Kubernetes architecture pdf

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Kubernetes architecture pdf

Containerization has brought a lot of flexibility to developers in managing application deployment. However, the more granular the application, the more component and therefore requires some kind of management for them. One still has to take care of the programming of the implementation of a certain number of containers at a certain node, network management between containers, following the allocation of resources, moving them around as they grow and much more. Almost all apps nowadays need to have answers for things would be replicating Auto-scaling components of balancing loading Running updates logging over monitoring components and health verification service Discovery authentication Google gave a combined solution for what Kubernetes is, or is called shortly - K8s. In this article, we will look into the moving parts of The Hububernets ? which are the key elements of the key elements of The Kubernetes ? which are the key elements of the key elements , what they are responsible for and what is their typical use. Then we will install them all using the docker container provided as a playground by the K8s team and review the implemented components. Glossary Before we dive into the configuration of components, you should get comfortable with some Glossary Kubernetes. The Kubunetes bridge aims to manage elastic applications that consist of several microservices that communicate with each other. Often these microservices are tightly coupled forming a group of containers that would usually be in a non-containerised configuration run together on a single server. This group, the smallest unit that can be programmed to be implemented through K8s is called a capsule. This group of containers would share storage, Linux namespaces, cgroups, IP addresses. They are therefore co-located share resources and are always scheduled together. The pods aren't meant to live long. They are created, destroyed and recreated on demand, based on the status of the server and the service itself. Service As pods have a short lifespan, there is no guarantee on the IP address on which they are served. This could make communication microservices hard. Imagine a typical Frontend communication with Backend services. Therefore, The K8s introduced the concept of a service, which is an abstraction on top of a number of pods, usually requiring to run a proxy on top, for other services to communicate with it through a virtual IP address. This is where you can configure the load balancing for numerous pods and expose them through a service. The Kubernetes components A K8s setup consists of several parts, some of them optional, some mandatory for the entire system to work. This is a high-level diagram of the architecture Let's take a look at each of the Component. The main node The main node is responsible for managing the Kubernetes cluster. This is the entry point for all administrative activities. The main node is the one that takes care of orchestrating the working nodes, where the actual services are running. Let's dive into each of the components of the main node. The API Server Server is the entry point for all REST commands used to control the cluster. Processes REST requests, validates them, and runs linked business logic. The condition of the result must be persistent somewhere, and that brings us to the next component of the main node. etcd storage etcd is a simple, distributed, consistent key-value store. It is mainly used for shared configuration and service discovery. It provides a REST API for CRUD operations, as well as an interface to record observers on specific nodes, which allows a reliable way to notify the rest of the cluster about configuration changes. An example of data stored by Kubernetes in etcd is the job being programmed, created and implemented, bridge/service and state details, namespaces and replication information, etc. programmer Deployment of configured pods and services on nodes happens due to the programmer component. The programmer has the information available about the resources available on the cluster members, as well as the ones needed for the service configured to run, and is therefore able to decide where to implement a particular service. Optional controller-manager you can run different types of controllers inside the main node. controller-manager is a daemon embedding those. A controller uses the apiserver to track the shared status of the cluster and makes corrective changes to the current state to change it to the one you want. An example of such a controller is the replication controller, which takes care of the number of pods in the system. The replica factor is configured by the user and it is the controller's responsibility to recreate a failed capsule or remove an extra-programmed one. Other examples of controllers are the endpoint controller, the namespace controller and the service account controller, but we won't dive into the details here. The Pods work node runs here, so that the work node