Manage the Jira Connector
This applies to: Visual Data Discovery
The Symphony Jira connector lets you access the data available in Jira. Obtain the connector server following this process: Obtain Additional Connector Servers
After setting up the connector, create data sources that specify the necessary connection information and identify the data you want to use. See Manage Visual Data Discovery Data Sources for more information. After data sources are configured, they can be used to create dashboards and visuals from your data. See Create Dashboards.
- Symphony Feature Support
- Connect to Jira
- Optimize Performance
- Custom SQL Optimization
- Custom Fields
- Retrieving and Calculating Story Points
Symphony Feature Support
Connector support for specific features is shown in the following table.
Key: Y - Supported; N - Not Supported; N/A - not applicable
Feature | Supported? |
---|---|
N |
|
Y |
|
Y |
|
Y |
|
Y |
|
N |
|
Y |
|
Y |
|
Y |
|
Y |
|
Y |
|
N |
|
N |
|
Y |
|
N |
|
N |
|
N |
|
N |
|
Y |
|
N |
|
N |
|
N |
|
Y |
|
Y |
|
Y |
Connect to Jira
To connect Symphony to your Jira instance, provided the JDBC url, a Jira user name, and password or API token.
Input Field | Description |
---|---|
JDBC Url |
jdbc:jira://;Host=host_name_or_your_server;Auth_Type=Basic Authentication |
User Name |
Jira user name |
Password |
Jira user password or API token generated for the Atlassian account. |
Configure your Jira rate limit using Atlassian's guidelines to minimize rate limit errors and prevent performance issues. Rate limit are configured per user, per project; add a test user account with no rate limit to test your projects. See https://developer.atlassian.com/cloud/jira/platform/rate-limiting/.
Optimize Performance
The Jira connector and Simba JDBC driver use schema tables to map your data to a compatible JDBC format you can use when creating your sources. Learn more here: Schema Tables.
Custom SQL Optimization
Large Jira boards and projects can affect the connector's performance. To minimize this impact, you can create your data source using a custom SQL query and pushdown filters. To optimize the query, you can:
Include pushdown filters
Design queries to filter on columns for which folding is supported
Limit your query using a
WHERE
clause andTOP
for columns that don't support pushdown filtersNarrow your data retrieval by filtering your data by epic, project, issue creation date, or completion date
Speed your initial load time by defining a small time range on the Global Settings tab
Example:
Raw Data Cache
You can reduce the number of queries Symphony makes to the source and speed up data query execution by enabling raw data caching. When enabled, an Entity Data Cache toggle is added to the Source Creation work area. Enable and define a caching schedule. Contact Technical Support for assistance enabling this feature.
Custom Fields
See Api_Field for custom fields mappings. The field custom_name
is type SQL_VARCHAR(1024)
and is often represented in JSON format. Use the SUBSTRING()
function to extract fields from the JSON.
Example:
Retrieving and Calculating Story Points
Jira stores time estimation and story points. The story points are a custom field mapping, see Api_Field. Use this information to build custom metrics and return commonly used calculations.
Committed story points:
SUM(story_points)
Completed story points:
SUM(story_points) WHERE fields_status_name = 'Done'
Percent completed:
(SUM(story_points) WHERE fields_status_name = 'Done') / (SUM(story_points))
Example:
Comments
0 comments
Please sign in to leave a comment.