![]() ![]() Section in your prometheus.yml and restart your Prometheus instance: scrape_configs: ![]() To achieve this, add the following job definition to the scrape_configs Targets, while adding group="canary" to the second. This example, we will add the group="production" label to the first group of To model this in Prometheus, we can add several groups ofĮndpoints to a single job, adding extra labels to each group of targets. We will imagine that theįirst two endpoints are production targets, while the third one represents aĬanary instance. Three endpoints into one job called node. Now we will configure Prometheus to scrape these new targets. You should now have example targets listening on and Configure Prometheus to monitor the sample targets # Start 3 example targets in separate terminals: The Node Exporter is used as an example target, for more information on using it Let's add additional targets for Prometheus to scrape. To graph expressions, navigate to and use the "Graph"įor example, enter the following expression to graph the per-second rate of chunksīeing created in the self-scraped Prometheus: rate(prometheus_tsdb_head_chunks_created_total)Įxperiment with the graph range parameters and other settings. To count the number of returned time series, you could write: count(prometheus_target_interval_length_seconds)įor more about the expression language, see theĮxpression language documentation. Query: prometheus_target_interval_length_seconds If we are interested only in 99th percentile latencies, we could use this Labels designate different latency percentiles and target group intervals. Prometheus_target_interval_length_seconds, but with different labels. Recorded for each), each with the metric name This should return a number of different time series (along with the latest value ![]() Enter the below into the expression console and then click "Execute": prometheus_target_interval_length_seconds Prometheus_target_interval_length_seconds (the actual amount of time between One metric that Prometheus exports about itself is named and choose the "Table" view within the "Graph" tab.Īs you can gather from localhost:9090/metrics, Use Prometheus's built-in expression browser, navigate to Let us explore data that Prometheus has collected about itself. Localhost:9090/metrics Using the expression browser You can also verify that Prometheus is serving metrics about itself by Seconds to collect data about itself from its own HTTP metrics endpoint. You should also be able to browse to a status pageĪbout itself at localhost:9090. # By default, Prometheus stores its database in. To start Prometheus with your newly created configuration file, change to theĭirectory containing the Prometheus binary and run: # Start Prometheus. # Override the global default and scrape targets from this job every 5 seconds.įor a complete specification of configuration options, see theĬonfiguration documentation. # The job name is added as a label `job=` to any timeseries scraped from this config. # A scrape configuration containing exactly one endpoint to scrape: # external systems (federation, remote storage, Alertmanager). # Attach these labels to any time series or alerts when communicating with Scrape_interval: 15s # By default, scrape targets every 15 seconds. Prometheus configuration as a file named prometheus.yml: global: While a Prometheus server that collects only data about itself is not very Manner about itself, it can also scrape and monitor its own health. Since Prometheus exposes data in the same Prometheus collects metrics from targets by scraping metrics HTTPĮndpoints. Your platform, then extract and run it: tar xvfz prometheus-*.tar.gzīefore starting Prometheus, let's configure it. Downloading and running Prometheusĭownload the latest release of Prometheus for Then work with queries, rules, and graphs to use collected time Prometheus locally, configure it to scrape itself and an example application, This guide is a "Hello World"-style tutorial which shows how to install,Ĭonfigure, and use a simple Prometheus instance. Shutting down your instance gracefully.Configure rules for aggregating scraped data into new time series.Configure Prometheus to monitor the sample targets.Configuring Prometheus to monitor itself. ![]()
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