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Elastic Docs ›Elasticsearch Guide [8.x] ›Ingest content with Elastic connectors ›Connectors references

Elastic S3 connector reference

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Elastic S3 connector reference

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The Elastic S3 connector is a connector for Amazon S3 data sources.

Elastic managed connector reference

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View Elastic managed connector reference
Availability and prerequisites
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This connector is available natively in Elastic Cloud as of version 8.12.0. To use this connector, satisfy all managed connector requirements.

Create a Amazon S3 connector
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Use the UI

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To create a new Amazon S3 connector:

  1. In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
  2. Follow the instructions to create a new native Amazon S3 connector.

For additional operations, see Connectors UI in Kibana.

Use the API

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You can use the Elasticsearch Create connector API to create a new native Amazon S3 connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
    is_native=True,
)
print(resp)
PUT _connector/my-s3-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Amazon S3",
  "service_type": "s3",
  "is_native": true
}
You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

  1. Run the following command, replacing values where indicated. Note the id and encoded return values from the response:

    resp = client.security.create_api_key(
    name="my-connector-api-key",
    role_descriptors={
        "my-connector-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "my-index_name",
                        ".search-acl-filter-my-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)
    const response = await client.security.createApiKey({
  name: "my-connector-api-key",
  role_descriptors: {
    "my-connector-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);
    POST /_security/api_key
{
  "name": "my-connector-api-key",
  "role_descriptors": {
    "my-connector-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "my-index_name",
            ".search-acl-filter-my-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}

  2. Use the encoded value to store a connector secret, and note the id return value from this response:

    resp = client.connector.secret_post(
    body={
        "value": "encoded_api_key"
    },
)
print(resp)
    const response = await client.connector.secretPost({
  body: {
    value: "encoded_api_key",
  },
});
console.log(response);
    POST _connector/_secret
{
  "value": "encoded_api_key"
}

  3. Use the API key id and the connector secret id to update the connector:

    resp = client.connector.update_api_key_id(
    connector_id="my_connector_id>",
    api_key_id="API key_id",
    api_key_secret_id="secret_id",
)
print(resp)
    const response = await client.connector.updateApiKeyId({
  connector_id: "my_connector_id>",
  api_key_id: "API key_id",
  api_key_secret_id: "secret_id",
});
console.log(response);
    PUT /_connector/my_connector_id>/_api_key_id
{
  "api_key_id": "API key_id",
  "api_key_secret_id": "secret_id"
}

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage
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To use this managed connector, see Elastic managed connectors.

For additional operations, see Connectors UI in Kibana.

S3 users will also need to Create an IAM identity

Create an IAM identity
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Users need to create an IAM identity to use this connector as a self-managed connector. Refer to the AWS documentation.

The policy associated with the IAM identity must have the following AWS permissions:

  • ListAllMyBuckets
  • ListBucket
  • GetBucketLocation
  • GetObject
Compatibility
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Currently the connector does not support S3-compatible vendors.

Configuration
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The following configuration fields are required to set up the connector:

AWS Buckets

List of S3 bucket names. * will fetch data from all buckets. Examples:

  • testbucket, prodbucket
  • testbucket
  • *

This field is ignored when using advanced sync rules.

AWS Access Key ID
Access Key ID for the AWS identity that will be used for bucket access.
AWS Secret Key
Secret Access Key for the AWS identity that will be used for bucket access.
Documents and syncs
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  • Content from files bigger than 10 MB won’t be extracted. (Self-managed connectors can use the self-managed local extraction service to handle larger binary files.)
  • Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.
Sync rules
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Basic sync rules are identical for all connectors and are available by default.

Advanced sync rules
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A full sync is required for advanced sync rules to take effect.

Advanced sync rules are defined through a source-specific DSL JSON snippet.

Use advanced sync rules to filter data to be fetched from Amazon S3 buckets. They take the following parameters:

  1. bucket: S3 bucket the rule applies to.
  2. extension (optional): Lists which file types to sync. Defaults to syncing all types.
  3. prefix (optional): String of prefix characters. The connector will fetch file and folder data that matches the string. Defaults to "" (syncs all bucket objects).

======= Advanced sync rules examples

Fetching files and folders recursively by prefix

Example: Fetch files/folders in folder1/docs.

