The AWS Bedrock AI integration of Collibra Platform uses the following asset types. The asset types come out of the box with your software.
Important
You can configure Edge connections and capabilities without an active AI Governance license. However, AI Governance must be enabled to harvest AI model metadata, ingest corresponding AI assets in Data Catalog, and access the dashboards and features necessary to visualize and govern your AI landscape.
| Asset type | Description |
|---|---|
|
AI Base Model
|
Represents foundational business concepts that define the model’s purpose and governing principles in your Amazon Bedrock workspace. |
|
AWS Bedrock AI Model
Version
|
A subtype of AI Model Version that represents AI model versions in Amazon Bedrock. |
|
AI Model Deployment
|
The operational instance where a model version is assigned computational resources to execute and generate real-time outputs. |
|
AI Agent
|
A system that uses one or more AI models to perceive its environment, make decisions, and take actions. |
|
AI Agent Version
|
A specific, immutable implementation of the model logic and parameters that serves as the audited "raw" model version before it is activated. For AWS Bedrock AI, this is always the |
|
AI Agent Tool
|
A service accessible to an AI agent that automates tasks, generates content, or delivers intelligent insights. |
|
AI Endpoint
|
The access point for external systems that provides a consistent interface while allowing for the seamless exchange of underlying deployments. |
|
Vendor
|
Represents pre-trained models provided natively by AI providers, such as AI Providers like Anthropic, Meta, and Amazon. These are only ingested on-demand when another asset references them. |
|
File
|
Represents the S3 endpoint output paths Amazon Bedrock workspace. You can ingest this data during the integration by selecting Do you want to ingest input and output assets? checkbox. |
|
Storage Container
|
Represents the S3 endpoint output paths Amazon Bedrock workspace. You can ingest this data during the integration by selecting Do you want to ingest input and output assets? checkbox. |
AWS Bedrock AI diagram view
For information on the data that is integrated from AWS Bedrock AI, go to Integrated AWS Bedrock AI data.
Steps
- Open the asset page.
- Click the
Diagram tab.
The diagram is shown in the default diagram view. - Click
to add a new view. - Select the Text option below the diagram view name.
The diagram view text editor is shown. - Copy the code from the Show JSON code section below and paste it in the diagram view text editor.
- Click Save.
- Edit the name and description of the diagram view as needed.
Show JSON code
Copy
{
"nodes": [
{
"id": "Foundational AI Model",
"type": {
"id": "00000000-0000-0000-0000-000000031422"
}
},
{
"id": "AWS Bedrock AI Model Version",
"type": {
"id": "00000000-0000-0000-0000-000000031408"
}
},
{
"id": "AI Model Deployment",
"type": {
"id": "00000000-0000-0000-0000-000000031500"
}
},
{
"id": "AI Endpoint",
"type": {
"id": "00000000-0000-0000-0000-000000031501"
}
},
{
"id": "AI Agent",
"type": {
"id": "00000000-0000-0000-0000-000000031450"
}
},
{
"id": "Vendor",
"type": {
"id": "00000000-0000-0000-0000-000000031403"
}
},
{
"id": "File Container",
"type": {
"id": "00000000-0000-0000-0001-002900000002"
}
},
{
"id": "File",
"type": {
"id": "00000000-0000-0000-0000-000000031304"
}
}
],
"edges": [
{
"from": "Foundational AI Model",
"to": "Foundational AI Model",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000007116"
},
"roleDirection": true
},
{
"from": "Foundational AI Model",
"to": "AWS Bedrock AI Model Version",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000077000"
},
"roleDirection": true
},
{
"from": "Foundational AI Model",
"to": "Vendor",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000077005"
},
"roleDirection": true
},
{
"from": "AWS Bedrock AI Model Version",
"to": "AWS Bedrock AI Model Version",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000007106"
},
"roleDirection": true
},
{
"from": "AWS Bedrock AI Model Version",
"to": "AI Model Deployment",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000077001"
},
"roleDirection": true
},
{
"from": "AWS Bedrock AI Model Version",
"to": "File Container",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000007102"
},
"roleDirection": true
},
{
"from": "AI Model Deployment",
"to": "AI Endpoint",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000077006"
},
"roleDirection": true
},
{
"from": "AI Model Deployment",
"to": "File Container",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000077004"
},
"roleDirection": true
},
{
"from": "AI Agent",
"to": "AWS Bedrock AI Model Version",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000007108"
},
"roleDirection": true
},
{
"from": "File Container",
"to": "File",
"label": "",
"style": "arrow",
"type": {
"id": "00000000-0000-0000-0000-000000007060"
},
"roleDirection": true
}
],
"showOverview": false,
"enableFilters": true,
"showLabels": true,
"showFields": true,
"showLegend": true,
"showPreview": true,
"visitStrategy": "directed",
"layout": "HierarchyLeftRight",
"maxNodeLabelLength": 50,
"maxEdgeLabelLength": 30,
"layoutOptions": {
"compactGroups": false,
"componentArrangementPolicy": "topmost",
"edgeBends": true,
"edgeBundling": true,
"edgeToEdgeDistance": 5,
"minimumLayerDistance": "auto",
"nodeToEdgeDistance": 5,
"orthogonalRouting": true,
"preciseNodeHeightCalculation": true,
"recursiveGroupLayering": true,
"separateLayers": true,
"webWorkers": true,
"nodePlacer": {
"barycenterMode": true,
"breakLongSegments": true,
"groupCompactionStrategy": "none",
"nodeCompaction": false,
"straightenEdges": true
}
}
}