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Elastic Jira connector reference

Elastic Jira connector reference

The Elastic Jira connector is a connector for Atlassian Jira. This connector is written in Python using the Elastic connector framework.

View the source code for this connector (branch 8.16, compatible with Elastic 8.16).

Elastic managed connector reference

View Elastic managed connector reference

Availability and prerequisites

This connector is available as a managed connector on Elastic Cloud, as of 8.9.1.

Jira Data Center support was added in 8.13.0 in technical preview and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Technical preview features are not subject to the support SLA of official GA features.

To use this connector natively in Elastic Cloud, satisfy all managed connector requirements.

Create a Jira connector

Use the UI

To create a new Jira connector:

Navigate to the Search → Connectors page in the Kibana UI.
Follow the instructions to create a new native Jira connector.

For additional operations, see Connectors UI in Kibana.

Use the API

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

For example:

PUT _connector/my-jira-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Jira",
  "service_type": "jira",
  "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:

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

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
        }
      ]
    }
  }
}

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

const response = await client.connector.secretPost({
  body: {
    value: "encoded_api_key",
  },
});
console.log(response);

POST _connector/_secret
{
  "value": "encoded_api_key"
}

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

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

To use this connector natively in Elastic Cloud, see Elastic managed connectors.

For additional operations, see Connectors UI in Kibana.

Compatibility

Jira Cloud, Jira Server, and Jira Data Center versions 7 or later.

Configuration

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

Jira data source

Dropdown to determine the Jira platform type: Jira Cloud, Jira Server, or Jira Data Center. Default value is Jira Cloud.

Jira Data Center username

The username of the account for Jira Data Center.

Jira Data Center password

The password of the account to be used for Jira Data Center.

Jira Cloud service account id

Email address to authenticate with Jira Cloud. Example: jane.doe@example.com

Jira Cloud API token

The API Token to authenticate with Jira Cloud.

Jira Server username

The username of the account for Jira Server.

Jira Server password

The password of the account to be used for Jira Server.

Jira Cloud service account id

The account email for Jira Cloud.

Jira Cloud API token

The API Token to authenticate with Jira Cloud.

Jira host url

The domain where Jira is hosted. Examples:

Jira project keys

Comma-separated list of Project Keys to fetch data from Jira server or cloud. If the value is * the connector will fetch data from all projects present in the configured projects. Default value is *. Examples:

EC, TP
*

Enable SSL

Whether SSL verification will be enabled. Default value is False.

SSL certificate

Content of SSL certificate. Note: In case of ssl_enabled is False, the ssl_ca value will be ignored. Example certificate:

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----

Enable document level security

Toggle to enable document level security (DLS). When enabled, full syncs will fetch access control lists for each document and store them in the _allow_access_control field. Access control syncs fetch users' access control lists and store them in a separate index.

To access user data in Jira Administration, the account you created must be granted Product Access for Jira Administration. This access needs to be provided by an administrator from the Atlassian Admin, and the access level granted should be Product Admin.

Documents and syncs

The connector syncs the following objects and entities:

Projects
- Includes metadata such as description, project key, project type, lead name, etc.
Issues
- All types of issues including Task, Bug, Sub-task, Enhancement, Story, etc.
- Includes metadata such as issue type, parent issue details, fix versions, affected versions, resolution, attachments, comments, sub-task details, priority, custom fields, etc.
Attachments

Note: Archived projects and issues are not indexed.

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 by default. You must first enable DLS. Otherwise, all documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync types

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

Sync rules

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

This connector supports advanced sync rules for remote filtering. These rules cover complex query-and-filter scenarios that cannot be expressed with basic sync rules. Advanced sync rules are defined through a source-specific DSL JSON snippet.

Advanced sync rules example

Example 1: Queries to index content based on status of Jira issues.

[
  {
    "query": "project = Collaboration AND status = 'In Progress'"
  },
  {
    "query": "status IN ('To Do', 'In Progress', 'Closed')"
  }
]

Example 2: Query to index data based on priority of issues for given projects.

[
  {
    "query": "priority in (Blocker, Critical) AND project in (ProjA, ProjB, ProjC)"
  }
]

Example 3: Query to index data based on assignee and created time.

[
  {
    "query": "assignee is EMPTY and created < -1d"
  }
]

Document level security

Document level security (DLS) enables you to restrict access to documents based on a user’s permissions. Refer to configuration on this page for how to enable DLS for this connector.

Enabling DLS for your connector will cause a significant performance degradation, as the API calls to the data source required for this functionality are rate limited. This impacts the speed at which your content can be retrieved.

When the data_source is set to Confluence Data Center or Server, the connector will only fetch 1000 users for access control syncs, due a limitation in the API used.

Refer to DLS in Search Applications to learn how to ingest data from a connector with DLS enabled, when building a search application. The example uses SharePoint Online as the data source, but the same steps apply to every connector.

Content Extraction

See Content extraction.

Known issues

Enabling document-level security impacts performance.

Enabling DLS for your connector will cause a significant performance degradation, as the API calls to the data source required for this functionality are rate limited. This impacts the speed at which your content can be retrieved.

Refer to Known issues for a list of known issues for all connectors.

Troubleshooting

See Troubleshooting.

