Worker Node – In Kubernetes Theory Points

Worker Node – In Kubernetes Overview 

• A worker node provides a running environment for client applications
• In Kubernetes the application containers are encapsulated in Pods, controlled by the cluster control plane agents
• Pod is the smallest scheduling work unit in Kubernetes. 
•  in a multi-worker Kubernetes cluster, the network traffic is handled directly by the worker nodes, and is not routed through the control plane node.

A worker node has the following components:

1. Container Runtime 
2. Node Agent - 
3. kubelet Proxy - 
4. kube-proxy Add-ons for DNS, dashboards, cluster-level monitoring and logging 

 

1. Container Runtime 

• Kubernetes supports several container runtimes: 
• CRI-O : A lightweight container runtime for Kubernetes, 
• Containerd : A simple and portable container runtime. 
• Docker Engine : A popular and complex container platform which uses containerd as a container runtime.
• Mirantis Container Runtime : Formerly known as the Docker Enterprise Edition.

2. Node Agent - kubelet

• The kubelet is an agent running on each control plane node and workers node
• It receives Pod definitions, from the API Server, and interacts with the container to run containers in the Pod. 
• The kubelet connects to container runtimes through a plugin interface like imageService and runtimeService
• The ImageService is responsible for all the image-related operations, while the 
• RuntimeService is responsible for all the Pod and container-related operations.

3. Proxy - kube-proxy

• Kube-proxy is Network agent which runs on each control plane node and workers node
• implements forwarding rules through Service API objects.
• The kube-proxy node agent operates with the iptables of the node. 
• Iptables is a firewall utility created for the Linux OS 

4. Add-ons

• Add-ons 
• are cluster features not yet available in Kubernetes, therefore implemented through 3rd-party services.
• Cluster DNS 
• is a DNS server required to assign DNS records to Kubernetes objects and resources.
• Dashboard - 
• A general purpose web-based user interface for cluster.
• Monitoring - 
• Collects cluster-level metrics and saves them to a central data store.
• Logging 
• Collects cluster-level container logs and saves them to a central log store for analysis.