![]() ![]() Once the exporters are up and we added the configuration in Prometheus configuration file, it starts to scrape the metrics at the intervals defined in the configuration of Prometheus. There are multiple exporters are available for collecting system & application metrics.Īs I mentioned, it is very easy to configure the exporters. Node exporter and App exporters will listen on particular ports and Prometheus server initiate a HTTP call to this particular exporter and fetch system / app metrics from end points. Prometheus expects to retrieve metrics via HTTP calls done to certain endpoints that are defined in Prometheus configuration. Prometheus actively scrape targets in order to retrieve metrics from them. This is one of the noticeable difference between Prometheus monitoring and other time series database. Which means, Prometheus server originate connection to end servers and scrape the metrics from the remote servers. You can install and start Prometheus on Physical/VM servers as a standalone service or containerised setup. It is easy to setup the Prometheus server. The toolkit is highly customizable and designed to deliver rich metrics without creating a drag on system performance. Prometheus is one of the best monitoring toolkits for containers and micro services. Prometheus is an open-source systems monitoring and alerting toolkit. API call to monitor remote Prometheus exporters A quick introduction to Prometheus ![]() Different methods to monitor Prometheus exporters. Python script to monitor Prometheus exporters from Prometheus servers. How to monitor Prometheus exporters? Monitor application and node exporter, Prometheus. ![]()
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