docs: Add Databricks integration documentation

site/guide/_sidebar.yaml

@@ -49,7 +49,15 @@ website:
                 - guide/integrations/link-external-models.qmd
                 - guide/mcp/connect-ai-assistants-via-mcp.qmd
                 - guide/integrations/configure-analytics-exports.qmd
-                - guide/integrations/integrations-examples.qmd
+                - file: guide/integrations/integrations-examples.qmd
+                  contents:
+                    - guide/integrations/integrations-examples/create-jira-ticket.qmd
+                    - guide/integrations/integrations-examples/create-servicenow-incident.qmd
+                    - guide/integrations/integrations-examples/synchronize-aws-bedrock.qmd
+                    - guide/integrations/integrations-examples/synchronize-aws-sagemaker.qmd
+                    - guide/integrations/integrations-examples/synchronize-with-databricks.qmd
+                    - guide/integrations/integrations-examples/synchronize-gitlab.qmd
+                    - guide/integrations/integrations-examples/use-webhooks-with-workflows.qmd
         - text: "---"
         - section: "Workflows"
           contents:

site/guide/integrations/configure-connections.qmd

@@ -16,7 +16,7 @@ Each connection enables you to authenticate and keep events flowing between plat
 
 - [x] {{< var link.login >}}
 - [x] You can manage workspace settings.[^1]
-- [x] The integration’s required secrets already exist in integration secrets.[^2]
+- [x] The integration's required secrets already exist in integration secrets.[^2]
 - [x] You coordinated with the external system owner to obtain the required credentials and configuration details for the connection.
 
 :::
@@ -121,6 +121,21 @@ Required configuration details:
 **[personal access token]{.smallcaps}**
 : Select a secret containing your GitLab Personal Access Token with `api` or `read_api` scope.
 
+### Databricks
+
+A unified analytics platform for data engineering, data science, and machine learning, including Unity Catalog for centralized metadata management.
+
+Required configuration details:
+
+**[databricks host]{.smallcaps}**
+: The URL of your Databricks workspace, such as `https://yourcompany.cloud.databricks.com`.
+
+**[client id]{.smallcaps}**
+: The ID of your SQL Warehouse (found in Databricks SQL Warehouses settings).
+
+**[client secret]{.smallcaps}**
+: The secret that stores your Databricks personal access token (PAT).
+
 ### Custom
 
 A user-defined connection to a third-party system that implements the {{< var vm.product >}} reference API.[^4] 

site/guide/integrations/integrations-examples/create-jira-ticket.qmd

@@ -0,0 +1,85 @@
+---
+# Copyright © 2023-2026 ValidMind Inc. All rights reserved.
+# Refer to the LICENSE file in the root of this repository for details.
+# SPDX-License-Identifier: AGPL-3.0 AND ValidMind Commercial
+title: "Create a Jira ticket"
+date: last-modified
+---
+
+Create a Jira ticket when model validation requires attention using an HTTP request workflow step.
+
+::: {.attn}
+
+## Prerequisites
+
+- [x] {{< var link.login >}}
+- [x] You are a [{{< fa hand >}} Customer Admin]{.bubble} or assigned another role with sufficient permissions to configure workflows.[^1]
+- [x] You understand how to configure workflows and add steps to workflows.[^2]
+- [x] A webhook secret is configured for your Jira Personal Access Token.[^3]
+- [x] You have admin access to Jira.
+
+:::
+
+## Configure the workflow step
+
+::: {.column-margin}
+![Create a Jira issue](integrations-examples-http-request-open-jira-ticket.png){width=80% fig-alt="Screenshot of the HTTP request step configured to create a Jira ticket, showing the required fields described in step 4." .screenshot}
+:::
+
+1. In the left sidebar, click **{{< fa gear >}} Settings**.
+
+2. Under {{< fa shield >}} Governance, select **Workflows**.
+
+3. Select the **Model Workflows** tab.
+
+4. Click on a workflow to modify or click **{{< fa plus >}} Add Model Workflow**[^4] to create a new workflow.
+
+5. From the **Workflow Steps** modal, drag and drop an **HTTP Request** step[^5] onto the canvas, then connect it to your workflow.
+
+6. Double-click the step to open the **Configure HTTP Request** modal.
+
+7. Configure the required fields, replacing the placeholder values with your own:
+
+   - **[url]{.smallcaps}** — `https://yourcompany.atlassian.net/rest/api/3/issue`
+   - **[method]{.smallcaps}** — POST
+   - **[headers]{.smallcaps}** — Add:
+     - `Content-Type`: `application/json`
+     - `Authorization`: `Bearer {{Jira Personal Access Token}}`
+
+   ::: {.callout-tip title="Use webhook secrets for credentials"}
+   Instead of entering credentials in plaintext, use a webhook secret: `Bearer {{secret:jira_pat}}`. See [Manage secrets](../manage-secrets.qmd#webhook-secrets).
+   :::
+
+   - **[body type]{.smallcaps}** — JSON
+   - **[body]{.smallcaps}** — Use the following JSON payload:
+
+   ```json
+   {
+     "fields": {
+       "project": {
+         "key": "MODEL"
+       },
+       "summary": "Model validation failed: {{Model Name}}",
+       "description": "The model [{{Model Name}}|{{Model URL}}] failed validation. Review artifacts in ValidMind.",
+       "issuetype": {
+         "name": "Bug"
+       }
+     }
+   }
+   ```
+
+8. Click **Update Step** to save your configuration.
+
+The HTTP request to create the Jira ticket is sent when the workflow executes the step.
+
+<!-- FOOTNOTES -->
+
+[^1]: [Manage permissions](../../configuration/manage-permissions.qmd)
+
+[^2]: [Introduction to workflows](../../workflows/introduction-to-workflows.qmd)
+
+[^3]: [Manage secrets](../manage-secrets.qmd)
+
+[^4]: [Add new workflows](../../workflows/configure-workflows.qmd#add-new-workflows)
+
+[^5]: [Workflow step types](../../workflows/workflow-step-types.qmd#http-request)

