Kubernetes - Cluster Control Plane and Data Plane Components Explained
Kubernetes is in short called k8s is a container orchestration and management solution gets its foundation from the Google's Borg which is also a cluster management solution.
In the broader perspective, it is a network manager and an orchestrator for the processors. Manages the underlying infrastructure and network configurations for containerized services through complex configuration steps.
In this guide you will get familiar with;
- K8s Archtitecture Overview
- Control Plane Components
- Data Plane Components
- Automation of Deployments
- The most important Thing
1 - K8s Archtitecture Overview
Consists of components including:
- Control Plane
- Scheduler
- API Server
- Controller Manager
- Etcd
- Data Plane
- Worker Nodes
- Pods
1.1 Control Plane
Control plane is responsible for keeping the cluster state in requested state with components. Each component has unique responsibility in contributing in state management in cluster.
Scheduler
Responsible for pod creation. As the new request come to the cluster declaring to create new pods for a specific service control plane recieves the request and sends to the scheduler. Scheduler then talks to the data plane and triggers the creation of the new pod.
API Server
REST API service in the control plane to retrieve cluster information. Used by control plane components and clients. Can be used through kubectl CLI tool and REST requests.
Controller Manager
Keeps track of health of critical cluster controllers. Node Controller, Deployment Controller, ReplicaSet Controller, StatefulSet Controller, DaemonSet Controller, Job Controller, CronJob Controller ...
The way it controls the state of these controllers is using a continues loop to periodically check the state of the controllers, in case of any failure it restarts the controller and maintains these critical cluster controllers.
Etcd
A distributed key - value database that keeps track of the cluster information. Responsible for providing necessary details about the cluster like deployments, node informations, pod informations and more.
Its essentially important for keeping the cluster state, and making sure the recovery is possible.
1.2 Data Plane
Worker Nodes
Can be a virtual machine or a physical computer that powers the kubernetes cluster resources. To increase the compute capacity of a cluster the increase in node count is required.
Pods
The smallest deployable units in a Kubernetes cluster. Runs one or multiple containers. These are ephemeral doesn't contain persistent volumes. If the pod is deleted, its local storage is also deleted.
Kubernetes provides kubernetes persistent volumes that can be attached to pods to keep the data volume consistent across pods.
Each node and pod also have its own components assigned by the cluster. These components prioritize in;
- Container Runtime: Provides a runtime for the container processes. Can be choosen from range of container runtimes to assign to the cluster. The most popular CR are docker runtime and containerd.
- Kubelet: Located in each node in the data plane. Responsible for managing pod and container's life-cycle by reporting the health status to the control plane.
- Kube-proxy: Placed in each node in the data plane. Takes responsibility in configuring network endpoints for the services. Maps pod ip's to service connections and contributes to load balancing.
2 - Automation of Deployments
Manages deployments through deployment files and CLI tools. These CLI tool is the essential hero in deploying application into your cluster.
Cluster recieves the deployment request from the network in a file called deployment.yaml that contains the recipie of where to find the application binary and points where the configurations for the application.
After control plane recieves the request and writes into etcd, creates a pod for the application and deploys it into the pod. The application deployment tracking is achieved through the same CLI tool.
This simplifies the deployment logic. However, doesn't keep the application versions which is significant in a CI/CD pipeline.
2.1 Helm
Application package manager for kubernetes clusters. Keeps track of the application versions in a helm repository that can be a github repo.
Contributes to the usage of kubernetes CLI tool (kubectl) in terms of deployments. Helm is also a CLI tool and makes it even more easier to deploy applications. Instead of creating each time a different deployment file, helm manages the latest state of the deployments.
For implementation details see : Deploying application in a version controlled way.
3 - The most important Thing
Each kubernetes setup is unique to its team and can choose different strategies. The best way to utilize the best is by teaching the team about the cluster periodically and letting the changes known by every team member.
Another possitive aspect of teaching to the team members is that they will know how to utilize the kubernetes services at the most efficient way possible. This would significantly reduce costs and also increase the efficiency.
Conclusion
disclaimer: written by Claude 3.5 Sonnet
Kubernetes, while seemingly complex, is actually quite an understandable system. With its control plane and data plane components, it's revolutionized the world of container orchestration.
Although each setup is unique, the core logic remains the same: effectively manage and scale applications. From the Scheduler to etcd, from Kubelet to Kube-proxy, each component plays a crucial role in maintaining the cluster's desired state.
The real power of Kubernetes lies not just in its technical capabilities, but in how teams utilize it. Regular education and open communication about the cluster setup can significantly boost efficiency and reduce costs.
Remember, Kubernetes is more than just a tool - it's a platform that evolves with your team's needs and skills. Keep learning, keep sharing, and you'll unlock its full potential.
Continue reading
Kubernetes deployments : Describes how deployments affect cluster's state.
Helm Overview : Start utilizing Helm charts in deployments.
Kubernetes Monitoring : Mentions about metrics api, and monitoring tools.
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