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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 main, compatible with Elastic 9.0).

Important

As of Elastic 9.0, managed connectors on Elastic Cloud Hosted are no longer available. All connectors must be self-managed.

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

Note

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.

To create a new Jira 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 Jira self-managed connector.

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"
}

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

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

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

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.

Note

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.

You can deploy the Jira connector as a self-managed connector using Docker. Follow these instructions.

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

Find all available Docker images in the official registry.

Tip

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.

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.

Note
  • 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.

Full syncs are supported by default for all connectors.

This connector also supports incremental syncs.

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.

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 (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.

Warning

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.

Warning

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.

Note

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.

See Content extraction.

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
  • 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.

See Troubleshooting.

See Security.