Container deployment has transformed established software development practices. New tools and techniques were necessary so Google developed Kubernetes, an open-source container orchestration system for automated scaling, deploying and managing applications.
It provides a unified API interface that can manage even the most intricate systems, spread across multiple servers and platforms.
Find out what makes Kubernetes an indispensable tool for managing and deploying containers.
What is Container Orchestration?
A container orchestration tool, such as Kubernetes, automates container management in a constantly shifting and chaotic environment. To fully understand its role, we shall dive deep into the complexity of container environments.
Containers are small virtual environments with individual memory, system files, and processing space. They do not need their own operating systems and are much lighter than traditional virtual machines. Their size and self-sufficiency make them portable and infinitely scalable across different devices and operating systems.
Developers can now design applications as a set of smaller, independent microservices. Ideally, a single service should only perform a single function. These microservices are then coupled and deployed quickly and easily on a Kubernetes cluster.
How Does Kubernetes Work?
Containers are designed to be as light-weight as possible. As a result, they are fragile and transitory. Instead of boosting the durability of an individual container, Kubernetes uses the unstable nature of a container and turns that weakness into an asset.
Kubernetes only needs a general framework of what you would like your cluster to look like. This framework is usually a basic manifest file you provide to Kubernetes using a command-line interface tool.
The default Kubernetes command-line interface is called kubectl. Kubectl is used to directly manage cluster resources and provide instructions to the Kubernetes API server. The API server then automatically adds and removes containers in your cluster to make sure that the defined desired state and the actual state of the cluster always match.
The main elements of a Kubernetes cluster are the Master Node, Worker Nodes, and Pods. The components that make global decisions about the cluster, like the API server, are located on the Master Node.
Note: See Understanding Kubernetes Architecture with Diagrams where we break down Kubernetes architecture and take a look at its core components.
Kubernetes Master Node
A Node is a physical machine or VM. The Master Node is the container orchestration layer of a cluster. The components of the Master Node administer Worker Nodes and assign individual tasks to each. It is responsible for establishing and maintaining communication within the cluster and for load balancing workloads.
|API Server||The API Server communicates with all the components within the cluster.|
|Key-Value Store (etcd)||A light-weight distributed key-value store used to accumulate all cluster data.|
|Controller||Uses the API Server to monitor the state of the cluster. It tries to move the actual state of the cluster to match the desired state from your manifest file.|
|Scheduler||Schedules newly created pods onto worker nodes. Always selects nodes with the least traffic to balance the workload.|
Kubernetes Worker Node
The Master Node components control the Worker Nodes. There are multiple instances of Worker Nodes, each performing their assigned tasks. These nodes are the machines where the containerized workloads and storage volumes are deployed.
|Kubelet||A daemon that runs on each node and responds to the master’s requests to create, destroy, and monitor pods on that machine.|
|Container Runtime||A container runtime retrieves images from a container image registry and starts and stops containers. This is usually a 3rd party software or plugin, such as Docker.|
|Kube-proxy||A network proxy that maintains network communication to your Pods from within or from outside the cluster.|
|Add-ons (DNS, Web UI..)||Additional features you can add to your cluster to extend certain functionalities.|
|Pod||A pod is the smallest element of scheduling in Kubernetes. It represents a ‘wrapper’ for the container with the application code. If you need to scale your app within a Kubernetes cluster, you can only do so by adding or removing pods. A node can host multiple pods.|
How to Manage Kubernetes Clusters
Kubernetes has several instruments that users or internal components utilize to identify, manage, and manipulate objects within the Kubernetes cluster.
Labels are simple key/value pairs that can be assigned to pods. Once assigned, pods are easier to identify and control. The labels group and organize the pods in a user-defined subset. The ability to group pods and give them meaningful identifiers improves a user’s control over a cluster.
Much like labels, annotations are also key/value pairs and can be used to attach metadata to objects. However, Kubernetes does not use annotations to select and identify objects.
