Have you ever heard of the term cloud computing and the promising benefits which it can bring forward? If yes then you must be aware of the relative terms that are often used with the term cloud computing or cloud based systems? Some of these terms you might have heard could be Kubernetes or Docker. Both of these are the half parts of a complete puzzle, without setting the first you can’t have the second and vice versa. In this article though, we are specifically going to talk about Kubernetes, its functions, advantages and how it can be deployed with the help of Azure DevOps systems.
But before the launch of the Kubernetes as a dedicated program using a definite pipeline, it is important to know what it is about, its relation with Docker and why you should tether with its deployment with a sophisticated cloud management systems such as azure DevOps infrastructure as code.
So, without further ado let’s get right into it;
What is Kubernetes, functions and advantages?
Kubernetes is a dedicated system that provides with agility and is also responsible for the scaling or development of the interpretable raw data, software packages and or special features within some kind of container based systems such as Docker. These packages then can be set to be delivered towards targeted customers to ensure faster deployment of the systems the packages are laced with end to end encryption that ensures complete safety and integrity of the data which is stored within Kubernetes systems and is designed for optimized deployment.
- It provides the effective scheduling of the systems that help in the deployment of the updates or resources in a dedicated manner. The scheduler will also help to discern the timing on which the next update is required to be installed.
- You can scale your business according to the specific needs. For example, you can upgrade or downgrade anytime, deducting, or including various system based resources or other technical elements as per your business requirements.
- You can recognize various IP systems or network configurations related to your network infrastructure by only jangling a few keys across your input source. Even from the cluster of interconnected and differentiated IP addresses used worldwide, you will be able to recognize your particular IP addresses with the help of unique codes.
Kubernetes provide effective scaling, software management as well as the deployment of the tools or software systems at a faster rate. The best thing that Kubernetes is engaged in is to manage the containers across multiple server systems or either a single or centralized server infrastructure.
Enough with the illustrations of Kubernetes such as what it is and what it can do, now is the time to move onto the specificity of this article which is to deploy Kubernetes with azure DevOps integrated systems starting right now.
Deploying Kubernetes using Azure DevOps systems
As sophisticated as the package might sound, you would require a few prerequisites to begin with, such as you would have to buy an Azure cloud based membership or subscription. This will help you to create an Azure container registry for the rest of the pieces of the puzzles to fall onto the right places. When you have taken care of all the prerequisites, you can begin with the actual process of deploying Kubernetes.
What all the steps of the process will negate to you is the process of coming up with a Docker based simulation that can help you send/push your Docker file source image and be interpreted by the Kubernetes based systems for effective deployment and agility. So, what are you doing basically is that you are setting up with Azure DevOps a Docker image utility for your projects to be pushed or deployed to Kubernetes for the sake of deploying them to targeted audience. Anyway when you have grabbed the essence of the process, the rest gets easy. Detailed instructions on how to do that are described as follows;
Come up with an Azure container registry
As described earlier you need a Docker simulated pipeline to be able to scale to a Kubernetes based interface which is why you will have to develop an Azure container registry. It is private registry within Docker summated across Azure DevOps platform which stores the dedicated data of the Docker source image and then pushes the images into a registry.
What you will have to do is to install Azure command-line interface, check the version of the azure-CLI version and use a variety of commands to set-up the Azure container registry. You won’t have to worry about the specificities of the process as you will be guided accordingly if fall into any complexities.
Continuous integration
CI or continuous integration is the next piece of the puzzle and is very much important to set-up because if not done properly the whole process of coding and programming would fall into a complete abyss. As you can gather that in the world of DevOps based systems and run through cloud computing, CI is the key to achieving the goals as set-up by the organizations based on their respective needs. CI applications within a dedicated pipeline would provide you with enough space to integrate or pitch in any other forms of codes/programming intervals that you might like to add and then have the system recognize those integrations as code which then can be processed further.
Continuous development via Azure Kubernetes cluster
Finally, when all is said and done, you would have to create a dedicated Azure Kubernetes cluster which would help you with the process of effective deployment, scaling the updates and effectively managing all of the systems in a definitive proportions.
All of the coding/programming details that you would require to go on with these integrations would be provided to you by the help of Azure DevOps and related technologies.
If you find the need of training your DevOps oriented teams or want to jump into a more vivid notion of how clustered mass of DevOps operate then it is recommended to choose a best DevOps course that you can come around. Doing so would extremely help you out with the knowledge you require to understand and work with DevOps oriented systems.