[
  {
    "bucket": "bucket1",
    "prefix": "folder1/docs"
  }

]

Example: Fetch files/folder starting with folder1.

[
  {
    "bucket": "bucket2",
    "prefix": "folder1"
  }
]

Fetching files and folders by specifying extensions

Example: Fetch all objects which start with abc and then filter using file extensions.

[
  {
    "bucket": "bucket2",
    "prefix": "abc",
    "extension": [".txt", ".png"]
  }
]
Content extraction
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See Content extraction.

Known issues
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There are no known issues for this connector.

See Known issues for any issues affecting all connectors.

Troubleshooting
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See Troubleshooting.

Security
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See Security.

Framework and source
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This connector is built with the Elastic connector framework.

View the source code for this connector (branch 8.x, compatible with Elastic 8.17).

Self-managed connector reference

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View self-managed connector reference
Availability and prerequisites
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This connector is available as a self-managed self-managed connector. This self-managed connector is compatible with Elastic versions 8.6.0+. To use this connector, satisfy all self-managed connector requirements.

Create a Amazon S3 connector
edit

Use the UI

edit

To create a new Amazon S3 connector:

  1. In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
  2. Follow the instructions to create a new Amazon S3 self-managed connector.

Use the API

edit

You can use the Elasticsearch Create connector API to create a new self-managed Amazon S3 self-managed connector.

For example:

resp = client.connector.put(
    connector_id="my-{service-name-stub}-connector",
    index_name="my-elasticsearch-index",
    name="Content synced from {service-name}",
    service_type="{service-name-stub}",
)
print(resp)
PUT _connector/my-s3-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Amazon S3",
  "service_type": "s3"
}
You’ll also need to create an API key for the connector to use.

The user needs the cluster privileges manage_api_key, manage_connector and write_connector_secrets to generate API keys programmatically.

To create an API key for the connector:

  1. Run the following command, replacing values where indicated. Note the encoded return values from the response:

    resp = client.security.create_api_key(
    name="connector_name-connector-api-key",
    role_descriptors={
        "connector_name-connector-role": {
            "cluster": [
                "monitor",
                "manage_connector"
            ],
            "indices": [
                {
                    "names": [
                        "index_name",
                        ".search-acl-filter-index_name",
                        ".elastic-connectors*"
                    ],
                    "privileges": [
                        "all"
                    ],
                    "allow_restricted_indices": False
                }
            ]
        }
    },
)
print(resp)
    const response = await client.security.createApiKey({
  name: "connector_name-connector-api-key",
  role_descriptors: {
    "connector_name-connector-role": {
      cluster: ["monitor", "manage_connector"],
      indices: [
        {
          names: [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*",
          ],
          privileges: ["all"],
          allow_restricted_indices: false,
        },
      ],
    },
  },
});
console.log(response);
    POST /_security/api_key
{
  "name": "connector_name-connector-api-key",
  "role_descriptors": {
    "connector_name-connector-role": {
      "cluster": [
        "monitor",
        "manage_connector"
      ],
      "indices": [
        {
          "names": [
            "index_name",
            ".search-acl-filter-index_name",
            ".elastic-connectors*"
          ],
          "privileges": [
            "all"
          ],
          "allow_restricted_indices": false
        }
      ]
    }
  }
}
  2. Update your config.yml file with the API key encoded value.

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

Usage
edit

To use this connector as a self-managed connector, see Self-managed connectors.

For additional operations, see Connectors UI in Kibana.

S3 users will also need to Create an IAM identity

Create an IAM identity
edit

Users need to create an IAM identity to use this connector as a self-managed connector. Refer to the AWS documentation.

The policy associated with the IAM identity must have the following AWS permissions:

  • ListAllMyBuckets
  • ListBucket
  • GetBucketLocation
  • GetObject
Compatibility
edit

Currently the connector does not support S3-compatible vendors.

Configuration
edit

When using the self-managed connector workflow, these fields will use the default configuration set in the connector source code. These configurable fields will be rendered with their respective labels in the Kibana UI. Once connected, you’ll be able to update these values in Kibana.

