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It’s no major news story that Kubernetes is one of the most commonly used container management systems in the tech space. Kubernetes’ robustness makes it possible for users to deploy, scale, and manage containerized applications. Its extensibility and portability have gained it loads of popularity in the cloud-computing ecosystem. In addition, Kubernetes also gives users the flexibility of choosing which programming language, or framework, to use and also allows users to be able to monitor and log errors.
Kubernetes is a powerful and extensible open-source platform for managing, scaling, and deploying containerized applications and services. It’s a system designed to handle the scheduling and coordinating of a container on a cluster and manage the workloads to ensure they run reliably. Kubernetes allows us, the users, to define the way our applications run, and how our application interacts with other applications. Kubernetes is a tool that allows us to manage our cloud infrastructure, and the complexities of having to manage a virtual machine or network so that we can focus on developing and scaling our application. Kubernetes provides a flexible and reliable platform to manage and scale containers with a simple, easy interface.
The Kubernetes project was created by Google, and has its roots in an internal project called BORG. Kubernetes was later donated to the Linux Foundation to form the Cloud Native Computing Foundation (CNCF).
Kubernetes is supported by Google Cloud, AWS, Microsoft Azure, and several other cloud computing companies. It has been widely accepted and has steady adoption growth which gives it an important position in the world of container management and orchestration.
It’s important that a developer understands how Kubernetes works to be able to get the most out of it. Kubernetes is structured in a layer-like form, where the high layer is an abstraction of the intricacy in the lower layer. We’ll outline some of the layers and foundational terms used in Kubernetes and how they function. Kubernetes architecture includes the following:
A pod is the smallest deployable unit of Kubernetes. It consists of a container, or group of containers, that share allocated resources like memory, life-cycle, and storage. Pods have a single IP address that is applied to every container within the pod. A pod is literally a representation of one or more containers that should be treated as a single application. Users are usually advised not to manage pods directly, rather they should work on high-level objects that use the pods. Kubernetes can be configured to deploy new replicas of your pod to your cluster in situations where you need to scale and a single pod can not carry the load of your application. Meanwhile it is usually a standard to run multiple replicas of a pod ro allow load balancing and failure resistance.
The Replication Controller is considered to be a wrapper on a pod. Often abbreviated as an rc, the Replication Controller manages and ensures that a specified number of pods are running at a particular time. The Replication Controller maintains the pods that it manages, restarts them when they fail, or replaces them when they’re deleted or terminated.
The Replication Controller runs a reconciliation loop that monitors the number of running pods and also ensures that the specified number of replicas are always running. It maintains the replicas by either creating new replicas or deleting extra replicas where necessary.
The Replica Set is abbreviated as rs, and its job is to maintain a set of replica pods running at a given time. The replica set is considered a subset iteration of how the replication controller works, and it’s much more flexible with pods it’s meant to manage.
The deployments define how the user wants to run your application by allowing the user to set details of the pods and how the pods would be replicated via nodes. You can modify your Deployments by changing configurations, and Kubernetes will automatically adjust the replica set and manage the shift from different application versions. A deployment automatically spins up the requested number of pods and monitors them when added to a Kubernetes cluster. Also, it automatically recreates a pod when it dies.
The service is a collection of pods, more like an abstraction over the pods, that provides an interface for external consumers or another application to interact with them. The service provides a single IP address mapped to the pods but can be made available outside of the clusters using one of several strategies available.
A node is a virtual machine or physical server that runs and manages pods. It collects pods that work together just like pods collect containers that work together.
A node includes a container runtime, kube-proxy and kubelet. We could think of a node as a machine that allows us to insert different layers of abstraction. A Node is simply viewed as a machine with a set of CPU and RAM resources that can be utilized. Also, any machine can substitute any other machine in a Kubernetes cluster.
This serves as the main contact point for administrators and users to manage containers on the nodes. It accepts user requests through HTTP calls, or by running commands on the command-line.
A cluster is one or more nodes that run our application. A Kubernetes cluster can be seen as a pool of Nodes combined together to form a more powerful machine. When a program is deployed on a Kubernetes cluster, it is intuitive enough to handle the distribution of work to individual nodes. Also, if a node is removed or added to the cluster, it will automatically shift the work around and which individual machine or machines are running the coed won’t matter to the programmer.
