAME_ALPHA/databricks.yml"
+          echo -e "  {{ .input_staging_catalog_name }}:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}\n\n  {{ .input_prod_catalog_name }}:\n    workspace:\n      host: {{template `databricks_prod_workspace_host` .}}\n\n  {{ .input_test_catalog_name }}:\n    workspace:\n      host: {{template `databricks_staging_workspace_host` .}}" >> "$PROJECT_NAME_ALPHA/databricks.yml"
       - name: Initialize Bundle
         id: initialize
         run: |
@@ -61,13 +65,14 @@ jobs:
         run: |
           git config --global user.name "Deploy CICD Bot"
           git config --global user.email "[email protected]"
-          git checkout -b add-cicd-for-{{`${{ github.event.inputs.project_name }}`}}
+          git checkout -b add-cicd-for-{{`${{ github.event.inputs.project_name }}`}}-{{`${{ env.timestamp }}`}}
           git add .github "$PROJECT_NAME_ALPHA/databricks.yml"
           git commit -m "Add CICD for {{`${{ github.event.inputs.project_name }}`}}"
-          git push origin add-cicd-for-{{`${{ github.event.inputs.project_name }}`}}
+          git push origin add-cicd-for-{{`${{ github.event.inputs.project_name }}`}}-{{`${{ env.timestamp }}`}}
+
       - name: Create Pull Request
         id: pr
         env:
           GITHUB_TOKEN: {{`${{ github.token }}`}}
         run: |
-          gh pr create --base {{ .input_default_branch }} --head add-cicd-for-{{`${{ github.event.inputs.project_name }}`}} --title "Deploy CICD for {{`${{ github.event.inputs.project_name }}`}}" --body "This PR was generated by the Deploy CICD workflow."
+          gh pr create --base {{ .input_default_branch }} --head add-cicd-for-{{`${{ github.event.inputs.project_name }}`}}-{{`${{ env.timestamp }}`}} --title "Deploy CICD for {{`${{ github.event.inputs.project_name }}`}}" --body "This PR was generated by the Deploy CICD workflow." --reviewer {{`${{ github.actor }}`}}

template/{{.input_root_dir}}/.github/workflows/{{.input_project_name}}-bundle-cd-prod.yml.tmpl

@@ -33,8 +33,8 @@ jobs:
       - name: Validate Bundle For Prod
         id: validate
         run: |
-          databricks bundle validate -t prod
+          databricks bundle validate -t {{ .input_prod_catalog_name }}
       - name: Deploy Bundle to Prod
         id: deploy
         run: |
-          databricks bundle deploy -t prod
+          databricks bundle deploy -t {{ .input_prod_catalog_name }}

template/{{.input_root_dir}}/.github/workflows/{{.input_project_name}}-bundle-cd-staging.yml.tmpl

@@ -33,8 +33,8 @@ jobs:
       - name: Validate Bundle For Staging
         id: validate
         run: |
-          databricks bundle validate -t staging
+          databricks bundle validate -t {{ .input_staging_catalog_name }}
       - name: Deploy Bundle to Staging
         id: deploy
         run: |
-          databricks bundle deploy -t staging
+          databricks bundle deploy -t {{ .input_staging_catalog_name }}

template/{{.input_root_dir}}/.github/workflows/{{.input_project_name}}-bundle-ci.yml.tmpl

@@ -46,7 +46,7 @@ jobs:
           ARM_CLIENT_SECRET: {{`${{ env.STAGING_ARM_CLIENT_SECRET }}`}}
           {{- end }}
         run: |
-          databricks bundle validate -t staging > ../validate_output.txt
+          databricks bundle validate -t {{ .input_staging_catalog_name }} > ../validate_output.txt
       - name: Create Comment with Bundle Configuration
         uses: actions/github-script@v6
         id: comment
@@ -90,7 +90,7 @@ jobs:
           ARM_CLIENT_SECRET: {{`${{ env.PROD_ARM_CLIENT_SECRET }}`}}
           {{- end }}
         run: |
-          databricks bundle validate -t prod > ../validate_output.txt
+          databricks bundle validate -t {{ .input_prod_catalog_name }} > ../validate_output.txt
       - name: Create Comment with Bundle Configuration
         uses: actions/github-script@v6
         id: comment

template/{{.input_root_dir}}/.github/workflows/{{.input_project_name}}-run-tests.yml.tmpl

