This repository contains an implementation of the Kubernetes custom metrics API (custom.metrics.k8s.io/v1beta1), suitable for use with the autoscaling/v2 Horizontal Pod Autoscaler in Kubernetes 1.6+.

The adapter takes the standard Kubernetes generic API server arguments (including those for authentication and authorization). By default, it will attempt to using Kubernetes in-cluster config to connect to the cluster.

It takes the following addition arguments specific to configuring how the adapter talks to Prometheus and the main Kubernetes cluster:

• --lister-kubeconfig=<path-to-kubeconfig>: This configures how the adapter talks to a Kubernetes API server in order to list objects when operating with label selectors. By default, it will use in-cluster config.

• --metrics-relist-interval=<duration>: This is the interval at which to update the cache of available metrics from Prometheus.

• --rate-interval=<duration>: This is the duration used when requesting rate metrics from Prometheus. It must be larger than your Prometheus collection interval.

• --prometheus-url=<url>: This is the URL used to connect to Prometheus. It will eventually contain query parameters to configure the connection.

The adapter gathers the names of available metrics from Prometheus a regular interval (see Configuration above), and then only exposes metrics that follow specific forms.

In general:

• Metrics must have the namespace label to be considered.

• For each label on a metric, if that label name corresponds to a Kubernetes resource (like pod or service), the metric will be associated with that resource.

• Metrics ending in _total are assumed to be cumulative, and will be exposed without the suffix as a rate metric.

Detailed information can be found under docs/format.md.

A brief walkthrough exists in docs/walkthrough.md.

Additionally, @luxas has an excellent example deployment of Prometheus, this adapter, and a demo pod which serves a metric http_requests_total, which becomes the custom metrics API metric pods/http_requests. It also autoscales on that metric using the autoscaling/v2beta1 HorizontalPodAutoscaler.

It can be found at https://github.com/luxas/kubeadm-workshop. Pay special attention to:

• Deploying the Prometheus Operator
• Setting up the custom metrics adapter and sample app