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docs: add AI Bridge structured log record types and monitoring cross-link (#23979)

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## What

Two small docs improvements for AI Bridge:

1. **`setup.md` – Structured Logging section**: Added a `record_type`
table documenting the six event types emitted by AI Bridge structured
logs (`interception_start`, `interception_end`, `token_usage`,
`prompt_usage`, `tool_usage`, `model_thought`) along with their key
fields. Previously only the `"interception log"` message prefix was
mentioned.

2. **`monitoring.md`**: Added a "Structured Logging" section that
cross-links to `setup.md#structured-logging`, so users landing on the
monitoring page can discover the feature without navigating to the setup
guide first.

<details><summary>Source reference</summary>

Record types and fields were extracted from
`enterprise/aibridgedserver/aibridgedserver.go` where they are emitted
as `slog.F("record_type", "...")` string literals under the
`InterceptionLogMarker` (`"interception log"`) message.

</details>
This commit is contained in:
Jiachen Jiang
2026-04-08 08:57:17 -07:00
committed by GitHub
parent b969d66978
commit c2592c9f12
2 changed files with 18 additions and 1 deletions
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docs/ai-coder/ai-bridge/monitoring.md
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@@ -10,6 +10,13 @@ We provide an example Grafana dashboard that you can import as a starting point
These logs and metrics can be used to determine usage patterns, track costs, and evaluate tooling adoption.
## Structured Logging
AI Bridge can emit structured logs for every interception event to your
existing log pipeline. This is useful for exporting data to external SIEM or
observability platforms. See [Structured Logging](./setup.md#structured-logging)
in the setup guide for configuration and a full list of record types.
## Exporting Data
AI Bridge interception data can be exported for external analysis, compliance reporting, or integration with log aggregation systems.
docs/ai-coder/ai-bridge/setup.md
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@@ -150,4 +150,14 @@ ingestion, set `--log-json` to a file path or `/dev/stderr` so that records are
emitted as JSON.
Filter for AI Bridge records in your logging pipeline by matching on the
`"interception log"` message.
`"interception log"` message. Each log line includes a `record_type` field that
indicates the kind of event captured:
| `record_type` | Description | Key fields |
|----------------------|-----------------------------------------|--------------------------------------------------------------------------------|
| `interception_start` | A new intercepted request begins. | `interception_id`, `initiator_id`, `provider`, `model`, `client`, `started_at` |
| `interception_end` | An intercepted request completes. | `interception_id`, `ended_at` |
| `token_usage` | Token consumption for a response. | `interception_id`, `input_tokens`, `output_tokens`, `created_at` |
| `prompt_usage` | The last user prompt in a request. | `interception_id`, `prompt`, `created_at` |
| `tool_usage` | A tool/function call made by the model. | `interception_id`, `tool`, `input`, `server_url`, `injected`, `created_at` |
| `model_thought` | Model reasoning or thinking content. | `interception_id`, `content`, `created_at` |