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S3 Storage

S3 Storage

PROD
This page contains the setup guide and reference information for the S3 connector. Configure and schedule S3 metadata workflows from the OpenMetadata UI:

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Requirements

We need the following permissions in AWS:

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S3 Permissions

For all the buckets that we want to ingest, we need to provide the following:
  • s3:ListBucket
  • s3:GetObject
  • s3:GetBucketLocation
  • s3:ListAllMyBuckets Note that the Resources should be all the buckets that you’d like to scan. A possible policy could be:
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket",
                "s3:GetBucketLocation",
                "s3:ListAllMyBuckets"
            ],
            "Resource": [
                "arn:aws:s3:::*"
            ]
        }
    ]
}

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CloudWatch Permissions

Which is used to fetch the total size in bytes for a bucket and the total number of files. It requires:
  • cloudwatch:GetMetricData
  • cloudwatch:ListMetrics The policy would look like:
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "cloudwatch:GetMetricData",
                "cloudwatch:ListMetrics"
            ],
            "Resource": "*"
        }
    ]
}

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OpenMetadata Manifest

In any other connector, extracting metadata happens automatically. In this case, we will be able to extract high-level metadata from buckets, but in order to understand their internal structure we need users to provide an openmetadata.json file at the bucket root. Supported File Formats: [ "csv", "tsv", "avro", "parquet", "json", "json.gz", "json.zip" ] You can learn more about this here. Keep reading for an example on the shape of the manifest file.

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OpenMetadata Manifest

Our manifest file is defined as a JSON Schema, and can look like this:

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Global Manifest

You can also manage a single manifest file to centralize the ingestion process for any container, named openmetadata_storage_manifest.json. You can also keep local manifests openmetadata.json in each container, but if possible, we will always try to pick up the global manifest during the ingestion.

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Metadata Ingestion

1

Visit the Services Page

The first step is ingesting the metadata from your sources. Under Settings, you will find a Services link an external source system to OpenMetadata. Once a service is created, it can be used to configure metadata, usage, and profiler workflows. To visit the Services page, select Services from the Settings menu.Visit Services Page
2

Create a New Service

Click on the ‘Add New Service’ button to start the Service creation.Create a new service
3

Select the Service Type

Select S3 as the service type and click Next.Select Service
4

Name and Describe your Service

Provide a name and description for your service.

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Service Name

OpenMetadata uniquely identifies services by their Service Name. Provide a name that distinguishes your deployment from other services, including the other Storage services that you might be ingesting metadata from.Add New Service
5

Configure the Service Connection

In this step, we will configure the connection settings required for this connector. Please follow the instructions below to ensure that you’ve configured the connector to read from your S3 service as desired.Configure service connection
6

Connection Details

When using a Hybrid Ingestion Runner, any sensitive credential fields—such as passwords, API keys, or private keys—must reference secrets using the following format:
password: secret:/my/database/password
This applies only to fields marked as secrets in the connection form (these typically mask input and show a visibility toggle icon). For a complete guide on managing secrets in hybrid setups, see the Hybrid Ingestion Runner Secret Management Guide.
  • AWS Access Key ID & 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 here.
  • 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, we need to know the region the service you want reach belongs to. Note that the AWS Region is the only required parameter when configuring a connection. When connecting to the services programmatically, there are different ways in which we can extract and use the rest of AWS configurations. You can find further information about configuring your credentials here.
  • 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 Secrets Access Key. Also, these will include an AWS Session Token. You can find more information on Using temporary credentials with AWS resources.
  • 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 a 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. You can inform this field if you’d like to use a profile other than default. Find here 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 you’ll 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, we’ll use 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.
  • Bucket Names (Optional): Provide the names of buckets that you would want to ingest, if you want to ingest metadata from all buckets or apply a filter to ingest buckets then leave this field empty.
7

Test the Connection

Once the credentials have been added, click on Test Connection and Save the changes.Test Connection
8

Configure Metadata Ingestion

In this step we will configure the metadata ingestion pipeline, Please follow the instructions belowConfigure Metadata Ingestion

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Metadata Ingestion Options

  • Name: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
  • Container Filter Pattern (Optional): To control whether to include a container as part of metadata ingestion.
    • Include: Explicitly include containers by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all containers with names matching one or more of the supplied regular expressions. All other containers will be excluded.
    • Exclude: Explicitly exclude containers by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all containers with names matching one or more of the supplied regular expressions. All other containers will be included.
  • Enable Debug Log (toggle): Set the Enable Debug Log toggle to set the default log level to debug.
  • Storage Metadata Config Source: Here you can specify the location of your global manifest openmetadata_storage_manifest.json file. It can be located in S3, a local path or HTTP.
9

Schedule the Ingestion and Deploy

Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The timezone is in UTC. Select a Start Date to schedule for ingestion. It is optional to add an End Date.Review your configuration settings. If they match what you intended, click Deploy to create the service and schedule metadata ingestion.If something doesn’t look right, click the Back button to return to the appropriate step and change the settings as needed.After configuring the workflow, you can click on Deploy to create the pipeline.Schedule the Workflow
10

View the Ingestion Pipeline

Once the workflow has been successfully deployed, you can view the Ingestion Pipeline running from the Service Page.View Ingestion Pipeline
If AutoPilot is enabled, workflows like usage tracking, data lineage, and similar tasks will be handled automatically. Users don’t need to set up or manage them - AutoPilot takes care of everything in the system.