@@ -4,6 +4,7 @@ on:
   pull_request:
     paths:
       - '{{template `project_name_alphanumeric_underscore` .}}/**'
+      - '.github/workflows/{{ .input_project_name }}-run-tests.yml'
 
 defaults:
   run:
@@ -54,18 +55,18 @@ jobs:
       - name: Validate Bundle For Test Deployment Target in Staging Workspace
         id: validate
         run: |
-          databricks bundle validate -t test
+          databricks bundle validate -t {{ .input_test_catalog_name }}
       - name: Deploy Bundle to Test Deployment Target in Staging Workspace
         id: deploy
         run: |
-          databricks bundle deploy -t test
+          databricks bundle deploy -t {{ .input_test_catalog_name }}
       {{- if (eq .input_include_feature_store `yes`) }}
       - name: Run Feature Engineering Workflow for Test Deployment Target in Staging Workspace
         id: feature_engineering
         run: |
-          databricks bundle run write_feature_table_job -t test
+          databricks bundle run write_feature_table_job -t {{ .input_test_catalog_name }}
       {{- end }}
       - name: Run Training Workflow for Test Deployment Target in Staging Workspace
         id: training
         run: |
-          databricks bundle run model_training_job -t test
+          databricks bundle run model_training_job -t {{ .input_test_catalog_name }}

template/{{.input_root_dir}}/README.md.tmpl

@@ -178,8 +178,9 @@ This stack comes with a workflow to set up CI/CD for projects that can be found
 {{ end }}
 
 To set up CI/CD for projects that were created through MLOps Stacks with the `Project_Only` parameter, 
-run the abovementioned workflow, specifying the `project_name` as a parameter. This workflow assumes that 
-all steps in the [MLOps Setup Guide](./docs/mlops-setup.md) have been completed. For example, for the monorepo case:
+run the above mentioned workflow, specifying the `project_name` as a parameter. This workflow assumes that 
+all steps in the [MLOps Setup Guide](./docs/mlops-setup.md#Steps) have been completed. For example, for the monorepo case:
+
 1. Setup your repository by initializing MLOps Stacks via Databricks CLI with the `CICD_and_Project` or `CICD_Only` parameter.
 2. Follow the [MLOps Setup Guide](./docs/mlops-setup.md) to setup authentication and get the repo ready for CI/CD.
 3. Create a new project by initializing MLOps Stacks again but this time with the `Project_Only` parameter.

template/{{.input_root_dir}}/cicd/databricks_template_schema.json

@@ -45,6 +45,24 @@
       "order": 9,
       "description": "Use Feature Store (yes) or not (no)",
       "type": "string"
+    },
+    "input_test_catalog_name": {
+      "order": 10,
+      "type": "string",
+      "description": "\nName of the Test Unity Catalog",
+      "default": "test"
+    },
+    "input_staging_catalog_name": {
+      "order": 13,
+      "type": "string",
+      "description": "\nName of the Staging Unity Catalog",
+      "default": "staging"
+    },
+    "input_prod_catalog_name": {
+      "order": 14,
+      "type": "string",
+      "description": "\nName of the Prod Unity Catalog",
+      "default": "prod"
     }
   },
   "success_message" : "\n✨ CICD files for your MLOps Project '{{.input_project_name}}' have been initialized!"

template/{{.input_root_dir}}/cicd_params.json.tmpl

@@ -5,5 +5,8 @@
   "input_default_branch": "{{ .input_default_branch }}",
   "input_release_branch": "{{ .input_release_branch }}",
   "cloud_specific_node_type_id": "{{template `cli_version` .}}",
-  "input_cli_version": "{{template `cli_version` .}}"
+  "input_cli_version": "{{template `cli_version` .}}",
+  "test_catalog_name": "{{ .input_test_catalog_name }}",
+  "staging_catalog_name": "{{ .input_staging_catalog_name }}",
+  "prod_catalog_name": "{{ .input_prod_catalog_name }}"
 }

template/{{.input_root_dir}}/docs/ml-pull-request.md.tmpl

@@ -78,14 +78,17 @@ After merging your pull request, subsequent runs of the model training and batch
 jobs in staging and production will automatically use your updated ML code.
 {{- end }}
 
-You can track the state of the ML pipelines for the current project from the MLflow registered model UI. Links:
+You can track the state of the ML pipelines for the current project from the MLflow registered model UI. 
+{{ if or (eq .input_setup_cicd_and_project `CICD_and_Project`) (eq .input_cicd_platform `Project_Only`) }}
+Links:
 {{ if (eq .input_include_models_in_unity_catalog `no`) }}
 * [Staging workspace registered model]({{template `databricks_staging_workspace_host` .}}/ml/models/staging-{{template `model_name` .}})
 * [Prod workspace registered model]({{template `databricks_prod_workspace_host` .}}/ml/models/prod-{{template `model_name` .}})
 {{- else -}} 
 * [Staging model in UC]({{template `databricks_staging_workspace_host` .}}/explore/data/models/staging/{{.input_project_name}}/{{template `model_name` .}})
 * [Prod model in UC]({{template `databricks_prod_workspace_host` .}}/explore/data/models/prod/{{.input_project_name}}/{{template `model_name` .}})
 {{end}}. 
+{{end}}
 
 In both the staging and prod workspaces, the MLflow registered model contains links to:
 * The model versions produced through automated retraining

template/{{.input_root_dir}}/docs/mlops-setup.md.tmpl

@@ -84,7 +84,7 @@ If the created project uses **Unity Catalog**, we expect a catalog to exist with
 For example, if the deployment target is dev, we expect a catalog named dev to exist in the workspace. 
 If you want to use different catalog names, please update the target names declared in the 
 {{- if (eq .input_setup_cicd_and_project `CICD_and_Project`)}}[{{ .input_project_name }}/databricks.yml](../{{template `project_name_alphanumeric_underscore` .}}/databricks.yml) 
-{{- else }} `databricks.yml` {{ end }} file. 
+{{- else }} `databricks.yml` {{ end }} file.
 If changing the staging, prod, or test deployment targets, you'll also need to update the workflows located in the .github/workflows directory.
 
