Why Kubernetes is a must learn to become Cloud Native
Kubernetes is a major pillar when talks come to being cloud native, because Kubernetes alongside its vast ecosystem of tools, will singlehandedly construct, scale, and operate any of your cloud applications. This major power that Kubernetes has is a valid reason Kubernetes is a must-learn in becoming cloud native. This article has looked more into Kubernetes and why it needs to be learned to become cloud native.
The term "Cloud Native" has been in circulation for a while, and it's known as a term that encompasses the various tools and techniques needed by software developers to scale, build, deploy and maintain cloud applications.
There are different, and many definitions given to what cloud native is in the tech world. But one way or the other, they all still arrive at the same central idea.
Cloud native architecture or technology is an approach used to build, develop and run scalable software applications that work in modern and dynamic environments. The environment can come as a private cloud, public cloud, or hybrid (both private and public) cloud. The technique of cloud native computing allows developers to manage and maintain loosely coupled systems to show significant changes with minimal effort, also with the help of automation. Examples of cloud native approaches are Immutable Infrastructure, Containers, Service Meshes, and Declarative APIs.
Organizations have been relying on this initiative to evolve their business and increase their capabilities to accelerate growth. The cloud native initiative is all about speed and scalability no matter the circumstance. As time goes by and businesses grow, so does the adoption.
The end-users keep wanting more ingenious features, speedy responsiveness, and no failure or crashes. Kubernetes, on the other hand, is an open source platform that is used in managing containerized workloads and services using automation and declarative configuration. There are quite some factors attached to Kubernetes being a must-learn to become cloud-native, and we'll be taking a detailed look into each factor to make you understand better.
Kubernetes is open source.
When technology is open source, it is accessible to anyone and everyone and can be viewed, modified, or even distributed. Kubernetes being open source gives it the advantage of being accessible to the public. Anyone can leverage this factor, and they can make modifications to make it better. Lots of enterprises use open source solutions to construct, deploy and manage scalable applications for their businesses. The open source ecosystem is used in developing many cloud native solutions, and kubernetes is a significant pillar in developing these cloud native solutions.
In 2017, the Cloud Native Computing Foundation (CNCF) gave a set of standardized APIs to improve Kubernetes. The standard APIs given for kubernetes will help easy migration from one version to another without encountering complications while continuous improvements are made on the project. The improvements wouldn't have been possible with Kubernetes not being open source.
Kubernetes helps in orchestrating a hybrid cloud.
Deploying a cloud native application is all fun and fabulous until your cloud provider experiences a downtime, and your cloud application also goes offline until things get restored. We use a few things to run our cloud applications, including cloud platform services, horizontal and automatic scaling, node handling and transient failures without degrading, etc. The usage of a cloud platform service is one of the major factors that will make our cloud application useful. Still, there are also times that these cloud service platforms will have network issues. Therefore, we won't be able to deploy in an automated fashion because of differences in each cloud provider's mechanism. But with kubernetes, this is no more a problem because you can quickly deploy your application to a mixture of public and private clouds as Kubernetes has solved the orchestration problem that affects hybrid cloud deployment.
Kubernetes is adapted for microservices architecture.
Microservices architecture is an architecture with bounded contexts and loosely coupled services, i.e., each service can be updated independently of the other. For microservices to have a smooth workflow, containerization is introduced whereby each service or microservice can be run in different containers and be operated in isolation from each other. Now, to orchestrate or manage these containers holding each service, Kubernetes is needed, and what does kubernetes do? It orchestrates because it's an orchestration platform to run multiple clusters.
Kubernetes is an API-first platform, and cloud native is also API-first.
API-first is a situation whereby your APIs are first considered when a development process starts. In Kubernetes, while deploying our instances, the ReplicaSet Controller always makes sure that it keeps the number of pods and cluster states used for deployment over time. That is what we refer to as API-first, as it considers the APIs with respect to what it has been made to do overtime. This is also the cloud native way because, before a development or update process starters for modern applications, users' feedback and requests are mainly first attended to through the help of the API-first concept.
Kubernetes "forces" applying the cloud native practices
In cloud native, applications are always needed to be scalable, portable, and fast. For enterprises that use cloud native technologies, the quicker and more scalable their applications are, the more agile business becomes. Users will want to have an always-on, highly available application that experiences no downtime. Cloud native applications will enable your developers to address any request or update needed in time, and these are the feature that kubernetes offers. The ability to continuously integrate, deliver, and deploy your apps allows the users not to experience any downtime and long wait.
