Kubernetes is the standard for running containerized applications. de facto Kubernetes (K8s) is an open-source system for automating deployment , scaling , and management of containerized applications. Kubernetes makes it easy to deploy and run containerized applications. Kubernetes is simple to use. Kubernetes is complex to understand because it provides a huge set of options to make your deployment easier. Aptly named, Kubernetes is a pilot (or) helmsman that helps you to sail the container world. Kubernetes is a portable and extensible system built by the community for the community. As Kelsey, correctly quotes Kubernetes does the things that the very best system administrator would do automation, failover, centralized logging, monitoring. It takes what we’ve learned in the DevOps community and makes it default, out of the box. In order to work with Kubernetes, it is very important to understand How Kubernetes works? How Kubernetes is architected? What are the various components in Kubernetes? Let us start hacking on Kubernetes. How does Kubernetes work? The Kubernetes run in a highly available cluster mode. Each Kubernetes cluster consists of one or more node and a few nodes. main other Main Node The main node consists of an API server, Scheduler, Controllers, etcd. This node is called the control plane of Kubernetes. This control plane is the brain of Kubernetes. That is the control plane is responsible for all the actions inside Kubernetes. It contains the following components: Through , we instruct or get information from the Kubernetes. API server The is responsible for scheduling the pods. Scheduler The are responsible for running the resource controllers. controllers The is a storage for the Kubernetes. It is key-value storage. etcd Node The worker nodes have a and . Kubelet proxy The Kubelets are the actual workhorse and the Kube-proxy handles the networking. Working We provide the yaml file to the Kubernetes cluster through command. kubectl apply The command calls the API server, which will send the information to the controller and simultaneously stores the information to the etcd. apply The then replicate this information across multiple nodes to survive any node failure. etcd The will check whether the given state matches the desired state. If it is not it initiates the pod deployment, by sending the information to the scheduler controller The checks are called as the that runs inside the Kubernetes. The job of this loop is to validate whether the state requested is maintained correctly. If the expected state and actual states mismatch this loop will do the necessary actions to convert the actual state into the expected state. reconciliation loop The has a queue inside. Once the message is received in the queue. scheduler The scheduler will then invoke the to do the intended action such as deploying the container. kubelet This is a 10000 feet bird view of how Kubernetes does the deployment. There are various components inside the Kubernetes. Let us take a look at what are they and how are they useful. Pods Similarly, in Kubernetes world, pods are a group of containers living together. A pod may have one or more containers in it. The pod is the smallest unit of deployment in Kubernetes. Usually, the containers that cannot live outside the scope of another container are grouped to form a pod. This is how you define a pod in Kubernetes. apiVersion: v1 kind: Pod metadata: name: myapp-pod labels: app: myapp spec: containers: - name: myapp-container image: busybox command: ['sh', '-c' , 'echo Hello Kubernetes! && sleep 3600' ] denotes the Kubernetes cluster which version of API to use when parsing and executing this file. apiVersion defines what is the of Kubernetes object, this file will refer to. kind kind includes all the necessary metadata to identify the Pod. metadata includes the container information. spec Deployments While pods are the unit of deployment. For an application to work, it needs one or more pods. Kubernetes considers this entire set as deployment. Thus deployment is recorded information about pods. Kubernetes uses this deployment information to manage and monitor the applications that are deployed in them. The below file is the sample deployment file that tells the Kubernetes to create a deployment of using the container. nginx nginx:1.7.9 apiVersion: apps/v1 kind: Deployment metadata: name: nginx-deployment labels: app: nginx spec: replicas: 3 selector: matchLabels: app: nginx template: metadata: labels: app: nginx spec: containers: - name: nginx image: nginx:1.7.9 ports: - containerPort: 80 Replicasets While deployment tells the Kubernetes what containers are needed for your application and how many replicas to run. The replica sets are the ones that ensure those replicas are up and running. ReplicaSet is responsible for managing and monitoring the replicas. StatefulSet Often times we will need to have persistent storage or permanent network identifiers or ordered deployment, scaling, and update. During those times we will use StatefulSets. You can define the StatefulSet like below: apiVersion: apps/v1 kind: StatefulSet metadata: name: web spec: selector: matchLabels: app: nginx # has to match .spec.template.metadata.labels serviceName: "nginx" replicas: 3 # by default is 1 template: metadata: labels: app: nginx # has to match .spec.selector.matchLabels spec: terminationGracePeriodSeconds: 10 containers: - name: nginx image: k8s.gcr.io/nginx-slim:0.8 ports: - containerPort: 80 name: