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varnish_main_client_req is an example of this, which provides the total number of HTTP requests that the varnish instance has handled in its life. Counters allow the value to either go up, stay the same or be reset to 0 (on a process restart). Counters - A cumulative, monotonic metric.The value may or may not have changed, but at every scrape_interval, there will be a new datapoint. This means that every 30s, there will be a new data point with a new timestamp. The setting for when the intervals should occur is specified by the scrape_interval in the prometheus.yaml config. Prometheus scrapes these metrics at regular intervals. See Range Selectors below for further information on this.Īll of these metrics are scraped from exporters. The instant vector and range vector are two of four types of expression language the final two are scalar, a simple numeric floating point value, and string, a simple string value. These are generated by appending a time selector to the instant-vector in square brackets (e.g.
LABEL MATRIX 7 SLOW CONNECTING TO DATABSE SERIES
If each series has multiple values, it is referred to as a range-vector. If each series only has a single value for each timestamp, as in the above example, the collection of series returned from a query is called an instant-vector. The timestamp doesn’t appear in the query console, but if you switch to the Graph tab within Prometheus, you can see the values for each timestamp in the chart.Įach distinct metric_name & label combination is called a time-series (often just called a series in the documentation). The timestamp, which has millisecond precision.
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When querying in the Prometheus console, the value shown is the value for the most recent timestamp collected. Each metric will have at least a job label, which corresponds to the scrape config in the prometheus config. One or more labels, which are simply key-value pairs that distinguish each metric with the same name (e.g.Taking the varnish_main_client_req metric as an example: Indeed, all Prometheus metrics are time based data. The core part of any query in PromQL are the metric names of a time-series. Through query building, you will end up with a graph per CPU by the deployment. A data visualization and monitoring tool, either within Prometheus or an external one, such as Grafana.Prometheus server port forwarded from the local connection.
LABEL MATRIX 7 SLOW CONNECTING TO DATABSE HOW TO
This article is a primer dedicated to the basics of how to run Prometheus queries. PromQL can be a difficult language to understand, particularly if you are faced with an empty input field and are having to come up with the formation of queries on your own. The result of each expression can be shown either as a graph, viewed as tabular data within Prometheus’ own expression browser, or consumed via external systems via the HTTP API. It is a powerful functional expression language, which lets you filter with Prometheus’ multi-dimensional time-series labels. Prometheus has its own language specifically dedicated to queries called PromQL.