Security

Self-managed connector

View self-managed connector reference

Availability and prerequisites

This connector is available as a self-managed self-managed connector. This self-managed connector is compatible with Elastic versions 8.7.0+.

Jira Data Center support was added in 8.13.0 in technical preview and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Technical preview features are not subject to the support SLA of official GA features.

To use this connector, satisfy all self-managed connector requirements.

Create a Jira connector

Use the UI

To create a new Jira connector:

Navigate to the Search → Connectors page in the Kibana UI.
Follow the instructions to create a new Jira self-managed connector.

Use the API

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

For example:

PUT _connector/my-jira-connector
{
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from Jira",
  "service_type": "jira"
}

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:

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

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
        }
      ]
    }
  }
}

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

To use this connector as a self-managed connector, see Self-managed connectors For additional usage operations, see Connectors UI in Kibana.

Compatibility

Jira Cloud, Jira Server, and Jira Data Center versions 7 or later.

Configuration

When using the self-managed connector workflow, initially these fields will use the default configuration set in the connector source code. These are set in the get_default_configuration function definition.

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:

data_source

Dropdown to determine the Jira platform type: Jira Cloud, Jira Server, or Jira Data Center. Default value is Jira Cloud.

data_center_username

The username of the account for Jira Data Center.

data_center_password

The password of the account to be used for Jira Data Center.

username

The username of the account for Jira Server.

password

The password of the account to be used for Jira Server.

account_email

Email address to authenticate with Jira Cloud. Example: jane.doe@example.com

api_token

The API Token to authenticate with Jira Cloud.

jira_url

The domain where Jira is hosted. Examples:

projects

Comma-separated list of Project Keys to fetch data from Jira server or cloud. If the value is * the connector will fetch data from all projects present in the configured projects. Default value is *. Examples:

EC, TP
*

This field can be bypassed by advanced sync rules.

ssl_enabled

Whether SSL verification will be enabled. Default value is False.

ssl_ca

Content of SSL certificate. Note: In case of ssl_enabled is False, the ssl_ca value will be ignored. Example certificate:

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----

retry_count

The number of retry attempts after failed request to Jira. Default value is 3.

concurrent_downloads

The number of concurrent downloads for fetching the attachment content. This speeds up the content extraction of attachments. Defaults to 100.

use_document_level_security

Toggle to enable document level security (DLS). When enabled, full syncs will fetch access control lists for each document and store them in the _allow_access_control field. Access control syncs fetch users' access control lists and store them in a separate index.

To access user data in Jira Administration, the account you created must be granted Product Access for Jira Administration. This access needs to be provided by an administrator from the Atlassian Admin, and the access level granted should be Product Admin.

use_text_extraction_service

Requires a separate deployment of the Elastic Text Extraction Service. Requires that ingest pipeline settings disable text extraction. Default value is False.

Deployment using Docker

You can deploy the Jira 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: jira
    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:8.16.0.0 \
/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

The connector syncs the following objects and entities:

Projects
- Includes metadata such as description, project key, project type, lead name, etc.
Issues
- All types of issues including Task, Bug, Sub-task, Enhancement, Story, etc.
- Includes metadata such as issue type, parent issue details, fix versions, affected versions, resolution, attachments, comments, sub-task details, priority, custom fields, etc.
Attachments

Note: Archived projects and issues are not indexed.

Content from files bigger than 10 MB won’t be extracted
Permissions are not synced by default. You must first enable DLS. Otherwise, all documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync types

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

Sync rules

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

This connector supports advanced sync rules for remote filtering. These rules cover complex query-and-filter scenarios that cannot be expressed with basic sync rules. Advanced sync rules are defined through a source-specific DSL JSON snippet.

Advanced sync rules example

Example 1: Queries to index content based on status of Jira issues.

[
  {
    "query": "project = Collaboration AND status = 'In Progress'"
  },
  {
    "query": "status IN ('To Do', 'In Progress', 'Closed')"
  }
]

Example 2: Query to index data based on priority of issues for given projects.

[
  {
    "query": "priority in (Blocker, Critical) AND project in (ProjA, ProjB, ProjC)"
  }
]

Example 3: Query to index data based on assignee and created time.

[
  {
    "query": "assignee is EMPTY and created < -1d"
  }
]

Document level security

Document level security (DLS) enables you to restrict access to documents based on a user’s permissions. Refer to configuration on this page for how to enable DLS for this connector.

Enabling DLS for your connector will cause a significant performance degradation, as the API calls to the data source required for this functionality are rate limited. This impacts the speed at which your content can be retrieved.

When the data_source is set to Confluence Data Center or Server, the connector will only fetch 1000 users for access control syncs, due a limitation in the API used.

Refer to DLS in Search Applications to learn how to ingest data from a connector with DLS enabled, when building a search application. The example uses SharePoint Online as the data source, but the same steps apply to every connector.

Content Extraction

See Content extraction.

Self-managed connector operations

End-to-end testing

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

To perform E2E testing for the Jira connector, run the following command:

$ make ftest NAME=jira

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=jira DATA_SIZE=small

Known issues

Enabling document-level security impacts performance.

Enabling DLS for your connector will cause a significant performance degradation, as the API calls to the data source required for this functionality are rate limited. This impacts the speed at which your content can be retrieved.

Refer to Known issues for a list of known issues for all connectors.

Troubleshooting

See Troubleshooting.

Security

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