The Problem
To control storage spend, organizations move infrequently accessed data to cold tiers like S3 Glacier and Deep Archive. The complication comes when users need it back: restoring large volumes can cost thousands of dollars in a single operation, so systems block the action until someone authorizes it. Users hit a permission error listing object count, size, and estimated cost – and open a ticket.
The balance is delicate: avoid blanket approvals that inflate cloud costs, without delaying legitimate research.
The Solution
The restore-approval agent manages the workflow end to end:
- If the user already ran the restore and pasted the error (objects, size, estimated cost), the agent extracts the figures from the ticket text.
- It compares them against predefined cost and size thresholds and decides whether to grant automatically or require manager approval. If approval is needed, it tags the designated manager on the ticket.
- If the user opened a ticket without the figures, the agent gives precise instructions to run the restore first and capture the error, so the workflow can proceed.
- Ticket status is updated throughout while awaiting replies – no manual overhead for support.
How It Works in Practice
- A user opens a ticket, with or without cost and size metrics.
- The agent checks for the required data and gives guidance if it’s missing.
- With data present, it compares against thresholds to decide whether manager approval is required.
- On approval, permissions are granted automatically and the ticket is updated.
The Results
Multiple rounds of back-and-forth between users, support, and managers became a structured, largely automated workflow. No expensive restore happens without explicit approval documented on the ticket – and small, cheap requests proceed without administrative delay.
Why It’s Worth Talking About
An agent orchestrating a real cost-based approval: structured extraction from free text, threshold-based financial logic, and targeted human escalation precisely where money is involved.