contains all the services needed to manage the network between containers, communicate with the main node, and assign resources to scheduled containers. Docker Docker runs on each of the work nodes and runs the configured pods. It is responsible for downloading images and starting containers. kubelet kubelet receives the configuration of a capsule from the apiserver and ensures that the containers described are in operation. This is the working service that is responsible for communicating with the main node. It also communicates with etcd to get information about the services and writes details about the newly created ones. kube-proxy kube-proxy acts as a network proxy and a load balancer for a service on a single working node. It handles network routing for TCP and UDP packages. And the final bit ? a command-line tool to communicate with the API service and send commands to the main node. Example configuration The easiest way to start is to run all the components described inside a docker container. Kububernetes offers a Instance docker that would start other parts of the system, and finally, the configuration image looks like this Premise the only thing you need for this setup is a docker daemon. The rest is taken care of the docker image. This example is intended for educational purposes. In a normal setup, you will have the commander and worker(s) separated and possibly running behind a firewall. Dockerizationd implementation Let's start by recovering and set the latest version of Kubernetes as an environmental variable so we can use it in subsequent calls. Run this command on the host server, where the docker daemon is running. export K8S_VERSION=$(curl-sS This will make a request to the stable kubernetes release file and set the K8_VERSION environment variable to the latest stable release release version We also assume that the host you are running on has amd64 architecture (you can refer to other architectures in this discussion). Exporting the system architecture as a variable on the arch export host server =amd64 Next, we run the hypercube docker instance, which will handle the downloading and startup of the other Kubernetes components. The hypercube container is given special, extended privileges so that it can access host resources, as well as run other containers on the host. This is done by mapping /root, /sys, and /var/run of the host to the container directories in read-write mode. Second, the container is run with the --privileged option that grants access to all host devices to the container and allows new containers to be started on the machine. This flag also requires the /var/lib/docker path to be a volume. --net=host and --pid=host allow access to the host's network namespace and PID, basically allowing the docker we run to see and control processed on the host and reuse network configurations. So putting that all together, and specifying gcr.io/google_containers/hyperkube-${ARCH}:${K8S_VERSION} image, as well as hypercube properties, we will run the following command on the host: docker run -d \ --volume=/:/rootfs:ro \ --volume=/sys:/sys:rw \ --volume=/var/lib/docker/:/var/lib/docker:rw \volume=/var/lib/kubelet/:/var/lib/kulet:-r\w\/-net=host \-pid=host \--name=hyperkube-installation program \-privileged \ gcr.io/google_containers/hyperkube-${ARCH}:${K8S_VERSION} \ /hyperkube kubelet \ --containerised \ --hostname-override=127.0.0.0.01 \-api-server s= \ --config=/etc/kubernetes/manifests \--allowprivileged --v=2 The container started running the hyperkube binary that starts itself all the components that we have discussed so far. This might take a moment, so after a while, if you run the docker PS command, you should see a similar to this: docker PS CONTAINER ID IMAGE COMMAND CREAT STATUS PORTS NAMES f267d9d1a24d f267d9d1a24d /setup-files.sh IP:1 About a minute ago Up About a minute k8s_setup.eb843218_k8s-master-127.0.0.1_default_721118f359852533089009890ac21208_3765dd28 09fc01b04ba6 gcr.io/google_containers/hyperkube-amd64:v1.2.4 /hyperkube programmer About a minute ago Up About one minute k8s_scheduler.dbfcc0_k8s-master-127.0.0.1_default_721118f359852533089009890ac21208_28c46205 4ac31a50c2bb gcr.io/google_containers/hyperkube-amd64:v1.2.4 /hyperkube apiserver About a minute ago Up About a minute k8s_apiserver.1082c1e0_k8s-master127.0.0.1_default_721118f359852533089009890ac21208_d5d50d58 375857e4dec5 gcr.io/google_containers/hyperkube-amd64:v1.2.4 /hyperkube proxy --m About a minute ago About a minute k8s_kube-proxy.a1014855_k8s-proxy-127.0.0.1_default_0cda4a663a246109121ac68b3c7e82b7_890d5a95 8b19a89a2695 gcr.io/google_containers/etcd:2.2.1 /usr/local/bin/etcd About one minute ago Up About one minute k8s_etcd.7e452b0b_k8s-etcd-127.0.0.1_default_1df6a8b4d6e129d5ed8840e370203c11_9e621ad8 3d6c9d9c60cd gcr.io/google_containers/hyperkube-amd64:v1.2.4 /hyperkube controlle About a Minute Ago Up About a minute k8s_controller-manager.76914b67_k8s-master-127.0.0.1_default_721118f359852533089009890ac21208_cb0abac9 155351af7913 gcr.io/google_containers/pause:2.0/puse About one minute ago Up About one minute