Annotations store information that is not meant to be used by Kubernetes’ internal resources. They could contain administrator contact information, general image or build info, specific data locations, or tips for logging. With annotations, this useful information no longer needs to be stored on external resources, boosting performance.
Namespaces in Kubernetes
Every object in a Kubernetes cluster has a unique ID and a name that denotes its resource type. A namespace is used to keep a group of resources separate. Each name within a namespace must be unique to stop name collision issues. There are no such limitations when using the same name in different namespaces.
This distinctive feature allows you to keep detached instances of the same object, with the same name, in a distributed environment.
To list existing namespaces in a cluster type the following command in your command-line interface:
kubectl get namespaces
The concept of microservices implicitly means that multiple instances of any given service need to be deployed and run simultaneously. Replication controllers manage the number of replicas for any given instance of a pod. By combining replication controllers with the user-defined labels, you are easily able to manage the number of pods in a cluster by using the appropriate label.
For example, we can set the number of replicas in our configuration file to five (5). If there are only three (3) replicas running at the moment, Kubernetes will spin up two (2) more to match our desired state. If 10 replicas are running, Kubernetes is going to terminate five (5) of them.
Kubernetes continuously works to harmonize the number of replicas with the number defined in your configuration file.
A deployment is a mechanism that lays out a template that ensures pods are up and running, updated, or rolled back as defined by the user. A deployment may exceed a single pod and spread across multiple pods.
Replication controllers control the number of replicas of a service. Pods are added or removed from a cluster regularly. During this process, pods often move around the cluster and even get deployed on different nodes. Due to this fact, the IP address of a pod is not constant. The Kubernetes Service uses a label selector to group pods and abstract them with a single virtual IP used to discover these pods and interact with them.
Why You Need Kubernetes?
Efficient Resource Usage
Container orchestration tools, like Kubernetes, conserve resources more efficiently than a human could ever do. Kubernetes monitors the cluster and makes choices on where to launch your containers based on the resources currently being consumed on your nodes.
Container Communication and Synchronization
Since an app often requires more than one container, Kubernetes can deploy multi-container applications and make sure that all the containers are synchronized and communicating with each other.
Kubernetes offers insight into the health of your application. It can provide vital information and metrics of your containers and clusters. When an application goes down, Kubernetes automatically recovers it by spinning another container with minimal downtime with the optimal use of system resources.
Without orchestration tools, scaling your applications would become a time-consuming process. Organizations can now quickly adapt to market needs by adding or removing containers depending on momentary workloads. For example, online retailers can instantly increase their application’s capacity during increased demand. In periods of lower demand, administrators can quickly scale the application back down.
How to Start With Kubernetes
Since Kubernetes is a system for setting up and coordinating containers, a prerequisite for using it is to have a containerization engine.
There are many container solutions out of which Docker is the most popular today. Other container providers include AWS, LXD, Java Containers, Hyper-V Containers, and Windows Server Containers.
Apart from containers, there are other projects and support that Kubernetes relies on to give their users the full experience. Some of them are:
- Docker or Atomic Registry (for the official registry)
- Ansible (for automation)
- OpenvSwitch and intelligent edge routing (for networking)
- LDAP, SELinux, RBAC, and OAUTH with multi-tenancy layers (for Kubernetes security)
- Heapster, Kibana, Hawkular, and Elastic (for telemetry)
For beginners who still have no experience of deploying multiple containers, Minikube is a great way to start. Minikube is a system for running a single node cluster locally and is excellent for learning the basics, before moving on to Kubernetes.
Deploying a cluster of containers across multiple servers and platforms is a complex operation. Without an effective Container Orchestration Tool, it would be highly impractical.
A system like Kubernetes automates the management of your clusters. Not only does it help deploy an application, but it also maintains and manages it more efficiently than any human administrator could.
You now have a good understanding or container orchestration and how Kubernetes works. Use this knowledge to create and maintain dynamic software deployments.