Sagemaker Connector | OpenMetadata ML Model Services

• Requirements
• Metadata Ingestion
• Troubleshooting

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Requirements

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "SageMakerPolicy",
            "Effect": "Allow",
            "Action": [
                "sagemaker:ListModels",
                "sagemaker:DescribeModel",
                "sagemaker:ListTags",
                "sagemaker:ListModelPackageGroups"
            ],
            "Resource": "*"
        }
    ]
}

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Metadata Ingestion

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Step 1: Add New Service

1. Navigate to Settings > Services.
2. Click Add New Service.

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Step 2: Select a Service and Connector

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Step 3: Add Service Name and Description

• Enter a unique, descriptive Service Name. OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other SageMaker services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

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Enter Connection Details

• AWS Access Key ID and AWS Secret Access Key: When you interact with AWS, you specify your AWS security credentials to verify who you are and whether you have permission to access the resources that you are requesting. AWS uses the security credentials to authenticate and authorize your requests (docs). Access keys consist of two parts: an access key ID (for example, AKIAIOSFODNN7EXAMPLE), and a secret access key (for example, wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY). You must use both the access key ID and secret access key together to authenticate your requests. You can find further information on how to manage your access keys.
• AWS Session Token (optional): If you are using temporary credentials to access your services, you will need to inform the AWS Access Key ID and AWS Secret Access Key. These will also include an AWS Session Token. Find more information on using temporary credentials with AWS resources.

• AWS Region: Each AWS Region is a separate geographic area in which AWS clusters data centers (docs). As AWS can have instances in multiple regions, OpenMetadata needs to know the region the service you want to reach belongs to. The AWS Region is the only required parameter when configuring a connection. Find further information about configuring your credentials.
• Endpoint URL (optional): To connect programmatically to an AWS service, you use an endpoint. An endpoint is the URL of the entry point for an AWS web service. The AWS SDKs and the AWS Command Line Interface (AWS CLI) automatically use the default endpoint for each service in an AWS Region, but you can specify an alternate endpoint for your API requests. Find more information on AWS service endpoints.
• Profile Name: A named profile is a collection of settings and credentials that you can apply to an AWS CLI command. When you specify a profile to run a command, the settings and credentials are used to run that command. Multiple named profiles can be stored in the config and credentials files. Provide this field if you’d like to use a profile other than default. Find more information about named profiles for the AWS CLI.

• Assume Role Arn: Typically, you use AssumeRole within your account or for cross-account access. In this field, set the ARN (Amazon Resource Name) of the policy of the other account. A user who wants to access a role in a different account must also have permissions that are delegated from the account administrator. The administrator must attach a policy that allows the user to call AssumeRole for the ARN of the role in the other account. This is a required field if you’d like to AssumeRole. Find more information on AssumeRole.
  When using Assume Role authentication, ensure you provide the following details:

  • AWS Region: Specify the AWS region for your deployment.
  • Assume Role ARN: Provide the ARN of the role in your AWS account that OpenMetadata will assume.
• Assume Role Session Name: An identifier for the assumed role session. Use the role session name to uniquely identify a session when the same role is assumed by different principals or for different reasons. By default, OpenMetadata uses the name OpenMetadataSession. Find more information about the Role Session Name.
• Assume Role Source Identity: The source identity specified by the principal that is calling the AssumeRole operation. You can use source identity information in AWS CloudTrail logs to determine who took actions with a role. Find more information about Source Identity.

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Test Connection

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Step 5: Configure Ingestion Options

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How Filter Patterns Work

• Include: Add one or more comma-separated regular expressions. OpenMetadata ingests only assets whose names match at least one expression. Leave blank to include all assets.
• Exclude: Add one or more comma-separated regular expressions. OpenMetadata skips any asset whose name matches an expression. Leave blank to exclude nothing.

• contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
• starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
• ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
• is exactly: matches the exact name only. For example, analytics matches only analytics.
• matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.

• ML Model: Controls which ML models OpenMetadata ingests from the source.

• Scan Mode: You can choose between the following scan modes:
  • Scan all: Ingests every asset of that type the connector can access. This is the default.
  • Only specific: Enables include rules so only assets matching at least one rule are ingested.
• Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector, for example, Exclude system databases for the Databases section.
• Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
• Preview: Shows a real-time summary of what will be in scope based on your current rules.
• Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.

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Step 6: Create & Deploy

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Configure Metadata Agent and Schedule Ingestion

1. Navigate to Settings > Services and select the service type.
2. Click the service you have added.
3. Select the Agents tab and click Add Agent > Metadata. For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
4. On the Configure Ingestion page, do the following and click Next.
   • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline.
   • Agent Setup: Configure the core parameters for this agent. The following fields are available:

     Field	Default	Description
     Db Service Prefixes	—	List of database service name prefixes used to resolve lineage between ML models and database assets. Accepted formats: DBService, DBService.Database, DBService.Database.Schema, DBService.Database.Schema.Table.
     Mark Deleted ML Models	On	Soft-delete ML models in OpenMetadata when they are removed from the source. Associated entities like lineage are also deleted.

     
   • Filter Patterns: Apply include or exclude rules to scope which ML models this agent ingests. These follow the same filter options described in Step 5: Configure Ingestion Options.
   • Scope & Behaviour: Control what metadata to include and how to handle deletions. Toggle each option on or off based on your needs:

     Toggle	Default	Description
     Enable Debug Log	Off	Sets the ingestion log level to DEBUG. Useful for troubleshooting.
     Override Metadata	Off	When on, source values overwrite existing descriptions, tags, owners, and display names in OpenMetadata. When off, OpenMetadata only updates fields that have no existing value.
     Override Lineage	Off	When on, existing lineage is replaced with newly extracted lineage on each run.

     
5. On the Schedule Interval page, set when the agent runs:
   • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
   • On-Demand: No automatic schedule; trigger the agent manually when needed.
   
6. Click Add to deploy the agent.

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