site/guide/integrations/integrations-examples/create-servicenow-incident.qmd

@@ -0,0 +1,77 @@
+---
+# Copyright © 2023-2026 ValidMind Inc. All rights reserved.
+# Refer to the LICENSE file in the root of this repository for details.
+# SPDX-License-Identifier: AGPL-3.0 AND ValidMind Commercial
+title: "Create a ServiceNow incident"
+date: last-modified
+---
+
+Create a ServiceNow incident when a data drift issue is detected during ongoing monitoring using an HTTP request workflow step.
+
+::: {.attn}
+
+## Prerequisites
+
+- [x] {{< var link.login >}}
+- [x] You are a [{{< fa hand >}} Customer Admin]{.bubble} or assigned another role with sufficient permissions to configure workflows.[^1]
+- [x] You understand how to configure workflows and add steps to workflows.[^2]
+- [x] A webhook secret is configured for your ServiceNow credentials.[^3]
+- [x] You have admin access to ServiceNow.
+
+:::
+
+## Configure the workflow step
+
+1. In the left sidebar, click **{{< fa gear >}} Settings**.
+
+2. Under {{< fa shield >}} Governance, select **Workflows**.
+
+3. Select the **Model Workflows** tab.
+
+4. Click on a workflow to modify or click **{{< fa plus >}} Add Model Workflow**[^4] to create a new workflow.
+
+5. From the **Workflow Steps** modal, drag and drop an **HTTP Request** step[^5] onto the canvas, then connect it to your workflow.
+
+6. Double-click the step to open the **Configure HTTP Request** modal.
+
+7. Configure the required fields, replacing the placeholder values with your own:
+
+    - **[url]{.smallcaps}** — `https://yourinstance.service-now.com/api/now/table/incident`
+    - **[method]{.smallcaps}** — POST
+    - **[headers]{.smallcaps}** — Add:
+      - `Content-Type`: `application/json`
+      - `Authorization`: `Basic {{ServiceNow Credentials}}`
+
+   ::: {.callout-tip title="Use webhook secrets for credentials"}
+   Instead of entering credentials in plaintext, use a webhook secret: `Basic {{secret:servicenow_creds}}`. See [Manage secrets](../manage-secrets.qmd#webhook-secrets).
+   :::
+
+    - **[body type]{.smallcaps}** — JSON
+    - **[body]{.smallcaps}** — Use the following JSON payload:
+
+   ```json
+   {
+     "short_description": "Data drift issue detected: {{Model Name}}",
+     "description": "A potential issue has been identified for model {{Model Name}} (link: [{{Model URL}}]({{Model URL}})). Please review the ongoing monitoring documentation in ValidMind.",
+     "urgency": "2",
+     "category": "Model Risk"
+   }
+   ```
+
+::: {.column-margin}
+![Create a ServiceNow incident](integrations-examples-http-request-open-servicenow-incident.png){width=80% fig-alt="Screenshot of the HTTP request step configured to create a ServiceNow incident, showing the required fields described in step 4." .screenshot}
+:::
+
+The HTTP request to create the ServiceNow incident is sent when the workflow executes the step.
+
+<!-- FOOTNOTES -->
+
+[^1]: [Manage permissions](../../configuration/manage-permissions.qmd)
+
+[^2]: [Introduction to workflows](../../workflows/introduction-to-workflows.qmd)
+
+[^3]: [Manage secrets](../manage-secrets.qmd)
+
+[^4]: [Add new workflows](../../workflows/configure-workflows.qmd#add-new-workflows)
+
+[^5]: [Workflow step types](../../workflows/workflow-step-types.qmd#http-request)

