Nightingale (n9e) Query Datasource Data

Query monitoring metrics, logs, and time-series data from various datasources on the Nightingale monitoring platform.

Based on the datasource type the user needs, read the corresponding file under the datasources/ directory to get the query method and parameter format:

datasources/prometheus.md - Prometheus / VictoriaMetrics metric queries (PromQL)
datasources/elasticsearch.md - Elasticsearch log queries (ES DSL / Lucene)
datasources/loki.md - Loki log queries (LogQL)
datasources/clickhouse.md - ClickHouse metric/log queries (SQL)
datasources/mysql.md - MySQL metric queries (SQL)
datasources/pgsql.md - PostgreSQL metric queries (SQL)
datasources/tdengine.md - TDengine time-series queries (SQL)
datasources/doris.md - Doris log queries (SQL)
datasources/opensearch.md - OpenSearch log queries (ES DSL)
datasources/victorialogs.md - VictoriaLogs log queries (LogsQL)

Prerequisites

The user needs to provide:

n9e address: e.g. http://<n9e-host>:<port>
Username/password: e.g. <username>/<password>
Query requirement description: e.g. "query CPU usage over the last hour", "search logs containing error"

If the user has not provided the above information, use the AskUserQuestion tool to ask.

Execution Steps

Step 1: Log in to obtain a Token

POST /api/n9e/auth/login
Content-Type: application/json
Body: {"username":"<username>","password":"<password>"}

Extract dat.access_token from the response, and include Authorization: Bearer <token> in all subsequent requests.

Step 2: Query available datasources

Retrieve the datasource list to determine the datasource ID and type to query:

POST /api/n9e/datasource/list
Authorization: Bearer <token>
Content-Type: application/json
Body: {}

Each datasource in the response contains id, name, and plugin_type.

If the user has not specified a datasource, use the AskUserQuestion tool to display the available datasources and let the user choose.

Step 3: Run the query based on the datasource type

Based on the datasource's plugin_type, read the corresponding datasources/*.md file to get the query API and parameter format.

Step 4: Format the output

Present the query result to the user as a readable Markdown table or list.

Datasource Type Quick Reference

plugin_type	Datasource	Query Language	Use Case	Reference File
`prometheus`	Prometheus / VictoriaMetrics	PromQL	Metric/time-series query	prometheus.md
`elasticsearch`	Elasticsearch	ES DSL / Lucene	Log query	elasticsearch.md
`opensearch`	OpenSearch	ES DSL / Lucene	Log query	opensearch.md
`loki`	Loki	LogQL	Log query	loki.md
`ck`	ClickHouse	SQL	Metric/log query	clickhouse.md
`mysql`	MySQL	SQL	Metric query	mysql.md
`pgsql`	PostgreSQL	SQL	Metric query	pgsql.md
`tdengine`	TDengine	SQL	Time-series query	tdengine.md
`doris`	Doris	SQL	Log query	doris.md
`victorialogs`	VictoriaLogs	LogsQL	Log query	victorialogs.md

Generic Proxy API

All datasources can access their native APIs through the generic proxy:

<ANY_METHOD> /api/n9e/proxy/<datasource_id>/<native API path>
Authorization: Bearer <token>

For example:

Prometheus: /api/n9e/proxy/1/api/v1/query?query=up
Elasticsearch: /api/n9e/proxy/2/_cat/health
Loki: /api/n9e/proxy/3/loki/api/v1/labels

Generic Time-Series Query API

All datasources (except Prometheus) can use the unified time-series query endpoint:

POST /api/n9e/ds-query
Authorization: Bearer <token>
Content-Type: application/json

json

{
  "cate": "<plugin_type>",
  "datasource_id": 1,
  "query": [<query object>]
}

Generic log query endpoint:

POST /api/n9e/logs-query
Authorization: Bearer <token>
Content-Type: application/json

json

{
  "cate": "<plugin_type>",
  "datasource_id": 1,
  "query": [<query object>]
}

The exact structure of the query object varies by datasource type; see each datasource file for details.

Generic Metadata API for SQL-type Datasources

ClickHouse, MySQL, PostgreSQL, and Doris share the following metadata query endpoints:

POST /api/n9e/db-databases     // List databases
POST /api/n9e/db-tables        // List tables
POST /api/n9e/db-desc-table    // View table structure

TDengine uses dedicated endpoints:

POST /api/n9e/tdengine-databases
POST /api/n9e/tdengine-tables
POST /api/n9e/tdengine-columns

Key Considerations

Query the datasource list first to get the ID: All queries require a datasource_id; obtain it first via POST /api/n9e/datasource/list
SQL queries are read-only: SQL-type datasources prohibit write operations such as CREATE, INSERT, UPDATE, DELETE, ALTER, DROP
Time variables: In SQL queries, use $from and $to to represent the time range; the system replaces them automatically
keys field: Time-series queries must specify valueKey (numeric column) and labelKey (grouping column); separate multiple columns with spaces
Unified response format: All API responses are wrapped in a {"dat": <data>} structure