What is Kubernetes? How a Kubernetes Scheduler Work?

Introduction

Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. One of the critical components of Kubernetes is the scheduler, which assigns pods to nodes based on resource availability and user-defined constraints. In this article, we will explore how the Kubernetes scheduler works, including the scheduling process, scheduling algorithms, and configuration options.

The Scheduling Process

Before diving into the details of how the Kubernetes scheduler works, let's first take a look at the overall scheduling process. When a new pod is created, it is added to the Kubernetes API server, which stores the pod's metadata and specification. The scheduler then watches for new pods that are not yet assigned to a node. Once a pod is detected, the scheduler selects a node for the pod to run on and assigns it to that node. The pod is then scheduled and ready to run. The scheduling process is a continuous loop that runs on the master node. The scheduler watches the Kubernetes API server for new pods and continuously evaluates the available nodes based on a set of constraints and criteria to determine the optimal node for a given pod.

Scheduling Algorithms

Kubernetes provides several scheduling algorithms that determine how the scheduler assigns pods to nodes. These algorithms use different strategies to evaluate nodes and select the best node for a given pod. Let's take a look at some of the most common scheduling algorithms used in Kubernetes.

1. Randomized Scheduler The randomized scheduler is the simplest scheduling algorithm and assigns pods to nodes randomly. This algorithm is not recommended for production environments since it does not take into account node resource availability or other constraints.
2. Least Resource Usage (Binpacking) The least resource usage algorithm, also known as binpacking, assigns pods to nodes that have the least amount of available resources. This algorithm is useful when running multiple pods with similar resource requirements, as it ensures that resources are used efficiently.
3. Most Resource Usage (Spreading) The most resource usage algorithm, also known as spreading, assigns pods to nodes that have the most available resources. This algorithm is useful when running multiple pods with varying resource requirements, as it ensures that pods are spread out evenly across nodes. 
4. Node Affinity The node affinity algorithm assigns pods to nodes based on user-defined constraints. For example, a pod may be assigned to a node based on the node's geographic location, availability zone, or hardware configuration.
5. Inter-pod Affinity The inter-pod affinity algorithm assigns pods to nodes based on their proximity to other pods. For example, a pod may be assigned to a node that is running other pods in the same application or service.

Configuration Options

Kubernetes provides several configuration options that allow users to customize the scheduling process. Let's take a look at some of the most common configuration options.

1. Taints and Tolerations Taints and tolerations are used to prevent pods from being scheduled on nodes that do not meet certain criteria. Taints are applied to nodes, while tolerations are applied to pods. When a pod is scheduled, it checks for taints on the nodes and only considers nodes that match its tolerations.
2. Node Selector Node selectors allow users to specify which nodes pods can be scheduled on based on node labels. Labels are key-value pairs that are assigned to nodes and can be used to group nodes by various criteria, such as geographic location, hardware configuration, or network topology. 
3. Resource Requests and Limits Resource requests and limits are used to specify the amount of resources a pod requires to run. Requests are used to reserve resources for a pod, while limits are used to restrict the amount of resources a pod can use. These values are used by the scheduler to select the appropriate node for a given pod. 
4. Pod Affinity and Anti-Affinity Pod affinity and anti-affinity are used to control the placement of pods based on their relationships with other pods. Pod affinity is used to ensure that pods are scheduled on nodes that are running other pods in the same application or service. Anti-affinity is used to ensure that pods are not scheduled on the same node as other pods in the same application or service. Pod affinity and anti-affinity are specified using label selectors, which identify the pods that should be considered for scheduling. For example, a pod may be set to have an affinity for other pods that have the same label value, while also having an anti-affinity for pods that have a different label value. 
5. Pod Priority and Preemption Pod priority and preemption are used to prioritize the scheduling of pods based on their importance. Pods can be assigned a priority value that determines their relative importance compared to other pods. When resources are limited, the scheduler will prioritize higher-priority pods over lower-priority pods. Preemption is used to evict lower-priority pods in order to make room for higher-priority pods. When a higher-priority pod cannot be scheduled due to resource constraints, the scheduler will evict one or more lower-priority pods to make room.

Conclusion

In this article, we have explored how the Kubernetes scheduler works, including the scheduling process, scheduling algorithms, and configuration options. The scheduler plays a critical role in ensuring that pods are assigned to nodes based on resource availability and user-defined constraints. By understanding the various scheduling options and how they can be used to optimize pod placement, users can ensure that their applications are running efficiently and effectively on the Kubernetes platform.