Top 30 Kubernetes Concepts
30 Kubernetes Concepts with Real World Examples
Introduction
Kubernetes has really set the standard when it comes to container orchestration. It’s changed the game in how we deploy, manage, and scale applications in the cloud. Whether you’re a seasoned DevOps pro or just starting to dip your toes into cloud-native technologies, getting a solid grasp on the core concepts of Kubernetes is crucial for managing today’s infrastructure effectively.
In this blog, we’re going to explore 30 essential Kubernetes concepts that every developer and DevOps professional should have in their toolkit. This blog will be a blend of theory and real-world examples, giving you both the knowledge and practical insights to apply these concepts in your day-to-day work.
Kubernetes Concepts :
1. Container :
Containers are a lightweight and portable way to package and run software applications. They provide a consistent and reproducible environment for running applications across different computing environments. In production, containers are often used to isolate applications and their dependencies, improve resource utilization, and streamline software delivery processes.
Real-world example : A web application can be containerized and run in a containerized environment such as Kubernetes, which allows easy scaling and management of the application.
2. Container Orchestration :
Container orchestration refers to the automated management of containerized applications, including deployment, scaling, and monitoring. It helps to abstract the underlying infrastructure and provides a unified API for managing applications across different environments.
Real-world example : Kubernetes is an example of container orchestration platform that automates the deployment, scaling, and management of containerized applications.
3. Kubernetes (K8s) :
Kubernetes is an open-source container orchestration platform that provides a unified API for managing containerized applications. It automates the deployment, scaling, and management of containerized applications, making it easier to manage applications in production.
Real-world example : Kubernetes is used by many companies, such as Airbnb, Spotify, and Lyft, to manage their containerized applications in production.
4. Core Concepts of K8s :
The core concepts of Kubernetes include Pods, ReplicaSets, Deployments, Services, ConfigMaps, Secrets, and Persistent Volumes. These concepts are used to define and manage the lifecycle of containerized applications in Kubernetes.
Real-world example : Pods are used to run one or more containers together, while ReplicaSets and Deployments are used to manage the scaling and rollout of these Pods.
5. K8s Architecture :
The Kubernetes architecture consists of a control plane and worker nodes. The control plane includes the Kube API server, ETCD, Kube Controller Manager, and Kube Scheduler, while the worker nodes include Kubelet and Kube Proxy. The control plane is responsible for managing the state of the cluster, while the worker nodes are responsible for running containers.
Real-world example : In a Kubernetes cluster, the control plane can be run on a set of dedicated servers or in the cloud, while the worker nodes can be run on a set of physical or virtual machines.
6. Kube API Server :
The Kube API server provides a unified API for managing Kubernetes objects, such as Pods, ReplicaSets, and Deployments. It also acts as the front-end for the Kubernetes control plane, handling authentication, authorization, and admission control.
Real-world example : The Kube API server is used by Kubernetes administrators to manage the state of the cluster and the applications running on it.
7. ETCD :
ETCD is a distributed key-value store that is used by Kubernetes to store the state of the cluster. It provides a consistent and reliable way to store and retrieve data, making it easy to manage the state of the cluster.
Real-world example : ETCD is used by Kubernetes to store information about the Pods, Services, ConfigMaps, Secrets, and other objects that are used to manage containerized applications.
8. Kube Controller Manager :
The Kube Controller Manager is responsible for running controllers that monitor the state of the cluster and make changes as necessary. It includes controllers for ReplicaSets, Deployments, Services, and other Kubernetes objects.
Real-world example : The Kube Controller Manager is used by Kubernetes to ensure that the state of the cluster is consistent and that containerized applications are running as expected.
9. Kube Scheduler :
The Kube Scheduler is responsible for scheduling Pods on worker nodes in the cluster. It takes into account factors such as resource requirements and node availability when making scheduling decisions.
Real-world example : The Kube Scheduler is used by Kubernetes to ensure that Pods are scheduled on worker nodes in an efficient and reliable manner, based on the available resources and constraints.
10. Kubelet :
The Kubelet is an agent that runs on each worker node in the Kubernetes cluster. It is responsible for managing the lifecycle of Pods on the node, including pulling container images and starting and stopping containers.
Real-world example : The Kubelet is used by Kubernetes to manage the containers running on each worker node in the cluster, ensuring that they are running as expected and that their resource usage is optimized.
11. Kube Proxy :
The Kube Proxy is responsible for managing network traffic between Pods in the Kubernetes cluster. It runs on each worker node and is responsible for routing traffic to the appropriate Pod.
Real-world example : The Kube Proxy is used by Kubernetes to ensure that network traffic between Pods is managed efficiently and securely, providing a stable and reliable network environment for containerized applications.
