Prometheus Adapter for Kubernetes Metrics APIs

This repository contains an implementation of the Kubernetes Custom, Resource and External Metric APIs.

This adapter is therefore suitable for use with the autoscaling/v2 Horizontal Pod Autoscaler in Kubernetes 1.6+.
It can also replace the metrics server on clusters that already run Prometheus and collect the appropriate metrics.

Quick Links

• Config walkthrough and config reference.
• End-to-end walkthrough
• Deployment info and files

Installation

If you're a helm user, a helm chart is listed on prometheus-community repository as prometheus-community/prometheus-adapter.

To install it with the release name my-release, run this Helm command:

For Helm2

$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm repo update
$ helm install --name my-release prometheus-community/prometheus-adapter

For Helm3 ( as name is mandatory )

$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm repo update
$ helm install my-release prometheus-community/prometheus-adapter

Official images

All official images for releases after v0.8.4 are available in registry.k8s.io/prometheus-adapter/prometheus-adapter:$VERSION. The project also maintains a staging registry where images for each commit from the master branch are published. You can use this registry if you need to test a version from a specific commit, or if you need to deploy a patch while waiting for a new release.

Images for versions v0.8.4 and prior are only available in unofficial registries:

• https://quay.io/repository/coreos/k8s-prometheus-adapter-amd64
• https://hub.docker.com/r/directxman12/k8s-prometheus-adapter/

Configuration

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 additional 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. By default, this value is set to 10 minutes.

• --metrics-max-age=<duration>: This is the max age of the metrics to be loaded from Prometheus. For example, when set to 10m, it will query Prometheus for metrics since 10m ago, and only those that has datapoints within the time period will appear in the adapter. Therefore, the metrics-max-age should be equal to or larger than your Prometheus' scrape interval, or your metrics will occaisonally disappear from the adapter. By default, this is set to be the same as metrics-relist-interval to avoid some confusing behavior (See this PR).

  Note: We recommend setting this only if you understand what is happening. For example, this setting could be useful in cases where the scrape duration is over a network call, e.g. pulling metrics from AWS CloudWatch, or Google Monitoring, more specifically, Google Monitoring sometimes have delays on when data will show up in their system after being sampled. This means that even if you scraped data frequently, they might not show up soon. If you configured the relist interval to a short period but without configuring this, you might not be able to see your metrics in the adapter in certain scenarios.

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

• --config=<yaml-file> (-c): This configures how the adapter discovers available Prometheus metrics and the associated Kubernetes resources, and how it presents those metrics in the custom metrics API. More information about this file can be found in docs/config.md.

Presentation

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

The rules governing this discovery are specified in a configuration file. If you were relying on the implicit rules from the previous version of the adapter, you can use the included config-gen tool to generate a configuration that matches the old implicit ruleset:

$ go run cmd/config-gen/main.go [--rate-interval=<duration>] [--label-prefix=<prefix>]

Example

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. Note that @luxas's tutorial uses a slightly older version of the adapter.

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

FAQs

Why do my metrics keep jumping between a normal value and a very large number?

You're probably switching between whole numbers (e.g. 10) and milli-quantities (e.g. 10500m). Worry not! This is just how Kubernetes represents fractional values. See the Quantity Values section of the walkthrough for a bit more information.

Why isn't my metric showing up?

First, check your configuration. Does it select your metric? You can find the default configuration in the deploy directory, and more information about configuring the adapter in the docs.

Next, check if the discovery information looks right. You should see the metrics showing up as associated with the resources you expect at /apis/custom.metrics.k8s.io/v1beta1/ (you can use kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1 to check, and can pipe to jq to pretty-print the results, if you have it installed). If not, make sure your series are labeled correctly. Consumers of the custom metrics API (especially the HPA) don't do any special logic to associate a particular resource to a particular series, so you have to make sure that the adapter does it instead.

For example, if you want a series foo to be associated with deployment bar in namespace somens, make sure there's some label that represents deployment name, and that the adapter is configured to use it. With the default config, that means you'd need the query foo{namespace="somens",deployment="bar"} to return some results in Prometheus.

Next, try using the --v=6 flag on the adapter to see the exact queries being made by the adapter. Try url-decoding the query and pasting it into the Prometheus web console to see if the query looks wrong.

My query contains multiple metrics, how do I make that work?

It's actually fairly straightforward, if a bit non-obvious. Simply choose one metric to act as the "discovery" and "naming" metric, and use that to configure the "discovery" and "naming" parts of the configuration. Then, you can write whichever metrics you want in the metricsQuery! The series query can contain whichever metrics you want, as long as they have the right set of labels.

For example, suppose you have two metrics foo_total and foo_count, both with the label system_name, which represents the node resource. Then, you might write

rules:
- seriesQuery: 'foo_total'
  resources: {overrides: {system_name: {resource: "node"}}}
  name:
    matches: 'foo_total'
    as: 'foo'
  metricsQuery: 'sum(foo_total{<<.LabelMatchers>>}) by (<<.GroupBy>>) / sum(foo_count{<<.LabelMatchers>>}) by (<<.GroupBy>>)'

I get errors about SubjectAccessReviews/system:anonymous/TLS/Certificates/RequestHeader!

It's important to understand the role of TLS in the Kubernetes cluster. There's a high-level overview here: https://github.com/kubernetes-incubator/apiserver-builder/blob/master/docs/concepts/auth.md.

All of the above errors generally boil down to misconfigured certificates. Specifically, you'll need to make sure your cluster's aggregation layer is properly configured, with requestheader certificates set up properly.

Errors about SubjectAccessReviews failing for system:anonymous generally mean that your cluster's given requestheader CA doesn't trust the proxy certificates from the API server aggregator.

On the other hand, if you get an error from the aggregator about invalid certificates, it's probably because the CA specified in the caBundle field of your APIService object doesn't trust the serving certificates for the adapter.

If you're seeing SubjectAccessReviews failures for non-anonymous users, check your RBAC rules -- you probably haven't given users permission to operate on resources in the custom.metrics.k8s.io API group.

My metrics appear and disappear

You probably have a Prometheus collection interval or computation interval that's larger than your adapter's discovery interval. If the metrics appear in discovery but occaisionally return not-found, those intervals are probably larger than one of the rate windows used in one of your queries. The adapter only considers metrics with datapoints in the window [now-discoveryInterval, now] (in order to only capture metrics that are still present), so make sure that your discovery interval is at least as large as your collection interval.

I get errors when query namespace prefixed metrics?

I have namespace prefixed metrics like { "name": "namespaces/node_memory_PageTables_bytes", "singularName": "", "namespaced": false, "kind": "MetricValueList", "verbs": [ "get" ] }, but I get error Error from server (InternalError): Internal error occurred: unable to list matching resources when access with kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1/namespaces/*/node_memory_PageTables_bytes .

Actually namespace prefixed metrics are special, we should access them with kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1/namespaces/*/metrics/node_memory_PageTables_bytes.

Community, discussion, contribution, and support

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You can reach the maintainers of this project at:

• Slack
• Mailing List