How to understand the roles of Kubernetes scheduler, controller manager, and etcd?

Introduction

Kubernetes is a powerful open-source container orchestration platform that has become the de facto standard for managing and deploying containerized applications. Understanding the roles of the key components within the Kubernetes architecture, such as the scheduler, controller manager, and etcd, is crucial for effectively utilizing and managing your Kubernetes-based infrastructure.

Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL kubernetes(("`Kubernetes`")) -.-> kubernetes/ClusterInformationGroup(["`Cluster Information`"]) kubernetes(("`Kubernetes`")) -.-> kubernetes/CoreConceptsGroup(["`Core Concepts`"]) kubernetes/ClusterInformationGroup -.-> kubernetes/cluster_info("`Cluster Info`") kubernetes/CoreConceptsGroup -.-> kubernetes/architecture("`Architecture`") subgraph Lab Skills kubernetes/cluster_info -.-> lab-415062{{"`How to understand the roles of Kubernetes scheduler, controller manager, and etcd?`"}} kubernetes/architecture -.-> lab-415062{{"`How to understand the roles of Kubernetes scheduler, controller manager, and etcd?`"}} end

Introduction to Kubernetes Architecture

Kubernetes is a powerful open-source container orchestration system that automates the deployment, scaling, and management of containerized applications. At the heart of Kubernetes lies its architecture, which consists of several key components that work together to provide a robust and scalable platform for running and managing containerized workloads.

Kubernetes Cluster Components

A Kubernetes cluster is composed of two main types of nodes: Master Nodes and Worker Nodes.

Master Nodes

The Master Nodes are responsible for the overall management and control of the Kubernetes cluster. They include the following key components:

API Server: The API Server is the central entry point for all Kubernetes operations. It exposes a RESTful API that allows clients, such as the Kubernetes command-line tool (kubectl), to interact with the cluster.
Scheduler: The Scheduler is responsible for placing new Pods (the smallest deployable units in Kubernetes) onto available Worker Nodes based on resource requirements, constraints, and other policies.
Controller Manager: The Controller Manager is responsible for maintaining the desired state of the cluster by monitoring the API Server and taking corrective actions when necessary.
etcd: etcd is a distributed key-value store that Kubernetes uses to store all of its configuration data and state information. It serves as the backbone of the Kubernetes cluster, ensuring data consistency and reliability.

Worker Nodes

The Worker Nodes are responsible for running the actual containerized applications. Each Worker Node runs the following components:

Kubelet: The Kubelet is the primary "node agent" that runs on each Worker Node. It is responsible for communicating with the Master Nodes and executing Pod-related operations, such as starting, stopping, and monitoring containers.
Kube-proxy: The Kube-proxy is a network proxy that runs on each Worker Node and manages the network rules that allow communication between Pods and the external network.
Container Runtime: The Container Runtime is the software responsible for running the containers on the Worker Nodes. Kubernetes supports several container runtimes, such as Docker, containerd, and CRI-O.

graph TD subgraph Kubernetes Cluster subgraph Master Nodes API[API Server] Scheduler[Scheduler] Controller[Controller Manager] etcd[etcd] end subgraph Worker Nodes Kubelet[Kubelet] Proxy[Kube-proxy] Runtime[Container Runtime] end end

This high-level overview of the Kubernetes architecture provides a solid foundation for understanding the roles of the Kubernetes Scheduler, Controller Manager, and etcd, which will be covered in the following sections.

Understanding the Kubernetes Scheduler

The Kubernetes Scheduler is a critical component responsible for placing Pods onto available Worker Nodes within the cluster. It plays a crucial role in ensuring the efficient and balanced utilization of cluster resources.

Scheduler Responsibilities

The Kubernetes Scheduler is responsible for the following tasks:

Pod Scheduling: The Scheduler is responsible for selecting the most appropriate Worker Node to run a new Pod based on various factors, such as resource requirements, constraints, and policies.
Resource Allocation: The Scheduler ensures that the resources requested by a Pod are available on the selected Worker Node, and it allocates those resources accordingly.
Load Balancing: The Scheduler tries to distribute Pods evenly across the available Worker Nodes, ensuring that the cluster's resources are utilized efficiently.
Affinity and Anti-Affinity: The Scheduler can consider Pod affinity and anti-affinity rules to co-locate or separate Pods based on specific requirements, such as running related Pods on the same node or avoiding Pods from the same service on the same node.