web volumeMounts: - name: www mountPath: /usr/share/nginx/html volumeClaimTemplates: - metadata: name: www spec: accessModes: [ "ReadWriteOnce" ] storageClassName: "my-storage-class" resources: requests: storage: 1 Gi We mounted the volume and also claimed the volume storage. DaemonSet Sometimes you need to run a pod on every node of your Kubernetes cluster. For example, if you are collecting metrics from every node, then we will need to schedule some pods on every node that collects the metrics. We can use DaemonSet for those nodes. Services The deployments define the actual state of the application running on the containers. Users will need to access the application or you might need to connect to the container to debug it. Services will help you. The services are the Kubernetes object that provides access to the containers from the external world or between themselves. We can define the service like below: apiVersion: v1 kind: Service metadata: name: my-service spec: selector: app: MyApp ports: - protocol: TCP port: 80 targetPort: 9376 The above service maps incoming connections on port 80 to the targetPort 9376. You can consider the services as the load balancer, proxy or traffic router in the world of Kubernetes. Networking This is the most important element of Kubernetes. The pods running should be exposed to the network. The containers that are running inside the pods should communicate between themselves and also to the external world. While service provides a way to connect to the pods, networking determines how to expose these services. In Kubernetes we can expose the service through the following ways: 1. Load Balancer The Load Balancer provides an external IP through which we can access the pods running inside. The Kubernetes will start the services and then asynchronouslystarts a load-balancer. 2. Node Port Each of the services will have a dynamically assigned port. We can access the services using the Kubernetes master IP. 3. Ingress Each of the services will have a separate address. These services are then accessed by an ingress controller. The ingress controller is not a public IP or external IP. Secrets Often for the applications, we need to provide passwords, tokens, etc., Kubernetes provides secrets object to store and manage the sensitive information. We can create a secret like below: apiVersion: v1 kind: Secret metadata: name: mysecret type: Opaque stringData: config.yaml: |- apiUrl: "https://my.api.com/api/v1" username: {{username}} password: {{password}} Best practices While Kubernetes is an ocean and whatever we have seen is just a drop in it. Since Kubernetes supports a wide range of applications and options, there are various different options and features available. Few best practices to follow while working with Kubernetes are: Make smaller YAML The yaml files are the heart of Kubernetes configuration. We can define multiple Kubernetes configurations in a single yaml. While yaml reduces the boilerplate when compared with JSON. But still yaml files are space-sensitive and error-prone. So always try to minimize the size of yaml files.  For every service, deployment, secrets, and other Kubernetes objects define them in a separate yaml file. Split your yaml files into smaller files. The applies here. single responsibility principle Smaller and Fast boot time for images Kubernetes automatically restarts the pods when there is a crash or upgrade or increased usage. It is important to have a faster boot time for the images. In order to have a faster boot time, we need to have smaller images. Alpine images are your friends. Use the Alpine images as the base and then add in components or libraries to the images only when they are absolutely necessary. Always remember to have smaller image sizes. Use builder pattern to create the images from Alpine images. Healthy - Zombie Process Docker containers will terminate only when all the processes running inside the container are terminated. The Docker containers will return healthystatus even when one of the processes is killed. This creates a Healthy-Zombie process. Try to have a single process inside the container. If running a single process is not possible then try to have a mechanism to figure out whether all the required processes are running. Clean up unused resources In the container world, it is quite common to have unused resources occupying the memory. It is important to ensure the resources are properly cleaned. Think about Requests & Limits Ensure that requests and limits are properly specified for all the containers. The requests are the limits that the container is guaranteed to get. The limits are is the maximum or minimum resource a container is allowed to use. Each container in the pod can request and limit their resources. resources: requests: memory: "100Mi" cpu: "100m" limits: memory: "200Mi" cpu: "500m" RED / USE pattern Monitor and manage your services using RED pattern. Requests Errors Duration Track the requests, errors in the response and the duration to receive the response. Based on this information, tweak your service to receive optimum performance. For the resources, use the USE pattern. Utilization Saturation Errors Monitor the resource utilization and how much the resources are saturated and what are the errors. Based on this information, tweak your resources to optimize resource allocation. Previously published at https://sendilkumarn.com/blog/kubernetes-for-everyone

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