site/guide/integrations/integrations-examples/synchronize-aws-bedrock.qmd

@@ -0,0 +1,99 @@
+---
+# Copyright © 2023-2026 ValidMind Inc. All rights reserved.
+# Refer to the LICENSE file in the root of this repository for details.
+# SPDX-License-Identifier: AGPL-3.0 AND ValidMind Commercial
+title: "Synchronize models with AWS Bedrock"
+date: last-modified
+---
+
+Link {{< var vm.product >}} models to foundation models and generative AI agents in Amazon Bedrock, supporting governance across your AI/ML ecosystem.
+
+::: {.attn}
+
+## Prerequisites
+
+- [x] {{< var link.login >}}
+- [x] You are a [{{< fa hand >}} Customer Admin]{.bubble} or assigned another role with sufficient permissions to configure connections.[^1]
+- [x] You have AWS IAM credentials with permissions to access Bedrock.
+
+:::
+
+AWS Bedrock exposes two primary integration surfaces:
+
+- **Foundation model layer** — Access to AWS-hosted and custom foundation models through the Bedrock model catalog (Discover and Tune views).
+
+- **Application layer** — Bedrock primitives such as agents, flows, and knowledge bases that represent built generative AI applications and workflows.
+
+## Configure the connection
+
+1. In the left sidebar, click **{{< fa gear >}} Settings**.
+
+2. Under {{< fa puzzle-piece >}} Integrations, select **Connections**.
+
+3. Click **{{< fa plus >}} Add Connection**.
+
+4. In the modal that opens, select **AWS Bedrock**.
+
+5. Complete:
+
+   - **[integration name]{.smallcaps}** — How other admins can identify the connection.
+   - **[description]{.smallcaps}** (optional) — The intended usage or additional details.
+   - **[aws region]{.smallcaps}** — The primary region where your Bedrock resources are deployed, for example `us-east-1`.
+   - **[aws access key id]{.smallcaps}** — The secret generated by AWS IAM with permissions to access Bedrock.
+   - **[aws secret access key]{.smallcaps}** — The secret generated by AWS IAM with permissions to access Bedrock.
+   - **[initial status]{.smallcaps}** — Set to `Operational` to enable immediately or `Disabled` if you plan to finish setup later.
+
+6. Click **Save Integration**.
+
+7. Test the connection:
+
+    a. Hover over the AWS Bedrock connection you just created.
+    b. When the **{{< fa ellipsis-vertical >}}** menu appears, click on it and select **{{< fa circle-check >}} Test Connection**.
+
+    If the test is successful, the message **{{< fa check-circle >}} Connection successful** displays.
+
+## Link models from Bedrock
+
+Once the connection is configured, you can link {{< var vm.product >}} models to your Bedrock resources:
+
+::: {.callout title="Model dependencies"}
+Bedrock agents, flows, and runtimes typically call foundation models (LLMs) under the hood. When you link these application-layer resources to {{< var vm.product >}}, consider also registering their underlying foundation models and creating dependency relationships between them.
+
+This builds a complete dependency graph showing how your AI applications relate to underlying models. Benefits include:
+
+- **Impact analysis** — See which applications are affected if a foundation model is deprecated or has compliance issues.
+- **Full audit trails** — Documentation and risk assessments capture the entire model stack, not just the top-level application.
+- **Governance visibility** — Track model versions and changes across your AI ecosystem.
+:::
+
+1. In the left sidebar, click **{{< fa cubes >}} Inventory**.
+
+2. Select a model by clicking on it or find your model by applying a filter or searching for it.[^2]
+
+3. Scroll down until you locate the **Amazon Bedrock** connection box in the right sidebar.
+
+4. Hover over the Amazon Bedrock box.
+
+5. When the **{{< fa ellipsis-vertical >}}** menu appears, click on it and select **{{< fa link >}} Link Model**.
+
+6. In the modal that opens, use the tabs to filter by resource type:
+
+   - **All** — View all available Bedrock resources.
+   - **Foundation Models** — AWS-hosted and custom foundation models from the Bedrock catalog.
+   - **Agents** — Generative AI agents you've built in Bedrock.
+   - **Flows** — Prompt flows and orchestration workflows.
+   - **AgentCore Runtimes** — Agent runtime environments.
+
+7. Click **[select model]{.smallcaps}** to choose the specific Bedrock resource to link.
+
+8. Optional: Click **Test Connection** to ensure the connection is working as expected.
+
+    If the test is successful, the message **{{< fa check-circle >}} Connection Test Successful** displays.
+
+9. Click **Link Model**.
+
+<!-- FOOTNOTES -->
+
+[^1]: [Manage permissions](../../configuration/manage-permissions.qmd)
+
+[^2]: [Working with the inventory](../../inventory/working-with-the-inventory.qmd#search-filter-and-sort-records)

