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Kapacitor

An Open-Source Time Series ETL and Alerting Engine

Kapacitor is an open-source framework built by the folks over at InfluxData and written in Go for processing, monitoring, and alerting on time series data

QuickStart

$ helm install stable/kapacitor --name foo --namespace bar

Introduction

This chart bootstraps A Kapacitor deployment and service on a Kubernetes cluster using the Helm Package manager.

Prerequisites

  • Kubernetes 1.4+
  • PV provisioner support in the underlying infrastructure (optional)

Installing the Chart

To install the chart with the release name my-release:

$ helm install --name my-release stable/kapacitor

The command deploys Kapacitor on the Kubernetes cluster in the default configuration. The configuration section lists the parameters that can be configured during installation.

Tip: List all releases using helm list

Uninstalling the Chart

To uninstall/delete the my-release deployment:

$ helm delete my-release --purge

The command removes all the Kubernetes components associated with the chart and deletes the release.

Configuration

The configurable parameters of the Kapacitor chart and the default values are listed in values.yaml.

The full image documentation contains more information about running Kapacitor in docker.

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

$ helm install --name my-release \
  --set influxURL=http://myinflux.mytld:8086,persistence.enabled=true \
    stable/kapacitor

The above command enables persistence and changes the size of the requested data volume to 200GB.

Alternatively, a YAML file that specifies the values for the parameters can be provided while installing the chart. For example,

$ helm install --name my-release -f values.yaml stable/kapacitor

Tip: You can use the default values.yaml

Persistence

The Kapacitor image stores data in the /var/lib/kapacitor directory in the container.

The chart optionally mounts a Persistent Volume volume at this location. The volume is created using dynamic volume provisioning.