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 The functions of AWS Bedrock AI integration is limited if you do not enable AI governance. When you enable AI Governance, you can add custom attributes or custom relations, for example, AI Model Version, to the AWS Bedrock AI Model Version asset.
| Asset type | Description |
|---|---|
|
AI Base Model
|
Represents foundational business concepts that define the model’s purpose and governing principles in your Amazon SageMaker 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 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
}
}
}