---
title: "Observability and Audit Logs: Who Changed What, and Why?"
slug: "observability-audit-log"
language: "en"
tags: ["감사 로그","sag 기술","아키텍처","플랫폼 운영"]
created: "2026-08-28T00:00:00.000Z"
published: "2026-10-08T10:11:35.279Z"
updated: "2026-10-08T10:11:42.446Z"
sample: false
---

# Observability and Audit Logs: Who Changed What, and Why?

## Definition in one sentence

**An audit log** is an operational record that tracks who or what changed state, the target, the before-and-after values, the time, and the correlation context.

> Key answer: Error logs alone make it difficult to explain which inputs and approval process led to a customer outcome. Recording excessive sensitive information is also risky.

## Why is this technology needed?

Error logs alone make it difficult to explain which inputs and approval process led to a customer outcome. Recording excessive sensitive information is also risky.

## How it works

Use request, job, and tenant correlation IDs in structured logs, and record business events in an append-only audit log. Minimize secrets and raw personal information.

When designing the system, do not consider accuracy alone. Define latency, cost, data boundaries, refresh cycles, and behavior on failure as well, so results can be reproduced in production. If automation is uncertain about a value, it is safer to leave it as unmeasured or requiring review rather than changing it to 0 or success.

## How this relates to SAG technology

SAG connects Goal creation, job execution, report revisions, expert approvals, and export events in tenant audit records. Result provenance and operational auditing are kept separate according to their purposes.

## Practical checklist

- Distinguish business events from system errors
- Remove sensitive values from logs
- Check whether activity can be traced from job execution through approval and export
- Distinguish the states for failures, empty results, and permission errors from success
- Revalidate before and after changes under the same conditions

## Research and official documentation

- [Official Google guide to AI features in Search](https://developers.google.com/search/docs/appearance/ai-features)

Reference documents support the underlying principles and recommendations. They do not guarantee search visibility, AI mentions, rankings, or revenue; the actual effects of implementation must be verified through observations of service data under the same conditions.

## Technical references by topic

- [OpenTelemetry tracing concepts](https://opentelemetry.io/docs/concepts/signals/traces/)


## How to continue reading about this technology

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

- [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)