IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.
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Elastic Jira connector reference

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Elastic Jira connector reference

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The Elastic Jira connector is a connector for Atlassian Jira.

Availability and prerequisites

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This connector is available as a connector client from the Python connectors framework. This connector client is compatible with Elastic versions 8.7.0+. To use this connector, satisfy all connector client requirements.

This connector is in beta 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. Beta features are not subject to the support SLA of official GA features.

Usage

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To use this connector as a native connector, see Native connectors logo cloud (managed service).

To use this connector as a connector client, see Connector clients.

For additional operations, see Using connectors.

Compatibility

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  • Jira Cloud or Jira Server versions 7 or later are compatible with Elastic connector frameworks.
  • Jira Data Center editions are not currently supported.

Configuration

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When using the connector client 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 Jira platform type: jira_cloud or jira_server. Default value is jira_cloud.
username
The username of the account for Jira server.
password
The password of the account to be used for Jira server.
account_email
The account email for Jira cloud.
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
  • *
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.

Deployment using Docker

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You can deploy the Jira connector as a self-managed connector client 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-python-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.password
  • connector_id
  • service_type

Use jira as the service_type value. Don’t forget to uncomment "jira" in the sources section of the yaml file.

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

elasticsearch:
  host: http://host.docker.internal:9200
  username: elastic
  password: <YOUR_PASSWORD>

connector_id: <CONNECTOR_ID_FROM_KIBANA>
service_type: jira

sources:
  # UNCOMMENT "jira" below to enable the Jira connector

  #mongodb: connectors.sources.mongo:MongoDataSource
  #s3: connectors.sources.s3:S3DataSource
  #dir: connectors.sources.directory:DirectoryDataSource
  #mysql: connectors.sources.mysql:MySqlDataSource
  #network_drive: connectors.sources.network_drive:NASDataSource
  #google_cloud_storage: connectors.sources.google_cloud_storage:GoogleCloudStorageDataSource
  #azure_blob_storage: connectors.sources.azure_blob_storage:AzureBlobStorageDataSource
  #postgresql: connectors.sources.postgresql:PostgreSQLDataSource
  #oracle: connectors.sources.oracle:OracleDataSource
  #mssql: connectors.sources.mssql:MSSQLDataSource

Note that the config file you downloaded might contain more entries, so you will need to manually copy/change the settings that apply to you. Normally you’ll only need to update elasticsearch.host, elasticsearch.password, connector_id and service_type to run the connector service.

Step 3: Run the Docker image

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

docker run \
-v ~/connectors-python-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors:8.9.2.0-SNAPSHOT \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to this guide in the Python framework repository for more details.

Documents and syncs

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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 of files bigger than 10 MB won’t be extracted.
  • 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.

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

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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"
  }
]

Content Extraction

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See Content extraction.

Connector client operations

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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 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

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There are currently no known issues for this connector. Refer to Known issues for a list of known issues for 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 included in the Python connectors framework.

View the source code for this connector (branch 8.9, compatible with Elastic 8.9).

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