Core Components of Kubernetes

Kubernetes (K8s) has several core components that ensure the proper functioning and management of containerized applications in a cluster. These components can be grouped into Control Plane, Nodes, and other key functionalities.

1. Control Plane

The Control Plane manages the state of the entire Kubernetes cluster, handling user requests, scheduling, monitoring, and coordination. The main components are:

• kube-apiserver: The API server exposes the Kubernetes API. All operations (create, update, delete resources) within the cluster are performed through this server. It acts as the entry point for all requests to the cluster.

• etcd: A distributed key-value store that holds all cluster data, such as Pod definitions, configurations, and state information. It provides consistency and durability for cluster state.

• kube-scheduler: The scheduler is responsible for assigning Pods to nodes in the cluster. It evaluates resource availability and constraints to place Pods on suitable nodes.

• kube-controller-manager: This component runs controllers (such as ReplicaSet, Deployment controllers) to maintain the desired state of resources. It ensures that the actual state of the cluster matches the desired state.

2. Nodes

Nodes are the worker machines in Kubernetes, where the containers run. Each node contains the following essential components:

• kubelet: A primary agent running on each node that ensures containers are running in Pods. It communicates with the API server to ensure the state of the containers matches the desired state.

• kube-proxy: Responsible for managing network connectivity on each node. It handles load balancing and network routing for services, utilizing iptables or ipvs.

• Container Runtime: A software responsible for running and managing containers. Common container runtimes include Docker, containerd, and CRI-O.

3. Scheduling and Resource Management

• Pod: The smallest deployable unit in Kubernetes. A Pod can contain one or more containers that share the same network, storage, and configuration.

• ReplicaSet: Ensures that a specified number of Pod replicas are running at any given time. If Pods fail or are deleted, ReplicaSet ensures new Pods are created to maintain the desired replica count.

• Deployment: A higher-level abstraction that manages ReplicaSets and Pods. It handles rolling updates and version management of Pods, providing declarative updates to applications.

• StatefulSet: Similar to Deployment, but it is used for managing stateful applications. It provides each Pod with a unique identity and persistent storage.

4. Networking and Service Discovery

• Service: A Kubernetes resource that provides stable network access to Pods. Services abstract Pod IPs and enable reliable communication between applications.

• Ingress: A collection of rules for routing external HTTP/HTTPS traffic to services within the cluster. Ingress provides HTTP(S) load balancing and allows URL-based routing.

• Network Policies: Define rules for controlling the network access between Pods, providing network isolation and security.

5. Storage and Persistence

• Persistent Volumes (PV): A piece of storage in the cluster that is independent of the lifecycle of Pods. It can be used by Pods to store persistent data.

• Persistent Volume Claims (PVC): A request for storage by a user. PVCs bind to available PVs based on their requirements (such as storage size).

• StorageClass: Defines the type and parameters of storage available in the cluster, enabling dynamic provisioning of PVs.

6. Security and Identity

• Role-Based Access Control (RBAC): RBAC manages permissions for accessing Kubernetes resources. It defines roles and bindings to control who can do what within the cluster.

• ServiceAccount: Represents an identity for processes running in a Pod. It can be associated with specific RBAC permissions.

• Network Policies: Allow you to define rules to control which Pods can communicate with each other, enhancing security through network isolation.

7. Monitoring and Logging

• Metrics Server: A cluster-wide monitoring component that collects resource usage data (like CPU and memory usage). This data is used for features like Horizontal Pod Autoscaling (HPA).

• Prometheus: A popular monitoring tool for Kubernetes that collects and stores metrics. It is commonly used with Grafana for visualizing cluster performance.

• Fluentd/EFK (Elasticsearch-Fluentd-Kibana): A logging stack used for collecting, storing, and viewing log data in Kubernetes clusters.