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Index Jira Data

Availability

Indexing tools are available in the Next environment (Release 1.7.0) and replace legacy Datasources/Datasets. For context, see Release Notes 1.7.0 and the Indexing Overview.

This guide provides a complete step-by-step walkthrough for indexing Jira data and then searching or chatting with the indexed content using ELITEA's AI-powered tools.

Overview

Jira indexing allows you to create searchable indexes from your Jira project management content:

  • Issues & Stories: User stories, bugs, tasks, epics, and sub-tasks with full descriptions
  • Custom Fields: Project-specific fields, custom workflows, and metadata
  • Attachments: Screenshots, documents, test files, and other media attached to issues
  • Comments: Discussion threads, status updates, and collaborative input on issues
  • Project Data: Sprint information, priorities, assignees, and project hierarchies

What you can do with indexed Jira data:

  • Semantic Search: Find issues, bugs, and stories across projects using natural language queries
  • Context-Aware Chat: Get AI-generated answers from your project data with citations to specific issues
  • Cross-Project Discovery: Search across multiple Jira projects and issue types
  • Knowledge Extraction: Transform Jira content into searchable organizational knowledge
  • Project Analysis: Analyze patterns, trends, and relationships in your project management data

Common use cases:

  • Finding similar bugs or issues across projects for faster resolution
  • Onboarding new team members by allowing them to ask questions about project history and processes
  • Analyzing sprint retrospectives and team feedback for continuous improvement
  • Support and customer service teams searching for known issues and solutions
  • Project managers extracting insights from historical project data and decisions

Prerequisites

Before indexing Jira data, ensure you have:

  1. Jira Credential: A Jira API token or authentication credentials configured in ELITEA
  2. Vector Storage: PgVector selected in Settings → AI Configuration
  3. Embedding Model: Selected in AI Configuration (defaults available) → AI Configuration
  4. Jira Toolkit: Configured with your Jira instance details and credentials

Required Permissions

Your Jira credential needs appropriate permissions based on what you want to index:

For Content Access: - Read access to Jira projects and issues - Permission to view the specific projects you want to index

For Comprehensive Indexing: - Access to view attachments (if including attachments) - Permission to view comments and issue history - Access to both public and restricted projects (based on your requirements)

Authentication Methods: - Basic Authentication: Username and API Key - Bearer Token: Jira API token


Step-by-Step: Creating a Jira Credential

  1. Generate Jira API Token in your Atlassian account (Security → API Tokens)
  2. Create Credential in ELITEA: Navigate to Credentials+ CreateJira → enter details and save

Detailed Instructions

For complete credential setup steps including token generation and security best practices, see:


Step-by-Step: Configure Jira Toolkit

  1. Create Toolkit: Navigate to Toolkits+ CreateJira
  2. Configure Settings: Set base URL, hosting option (Cloud/Server), and assign your Jira credential
  3. Enable Tools: Select Index Data, List Collections, Search Index, Stepback Search Index, Stepback Summary Index, and Remove Index tools
  4. Save Configuration

Tool Overview:

  • Index Data: Creates searchable indexes from Jira issues and content
  • List Collections: Lists all available collections/indexes to verify what's been indexed
  • Search Index: Performs semantic search across indexed content using natural language queries
  • Stepback Search Index: Advanced search that breaks down complex questions into simpler parts for better results
  • Stepback Summary Index: Generates summaries and insights from search results across indexed content
  • Remove Index: Deletes existing collections/indexes when you need to clean up or start fresh

Detailed Instructions

For complete toolkit configuration including hosting options and authentication setup, see:


Step-by-Step: Index Jira Data

Content Indexing (from Toolkit)

  1. Open Toolkit Test Settings:

    • Navigate to your Jira toolkit's detail page
    • In the Test Settings panel (right side), select a model (e.g., gpt-4o)
  2. Configure Index Data Tool:

    • From the tool dropdown, select "Index Data"
    • Configure the following parameters:
    Parameter Description Example Value
    Collection Suffix * Suffix for collection name (required) issues or proj
    Progress Step (0 - 100) Step size for progress reporting during indexing 10 or 25
    Clean Index Remove existing index data before re-indexing ✓ (checked) or ✗ (unchecked)
    Chunking Config Configuration for document chunking Default or custom settings
    JQL JQL query to filter issues project=PROJ AND status=Open
    Fields To Extract Additional fields to extract from issues customfield_10001,priority
    Fields To Index Additional fields to include in indexed content reporter,assignee
    Include Attachments Index attachment content ✓ (checked) or ✗ (unchecked)
    Max Total Issues Maximum number of issues to index 1000 (default)
    Skip Attachment Extensions File extensions to skip when processing attachments .png,.jpg,.gif
    Chunking Tool Method for splitting content into chunks markdown (default)
  3. Run Jira Indexing:

    • Click "Run Tool"
    • Wait for completion (may take several minutes for large projects)
    • Check the output for success confirmation or error messages

    Jira Index Configuration


Verification: Confirm Index Success

After indexing completes, verify the index was created successfully:

Method 1: Using Test Settings (Technical Verification)

  1. Use List Collections Tool:

    • In Test Settings, select "List Collections" tool
    • Run tool to see all available collections
    • Look for your collection with the specified suffix
  2. Test Basic Search:

    • Select "Search Index" tool
    • Query: e.g., bug login authentication
    • Collection Suffix: Your specified suffix
    • Run tool and verify relevant results are returned

Search and Chat with Indexed Data

Once your Jira data is indexed, you can use the toolkit to search and interact with your content in multiple ways:

