Prometheus Agent

The Prometheus Agent provides an intelligent interface for querying and analyzing Prometheus metrics. It translates natural language queries into PromQL, handles authentication, and processes time-series data while maintaining Prometheus-specific optimizations.

Prometheus Agent workflow and architecture

Configuration Parameters

Required Input Parameters

prometheus_url: Prometheus server URL
username: Authentication username
password: Authentication password
query: Natural language or PromQL query

Optional Configuration

llm: Language model configuration
- model_name: Model identifier
- temperature: Response creativity
- max_tokens: Response length limit
query_params: Query configuration
- time_range: Query time window
- step: Query resolution
- timeout: Query timeout

Output Format

{
  "query_response": {
    "status": "success" | "error",
    "data": {
      "resultType": "matrix" | "vector" | "scalar" | "string",
      "result": [
        {
          "metric": {
            "name": string,
            "labels": object
          },
          "values": [
            [timestamp, value]
          ]
        }
      ]
    },
    "stats": {
      "timings": {
        "query_time": number,
        "execution_time": number
      },
      "samples": {
        "total": number,
        "filtered": number
      }
    },
    "metadata": {
      "promql": string,
      "query_range": {
        "start": string,
        "end": string,
        "step": string
      },
      "warnings": array
    },
    "analysis": {
      "summary": string,
      "trends": array,
      "anomalies": array,
      "recommendations": array
    }
  }
}

Features

Natural language to PromQL translation
Time-series data analysis
Query optimization
Performance monitoring
Metric exploration
Alert analysis
Trend detection
Anomaly identification

Note: Consider query time ranges and resolution carefully. Large time ranges with small step values can impact performance.

Tip: Use specific metric names and labels in queries for better performance. Enable analysis features for deeper insights.

Example Usage

const prometheusAgent = new PrometheusAgent({
  prometheus_url: "https://prometheus.example.com",
  username: "prom_user",
  password: "****",
  llm: {
    model_name: "gpt-4",
    temperature: 0.3
  },
  query_params: {
    time_range: "1h",
    step: "1m",
    timeout: "30s"
  }
});

const response = await prometheusAgent.query({
  query: "Show me CPU usage across all nodes for the last hour"
});