---
title: "Idempotency, Job Queues, and Usage Ledgers: Operational Design That Preserves Results Across Retries"
slug: "idempotency-jobs-usage-ledger"
language: "en"
tags: ["멱등성","작업 큐","사용량 원장","운영","플랫폼 운영"]
created: "2026-09-28T00:00:00.000Z"
published: "2026-10-08T10:17:08.767Z"
updated: "2026-10-08T10:17:13.877Z"
sample: false
---

# Idempotency, Job Queues, and Usage Ledgers: Operational Design That Preserves Results Across Retries

## Production services receive the same request multiple times

A user may click a button twice, or a network interruption may cause the client to resend a request. A serverless function may also be restarted after terminating partway through processing. In these environments, if a single request results in two jobs or a double deduction of usage, it becomes difficult to trust the outcome.

Idempotency is the property that repeated requests expressing the same intent produce their final effect only once. SAG associates a logical idempotency key with creation and execution requests, and returns the existing result when that key is already being processed or has been completed.

## Manage job states explicitly

For inspections that take a long time, it is safer to hand them off to a job queue and manage their state rather than trying to complete them within the request.

- queued: waiting to run
- running: being processed by a worker
- succeeded: the result and settlement are complete
- failed: a failure that can be retried
- dead-letter: the automatic retry limit has been exceeded and operational review is required

State transitions must be handled atomically in the database so that two workers do not pick up the same job at the same time. Recording the retry count and next execution time as well also makes it possible to distinguish temporary external outages from persistent errors.

## Record usage in a ledger, not as a single value

If you simply overwrite the current usage number, it is difficult to determine when and through which job it increased. A usage ledger records reservations, confirmations, and cancellations as separate entries. Reserve against the limit when a job starts, confirm the reservation if it succeeds, and roll it back if it fails before execution. Settlement for the same job key is allowed only once.

## Operational validation, including failures

In addition to successful cases, test duplicate submissions, worker conflicts, limit breaches, retries after failures, and repeated requests after completion. Idempotency and ledgers are not visible features to users, but they are key architectural safeguards against operational incidents like “I clicked the button once—why was I charged twice?”

## Technical references by topic

- [PostgreSQL Transaction Isolation](https://www.postgresql.org/docs/current/transaction-iso.html)


## How to continue exploring this technology

Explore tenant permissions, job retries, caches, and approval history.

- [Designing a reliable customer space](/ko/blog?tag=%ED%94%8C%EB%9E%AB%ED%8F%BC%20%EC%9A%B4%EC%98%81)
- [Feature Guide FAQ](/en/faq)