Scheduler Algorithm

The Kubernetes Scheduler uses a multi-step algorithm to select the most suitable Worker Node for a new Pod. The main steps in this algorithm are:

Filtering: The Scheduler first filters out the Worker Nodes that do not meet the Pod's requirements, such as resource requests, node selectors, and node taints.
Scoring: The Scheduler then scores the remaining eligible Worker Nodes based on various factors, such as available resources, node utilization, and user-defined priorities.
Selection: Finally, the Scheduler selects the Worker Node with the highest score to host the new Pod.

graph LR Filtering --> Scoring --> Selection

Scheduler Configuration

The Kubernetes Scheduler can be configured to use different scheduling algorithms and policies. This can be done by modifying the Scheduler's configuration file, which is typically located at /etc/kubernetes/manifests/kube-scheduler.yaml on the Master Node.

For example, to configure the Scheduler to use a custom scoring function, you can add the following configuration to the kube-scheduler.yaml file:

apiVersion: kubescheduler.config.k8s.io/v1beta1
kind: KubeSchedulerConfiguration
algorithmSource:
  customPlugin:
    name: MyCustomScorer
    weight: 10

This configuration would instruct the Scheduler to use a custom scoring plugin named "MyCustomScorer" with a weight of 10 during the scoring phase of the scheduling algorithm.

By understanding the responsibilities and inner workings of the Kubernetes Scheduler, you can effectively manage and optimize the scheduling of Pods in your Kubernetes cluster.

Kubernetes Controller Manager and etcd Roles

In addition to the Kubernetes Scheduler, two other critical components in the Kubernetes architecture are the Controller Manager and etcd.

Kubernetes Controller Manager

The Kubernetes Controller Manager is responsible for maintaining the desired state of the Kubernetes cluster by monitoring the API Server and taking corrective actions when necessary. It consists of several individual controllers, each responsible for a specific aspect of the cluster's management.

Controller Manager Responsibilities

Node Controller: Responsible for monitoring the status of Worker Nodes and taking appropriate actions, such as marking a node as unhealthy or draining Pods from a node that is about to be decommissioned.
Replication Controller: Ensures that the desired number of replicas for a Deployment or ReplicaSet are running at all times.
Endpoints Controller: Manages the Endpoints objects, which represent the network endpoints for a Service.
Service Account & Token Controllers: Manage service accounts and their associated authentication tokens.
Garbage Collector: Deletes objects that have been marked for deletion, such as Pods or Deployments.

The Controller Manager runs as a single process on the Master Node and communicates with the API Server to perform its management tasks.

etcd

etcd is a distributed, consistent, and highly-available key-value store that Kubernetes uses to store all of its configuration data and state information. It serves as the backbone of the Kubernetes cluster, ensuring data consistency and reliability.

etcd Responsibilities

Data Storage: etcd stores all Kubernetes objects, such as Pods, Services, and Deployments, as well as their associated metadata and configuration data.
Cluster Coordination: etcd provides a reliable and consistent way for Kubernetes components to coordinate their actions and maintain the desired state of the cluster.
Distributed Locking: etcd's built-in distributed locking mechanism is used by Kubernetes components to ensure exclusive access to shared resources, such as the Kubernetes API.
High Availability: etcd is designed to be highly available, with the ability to tolerate the failure of individual nodes and automatically recover from such failures.

graph TD API[API Server] --> Controller[Controller Manager] API[API Server] --> etcd[etcd] Controller[Controller Manager] --> etcd[etcd]

By understanding the roles and responsibilities of the Kubernetes Controller Manager and etcd, you can gain a deeper understanding of how Kubernetes maintains the desired state of the cluster and ensures the reliability and consistency of its data.

Summary

In this tutorial, we have explored the roles and responsibilities of the Kubernetes scheduler, controller manager, and etcd, and how they work together to provide a robust and scalable container orchestration platform. By understanding these core components, you can better optimize your Kubernetes deployments, troubleshoot issues, and ensure the reliable operation of your containerized applications.