site/guide/integrations/integrations-examples/synchronize-aws-sagemaker.qmd

@@ -0,0 +1,82 @@
+---
+# Copyright © 2023-2026 ValidMind Inc. All rights reserved.
+# Refer to the LICENSE file in the root of this repository for details.
+# SPDX-License-Identifier: AGPL-3.0 AND ValidMind Commercial
+title: "Synchronize models with AWS SageMaker"
+date: last-modified
+---
+
+Synchronize models registered in the {{< var vm.product >}} model inventory with AWS SageMaker models.
+
+::: {.attn}
+
+## Prerequisites
+
+- [x] {{< var link.login >}}
+- [x] You are a [{{< fa hand >}} Customer Admin]{.bubble} or assigned another role with sufficient permissions to configure connections.[^1]
+- [x] You have AWS IAM credentials with permissions to read the SageMaker model registry.
+
+:::
+
+## Configure the connection
+
+::: {.column-margin}
+![Connect with AWS SageMaker](integrations-examples-aws-sagemaker.png){width=80% fig-alt="Screenshot of the AWS Sagemaker connection configured to synchronize models, showing the required fields described in step 5." .screenshot}
+:::
+
+::: {.column-margin}
+![A linked AWS SageMaker model](integrations-examples-aws-sagemaker-linked-model.png){width=60% fig-alt="Screenshot of the model linked to AWS SageMaker, showing the required fields described in step 4." .screenshot}
+:::
+
+1. In the left sidebar, click **{{< fa gear >}} Settings**.
+
+2. Under {{< fa puzzle-piece >}} Integrations, select **Connections**.
+
+3. Click **{{< fa plus >}} Add Connection**.
+
+4. In the modal that opens, select **AWS Sagemaker**.
+
+5. Complete:
+
+   - **[integration name]{.smallcaps}** — How other admins can identify the connection.
+   - **[description]{.smallcaps}** (optional) — The intended usage or additional details.
+   - **[aws region]{.smallcaps}** - The primary region where your SageMaker model registry lives, for example `us-west-2`.
+   - **[aws access key id]{.smallcaps}** — The secret generated by AWS IAM with permissions to read the model registry.
+   - **[aws secret access key]{.smallcaps}** — The secret generated by AWS IAM with permissions to read the model registry.
+   - **[initial status]{.smallcaps}** — Set to `Operational` to enable immediately or `Disabled` if you plan to finish setup later.
+
+6. Click **Save Integration**. 
+
+7. Test the connection:
+
+    a. Hover over the AWS SageMaker connection you just created.
+    b. When the **{{< fa ellipsis-vertical >}}** menu appears, click on it and select **{{< fa circle-check >}} Test Connection**.
+
+    If the test is successful, the message **{{< fa check-circle >}} Connection successful** displays.
+
+
+## Link the models
+
+1. In the left sidebar, click **{{< fa cubes >}} Inventory**.
+
+2. Select a model by clicking on it or find your model by applying a filter or searching for it.[^2]
+
+3. Scroll down until you locate the **Amazon Sagemaker** connection box in the right sidebar.
+
+4. Hover over the Amazon SageMaker box.
+
+5. When the **{{< fa ellipsis-vertical >}}** menu appears, click on it and select **{{< fa link >}} Link Model**.
+
+6. In the modal that opens, click the [select model]{.smallcaps} dropdown to pick the AWS SageMaker model to link.
+
+7. Optional: Click **Test Connection** to ensure the connection is working as expected.
+
+    If the test is successful, the message **{{< fa check-circle >}} Connection Test Successful** displays.
+
+8. Click **Link Model**.
+
+<!-- FOOTNOTES -->
+
+[^1]: [Manage permissions](../../configuration/manage-permissions.qmd)
+
+[^2]: [Working with the inventory](../../inventory/working-with-the-inventory.qmd#search-filter-and-sort-records)