Post Migration Report Improvements

Description
Improve the Post Migration Report generated after Xray Data Center -> Cloud migrations by including a project-level breakdown of migrated Xray entities instead of only aggregated totals.

Currently, the report provides only overall migration statistics, making it difficult to validate whether all expected data was migrated for each project.

The proposed enhancement is to include a table showing the number of migrated entities per project, such as:

• Tests
• Pre-Conditions
• Test Sets
• Test Executions
• Test Plans
• Test Runs
• Attachments
• Total Attachment Size

This would provide a clear and actionable migration validation report immediately after migration completion.

User friction
Customers performing migrations need to validate whether all expected data was migrated successfully.

Today, they must manually:

• Run SQL queries on Data Center.
• Generate custom reports.
• Compare source and target environments project by project.
• Cross-reference migration logs.

This process is time-consuming, error-prone, and particularly difficult for large migrations involving dozens or hundreds of projects.

Steps to reproduce / Actual Result:
1. Perform an Xray Data Center → Cloud migration.
2. Download the generated Post Migration Report.
3. Attempt to validate migrated data per project.

Actual Result:
The report only contains global migration statistics and execution times.
There is no visibility into:

• Which projects were migrated.
• How many entities were migrated per project.
• Whether specific projects contain missing data.

Users must perform additional manual validation outside the migration report.

IMPACT
Migration validation is one of the most critical post-migration activities.
Without project-level information:

• Validation requires significant manual effort.
• Support teams spend additional time assisting customers.
• Customers have less confidence in migration outcomes.
• Troubleshooting missing data becomes considerably harder.

What would improve if solved:

• Faster migration validation.
• Easier identification of missing or incomplete project migrations.
• Reduced need for SQL queries and manual comparisons.
• Improved customer confidence in migration results.
• Faster troubleshooting when discrepancies are found.

Impact on stakeholders:
Customers

• Simplified migration verification.
• Reduced validation effort.
• Better visibility into migration results.

Support Engineers

• Faster post-migration analysis.
• Reduced number of validation-related tickets.
• Easier troubleshooting of migration discrepancies.

Migration Team

• Improved migration transparency.
• Better migration success reporting.

Current workaround:
Customers and Support Engineers manually generate project-level statistics using:

• SQL queries.
• Xray reports.
• Custom scripts.
• Manual comparisons between the Data Center and Cloud.

CONTEXT & EXAMPLES:
A project-level summary table similar to the following would significantly improve migration validation:

This information could be generated either:

• Before migration (planned scope), or
• After migration (actual migrated data), preferably both.

Concrete example:
A customer migrating 150 projects notices that some Tests are missing in Cloud.
With the current report, they only know the total number of migrated entities.
With a project-level migration report, they could immediately identify:

• Which project has fewer Tests than expected.
• Whether Test Executions migrated correctly.
• Whether Attachments or Test Runs are missing from a specific project.

This would reduce investigation time from hours to minutes.

Workaround risk:
Manual validation:

• Consumes significant time.
• Requires database access and SQL knowledge.
• Increases the likelihood of human error.
• Becomes impractical for large enterprise migrations involving hundreds of projects and millions of Xray entities.