Time-series-based monitoring with Prometheus

Lighting Up the Dark

Target Practice

Monitoring only yourself doesn't make much sense. Targets for Prometheus are stored in the prometheus.yml file. If the file is not in the program directory, you can pass in the path to the file to your distributed monitoring system with the -config.file option. To query the metrics of a node_exporter running locally, you would add the following definition to the scrape_configs section:

- job_name: 'node'
    - targets: ['localhost:9100']

You can add more instances by expanding the list of targets (e.g., ['localhost:9100', '',]). You can stipulate other types of jobs, such as instrumented applications or other exporters, as separate job_name sections.


In environments with short-lived instances, such as Docker or Kubernetes, you would not copy the instances manually to a configuration file. Another Prometheus feature, service discovery, can help. The monitoring software independently discovers monitoring targets for Azure, the Google Container Engine (GKE), Amazon Web Services (AWS), or Kubernetes. The entire list, configuration parameters, and formats are available online [15].

File-based service discovery plays a special role: It parses all the pattern-matching files listed in prometheus.yml. Prometheus automatically detects changes to the files. With this mechanism, you can tap into configuration tools such as Ansible – only your imagination sets the limits.


As a diagram of the project architecture shows [16], Prometheus takes care of querying the targets and saving the metrics in a (local) time series database. Furthermore, it comes with the intelligent PromQL query language that lets you query stored metrics for visualization, aggregation, and alerting.

Prometheus forwards alerts to the alert manager, which can deduplicate and mute the alerts (e.g., during maintenance windows). The manager then uses email, Slack, or a generic webhook to forward the alerts to the admin.

The Pushgateway is another component that fields and caches results from short-lived programs. Prometheus can receive metrics sent from batch jobs, as well.

To replace the built-in web interface referred to earlier, Grafana [17], which is not associated with the Prometheus project, can be used for more elaborate dashboards (see also the article on Grafana in this issue). Grafana is now regarded as the standard tool for visualization and dashboards and already offers a wide variety of prebuilt dashboards for Prometheus that you can import into your own Grafana installation [18]. Figure 3 shows one that I use to monitor my VDSL Internet connection [19].

Figure 3: Example of a Grafana dashboard with Prometheus metrics.

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