Garbage collection is a collective term for the various mechanisms Kubernetes uses to clean up cluster resources. This allows the clean up of resources like the following: Terminated pods Completed Jobs Objects without owner references Unused containers and container images Dynamically provisioned PersistentVolumes with a StorageClass reclaim policy of Delete Stale or expired CertificateSigningRequests (CSRs) Nodes deleted in the following scenarios: On a cloud when the cluster uses a cloud controller manager On-premises when the cluster uses an addon similar to a cloud controller manager Node Lease objects Owners and dependents Many objects in Kubernetes link to each other through owner references.

In Kubernetes, a HorizontalPodAutoscaler automatically updates a workload resource (such as a Deployment or StatefulSet), with the aim of automatically scaling capacity to match demand. Horizontal scaling means that the response to increased load is to deploy more Pods. This is different from vertical scaling, which for Kubernetes would mean assigning more resources (for example: memory or CPU) to the Pods that are already running for the workload. If the load decreases, and the number of Pods is above the configured minimum, the HorizontalPodAutoscaler instructs the workload resource (the Deployment, StatefulSet, or other similar resource) to scale back down.

By default, containers run with unbounded compute resources on a Kubernetes cluster. Using Kubernetes resource quotas, administrators (also termed cluster operators) can restrict consumption and creation of cluster resources (such as CPU time, memory, and persistent storage) within a specified namespace. Within a namespace, a Pod can consume as much CPU and memory as is allowed by the ResourceQuotas that apply to that namespace. As a cluster operator, or as a namespace-level administrator, you might also be concerned about making sure that a single object cannot monopolize all available resources within a namespace.

You can use topology spread constraints to control how Pods are spread across your cluster among failure-domains such as regions, zones, nodes, and other user-defined topology domains. This can help to achieve high availability as well as efficient resource utilization. You can set cluster-level constraints as a default, or configure topology spread constraints for individual workloads. Motivation Imagine that you have a cluster of up to twenty nodes, and you want to run a workload that automatically scales how many replicas it uses.

When you specify a Pod, you can optionally specify how much of each resource a container needs. The most common resources to specify are CPU and memory (RAM); there are others. When you specify the resource request for containers in a Pod, the kube-scheduler uses this information to decide which node to place the Pod on. When you specify a resource limit for a container, the kubelet enforces those limits so that the running container is not allowed to use more of that resource than the limit you set.

This task demonstrates running multiple Jobs based on a common template. You can use this approach to process batches of work in parallel. For this example there are only three items: apple, banana, and cherry. The sample Jobs process each item by printing a string then pausing. See using Jobs in real workloads to learn about how this pattern fits more realistic use cases. Before you begin You should be familiar with the basic, non-parallel, use of Job.

The architectural concepts behind Kubernetes.

Kubernetes is an open source container orchestration engine for automating deployment, scaling, and management of containerized applications. The open source project is hosted by the Cloud Native Computing Foundation.

FEATURE STATE: Kubernetes v1.24 [stable] This page shows how to use a SOCKS5 proxy to access the API of a remote Kubernetes cluster. This is useful when the cluster you want to access does not expose its API directly on the public internet. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts.

Kubernetes offers a DNS cluster addon, which most of the supported environments enable by default. In Kubernetes version 1.11 and later, CoreDNS is recommended and is installed by default with kubeadm. For more information on how to configure CoreDNS for a Kubernetes cluster, see the Customizing DNS Service.