99 lines
3.2 KiB
Go
99 lines
3.2 KiB
Go
/*
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Copyright 2016 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package top
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import (
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"github.com/spf13/cobra"
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metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
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"k8s.io/cli-runtime/pkg/genericiooptions"
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cmdutil "k8s.io/kubectl/pkg/cmd/util"
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"k8s.io/kubectl/pkg/util/i18n"
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"k8s.io/kubectl/pkg/util/templates"
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metricsapi "k8s.io/metrics/pkg/apis/metrics"
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)
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const (
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sortByCPU = "cpu"
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sortByMemory = "memory"
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)
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var (
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supportedMetricsAPIVersions = []string{
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"v1beta1",
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}
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topLong = templates.LongDesc(i18n.T(`
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Display resource (CPU/memory) usage.
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This command provides a view of recent resource consumption for nodes and pods.
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It fetches metrics from the Metrics Server, which aggregates this data from the
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kubelet on each node. The Metrics Server must be installed and running in the
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cluster for this command to work.
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The metrics shown are specifically optimized for Kubernetes autoscaling
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decisions, such as those made by the Horizontal Pod Autoscaler (HPA) and
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Vertical Pod Autoscaler (VPA). Because of this, the values may not match those
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from standard OS tools like 'top', as the metrics are designed to provide a
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stable signal for autoscalers rather than for pinpoint accuracy.
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When to use this command:
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* For on-the-fly spot-checks of resource usage (e.g. identify which pods
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are consuming the most resources at a glance, or get a quick sense of the load
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on your nodes)
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* Understand current resource consumption patterns
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* Validate the behavior of your HPA or VPA configurations by seeing the metrics
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they use for scaling decisions.
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It is not intended to be a replacement for full-featured monitoring solutions.
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Its primary design goal is to provide a low-overhead signal for autoscalers,
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not to be a perfectly accurate monitoring tool. For high-accuracy reporting,
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historical analysis, dashboarding, or alerting, you should use a dedicated
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monitoring solution.`))
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)
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func NewCmdTop(f cmdutil.Factory, streams genericiooptions.IOStreams) *cobra.Command {
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cmd := &cobra.Command{
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Use: "top",
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Short: i18n.T("Display resource (CPU/memory) usage"),
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Long: topLong,
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Run: cmdutil.DefaultSubCommandRun(streams.ErrOut),
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}
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// create subcommands
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cmd.AddCommand(NewCmdTopNode(f, nil, streams))
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cmd.AddCommand(NewCmdTopPod(f, nil, streams))
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return cmd
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}
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func SupportedMetricsAPIVersionAvailable(discoveredAPIGroups *metav1.APIGroupList) bool {
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for _, discoveredAPIGroup := range discoveredAPIGroups.Groups {
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if discoveredAPIGroup.Name != metricsapi.GroupName {
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continue
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}
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for _, version := range discoveredAPIGroup.Versions {
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for _, supportedVersion := range supportedMetricsAPIVersions {
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if version.Version == supportedVersion {
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return true
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}
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}
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}
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}
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return false
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}
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