---
sourceDocument: Australia IT Operations Management
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/de-DE/it-operations-management

 Release :

    - australia

ft:locale :

    - de-DE

ft:publication_title :

    - Australia IT Operations Management

ft:clusterId :

    - itom

bundleId :

    - itom

workflow :

    - Technology


---

# Amazon Bedrock

# Amazon Bedrock pattern-based discovery {#ariaid-title1}

* Freigeben Version: Australia
* 
* Aktualisiert 12. März 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 7 Minuten Lesedauer

AI Agent Topology Mapping discovers Amazon Bedrock AI services and agents during horizontal discovery. Discovering some of these resources may require updating to the latest version of the AI Agent Topology Mapping application from the ServiceNow Store.

## Request new or enhanced Patterns on the ServiceNow® Store {#amazon-bedrock-pattern__id_ztn_lkb_5yb}

Visit the [ServiceNow Store](https://store.servicenow.com/sn_appstore_store.do#!/store/application/06a71b1367e4130051c9027e2685ef1e/1.6.0?referer=/store/search?listingtype=allintegrations%253Bancillary_app%253Bcertified_apps%253Bcontent%253Bindustry_solution%253Boem%253Butility%253Btemplate&q=Patterns&sl=sh) to view all the available updates and for information about submitting requests to the store. For cumulative release notes information for all released apps, see the [ServiceNow Store version history release notes](https://docs.servicenow.com/bundle/store-release-notes/page/release-notes/store/sn-store-release-notes.html).{#amazon-bedrock-pattern__p_d21_nfg_h1c}

## Prerequisites {#amazon-bedrock-pattern__section_prerequisites}

Verify that the applications are up to date
:
    * AI Agent Topology Mapping
    * Discovery and Service Mapping Patterns
    * Visibility Content
    * CMDB CI Class Models
    {#amazon-bedrock-pattern__ul_dlg_343_23c}

Update the method used for pointed discovery for the AWS CloudFormation Template (CFT) stack
:   If you use Cloud Provisioning and Governance, you must update the getOperationGR(type) method. This update enables the pointed discovery to list the resources correctly for the AWS CFT stack after provisioning. For further information about the steps required to update this method, see the Knowledge Base article [KB0858437](https://support.servicenow.com/nav_to.do?uri=kb_knowledge.do?sys_id=54ecb719db1f1cd0fb115583ca961917).

Activate the cloud-related CI relationships
:   To include discovered components into service instances, enable CI relationships used in tag-based discovery by Service Mapping. These CI relationships are available from the 1.0.68 release on the ServiceNow Store. For operational steps, see [Tag-based discovery configuration](https://servicenow-prod.fluidtopics.net/icbbyreoUvJ8l1PjBdxohw "You can refine the default configuration to control which CIs Service Mapping includes in application services during the tag-based discovery process.").

Set up service accounts on the AWS Management Console

:   An AWS Organization is a collection of AWS accounts under a single account. In AWS Organizations, parent accounts are called management accounts. The sub-accounts that belong to a management account are called member accounts.

    The advantages of using management accounts in Discovery are:

    Easy population of member accounts
    :   After you configure the management account and supply the necessary credentials, you can test the connection to the account. If the test succeeds, Discovery returns a list of the member accounts in that management account. From this list, you can choose one or more member to include in the Discovery of the management account.

    (Optional) Discover member resources using dynamically acquired credentials

    :   When you run Discovery on your cloud resources, you don't need separate credentials for each member account. The Cloud Discovery process handles credentials automatically by acquiring a temporary credential for each member via an AWS API. You can elect to use the default configuration or customize the MID Server to assume other roles for additional controls and security.

    For more information, see [Setting up AWS service accounts](https://servicenow-prod.fluidtopics.net/DOF48Jk0A_NECIHpPMLBrg "Create and configure cloud service accounts at ServiceNow AI Platform for the corresponding Amazon Web Services (AWS) service accounts.").

