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Persistent Volumes | Kubernetes
This document describes persistent volumes in Kubernetes. Familiarity with volumes, StorageClasses and VolumeAttributesClasses is suggested. Introduction Managing storage is a distinct problem from managing compute instances. The PersistentVolume subsystem provides an API for users and administrators that abstracts details of how storage is provided from how it is consumed. To do this, we introduce two new API resources: PersistentVolume and PersistentVolumeClaim. A PersistentVolume (PV) is a piece of storage in the cluster that has been provisioned by an administrator or dynamically provisioned using Storage Classes.kubernetes.io/docs/concepts/storage/persistent-volumes/Registered: Wed Jun 04 06:44:46 UTC 2025 - 555.8K bytes - Viewed (0) -
Network Policies | Kubernetes
If you want to control traffic flow at the IP address or port level (OSI layer 3 or 4), NetworkPolicies allow you to specify rules for traffic flow within your cluster, and also between Pods and the outside world. Your cluster must use a network plugin that supports NetworkPolicy enforcement.kubernetes.io/docs/concepts/services-networking/network-policies/Registered: Wed Jun 04 06:43:27 UTC 2025 - 506.1K bytes - Viewed (0) -
Limit Ranges | Kubernetes
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.kubernetes.io/docs/concepts/policy/limit-range/Registered: Wed Jun 04 06:44:36 UTC 2025 - 465.7K bytes - Viewed (0) -
Security For Windows Nodes | Kubernetes
This page describes security considerations and best practices specific to the Windows operating system. Protection for Secret data on nodes On Windows, data from Secrets are written out in clear text onto the node's local storage (as compared to using tmpfs / in-memory filesystems on Linux). As a cluster operator, you should take both of the following additional measures: Use file ACLs to secure the Secrets' file location. Apply volume-level encryption using BitLocker.kubernetes.io/docs/concepts/security/windows-security/Registered: Wed Jun 04 06:40:51 UTC 2025 - 448.5K bytes - Viewed (0) -
Pod Security Standards | Kubernetes
A detailed look at the different policy levels defined in the Pod Security Standards.kubernetes.io/docs/concepts/security/pod-security-standards/Registered: Wed Jun 04 06:40:56 UTC 2025 - 468.3K bytes - Viewed (0) -
Controlling Access to the Kubernetes API | Kube...
This page provides an overview of controlling access to the Kubernetes API. Users access the Kubernetes API using kubectl, client libraries, or by making REST requests. Both human users and Kubernetes service accounts can be authorized for API access. When a request reaches the API, it goes through several stages, illustrated in the following diagram: Transport security By default, the Kubernetes API server listens on port 6443 on the first non-localhost network interface, protected by TLS.kubernetes.io/docs/concepts/security/controlling-access/Registered: Wed Jun 04 06:41:41 UTC 2025 - 457.9K bytes - Viewed (0) -
Pod Topology Spread Constraints | Kubernetes
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.kubernetes.io/docs/concepts/scheduling-eviction/topology-spread-constraints/Registered: Wed Jun 04 06:41:45 UTC 2025 - 504.7K bytes - Viewed (0) -
Autoscaling Workloads | Kubernetes
With autoscaling, you can automatically update your workloads in one way or another. This allows your cluster to react to changes in resource demand more elastically and efficiently.kubernetes.io/docs/concepts/workloads/autoscaling/Registered: Wed Jun 04 06:41:50 UTC 2025 - 455K bytes - Viewed (0) -
Resource Management for Pods and Containers | K...
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.kubernetes.io/docs/concepts/configuration/manage-resources-containers/Registered: Wed Jun 04 06:45:41 UTC 2025 - 519.7K bytes - Viewed (0) -
Volume Snapshots | Kubernetes
In Kubernetes, a VolumeSnapshot represents a snapshot of a volume on a storage system. This document assumes that you are already familiar with Kubernetes persistent volumes. Introduction Similar to how API resources PersistentVolume and PersistentVolumeClaim are used to provision volumes for users and administrators, VolumeSnapshotContent and VolumeSnapshot API resources are provided to create volume snapshots for users and administrators. A VolumeSnapshotContent is a snapshot taken from a volume in the cluster that has been provisioned by an administrator.kubernetes.io/docs/concepts/storage/volume-snapshots/Registered: Wed Jun 04 06:45:01 UTC 2025 - 469.8K bytes - Viewed (0)