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).
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+.
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:
- In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
- 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"
}
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: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 keyencoded
value.
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
, orJira Data Center
. Default value isJira 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
isFalse
, thessl_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.NoteTo 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.
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>1
- 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/integrations/elastic-connectors:9.0.0 \
/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.
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.
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.
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.
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.