FEATURE STATE: Kubernetes v1.11 [beta] Since cloud providers develop and release at a different pace compared to the Kubernetes project, abstracting the provider-specific code to the cloud-controller-manager binary allows cloud vendors to evolve independently from the core Kubernetes code. The cloud-controller-manager can be linked to any cloud provider that satisfies cloudprovider.Interface. For backwards compatibility, the cloud-controller-manager provided in the core Kubernetes project uses the same cloud libraries as kube-controller-manager. Cloud providers already supported in Kubernetes core are expected to use the in-tree cloud-controller-manager to transition out of Kubernetes core.

FEATURE STATE: Kubernetes v1.26 [stable] Starting from Kubernetes v1.20, the kubelet can dynamically retrieve credentials for a container image registry using exec plugins. The kubelet and the exec plugin communicate through stdio (stdin, stdout, and stderr) using Kubernetes versioned APIs. These plugins allow the kubelet to request credentials for a container registry dynamically as opposed to storing static credentials on disk. For example, the plugin may talk to a local metadata server to retrieve short-lived credentials for an image that is being pulled by the kubelet.

FEATURE STATE: Kubernetes v1.26 [stable] Kubernetes keeps many aspects of how pods execute on nodes abstracted from the user. This is by design. However, some workloads require stronger guarantees in terms of latency and/or performance in order to operate acceptably. The kubelet provides methods to enable more complex workload placement policies while keeping the abstraction free from explicit placement directives. For detailed information on resource management, please refer to the Resource Management for Pods and Containers documentation.

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Configure Fast Single-Row Predictions Source: R/lgb.Booster.R lgb.configure_fast_predict.Rd Pre-configures a LightGBM...

Compute feature importance in a model Source: R/lgb.importance.R lgb.importance.Rd Creates a data.table of feature im...

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

This page shows you how to configure a Pod to use a PersistentVolumeClaim for storage. Here is a summary of the process: You, as cluster administrator, create a PersistentVolume backed by physical storage. You do not associate the volume with any Pod. You, now taking the role of a developer / cluster user, create a PersistentVolumeClaim that is automatically bound to a suitable PersistentVolume. You create a Pod that uses the above PersistentVolumeClaim for storage.