The Scenario
The migration ticket has been open for six weeks. Your team is finally ready to move a 200-dashboard Kibana instance to a new cluster — but nobody has a definitive list of what's actually in there.
You volunteered to build the inventory. Open Kibana. Click into Saved Objects. There are dashboards, visualizations, lenses, index patterns, maps — and the built-in export gives you a JSON blob that's not remotely usable as a planning document.
The bad version:
- Export the Saved Objects JSON, open it in a text editor, and try to parse which fields correspond to type, title, and ID across hundreds of nested objects.
- Paste fragments into a worksheet manually, realize you've missed the "last updated" timestamps, go back and repeat.
- Spend two hours reformatting before you have a single worksheet that the team can actually sort and filter.
That two hours belongs to migration planning, not data wrangling. The engineering lead is already asking for the triage sheet.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It connects to Kibana, reads the saved objects API, and writes the structured output directly to your workbook. You don't touch the JSON.
List all saved objects in Kibana—including dashboards, visualizations, and index patterns—and write each one to this sheet with columns for object type, title, ID, and last updated date.
What You Get
- Column A: object type (dashboard, visualization, lens, index-pattern, map, etc.)
- Column B: display title as it appears in Kibana
- Column C: saved object ID (the UUID you'll need for the migration scripts)
- Column D: last updated timestamp in ISO 8601 format
- One row per object, ready to sort by type or filter by date
What If the Data Is Not Quite Ready
The index patterns are missing from the export
Kibana's Saved Objects API returns different object types depending on the query. If your initial pull didn't capture index patterns separately:
Fetch all Kibana data views and paste their IDs, names, and index patterns into rows below the existing data in column A starting at the first empty row, without overwriting what's already there.
You need to flag deprecated index patterns for the team
The migration team wants to know which data views reference deprecated indices before they move anything:
Fetch all Kibana data views and paste their IDs, names, and index patterns into this sheet, then flag any data view whose index pattern contains 'deprecated-*' by marking column D as 'Review'.
You want a count of each object type for the migration estimate
Before committing to a timeline, you need to know how many of each type exist:
From the saved objects already in column A of this sheet, count how many objects exist for each type and write a summary table starting in column F with headers 'Object Type' and 'Count'.
Clean up, deduplicate, and produce the final migration triage sheet in one shot
Pull all Kibana saved objects into this sheet, remove any duplicate IDs, add a 'Status' column E defaulting to 'Migrate', flag any visualization whose title contains 'test' or 'temp' or 'old' by setting column E to 'Review', and sort the whole sheet by object type ascending.
The pattern is to fold cleanup and conditional logic into the same ask — you get a ready-to-use triage sheet without a second round of manual formatting.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook you're using to plan a Kibana migration or audit, then ask it to pull your full saved objects inventory. You can also see related approaches in Audit Kibana Detection Rules Into an Excel workbook or browse the full Kibana integration overview.