12. Pod :
A Pod is the smallest deployable unit in Kubernetes. It represents a single instance of a running process in a container. Pods are used to run one or more containers together, and can be scaled up or down as needed.
Real-world example : In Kubernetes, a web application can be run in a Pod, with multiple instances of the Pod running to ensure high availability and scalability.
13. Yaml :
YAML is a human-readable data serialization language used to define the configuration of Kubernetes objects. It is used to define and manage the state of Kubernetes objects such as Pods, ReplicaSets, and Deployments.
Real-world example : Kubernetes administrators use YAML to define and manage the configuration of the various objects used to manage containerized applications running on the Kubernetes cluster.
14. Replica Set :
A ReplicaSet is a Kubernetes object that manages the scaling and replication of Pods. It ensures that the specified number of replicas of a Pod is running at any given time.
Real-world example : A ReplicaSet can be used to ensure that multiple instances of a web application are running in the Kubernetes cluster, with automatic scaling based on demand.
15. Deployments :
A Deployment is a Kubernetes object that manages the rolling out and rolling back of changes to the state of the cluster. It provides a declarative way to manage updates to containerized applications running in the Kubernetes cluster.
Real-world example : A Deployment can be used to manage the rollout of a new version of a web application, with automated rollbacks in case of failures.
16. Services (NodePort, ClusterIP & Load Balancer) :
Services are Kubernetes objects that allow you to expose your application to the network and access it from other pods or external clients. There are three types of Services: NodePort, ClusterIP, and LoadBalancer.
Real World Example : Suppose we have a web application running on a Kubernetes cluster. We can create a ClusterIP Service to allow other pods within the cluster to access the application. We can also create a NodePort Service to expose the application to external clients, allowing them to connect to the application using a specific port on any node in the cluster. Finally, we can create a LoadBalancer Service to load balance incoming traffic across multiple nodes in the cluster.
17. Namespaces :
Namespaces are a way to organize resources in a Kubernetes cluster. They provide a way to group related resources together and isolate them from each other. Each namespace has its own set of resources and cannot access resources in other namespaces.
Real World Example : Suppose we have multiple teams sharing a Kubernetes cluster. Each team can create its own namespace to isolate its resources from the resources of other teams. This allows each team to manage its own resources independently, without interfering with other teams.
18. Imperative Vs Declarative :
Imperative and declarative are two different ways of defining and managing resources in Kubernetes. Imperative commands tell Kubernetes what to do and how to do it, while declarative commands tell Kubernetes what we want and let it decide how to achieve it.
Real World Example : Suppose we want to create a Kubernetes Deployment for our web application. We can use an imperative command like kubectl create deployment to create the Deployment and specify all the details of the Deployment at once. Alternatively, we can use a declarative command like kubectl apply to apply a YAML file that defines the Deployment and let Kubernetes decide how to create and manage the resources. Declarative commands are usually preferred, as they are more flexible and allow for better version control.
19. Manual Scheduling :
Manual scheduling is the process of manually assigning pods to specific nodes in a Kubernetes cluster. This can be useful in certain situations, such as when you need to ensure that certain pods run on specific nodes.
Real World Example : Suppose we have a cluster with multiple nodes, each with different resource capacities. We can use manual scheduling to ensure that certain pods run on nodes with specific resource capacities to optimize performance. We can also use manual scheduling to ensure that certain pods are colocated with other pods that they need to communicate with frequently.
20. Labels :
Labels are key-value pairs that are attached to Kubernetes objects, such as pods, deployments, services, and more. Labels are used to identify and organize objects and to filter them for various operations. They are not unique, and multiple objects can have the same labels.
Real-world example : With labels, you can use Kubernetes commands to filter and manage objects. For example, you can list all the pods that have the ‘environment: prod’ label using the following command: > kubectl get pods -l environment=prod
21. Selectors :
Selectors are used in Kubernetes to select a subset of objects based on their labels. Selectors are used with services, deployments, replica sets, and other controllers to identify which pods to target.
Real-world example : Suppose you have a service that needs to target only the pods with the label ‘app: frontend’.
You can define the selector for the service using the following YAML definition :
22. Taints & Tolerations in K8s :
Taints and tolerations are used in Kubernetes to control which nodes can run which pods. A taint is a property that is applied to a node, and a toleration is a property that is applied to a pod. If a pod has a toleration that matches the taint on a node, the pod can be scheduled on that node.
Real-world example : Suppose you have a node in your Kubernetes cluster that is running a database, and you want to ensure that only pods that are suitable for running a database are scheduled on that node. You can apply a taint to the node using the following command: > kubectl taint nodes <node-name> db=required:NoSchedule This taint specifies that the node requires a database and that no pods should be scheduled on the node unless they have a toleration for the db=required taint.
