Tasks
Install Tools
Configure Pods and Containers
Assign Memory Resources to Containers and Pods
Assign CPU Resources to Containers and Pods
Configure Quality of Service for Pods
Assign Extended Resources to a Container
Configure a Pod to Use a Volume for Storage
Configure a Pod to Use a PersistentVolume for Storage
Configure a Pod to Use a Projected Volume for Storage
Configure a Security Context for a Pod or Container
Configure Service Accounts for Pods
Pull an Image from a Private Registry
Configure Liveness and Readiness Probes
Assign Pods to Nodes
Configure Pod Initialization
Attach Handlers to Container Lifecycle Events
Configure Containers Using a ConfigMap
Use ConfigMap Data in Pods
Translate a Docker Compose File to Kubernetes Resources
Inject Data Into Applications
Define a Command and Arguments for a Container
Define Environment Variables for a Container
Expose Pod Information to Containers Through Environment Variables
Expose Pod Information to Containers Through Files
Distribute Credentials Securely Using Secrets
Inject Information into Pods Using a PodPreset
Run Applications
Run a Stateless Application Using a Deployment
Run a Single-Instance Stateful Application
Run a Replicated Stateful Application
Update API Objects in Place Using kubectl patch
Upgrade from PetSets to StatefulSets
Scale a StatefulSet
Delete a Stateful Set
Force Delete StatefulSet Pods
Perform Rolling Update Using a Replication Controller
Horizontal Pod Autoscaler
Horizontal Pod Autoscaler Walkthrough
Specifying a Disruption Budget for your Application
Run Jobs
Access Applications in a Cluster
Web UI (Dashboard)
Accessing Clusters
Configure Access to Multiple Clusters
Use Port Forwarding to Access Applications in a Cluster
Provide Load-Balanced Access to an Application in a Cluster
Use a Service to Access an Application in a Cluster
Connect a Front End to a Back End Using a Service
Create an External Load Balancer
Configure Your Cloud Provider's Firewalls
List All Container Images Running in a Cluster
Communicate Between Containers in the Same Pod Using a Shared Volume
Configuring DNS for a Cluster
Monitor, Log, and Debug
Core metrics pipeline
Tools for Monitoring Compute, Storage, and Network Resources
Get a Shell to a Running Container
Monitor Node Health
Logging Using Stackdriver
Events in Stackdriver
Logging Using Elasticsearch and Kibana
Determine the Reason for Pod Failure
Debug Init Containers
Debug Pods and Replication Controllers
Debug Services
Troubleshoot Clusters
Troubleshoot Applications
Debug a StatefulSet
Application Introspection and Debugging
Auditing
Developing and debugging services locally
Use Explorer to Examine the Runtime Environment
Extend Kubernetes
Use an HTTP Proxy to Access the Kubernetes API
Extend the Kubernetes API with CustomResourceDefinitions
Extend the Kubernetes API with ThirdPartyResources
Migrate a ThirdPartyResource to CustomResourceDefinition
Configure the aggregation layer
Setup an extension API server
Install Service Catalog using Helm
Install Service Catalog using SC
Administer a Cluster
Manage Memory, CPU, and API Resources
Configure Default Memory Requests and Limits for a Namespace
Configure Default CPU Requests and Limits for a Namespace
Configure Minimum and Maximum Memory Constraints for a Namespace
Configure Minimum and Maximum CPU Constraints for a Namespace
Configure Memory and CPU Quotas for a Namespace
Configure a Pod Quota for a Namespace
Configure Quotas for API Objects
Advertise Extended Resources for a Node
Control CPU Management Policies on the Node
Access Clusters Using the Kubernetes API
Access Services Running on Clusters
Securing a Cluster
Encrypting data at rest
Operating etcd clusters for Kubernetes
Static Pods
Cluster Management
Cluster Management Guide for Version 1.6
Upgrading kubeadm clusters from 1.6 to 1.7
Upgrading kubeadm clusters from 1.7 to 1.8
Share a Cluster with Namespaces
Namespaces Walkthrough
Autoscale the DNS Service in a Cluster
Safely Drain a Node while Respecting Application SLOs
Configure Out Of Resource Handling
Reserve Compute Resources for System Daemons
Guaranteed Scheduling For Critical Add-On Pods
Declare Network Policy
Reconfigure a Node's Kubelet in a Live Cluster
Set Kubelet parameters via a config file
Install Network Policy Provider
Change the Reclaim Policy of a PersistentVolume
Limit Storage Consumption
Change the default StorageClass
Kubernetes Cloud Controller Manager
Developing Cloud Controller Manager
Set up High-Availability Kubernetes Masters
Configure Multiple Schedulers
IP Masquerade Agent User Guide
Configure private DNS zones and upstream nameservers in Kubernetes
Federation - Run an App on Multiple Clusters
Cross-cluster Service Discovery using Federated Services
Set up Cluster Federation with Kubefed
Set up CoreDNS as DNS provider for Cluster Federation
Set up placement policies in Federation
Federated Cluster
Federated ConfigMap
Federated DaemonSet
Federated Deployment
Federated Events
Federated Horizontal Pod Autoscalers (HPA)
Federated Ingress
Federated Jobs
Federated Namespaces
Federated ReplicaSets
Federated Secrets
Manage Cluster Daemons
Manage GPUs
Manage HugePages
Extend kubectl with plugins
Core metrics pipeline
Starting from Kubernetes 1.8, resource usage metrics, such as container CPU and memory usage,
are available in Kubernetes through the Metrics API. These metrics can be either accessed directly
by user, for example by using kubectl top command, or used by a controller in the cluster, e.g.
Horizontal Pod Autoscaler, to make decisions.
The Metrics API
Through the Metrics API you can get the amount of resource currently used by a given node or a given pod. This API doesn’t store the metric values, so it’s not possible for example to get the amount of resources used by a given node 10 minutes ago.
The API no different from any other API:
- it is discoverable through the same endpoint as the other Kubernetes APIs under
/apis/metrics.k8s.io/path - it offers the same security, scalability and reliability guarantees
The API is defined in k8s.io/metrics repository. You can find more information about the API there.
Note: The API requires metrics server to be deployed in the cluster. Otherwise it will be not available.
Metrics Server
Metrics Server is a cluster-wide aggregator of resource usage data.
Starting from Kubernetes 1.8 it’s deployed by default in clusters created by kube-up.sh script
as a Deployment object. If you use a different Kubernetes setup mechanism you can deploy it using the provided
deployment yamls.
It’s supported in Kubernetes 1.7+ (see details below).
Metric server collects metrics from the Summary API, exposed by Kubelet on each node.
Metrics Server registered in the main API server through Kubernetes aggregator, which was introduced in Kubernetes 1.7.
Learn more about the metrics server in the design doc.