Use IAM user policy on the AWS Management Console
:   To use the IAM user policy instead of credentials during discovery, configure the MID Server for AWS IAM roles. For more information, see [configure the MID Server for AWS IAM roles](https://servicenow-prod.fluidtopics.net/RkNoUH5pjORwMxoT_1Lm8A "Configure the MID Server to retrieve the temporary security credentials associated with an IAM role.").  
    To create the IAM user policy for provisioning AWS resources, see [Control AWS access and permissions using policies](https://servicenow-prod.fluidtopics.net/1eLBs8e2SfKSi9eKhzwhZg "Configure policies with the necessary level of permissions to provide access to the AWS resources for Cloud Discovery and Cloud Provisioning and Governance."). Ensure that the IAM user policy covers the following AWS resources:

        {
            "Version": "2012-10-17",
            "Statement": [
                {
                    "Action": [
                "elasticloadbalancing:DescribeLoadBalancerPolicyTypes",
                "elasticloadbalancing:DescribeLoadBalancers",
                "elasticloadbalancing:DescribeLoadBalancerPolicies",
                "elasticloadbalancing:DescribeInstanceHealth",
                "elasticloadbalancing:DescribeTags",
                "elasticloadbalancing:DescribeLoadBalancerAttributes",
                "account:ListRegions",
                "elasticloadbalancing:Describe*",
                "ec2:Describe*",
                "ec2:DescribeNetworkInterfaceAttribute",
                "ec2:DescribeInstanceStatus",
                "ec2:DescribeCustomerGateways",
                "ec2:DescribeSecurityGroups",
                "ec2:DescribeHosts",
                "ec2:DescribeImages",
                "ec2:DescribeVpcs",
                "ec2:DescribeAccountAttributes",
                "ec2:DescribeInstanceAttribute",
                "ec2:DescribeInstanceCreditSpecifications",
               
                    ],
                    "Effect": "Allow",
                    "Resource": "*"
                }
            ]
        }

Configure access to the AWS resources

:   To discover a single account, create an IAM account in the AWS Management Console, and ensure that it has the "ReadOnlyAccess" policy applied. To discover several member or child accounts, configure the credentials as described in [Access setup for AWS service accounts](https://servicenow-prod.fluidtopics.net/mICEscb52cSuRR3vZTjRLQ "Cloud Discovery and Cloud Provisioning and Governance need access to resources in the Amazon Web Services (AWS) service accounts. Learn about different methods of configuring such access.").

Configure the Discovery schedule to support GovCloud
:   Discovering AWS GovCloud (US) accounts requires using a datacenter URL when setting up an AWS service account. For more information, see [Create AWS service accounts](https://servicenow-prod.fluidtopics.net/uTa4K3UBhqLrbRzrstyZrA "Create AWS service accounts on the ServiceNow AI Platform to access your AWS account during AWS discovery.").

Configure a discovery schedule
:   [Create an AWS Discovery schedule in Discovery Admin Workspace](https://servicenow-prod.fluidtopics.net/2fdtwCb~uBx55Ex3C6kFZw "Use the Discovery Admin Workspace dashboard to create an Amazon Web Services (AWS) Discovery schedule.").

(Optional) Discover datacenters only for new members
:   Starting with Zurich Patch 2, you can discover datacenters only for new members added since the last discovery. For more information, see [Discover datacenters only for new cloud accounts](https://servicenow-prod.fluidtopics.net/mPeqPk2RkpS7brL3bHB2Tg "If you have multiple cloud accounts and datacenters in AWS and Azure, you can discover datacenters for new cloud accounts only, instead of refreshing the entire list.").

(optional) Optimize discovery by including only datacenters with resources
:   Starting with Discovery and Service Mapping Patterns version 1.29.0, you can optimize discovery by limiting it to only AWS datacenters with resources.

    * Verify your service account has the following role permissions to access Config API:
      * `config:GetDiscoveredResourceCounts`
      * `config:DescribeConfigurationRecorderStatus`
      {#amazon-bedrock-pattern__ul_isx_t1c_fhc}
    * Verify AWS Config recorder is enabled and configured to record the all resource types.

      For instructions on configuring AWS Config recorder, go to the [AWS Documentation](https://docs.aws.amazon.com/) and search for the "Recording resources in the AWS Config console" article.
    * Enable discovery of only datacenters with resources by setting the mid.cloud.discovery.sonar.discover_all_aws_datacenters MID Server property to false. For more information, see [Limit AWS discovery to datacenters with resources](https://servicenow-prod.fluidtopics.net/vfaq3qB9CiQm182PwtIoUg "Optimize AWS discovery by limiting it to datacenters with resources.").
    {#amazon-bedrock-pattern__ul_cqf_q1c_fhc}
:   For more information, see the AWS resources discovery by datacenters section in [AWS discovery using patterns](https://servicenow-prod.fluidtopics.net/VRVjHOLBToHiwjz2ZRkbUg "Discovery and Service Mapping Patterns uses patterns to discover components of the Amazon AWS Cloud deployment during horizontal discovery. Discovering some of these resources may require updating to the latest version of the Discovery and Service Mapping Patterns application from the ServiceNow Store.").