Using Toolkit in Conversations and Agents

Your Jira toolkit can be used in two main contexts:

  1. In Conversations: Add the toolkit as a participant to ask questions and search your indexed Jira data
  2. In Agents: Include the toolkit when creating AI agents to give them access to your Jira project data

How to use:

  • Start a New Conversation or Create an Agent
  • Add Toolkit as Participant: Select your Jira toolkit from the available toolkits
  • Ask Natural Language Questions: The toolkit will automatically search your indexed data and provide relevant answers with citations

Real-Life Example Workflow

Let's walk through a complete example of indexing and using a software project's Jira data:

Step 1: Setup Jira Toolkit for Software Project

Step 2: Use in Conversations

Add toolkit to a conversation and start asking questions:

  • Navigate to Conversations+ New Conversation
  • In the participants section click + to add Toolkit
  • Select your Jira toolkit from the available toolkits list

Step 3: Index the Project Issues

  • User Request in Chat:

    "Index all issues from project EL with suffix 'issues'. Include comments but skip attachments and image files. Clean any existing index first."

Jira List

Step 4: Verify Index Creation

  • User Request in Chat:

    "List my collections"

  • Jira Toolkit Response:

Jira List

This confirms the indexing completed successfully and your project collection is available for searching.

Step 5: Start the conversation and begin asking questions about your indexed content

  • User: "What are the most common login bugs we've encountered?"

  • Jira Toolkit: "Based on your indexed project data, here are the most common login bugs:

    1. Session Timeout Issues: Multiple reports of users being logged out unexpectedly (EL-234, EL-287, EL-301)
    2. Password Reset Failures: Email delivery issues preventing password resets (EL-156, EL-189)
    3. Two-Factor Authentication Problems: Users unable to complete 2FA setup (CALC-EL, CALC-EL)

Sources: CALC-234 (Priority: High), CALC-287 (Status: Resolved), CALC-301 (Assignee: john.doe)"

Jira Search

  • User: "Retrieve from my collection tests related to profile setup"

  • Jira Toolkit: "Here are the tests related to profile setup from your indexed data:

    Test Cases Found: 1. User Profile Creation Test: Verify new user can create complete profile (CALC-445) 2. Profile Validation Test: Test profile field validation and error handling (CALC-446) 3. Profile Picture Upload Test: Test image upload functionality in user profiles (CALC-447)

    Setup Requirements: 1. Test user accounts with different permission levels 2. Valid and invalid profile data sets 3. Image files for upload testing (various formats and sizes)

Sources: CALC-445 (Test: Profile Creation), CALC-446 (Test: Validation), CALC-447 (Test: Image Upload)"

Jira Search

Troubleshooting & Tips

Common Errors and Solutions

"Authentication failed" or "Unauthorized access":

  • Verify your Jira credential has the correct API token
  • Ensure your token has appropriate permissions for the projects you want to index
  • Check that your token hasn't expired in your Atlassian account settings

"JQL query syntax error":

  • Verify your JQL syntax is correct using Jira's query builder
  • Common examples: project=PROJ, status IN (Open, Resolved), updated >= -4w
  • Test your JQL query directly in Jira before using it for indexing

"No issues indexed" or "Empty result set":

  • Check your JQL filter isn't too restrictive
  • Verify the project key is correct and case-sensitive
  • Try indexing without JQL filter first, then add restrictions
  • Ensure your account has permission to view the specified projects

"Vector database connection failed" or "PgVector errors":

  • Ensure PgVector is properly configured in Settings → AI Configuration
  • Verify the vector database is running and accessible
  • Check connection credentials and database permissions
  • Restart the vector database service if connection issues persist

"Attachment processing errors":

  • Large attachments may cause timeouts; consider using Skip Attachment Extensions
  • Binary files (executables, videos) should be excluded via Skip Attachment Extensions
  • Check available storage space for the vector database

Performance and Scope Considerations

For Large Jira Projects:

  • Use specific JQL filters: project=PROJ AND updated >= -12w (last 12 weeks)
  • Filter by issue type: project=PROJ AND issuetype IN (Bug, Story)
  • Set reasonable Max Total Issues limits: start with 500-1000 issues for testing
  • Consider indexing by project phases: current sprint, recent releases, archived items

Search Result Quality

If search returns few/no results:

  • Lower the cut-off score from 0.5 to 0.35 or 0.3
  • Increase search_top from 10 to 20 or 30
  • Try rephrasing your query with Jira-specific terms (issue keys, component names)
  • Verify the indexed content contains relevant information for your query

For better search quality:

  • Include both issue descriptions and attachments for comprehensive coverage
  • Use natural language queries rather than exact Jira field names
  • Leverage stepback search for complex project questions that require reasoning
  • Create separate indexes for different project types (development vs support, current vs archived)

Content-Specific Indexing Tips

For Software Development Projects:

  • Focus on bugs and stories: issuetype IN (Bug, Story, Task)
  • Include recent issues: updated >= -13w (last quarter)
  • Index both current and resolved issues for historical context

For Support and Helpdesk:

  • Include all issue types for comprehensive ticket history
  • Focus on resolved issues with solutions: status=Resolved AND resolution!=Duplicate
  • Consider including comments as they often contain valuable troubleshooting steps

For Project Management:

  • Include epics and high-level planning issues: issuetype IN (Epic, Initiative)
  • Index across multiple projects for portfolio-level insights
  • Include both active and completed projects for lessons learned

References

Related Documentation

For additional information and detailed setup instructions, see: