The Scenario
Finance sent a note this morning: cloud storage costs came in 23% over budget last quarter and they want an itemized breakdown of what is in Yandex Object Storage before the budget review call on Friday. Your DevOps team has been spinning up buckets across three teams for two years with no central registry. Nobody knows exactly how many there are or what they contain.
You have API access. You do not have a tidy inventory anywhere.
The bad version:
- Open the Yandex Cloud console, navigate to Object Storage, manually count and note down each bucket name and creation date
- Open a separate tab, check the access keys panel, come back, realize the console does not show size information on the main bucket list — you would need to drill into each one
- Copy the list into a workbook by hand, realize you missed four buckets that are in a different folder, start over
The call is Friday. This is Wednesday afternoon.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. Through the Yandex integration, it can call the Object Storage bucket listing API and write every bucket — name, creation date, and any available region or size metadata — directly into your workbook.
List all Yandex Object Storage buckets in our account and write bucket name and creation date into columns A and B of this worksheet. One row per bucket. Add a header row.
What You Get
- Row 1: headers — Bucket Name, Creation Date
- One row per bucket returned by the API
- Creation date in the format Yandex returns it
- If size or region data is available in the API response, you can ask for those in the same prompt — SheetXAI will write them into additional columns
What If the Data Is Not Quite Ready
Include region and size data where available
The finance team specifically wants to know which buckets are in which region — cost rates differ by region.
Fetch all Yandex Object Storage buckets and write bucket name, creation date, and region into columns A through C. If size data is available in the API response, write it into column D. One row per bucket.
Flag buckets created before a specific date as candidates for review
Any bucket created before January 2024 predates the current team's storage policy and should be reviewed.
List all Yandex Object Storage buckets and write name and creation date into columns A and B. In column C, write "Pre-policy — review" for any bucket created before 2024-01-01, and "Current" for all others.
Cross-reference the bucket list against a known-active registry
You have a second worksheet, Active Registry, listing the buckets your team currently acknowledges as intentional. Anything in Object Storage that is not on that list is potentially orphaned.
List all Yandex Object Storage buckets and write bucket names into column A of the Audit worksheet. Then for each bucket name in column A, check whether it appears in column A of the Active Registry worksheet. Write "Registered" in column B if it matches, and "Unregistered — investigate" if it does not.
Pull bucket list, sort by creation date oldest-first, flag pre-policy buckets, and add a running count in one pass
The output format finance wants is oldest-first, with a sequential index for easy reference on the call.
Fetch all Yandex Object Storage buckets. Sort by creation date ascending. Write a sequential row number into column A, bucket name into column B, creation date into column C, and region into column D. In column E, flag any bucket created before 2024-01-01 as "Legacy" and the rest as "Current". Start at row 2 with a header row at row 1.
That is the workbook you bring to the Friday call, not a starting point for more manual work.
Try It
Get the 7-day free trial of SheetXAI and open the Excel workbook where you are building the storage inventory, then ask it to pull the full bucket list and flag anything that predates your current storage policy. See also: auditing Metrica access grants and verifying Yandex Disk links.