(Optional) Populate Service Account and Logical Datacenter fields in cloud CIs
:   Starting with Discovery and Service Mapping Patterns version 1.30.0, you can improve query performance by populating Service Account and Logical Datacenter fields directly in cloud CIs. For more information, see [Improved query performance with direct field population in CI tables](https://servicenow-prod.fluidtopics.net/fv_6mvxBkpH9GnKa1~2XMQ "The Populate Service Account and LDC IN CMDB scheduled job populates the Service Account and Logical Datacenter fields in cloud configuration item (CI) tables, and the Virtual Machine Object field in the Hardware [cmdb_ci_hardware] table. This direct population reduces query complexity and improves query performance.").

## Verify the REST API Permissions {#amazon-bedrock-pattern__id_jb1_qgh_23c}

Download the [Cloud Discovery patterns spreadsheet](https://downloads.docs.servicenow.com/resource/enus/api/servicenow-discovery-patterns-api-details.xlsx) so you can grant user permissions required for running the Discovery patterns. In addition to permissions, the spreadsheet also includes useful information such as pattern names, types, CI Classes, and links to vendor documentation. New patterns are available
quarterly, so check periodically to be sure you have the latest version of the spreadsheet.{#amazon-bedrock-pattern__cloud-discovery-api-paragraph}

## Data collection {#amazon-bedrock-pattern__section_dvn_tcp_l3c}

The Amazon AWS - Bedrock Agents pattern collects AI System Digital Assets, AI Prompt Digital Assets, and Key Value information. You can view this information in the Related Links section of the CI record by
navigating to AllConfigurationAWSAWS Bedrock Agents and selecting the relevant record.

AI Agent Topology Mapping application populates data in both CMDB and non-CMDB tables.

## Data stored in non-CMDB tables {#amazon-bedrock-pattern__section_nbj_bcp_l3c}

The AI Agent Topology Mapping application populates data in non-CMDB tables when running the Amazon AWS - Bedrock Agents pattern.

If you have the AI Control Tower application, you can view the information in the AI Control Tower Workspace.  
{#amazon-bedrock-pattern__table_alm_ai_system__entry__2}

| Field | Description |
|-|-|
| Display name \[display_name\] | Display name of the Bedrock agent. |
| External record reference \[external_ref_id\] | Amazon Resource Name (ARN) of the Bedrock agent. |
| Model \[model\] | References the AI System Component Product Model \[cmdb_ai_system_component_product_model\] table. |
| Asset type \[model_category\] | Asset type of the agent. Value is set to Agentic AI. |
| State \[install_status\] | State of the agent. Value is set to Deployed. |
| AI prompts \[ai_prompts\] | References the AI Prompt Digital Asset \[alm_ai_prompt_digital_asset\] table. |
| AI models \[ai_models\] | References the AI Model Digital Asset \[alm_ai_model_digital_asset\] table. |
| Configuration Item \[ci\] | References the AI Function \[cmdb_ci_function_ai\] table. |
[Tabelle : 1. AI System Digital Asset \[alm_ai_system_digital_asset\]]

{#amazon-bedrock-pattern__table_alm_ai_system}  
{#amazon-bedrock-pattern__table_cmdb_ai_system_component__entry__2}

| Field | Description |
|-|-|
| Name \[name\] | Name of the Bedrock agent. |
| Short description \[short_description\] | Description of the Bedrock agent. |
| Status \[status\] | Operational status of the agent as returned by Bedrock. For example: PREPARED. |
| Version \[version\] | Version of the Bedrock agent. |
| Manufacturer \[manufacturer\] | Manufacturer of the agent model. Value is set to AWS. |
| Model categories \[cmdb_model_category\] | Model category. Value is set to Agentic AI. |
[Tabelle : 2. AI System Component Product Model \[cmdb_ai_system_component_product_model\]]

{#amazon-bedrock-pattern__table_cmdb_ai_system_component}  
{#amazon-bedrock-pattern__table_alm_ai_prompt__entry__2}

| Field | Description |
|-|-|
| Prompt information \[prompt_info\] | Instruction text defined for the Bedrock agent. |
| Model \[model\] | References the AI Prompt Product Model \[cmdb_ai_prompt_product_model\] table. |
| Asset type \[model_category\] | Asset type of the prompt. Value is set to AI prompt. |
| Configuration Item \[ci\] | References the AI Function \[cmdb_ci_function_ai\] table. |
[Tabelle : 3. AI Prompt Digital Asset \[alm_ai_prompt_digital_asset\]]

