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1 change: 1 addition & 0 deletions SUMMARY.md
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* [UDP](pipeline/outputs/udp.md)
* [Vivo Exporter](pipeline/outputs/vivo-exporter.md)
* [WebSocket](pipeline/outputs/websocket.md)
* [ZeroBus](pipeline/outputs/zerobus.md)

## Stream processing

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---
description: Send logs to Databricks via ZeroBus

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---

# ZeroBus

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{% hint style="info" %}
**Supported event types:** `logs`
{% endhint %}

The _ZeroBus_ output plugin lets you ingest log records into a [Databricks](https://www.databricks.com/) table through the ZeroBus streaming ingestion interface. Records are converted to JSON and sent via the ZeroBus SDK using gRPC.

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Before you begin, you need a Databricks workspace with a Unity Catalog table configured for ZeroBus ingestion, and an OAuth2 service principal (client ID and client secret) with appropriate permissions.

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## Configuration parameters

| Key | Description | Default |
| :--- | :--- | :--- |
| `endpoint` | ZeroBus gRPC endpoint URL. If no scheme is provided, `https://` is automatically prepended. | _none_ |

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| `workspace_url` | Databricks workspace URL. If no scheme is provided, `https://` is automatically prepended. | _none_ |

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| `table_name` | Fully qualified Unity Catalog table name in `catalog.schema.table` format. | _none_ |
| `client_id` | OAuth2 client ID for authentication. | _none_ |

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| `client_secret` | OAuth2 client secret for authentication. | _none_ |

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| `add_tag` | If enabled, the Fluent Bit tag is added as a `_tag` field in each record. | `true` |
| `time_key` | Key name for the injected timestamp. The timestamp is formatted as RFC 3339 with nanosecond precision. Set to an empty string to disable timestamp injection. | `_time` |
| `log_key` | Comma-separated list of record keys to include in the output. When unset, all keys are included. | _none_ |
| `raw_log_key` | If set, the full original record (before filtering by `log_key`) is stored as a JSON string under this key name. | _none_ |

## Get started

To send log records to Databricks via ZeroBus, configure the plugin with your ZeroBus endpoint, workspace URL, table name, and OAuth2 credentials.

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### Configuration file

{% tabs %}
{% tab title="fluent-bit.yaml" %}

```yaml
pipeline:
inputs:
- name: tail
tag: app.logs
path: /var/log/app/*.log

outputs:
- name: zerobus
match: '*'
endpoint: https://<workspace-id>.zerobus.<region>.cloud.databricks.com
workspace_url: https://<instance-name>.cloud.databricks.com
table_name: catalog.schema.logs
client_id: <your-client-id>
client_secret: <your-client-secret>
```

{% endtab %}
{% tab title="fluent-bit.conf" %}

```text
[INPUT]
Name tail
Tag app.logs
Path /var/log/app/*.log

[OUTPUT]
Name zerobus
Match *
Endpoint https://<workspace-id>.zerobus.<region>.cloud.databricks.com
Workspace_Url https://<instance-name>.cloud.databricks.com
Table_Name catalog.schema.logs
Client_Id <your-client-id>
Client_Secret <your-client-secret>
```

{% endtab %}
{% endtabs %}

### Record format

Each log record is converted to a JSON object before ingestion. The plugin applies the following transformations in order:

1. If `raw_log_key` is set, the full original record is captured as a JSON string before any filtering.
2. If `log_key` is set, only the specified keys are included in the output record.
3. If `raw_log_key` is set, the captured JSON string is injected under the configured key (unless a key with that name already exists).
4. If `time_key` is set, a timestamp in RFC 3339 format with nanosecond precision (for example, `2024-01-15T10:30:00.123456789Z`) is injected (unless a key with that name already exists).
5. If `add_tag` is enabled, the Fluent Bit tag is injected as `_tag` (unless a key with that name already exists).
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For example, given the following input record:

```json
{"level": "info", "message": "request completed", "status": 200}
```

The default configuration produces:

```json
{
"level": "info",
"message": "request completed",
"status": 200,
"_time": "2024-01-15T10:30:00.123456789Z",
"_tag": "app.logs"
}
```

### Filtering keys

Use `log_key` to select specific fields from the record. Combined with `raw_log_key`, you can send a filtered record while preserving the original data:

{% tabs %}
{% tab title="fluent-bit.yaml" %}

```yaml
pipeline:
outputs:
- name: zerobus
match: '*'
endpoint: https://<workspace-id>.zerobus.<region>.cloud.databricks.com
workspace_url: https://<instance-name>.cloud.databricks.com
table_name: catalog.schema.logs
client_id: <your-client-id>
client_secret: <your-client-secret>
log_key: level,message
raw_log_key: _raw
```

{% endtab %}
{% tab title="fluent-bit.conf" %}

```text
[OUTPUT]
Name zerobus
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Match *
Endpoint https://<workspace-id>.zerobus.<region>.cloud.databricks.com
Workspace_Url https://<instance-name>.cloud.databricks.com
Table_Name catalog.schema.logs
Client_Id <your-client-id>
Client_Secret <your-client-secret>
Log_Key level,message
Raw_Log_Key _raw
```

{% endtab %}
{% endtabs %}

This produces:

```json
{
"level": "info",
"message": "request completed",
"_raw": "{\"level\":\"info\",\"message\":\"request completed\",\"status\":200}",
"_time": "2024-01-15T10:30:00.123456789Z",
"_tag": "app.logs"
}
```
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