Pull from Jira
How to authenticate
Jira offers two authentication methods to connect with Parabola. Choose the method that best fits your organization's security requirements.
Option 1: Basic Authentication (Recommended for simplicity)
- Log in to your Atlassian account at https://id.atlassian.com/manage-profile/security
- Navigate to Security → API tokens
- Click Create API token and give it a descriptive name
- Copy the generated token and store it securely (you'll only see it once)
- In Parabola, add a Pull from Jira step
- Click Authenticate and select Basic Auth
- Enter your Atlassian account email address as the username
- Paste your API token as the password
Option 2: OAuth 2.0 (For enhanced security)
- Go to the Atlassian Developer Console at https://developer.atlassian.com/console/myapps/
- Create a new OAuth 2.0 integration or select an existing one
- Note your Client ID and Client Secret
- Set the callback URL to:
/api/steps/generic_api/callback - Configure the required OAuth scopes for your use case (e.g.,
read:jira-work,read:jira-user) - In Parabola, add a Pull from Jira step
- Click Authenticate and select OAuth 2.0
- Enter your Client ID and Client Secret
- Complete the OAuth authorization flow when prompted
Available data
Using the Jira integration in Parabola, you can bring in:
- Issues: Comprehensive issue details including summary, description, status, priority, assignee, reporter, dates, custom fields, comments, attachments, and work logs
- Issue search results: Flexible JQL-based queries to retrieve filtered sets of issues with customizable field selection and pagination
- Issue transitions: Available workflow transitions for issues and their associated screens and fields
- Projects: Project metadata including name, key, lead, description, issue types, components, versions, and project categories
- Project versions: Release versions with details on release dates, descriptions, archived status, and issue counts by status
- Users: User account information including display names, email addresses (subject to privacy settings), account IDs, active status, and avatar URLs
- Fields: System and custom field definitions with their schemas, allowed values, and configuration details
Common use cases
- Sprint and release reporting: Track issue completion rates, velocity metrics, and release progress by pulling issues filtered by sprint, version, or time period into automated dashboards
- Cross-system issue reconciliation: Combine Jira issue data with external systems like Zendesk, Salesforce, or internal databases to match customer tickets with engineering work and create unified views
- Team capacity and workload analysis: Pull assignee and issue status data to calculate team utilization, identify bottlenecks, and balance workload distribution across team members
- SLA compliance monitoring: Track time-to-resolution metrics by combining issue creation dates, status transitions, and resolution timestamps to ensure service level agreements are met
- Automated status updates: Query Jira for issues meeting specific criteria (e.g., stale tickets, overdue items) and trigger notifications via Slack or email to keep stakeholders informed
- Historical trend analysis: Extract issue data over time to analyze patterns in bug rates, feature delivery velocity, or support ticket volume for continuous improvement
Tips for using Parabola with Jira
- Use JQL for precise filtering: Leverage Jira Query Language in the search endpoint to filter issues precisely (e.g.,
project = PROJ AND status = "In Progress" AND updated >= -7d) rather than pulling all data and filtering afterward - Schedule flows to run automatically: Set your Parabola flow to refresh on a daily or hourly schedule to keep dashboards current without manual intervention
- Start with essential fields: When pulling issues, request only the fields you need (e.g.,
fields=summary,status,assignee,updated) to improve performance and reduce processing time - Combine multiple endpoints: Use separate steps to pull issues, then enrich them with user details or project information by joining on account IDs or project keys
- Leverage pagination: For large datasets, the Jira API returns results in pages—Parabola handles this automatically, but be mindful of API rate limits for very large queries
- Add alerts for anomalies: Set up Parabola alerts via Slack or email when your flow detects critical conditions, such as a spike in critical bugs or issues breaching SLA thresholds