k8s_POD.6059dfa2_k8s-master127.0.0.1_default_721118f359852533089009890ac21208_4365c22c 84b32314d407 gcr.io/google_ containers/puse:2.0 /puse About one minute ago Up About one minute k8s_POD.6059dfa2_k8s-etcd-127.0.0.1_default_1df6a8b4d6e129d5ed8840e370203c11_1003b43b 5e44113ee806 gcr.io/google_containers/pause:2.0 /puse About one minute ago Up About one minute k8s_POD.6059dfa2_k8s-proxy-127.0.0.1_default_0cda4a663a246109121ac68b3c7e82b7_f37316b9 197cd 920afc5 gcr.io/google_containers/hyperkube-amd64:v1.2.4 /hyperkube kubelet - About a minute ago Up About a minute hyperkube-installer Looking at the names of docker courts, it is not hard to guess what each component stands for: The first container in the list k8s_setup.k8s-master-127.0.0.1, takes care of setting up the main node, what it does, can be drilled down to create the basic auth file for access to kubernetes api server service tokens for accessing the ca CA server api and keys for https access to the Kubernetes API server You can see in the list , containers for each of the components that we discussed ? k8s_scheduler, k8s_apiserver, k8s_kube-proxy, k8s_etcd and k8s_controller-manager The following 3 bridge containers are so-call break containers, which are used to set the network initially before launching the actual container and finally the installation container we started to put all this together Implementing the new bridge Now that we have a small Kubernetes setup on our host, we should command line tool implement our bridge and the first service. We will use the docker installation container to demonstrate the kubectl in action. Enter the installation container using docker exec -it -it /bin/bash Export the K8S_VERSION variable again while being inside the export installation container K8S_VERSION=$(curl -sS The following command will download the correct version of the kubectl and place it inside /usr/bin/kubectl curl -sSL K 8S_VERSION/bin/linux/amd64/kutlbec /usr/bin/kubectl Make it executable chmod +x /usr/bin/kubectl Now you should be able to run a simple command version kubectl and get a similar output kubectl version Client Version: version. Info{Major:1, Minor:2, GitVersion:v1.2.4, GitCommit:3eed1e3be6848b877ff80a93da3785d9034d0a4f, GitTreeState:clean} Server version: version. Info{Major:1, Minor:2, GitVersion:v1.2.4, GitCommit:3eed1e3be6848b877ff80a93da3785d9034d0a4f, GitTreeState:clean} To list the nodes kubectl get nodes NAME STATUS AGE 127.0.0.1 Ready

1d And finally, to deploy a sample nginx as a kubectl bridge run nginx --image=nginx --port=80 You can now exit the hyperkube-installer container we are in, using CTRL+D, and wait a bit for the nginx image to be downloaded. If you run the docker PS command on the host again, you will see 2 more containers appear docker PS CONTAINER ID IMAGE COMMAND CREAT STATUS PORTS NAMES b99ae41911d9 nginx nginx -g daemon off 31 minutes ago Up 31 minutes k8s_nginx.c8c72836_nginx-198147104-sdqet_default_791e301f-358 b-11e6-94ba-080027faa9e4_cde648eb eff5259a994 gcr.io/google_containers/pause:2.0 /puse 31 minutes ago Up to 31 minutes k8s_POD.cf58006d_nginx-198147104-sdqet_default_791e301f-358b-11e6-94ba-080027faa9e4_3e7040c5 2 containers were created with our command kubectl run - the first is the actual nginx container created and deployed by Kubernetes. The second, as explained above, is an infrastructure container - this is the first container that is turned on for a capsule, it sets the network for the bridge, then breaks. All other containers for a particular capsule, join the network configured by this container. To access the implemented nginx container, we will need to declare it as a service and obtain a specific IP address assigned to it. Login back to our container playground docker exec -it hyperkube-installer /bin/bash The following command exposes the implementation of nginx as a service and maps port 80 of the nginx service to port 8080 of the host kubectl exposes the implementation nginx --port=8080 --target-port=80 Now to see the list of services, we run kubectl get nginx service. The result should be similar to CLUSTER-IP EXTERNAL-IP PORT(S) AGE nginx 10.0.0.185 8080/TCP 12s You can see the list of services with the assigned IP address and portsexposed. Let's just take the IP address and set it to a variable to try to access nginx. ip=$(kubectl get svc nginx Now that the IP variable points to the correct service (in this case, that would be 10.0.0.185), 10.0.0.185), can run curl for the default nginx curl page http://$ip:8080/ The output should contain the usual nginx welcome page. This guide gives you a high-level overview of the architecture and moving parts of a Kubernetes configuration. We implemented a mini-kubernetes setup in a docker container, and deployed our punch bridge. To gain a deeper understanding, you are very encouraged to deploy each of the components separately and configure their communication from scratch. Our curated newsletter throughout programming, productivity and inspiration. Keep up to date with the X-Team culture. Culture.

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