The following configuration fields are required to set up the connector:

buckets

List of S3 bucket names. * will fetch data from all buckets. Examples:

  • testbucket, prodbucket
  • testbucket
  • *

This field is ignored when using advanced sync rules.

aws_access_key_id
Access Key ID for the AWS identity that will be used for bucket access.
aws_secret_access_key
Secret Access Key for the AWS identity that will be used for bucket access.
read_timeout
The read_timeout for Amazon S3. Default value is 90.
connect_timeout
Connection timeout for crawling S3. Default value is 90.
max_attempts
Maximum retry attempts. Default value is 5.
page_size
Page size for iterating bucket objects in Amazon S3. Default value is 100.
Deployment using Docker
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You can deploy the Amazon S3 connector as a self-managed connector using Docker. Follow these instructions.

Step 1: Download sample configuration file

Download the sample configuration file. You can either download it manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output ~/connectors-config/config.yml

Remember to update the --output argument value if your directory name is different, or you want to use a different config file name.

Step 2: Update the configuration file for your self-managed connector

Update the configuration file with the following settings to match your environment:

  • elasticsearch.host
  • elasticsearch.api_key
  • connectors

If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:

# When connecting to your cloud deployment you should edit the host value
elasticsearch.host: http://host.docker.internal:9200
elasticsearch.api_key: <ELASTICSEARCH_API_KEY>

connectors:
  -
    connector_id: <CONNECTOR_ID_FROM_KIBANA>
    service_type: s3
    api_key: <CONNECTOR_API_KEY_FROM_KIBANA> # Optional. If not provided, the connector will use the elasticsearch.api_key instead

Using the elasticsearch.api_key is the recommended authentication method. However, you can also use elasticsearch.username and elasticsearch.password to authenticate with your Elasticsearch instance.

Note: You can change other default configurations by simply uncommenting specific settings in the configuration file and modifying their values.

Step 3: Run the Docker image

Run the Docker image with the Connector Service using the following command:

docker run \
-v ~/connectors-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors:8.17.0.0 \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to DOCKER.md in the elastic/connectors repo for more details.

Find all available Docker images in the official registry.

We also have a quickstart self-managed option using Docker Compose, so you can spin up all required services at once: Elasticsearch, Kibana, and the connectors service. Refer to this README in the elastic/connectors repo for more information.

Documents and syncs
edit
  • Content from files bigger than 10 MB won’t be extracted by default. You can use the self-managed local extraction service to handle larger binary files.
  • Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.
Sync rules
edit

Basic sync rules are identical for all connectors and are available by default.

Advanced sync rules
edit

A full sync is required for advanced sync rules to take effect.

Advanced sync rules are defined through a source-specific DSL JSON snippet.

Use advanced sync rules to filter data to be fetched from Amazon S3 buckets. They take the following parameters:

  1. bucket: S3 bucket the rule applies to.
  2. extension (optional): Lists which file types to sync. Defaults to syncing all types.
  3. prefix (optional): String of prefix characters. The connector will fetch file and folder data that matches the string. Defaults to "" (syncs all bucket objects).

======= Advanced sync rules examples

Fetching files and folders recursively by prefix

Example: Fetch files/folders in folder1/docs.

[
  {
    "bucket": "bucket1",
    "prefix": "folder1/docs"
  }

]

Example: Fetch files/folder starting with folder1.

[
  {
    "bucket": "bucket2",
    "prefix": "folder1"
  }
]

Fetching files and folders by specifying extensions

Example: Fetch all objects which start with abc and then filter using file extensions.

[
  {
    "bucket": "bucket2",
    "prefix": "abc",
    "extension": [".txt", ".png"]
  }
]
Content extraction
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See Content extraction.

End-to-end testing
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The connector framework enables operators to run functional tests against a real data source. Refer to Connector testing for more details.

To execute a functional test for the Amazon S3 self-managed connector, run the following command:

make ftest NAME=s3

By default, this will use a medium-sized dataset. To make the test faster add the DATA_SIZE=small argument:

make ftest NAME=s3 DATA_SIZE=small
Known issues
edit

There are no known issues for this connector.

See Known issues for any issues affecting all connectors.

Troubleshooting
edit

See Troubleshooting.

Security
edit

See Security.

Framework and source
edit

This connector is built with the Elastic connector framework.

View the source code for this connector (branch 8.x, compatible with Elastic 8.17).

« Redis connector reference Elastic Salesforce connector reference »