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prometheus-sql's Introduction

Prometheus SQL

GoDoc

Service that generates basic metrics for SQL result sets and exposing them as Prometheus metrics.

This service relies on the SQL Agent service to execute and return the SQL result sets.

Behavior

  • Static configuration files are used to define the queries to monitor.
  • Each query has a designated worker for execution.
  • An interval is used to define how often to execute the query.
  • Failed queries are automatically retried using a backoff mechanism.
  • Faceted metrics are supported.
  • A single metric's different facets can be filled in from different data sources.

Format

  • Metric names are exposed in the format query_result_<metric name>.
  • With faceted metrics, the name of the data column is determined by the data-field key in config, and all other columns (and column values) are exposed as labels.
  • If the result set consists of a single row and column, the metric value is obvious and data-field is not needed.
  • Label names under the same metric should be consistent.
  • Each different query (query entry in config) for the same metric should lead to different label values.

Build

Build directly via console

  1. Get project dependencies:

    go get -d
  2. Build via console:

    go build

Build with Docker

  1. Build Docker image:

    docker build -t dbhi/prometheus-sql .

Build with Docker insida a Vagrant box

  1. Start VM with Vagrant:

    vagrant up
  2. Login as vagrant user with password vagrant

  3. Build Docker image inside VM:

    docker build -t dbhi/prometheus-sql .

Usage

Usage of prometheus-sql:
  -host string
        Host of the service.
  -port int
        Port of the service. (default 8080)
  -queries string
        Path to file containing queries. (default "queries.yml")
  -queryDir string
        Path to directory containing queries.
  -service string
        Query of SQL agent service.

Queries file

A queries file is required for the application to know which data source to query and which queries that shall be monitored.

In the repository there is an example file that you can have a look at.

Run via console

Create a queries.yml file in the current directory and run the following:

prometheus-sql

or for an alternate path, use the -queries or the -queryDir option:

prometheus-sql -queries /path/to/queries.yml

Run using Docker

Run the SQL agent service.

docker run -d --name sqlagent dbhi/sql-agent

Run this service. Mount the queries.yml file and link the SQL Agent service.

docker run -d \
    -p 8080:8080 \
    -v /path/to/queries.yml:/queries.yml \
    --link sqlagent:sqlagent \
    dbhi/prometheus-sql

To view a plain text version of the metrics, open up the browser to the http://localhost:8080/metrics (or http://192.168.59.103:8080/metrics for boot2docker users).

Run using a Docker Compose file

Alternately, use the docker-compose.yml file included in this repository. The volumes section be added for mounting the queries.yml file.

prometheus-sql's People

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