To allow a pod to be scheduled on the node, you can add a toleration to the pod using the following YAML definition :
23. Node Affinity in K8s :
Node affinity is a feature in Kubernetes that allows you to specify which nodes should run which pods based on node labels. Node affinity can be used to ensure that certain pods are always scheduled on specific nodes, or to spread pods across different nodes based on their properties.
Real-world example : Suppose you have a set of pods that require GPUs to run, and you have some nodes in your cluster that have GPUs attached. You can use node affinity to ensure that the pods are scheduled on the nodes with GPUs.
You can define node affinity using the following YAML definition :
24. Resource Limits :
Resource limits in Kubernetes are used to restrict the amount of CPU and memory that a container can consume. This is important in production environments because it ensures that containers do not consume all available resources, which could result in system instability or downtime. Kubernetes provides two types of resource limits: requests and limits. Requests specify the minimum amount of CPU and memory that a container needs, while limits specify the maximum amount of CPU and memory that a container can consume.
Real-world example : Let’s say you have a deployment that consists of multiple containers, each of which needs a specific amount of CPU and memory to function properly. By setting resource limits on each container, you can ensure that they do not exceed their allocated resources and cause performance issues. For example, if you have a container that runs a CPU-intensive application, you can set a CPU limit to ensure that it does not consume all available CPU resources, causing other containers to suffer.
25. DaemonSets :
DaemonSets are a type of Kubernetes controller that ensures that a specific pod runs on all nodes in a cluster. This is useful for tasks that need to run on every node, such as logging or monitoring agents. DaemonSets are also used for tasks that need to run before other pods are deployed, such as setting up network plugins or storage volumes.
Real-world example : Let’s say you have a cluster with 10 nodes, and you want to deploy a logging agent on each node to collect logs from all running containers. By creating a DaemonSet, you can ensure that the logging agent runs on every node in the cluster. This ensures that you have comprehensive logs for troubleshooting and analysis.
26. Static Pods :
Static Pods are a type of pod that is managed directly by the kubelet on a node, rather than by the Kubernetes API server. Static Pods are useful for cases where you need to run a specific pod on a specific node, or for cases where you want to run a pod without the complexity of a full Kubernetes deployment.
Real-world example : Let’s say you have a specific node that has unique hardware requirements, and you want to run a pod that takes advantage of these requirements. By creating a Static Pod, you can specify that the pod should run on that specific node, and the kubelet will ensure that the pod is created and managed.
27. Multiple Scheduler :
Kubernetes provides the ability to use multiple schedulers to schedule pods. This allows you to use different scheduling algorithms for different types of workloads or to use different scheduling strategies for different nodes in a cluster.
Real-world example : Let’s say you have a cluster with different types of nodes, each with different hardware capabilities. By using multiple schedulers, you can ensure that workloads are scheduled on the appropriate nodes based on their requirements. For example, you can use a scheduler that prioritizes CPU utilization for workloads that are CPU-intensive and a scheduler that prioritizes memory utilization for workloads that are memory-intensive. This helps to ensure that workloads are scheduled efficiently and that resources are used effectively.
28. Logging & Monitoring :
Logging and monitoring are essential for maintaining and troubleshooting Kubernetes clusters. Kubernetes provides built-in logging and monitoring mechanisms that can be used to collect and analyze data from the cluster components, workloads, and applications.
Real-world examples : In a production environment, Kubernetes logging and monitoring can be used to identify and troubleshoot issues, detect and prevent security threats, and optimize resource utilization. Some popular logging and monitoring tools used with Kubernetes include Prometheus, Grafana, Elastic Stack, Fluentd, and Sysdig.
29. Monitor Cluster Components :
Kubernetes clusters consist of various components, including the API server, etcd, kubelet, kube-proxy, and more. Monitoring these components is critical for maintaining the health and availability of the cluster.
Real-world examples : Cluster component monitoring can help identify issues such as pod scheduling problems, networking issues, or storage-related problems that may affect the overall performance of the cluster. Tools such as Prometheus and Grafana can be used to monitor the health and performance of Kubernetes cluster components.
30. Metrics :
Kubernetes provides metrics through its API server that can be used to monitor the performance and health of cluster components, workloads, and applications. These metrics include information on CPU usage, memory utilization, network traffic, and more.
Real-world examples : Metrics are critical for understanding and optimizing resource utilization in Kubernetes. They can be used to identify bottlenecks, optimize resource allocation, and monitor the performance of applications running in the cluster. Tools such as Prometheus and Grafana can be used to collect and analyze metrics from Kubernetes clusters.
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