Kubernetes has a huge ecosystem
As Kubernetes has grown big and extended across to dominate the container environment and the cloud native community, it has fostered a number of tools and services in the extensive ecosystem to make its usage and functionality more efficient. Some of the tools in its ecosystem are described thus:
- Cluster monitoring
The tools of this category are used in monitoring clusters and for alerting if any development takes place within the cluster; example of the tools are:
Prometheus - A system and service monitoring system;
Grafana - it lets you be able to query, visualize, set alerts and understand your metrics information on tools like Prometheus, Graphite and InfluxDB;
Thanos - A metrics setup with high storage capacity.
- Cluster management
As clusters have been created in kubernetes, they need to be adequately managed, and there are many tools used for this, few of them are
Rancher - an open source container management platform that makes it easy to run Kubernetes anywhere. It is mainly built for organizations that deploy containers in production;
Kind - a tool used in running Kubernetes clusters locally with Docker container nodes.
- Logging and tracing
The containers used in kubernetes run into some problems at times, and we'll need to narrow down or track the error. This is where logging and tracing tools help us.
Loki is a horizontally-scalable logging system, multi-tenant log aggregation system, and highly available logging tool inspired by Prometheus.
Jaeger is a distributed tracing platform used in monitoring microservices-based distributed systems. It was created by Uber Technologies and donated to the CNCF.
Troubleshooting your Kubernetes clusters, nodes, pods, or containers is by identifying, diagnosing, and resolving any issue they have. And to do this, you will need tools to help; a few of these tools are:
K9 - It is a Kubernetes CLI that has a terminal UI that can be used to interact with our clusters
Kubectl-debug allows you to run a new container in running pods with all the troubleshooting tools installed for debugging purposes.
- GitOps tools
"GitOps is a way to do Kubernetes cluster management and application delivery. GitOps works by using Git as a single source of truth for declarative infrastructure and applications," as defined by Weaveworks, a Kubernetes management firm that first introduced the term in 2017. To operate GitOps, it is recommended to use one of the existing GitOps tools rather than building your own one.
FluxCD is a continuous delivery tool that synchronizes the Kubernetes environment with a declarative configuration source. It monitors changes to the version control system and automatically updates and deploys new codes to the environment.
Argo CD is a declarative, GitOps continuous delivery tool for Kubernetes.
Jenkins X is the GitOps variant of Jenkins that automates the continuous delivery of change through your environments via GitOps and creates previews on Pull Requests to help you accelerate.
- Security tools
The strong pillar in Kubernetes security is the 4C's of cloud-native security - Cloud, Cluster, Container, and Code. To handle security, we need security tools, and some of them are:
Terrascan- a static code analyzer for IaC,
Kube-hunter - a tool developed to increase awareness and visibility to hunt security issues in the Kubernetes environment. It specifically hunts for weaknesses in Kubernetes clusters,
Kubeaudit is a Go package and command-line tool used to audit kubernetes clusters for various security concerns like don't run privilege, drop scary capabilities - don't add new ones, use a read-only root filesystem, etc.
- Machine Learning
With the scheduling, scalability and batch processing features that it offers, Kubernetes is used by data scientists and ML engineers to scale, optimize and distribute models across cluster of servers. The ecosystem of Kubernetes when it comes to ML is getting more and more noticed and tools from this ecosystem are being adopted as more engineers are adopting Docker and Kubernetes, some of these tools are:
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
Kubeflow is a project dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable.
Pachyderm is a tool to manage data versioning and pipelines for MLOps. It provides the data foundation that allows data science teams to automate and scale their machine learning lifecycle while guaranteeing reproducibility.
- CI/CD tools
Continuous Integration and Delivery are best practices for DevOps teams; there are various CI/CD tools. A few of them are Skaffold - a command-line tool used for continuous development in Kubernetes applications.
ArgoCD - a declarative, GitOps continuous delivery tool for Kubernetes
Spinnaker - an open source continuous delivery platform used in releasing high velocity and high confidence software changes.
- NoCode CI/CD tools
NoCode is disrupting every workflow in software development, and DevOps is not left out.
Looking at NoCode from the perspective of a business owner, it is a very empowering technology that will help you get things done quickly while spending less.
In 2017, GitHub CEO Christ Wanstrath said in one of the company’s annual user conferences, “The future of coding is no coding at all.”
Kubernetes is one of the most complex but beneficial technologies used in DevOps. Using NoCode tools such WildCard to handle the complexity of Kubernetes will reduce the learning curve and help you deploy Kubernetes applications faster.
It’s a NoCode platform that provides a solution to help organizations, and developers, even those without DevOps experience or coding knowledge, to successfully implement and manage versioned infrastructure using NoCode CI/CD pipelines. It enables collaboration, auditing, and automation.
You can use Wildcard to build, deploy, and manage applications without writing a single line of code. Start for free by singing using Github or GitLab.
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