Prometheus

https://img.shields.io/pypi/v/kpireport-prometheus
pip install kpireport-prometheus

The Prometheus plugin provides both a Datasource capable of returning PromQL query results and a View that summarizes alerts fired by the Prometheus server over the report interval.

Datasource

Show/hide example configuration YAML
datasources:
   prom:
      plugin: prometheus
      args:
         host: prometheus:9090
views:
   # Using Plot plugin to graph data
   server_load:
      plugin: plot
      title: Load
      args:
         datasource: prom
         query: |
         100 - (avg by(hostname) (irate(node_cpu_seconds_total{mode="idle"}[5m])) * 100

Alert summary

Show/hide example configuration YAML
critical_alerts:
   plugin: prometheus.alert_summary
   title: Critical alerts
   args:
      datasource: prom
      labels:
         severity: critical
warning_alerts:
   plugin: prometheus.alert_summary
   title: Warnings
   args:
      datasource: prom
      show_timeline: False
      labels:
         severity: warning
prometheus.alert_summary

An example rendered alert summary. The timeline at the top displays the points in time when any alert was firing over the report window. Individual alert labels are not shown; the view’s purpose is to highlight trends or patterns that can be looked at in more detail at the source.

API

class kpireport_prometheus.PrometheusDatasource(report, **kwargs)

Bases: kpireport.datasource.Datasource

Datasource that executes PromQL queries against a Prometheus server.

host

the hostname of the Prometheus server (may include port), e.g., https://prometheus.example.com:9090. If no protocol is given, “http://” is assumed.

Type

str

basic_auth

HTTP Basic Auth credentials to use when authenticating to the server. Must be a dictionary with username and password keys.

Type

dict

query(query: str, step='1h') pandas.core.frame.DataFrame

Execute a PromQL query against the Prometheus server.

Parameters
  • query (str) – the PromQL query

  • step (str) – the step size for the range query. The Datasource will execute a range query over the report window and capture all time series data within the report boundaries. The step size indicates the query resolution. A lower value provides more granularity but at the cost of a more expensive query and more data points to analyze. If your report window is significantly short, it may make sense to reduce this.

Returns

a table of time series results.

The timeseries value will be in a time column; any labels associated with the metric will be added as additional columns.

Return type

pandas.DataFrame

class kpireport_prometheus.PrometheusAlertSummary(report: Report, datasources: kpireport.datasource.DatasourceManager, **kwargs)

Bases: kpireport.view.View

Display a list of alerts that fired recently.

Supported output formats: html, md, slack

datasource

the ID of the Prometheus Datasource to query

Type

str

resolution

the size of the time window used to group alerts–the window is used to define buckets. A higher resolution is a lower time window (e.g., “5m” versus “1h”–“5m” is the higher resolution). Higher resolutions mean the timeline and time estimates for outage length will be more accurate, but may decrease performance when the report interval is large, as it requires pulling more data from Prometheus. (default "15m")

Type

str

hide_labels

a set of labels to hide from the output display. Alerts containing these labels will still be listed, but the label values will not be printed. (default ["instance", "job"])

Type

List[str]

labels

a set of labels that the alert must contain in order to be displayed (default None)

Type

Dict[str,str]

ignore_labels

a set of labels that the alert must _not_ contain in order to be displayed (default None)

Type

Dict[str,str]

show_timeline

whether to show a visual timeline of when alerts were firing (default True)

Type

bool

timeline_height

rendered height of the timeline in pixels (default 15)

Type

int

Changelog

0.0.1

Prelude

Initial commit.

New Features

  • Initial commit.