With the simplified explanations of the architecture and terms in Kubernetes above, you can quickly deploy an application locally on your machine with Minikube, before trying it out on any cloud service of your choice.
The quick steps involved in deploying your containerized application will be highlighted below:
1. Create a namespace
kubectl create namespace <application_name>
2. Create a Deployment manifest file. Your manifest file should look like this:
apiVersion: app/v1 kind: Deployment metadata: name: <metadata_name> spec: replicas: 1 selector: matchLabels: app: <application_name> template: metadata: labels: app: <application_name> spec: containers: - name: <container_name> image: <username>/<container_name>:<version>
3. After creating the Deployment manifest file, the next step is to apply the deployment
kubectl apply -f <deploy_file_name>.yaml
4. The next step is to create or open the container port to be able to interact with the application on a browser. To do that we’ll run:
kubectl port-forward deployment/<metadata_name> -n <application_name> <port_number>:<port_number>
If you open http://localhost:3000/ on your preferred browser, you should be able to interact with the server as though it were running locally.
Kindly note that this is just a quick example of how deployment is on Kubernetes. There are actually more things to learn and do to deploy and scale in a Production environment.
This example is just to familiarize you with what the deployment process looks like.
Some of the important reasons why a developer might be interested in knowing or learning about Kubernetes are:
As we’ve shown above, Kubernetes comes with a lot of advantages. Let’s take a closer look at a few of those numerous advantages:
The popularity of a type of software plays a very vital role in the adoption and growth of that software. In the cloud community, Kubernetes is the most popular container orchestration platform and it has a large community of end-user, contributors, and maintainers because of its open-source nature. It’s also important to note that Kubernetes has support on many cloud computing platforms and cloud providers like Google Cloud, Microsoft Azure, AWS, etc.
One important advantage of Kubernetes is its quick deployment and application update features that enables improved productivity for developers. It allows the developer to focus on logically building the application. Kubernetes also has tools that help the developer quickly create CI/CD pipelines for easy deployment and application updates.
Kubernetes helps you scale without incurring operational increases and development team management. With Kubernetes, you’ll have less work on your infrastructure as you’ll only need to interact with Kubernetes.
Kubernetes has the ability to extend its functionality to cater to your application needs. The more complex your system becomes, the more flexible Kubernetes can be to manage it. Also, the Kubernetes’ community shares add-ons and extensions, so there are always enough tools to use in your Kubernetes journey.
Kubernetes helps enterprises save deployment and scaling costs with its expedient architecture. Kubernetes satisfies the needs of enterprises without incurring extensive cost on provisioning infrastructures for your applications.
Kubernetes is orchestrated in a way that operations, and the way services are managed, remains the same regardless of where you run your Kubernetes application.
The method for handling your infrastructure and application is the same for all Kubernetes applications. For example, your CI/CD pipeline remains the same for all applications. You won’t have to manage the dependencies on all your servers any longer as your applications will be shipped with self-contained dependencies.
Kubernetes allows developers, or enterprises, to easily run their application on a multi-cloud system. Kubernetes makes it easy to run your application on a multi-cloud provider and fully supports multi-cloud container deployment.
Kubernetes has numerous features to secure your clusters such as Kubernetes Secrets API, Pod Security Policies, Network Policies, etc., to thoroughly secure sensitive information.
As much as Kubernetes is beneficial, there are also some challenges to Kubernetes. Some of the disadvantages of Kubernetes include:
Kubernetes management comes with a lot of complexities - there are the difficulties faced in installing, configuring, and operating Kubernetes. It requires experience, continuous practice, and extensive training to become familiar enough to be able to debug and troubleshoot.
Kubernetes has a steep learning curve. And it’s highly recommended that a developer interested in learning Kubernetes becomes well-versed in best practices and has some tutelage from an experienced Kubernetes developer.
Kubernetes is in high-demand and it’s really important for developers to know a thing or two about Kubernetes to enable them to build scalable applications and easily deploy them.
Kubernetes gives the developer the ability to focus on logically building world-class applications with little to no worry about deployment, scheduling, and scaling with automatic deployment features and reliable infrastructures.
Prevent Kubernetes NetworkPolicy misconfigurations by enforcing policy as code