{#amazon-bedrock-pattern__table_alm_ai_prompt}  
{#amazon-bedrock-pattern__table_cmdb_ai_prompt_product_model__entry__2}

| Field | Description |
|-|-|
| Name \[name\] | Name of the Bedrock agent, used to identify the associated prompt model. |
| Manufacturer \[manufacturer\] | Manufacturer of the prompt model. Value is set to AWS. |
[Tabelle : 4. AI Prompt Product Model \[cmdb_ai_prompt_product_model\]]

{#amazon-bedrock-pattern__table_cmdb_ai_prompt_product_model}  
{#amazon-bedrock-pattern__table_alm_ai_model__entry__2}

| Field | Description |
|-|-|
| Display name \[display_name\] | Name of the foundation model. |
| External record reference \[external_ref_id\] | ARN of the foundation model. |
| Model \[model\] | References the AI Model Product Model \[cmdb_ai_model_product_model\] table. |
| Asset type \[model_category\] | Asset type of the model. Value is set to AI model. |
| Vendor \[vendor\] | Provider of the foundation model. |
[Tabelle : 5. AI Model Digital Asset \[alm_ai_model_digital_asset\]]

{#amazon-bedrock-pattern__table_alm_ai_model}  
{#amazon-bedrock-pattern__table_cmdb_ai_model_product_model__entry__2}

| Field | Description |
|-|-|
| Name \[name\] | Name of the foundation model. |
| Model number \[model_number\] | Model ID assigned by Amazon Bedrock. |
| Manufacturer \[manufacturer\] | Provider of the foundation model. |
| Model categories \[cmdb_model_category\] | Model category. Value is set to AI model. |
[Tabelle : 6. AI Model Product Model \[cmdb_ai_model_product_model\]]

{#amazon-bedrock-pattern__table_cmdb_ai_model_product_model}

## Data stored in CMDB tables {#amazon-bedrock-pattern__section_data_collected}

AI Agent Topology Mapping populates the data in the CMDB when running the Amazon AWS - Bedrock Agents pattern.  
{#amazon-bedrock-pattern__table_ai_function__entry__2}

| Field | Description |
|-|-|
| Name \[name\] | Name of the Bedrock agent. |
| Object ID \[object_id\] | ARN of the Bedrock agent. |
| Description \[short_description\] | Description of the Bedrock agent. |
| Model number \[model_number\] | Agent ID assigned by Amazon Bedrock. |
| Operational status \[operational_status\] | Operational status of the resource. Default value is set to Operational. |
| Install Status \[install_status\] | Install status of the resource. Default value is set to Installed. |
| Product instance identifier \[product_instance_id\] | Version of the Bedrock agent. |
| Comments \[comments\] | Resource type identifier. Value is set to AWS::Bedrock::Agent. |
| Manufacturer \[manufacturer\] | Manufacturer of the resource. Value is set to AWS. |
[Tabelle : 7. AI Function \[cmdb_ci_function_ai\]]

{#amazon-bedrock-pattern__table_ai_function}

## CI relationships {#amazon-bedrock-pattern__section_relationships}

The Amazon AWS - Bedrock Agents pattern creates the following relationships to support Amazon Bedrock discovery.  
{#amazon-bedrock-pattern__table_relationships__entry__3}

| CI | Relationship | CI |
|-|-|-|
| AI Function \[cmdb_ci_function_ai\] | Deployed as::Deployment of | AI System Digital Asset \[alm_ai_system_digital_asset\] |
| AI Function \[cmdb_ci_function_ai\] | Hosted on::Hosts | AWS Datacenter \[cmdb_ci_aws_datacenter\] |
| Key Value \[cmdb_key_value\] | References | AI Function \[cmdb_ci_function_ai\] |
[ ]

{#amazon-bedrock-pattern__table_relationships}

## AWS tag discovery {#amazon-bedrock-pattern__section_tag_discovery}

The Amazon AWS - Bedrock Agents pattern collects tags and populates them in the Key Value \[cmdb_key_value\] table.  
{#amazon-bedrock-pattern__table_key_value__entry__2}

| Field | Description |
|-|-|
| Key \[key\] | Tag name. |
| Value \[value\] | Tag value. |
| Configuration item \[configuration_item\] | References the AI Function \[cmdb_ci_function_ai\] table. |
[Tabelle : 8. Key Value \[cmdb_key_value\]]

{#amazon-bedrock-pattern__table_key_value}