Kubelet: Difference between revisions
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The kubelet is watching the API server for work (pod) assignments and attempts to run them. If it is not successful for any reason, it reports the condition back to the API server. The task of actually running the pods is delegated to the local [[Kubernetes Control Plane and Data Plane Concepts#Container_Runtime|container runtime]]. | The kubelet is watching the API server for work (pod) assignments and attempts to run them. If it is not successful for any reason, it reports the condition back to the API server. The task of actually running the pods is delegated to the local [[Kubernetes Control Plane and Data Plane Concepts#Container_Runtime|container runtime]]. | ||
The kubelet also takes part in resource metrics collection | |||
=Cache= | =Cache= | ||
Revision as of 23:25, 5 October 2020
External
Internal
Overview
Each node runs an agent called kubelet, which is responsible with the node's registration with the cluster. Once a node is registered, its CPU, RAM and storage are pooled into the wider cluster pools of corresponding resources.
The kubelet acts as a bridge between the Kubernetes master and the nodes, managing the pods and containers running on a machine.
The kubelet is watching the API server for work (pod) assignments and attempts to run them. If it is not successful for any reason, it reports the condition back to the API server. The task of actually running the pods is delegated to the local container runtime.
The kubelet also takes part in resource metrics collection
Cache
The kubelet has a cache it uses to serve various values to the node. For example, the secrets projected as files in pods running on the node are fed from this cache. The type of the cache is configurable. The cached values can be propagated via watch (default), ttl-based or simply redirecting all requests to the API server.
Image Pulling
The kubelet performs image pulling on behalf of the pods scheduled on the node.