 The SP must have proper permission in each respective environment and the catalog for the environments.
@@ -113,8 +113,10 @@ to add the secrets to GitHub:
 - `STAGING_WORKSPACE_TOKEN` : service principal token for staging workspace
 - `PROD_WORKSPACE_TOKEN` : service principal token for prod workspace
 - `WORKFLOW_TOKEN` : [Github token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens#creating-a-personal-access-token-classic) with workflow permissions. This secret is needed for the Deploy CI/CD Workflow.
-Be sure to update the [Workflow Permissions](https://docs.github.com/en/actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token) section under Repo Settings > Actions > General to allow `Read and write permissions`,
-and to allow workflows to be able to open pull requests (PRs).
+
+Next, be sure to update the [Workflow Permissions](https://docs.github.com/en/actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token) section under Repo Settings > Actions > General:
+- Allow `Read and write permissions`,
+- Allow workflows to be able to open pull requests (PRs).
   {{ end }}
 
 {{ if and (eq .input_cicd_platform `github_actions`) (eq .input_cloud `azure`) }}
@@ -138,6 +140,9 @@ After setting up authentication for CI/CD, you can now set up CI/CD workflows. W
 This workflow is manually triggered with `project_name` as parameter. This workflow will need to be triggered for each project to set up its set of CI/CD workflows that can be used to deploy ML resources and run ML jobs in the staging and prod workspaces. 
 These workflows will be defined under `.github/workflows`.
 
+If you want to deploy CI/CD for an initialized project (`Project-Only` MLOps Stacks initialization), you can manually run the `deploy-cicd.yml` workflow from the [Github Actions UI](https://docs.github.com/en/actions/using-workflows/manually-running-a-workflow?tool=webui) once the project code has been added to your main repo. 
+The workflow will create a pull request with all the changes against your {{ .input_default_branch }} branch. Review and approve it to commit the files to deploy CI/CD for the project. 
+
 {{ else if (eq .input_cicd_platform `azure_devops`) -}}
 ## Configure CI/CD - Azure DevOps
 

template/{{.input_root_dir}}/{{template `project_name_alphanumeric_underscore` .}}/README.md.tmpl

@@ -237,10 +237,20 @@ i.e. for each environment
 You can run unit tests for your ML code via `pytest tests`.
 
 {{ end }}
+
 ## Next Steps
-When you're satisfied with initial ML experimentation (e.g. validated that a model with reasonable performance can be
-trained on your dataset) and ready to deploy production training/inference
-pipelines, ask your ops team to set up CI/CD for the current ML project if they haven't already. CI/CD can be set up as part of the 
-MLOps Stacks initialization even if it was skipped in this case, or this project can be added to a repo setup with CI/CD already,
-following the directions under "Setting up CI/CD" in the repo root directory README.
+
+When you're satisfied with initial ML experimentation (e.g. validated that a model with reasonable performance can be trained on your dataset) and ready to deploy production training/inference pipelines, ask your ops team to set up CI/CD for the current ML project if they haven't already. CI/CD can be set up as part of the
+
+MLOps Stacks initialization even if it was skipped in this case, or this project can be added to a repo setup with CI/CD already, following the directions under "Setting up CI/CD" in the repo root directory README.
+
+To add CI/CD to this repo:
+ 1. Run `databricks bundle init mlops-stacks` via the Databricks CLI
+ 2. Select the option to only initialize `CICD_Only`
+ 3. Provide the root directory of this project and answer the subsequent prompts
+
+If you already have CI/CD setup in a separate repo:
+1. Create a new folder in your root CI/CD repo
+1. Copy the contents of your current project folder into the new folder
+
 More details can be found on the homepage [MLOps Stacks README](https://github.com/databricks/mlops-stacks/blob/main/README.md).

template/{{.input_root_dir}}/{{template `project_name_alphanumeric_underscore` .}}/databricks.yml.tmpl

@@ -27,15 +27,15 @@ targets:
 
 {{ if (eq .input_setup_cicd_and_project `CICD_and_Project`)}}
 
-  staging:
+  {{ .input_staging_catalog_name }}:
     workspace:
       host: {{template `databricks_staging_workspace_host` .}}
 
-  prod:
+  {{ .input_prod_catalog_name }}:
     workspace:
       host: {{template `databricks_prod_workspace_host` .}}
 
-  test:
+  {{ .input_test_catalog_name }}:
     workspace:
       host: {{template `databricks_staging_workspace_host` .}}
 {{ end }}