There's a new change that is being implemented in organization – them migrating their traditional models-based delivery processes to the DevOps model. Clearly, opting for the best technology available in the market is a priority for enterprises today.
One solution that is actively being sought and adapted to by organizations is cloud (technologies) with microservice architecture. The aim is to containerize application(s) and use the DevOps model for continuous integration and delivery, using tools such as Docker and Kubernetes for container orchestration.
Think of a scenario where a product needs to include web applications which are meant to be light weight and fast, such as MEAN stack or full stack; where there are constant changes with respect to the market; where new changes are expected to be part of product because this product has to be released to consumers. Along with this, take addressing maintenance and, versioning of changes into account too.
In the traditional model, development, testing, build, deployment and production releases are each separate processes. Some of these are handled manually, resulting in slowing their completion.
The current model, if adopted without implementing DevOps, includes a number of tasks which are carried out manually. For instance, building the code, testing it, deploying the specific changed version(s) of the code, deployment in a specific environment, version maintenance, rollback handling, and finally production deployment.
Manual intervention in each individual process adds to the time taken to complete it, apart from not guaranteeing agility.
To migrate from the tradition workflow to implement DevOps methodology in projects; considering microservice-type architecture instead of monolithic architecture for better advantages; migrating a project or products from on-premises servers to cloud servers – all three are considerations which help in being cost effective.
Consider a simple Nodejs and Reactjs based with mongo database web applications which can be exposed as an application though Nginx ingress. These web apps are designed with microservice architecture, and so, the aforementioned challenges can be overcome by containerising the application using Dockers and through open source tools - such as Jenkins - automating continuous integration and delivery. The goal is to use helm for versioning and package management and finally, Kubernetes for container orchestration on AWS Cloud servers.
Prerequisites:Kubernetes cluster has to be brought up for the deployment process as a prerequisite. Kubernetes cluster must have a master and a slave node type server availability, where the master node will maintain the assigning of an application to specific available nodes based on CPU requirements. This process is seem less and highly available.
Using Kubernetes orchestration for applications, a blue green deployment can be managed (deployment without downtime).
Mentioned below are Kubernetes services for different cloud providers:
Development: To develop web applications which are fast, REST APIs with responsive UIs for front end by using nodejs and react js/angular js for full stack development
Repository: GitHub can be used as a code repository and to handle branches
Packaging: Helm is a Kubernetes packaging manager which can be used to maintain the microservice as a deployment package to deploy on Kubernetes cluster(s). These packages can also be maintained on Git repositories
Continuous Integration and Continuous Deployment: Open source tools like Jenkins can be used to provide continuous integration and continuous delivery/deployment, wherein a pipeline can be built for each process to build, test, deploy and finally deliver.
Pipeline: All the above steps can be automated through Jenkins using Jenkins pipeline.
Step1: On code commit on any code repository, integrate the code repo with Jenkins and pull the changed code on to the master server
Step2: Build a Docker image with changed code, version the image and push the Docker image to any registery (eg: can use Docker hub)
Step3: Deploy the newly built Docker image as a container (pod) on the Kubernetes cluster as a helm package (versioning and rollback can be handled though helm)
Step5: On test success, this gets finally deployed to production automatically. Alternatively, this step can be completed with manual go
Kubernetes orchestration works well for web applications which are completely on the cloud. Even though on-premises orchestration can be handled using RKE and other available solutions which seem a bit complex, the high availability and seamless implementation of applications are handled well and easily for cloud deployments.
Contact Us Today
Today, any slight contact made with a present or future customer is an interaction that leaves behind a trail of intelligence – where did they come from, what prompted them to click or purchase, and how can the customer journey be improved. For e-commerce companies in particular, this information is a goldmine as it can help them accurately predict what their customers want and present them with the right product at the right time. In effect, analytics enables companies to study what happened in the past, in order to make better predictions for the future.Explore
Merely a half century or so ago, a semi-metallic contraption able to emulate the human brain in learning entirely new things by processing data would have promptly been hailed as the devil’s instrument, and then probably dismantled. Today, billions of dollars are invested, and some of the world’s most brilliant minds spend their time attempting to help machines get better at learning things on their own. And, though in its nascent stages, artificial intelligence powered by machine learning has started having a very tangible, real impact on the world around us.Explore
The next wave of technological disruption is here, and it is called Artificial Intelligence (AI). Whether or not AI has yet gone mainstream remains a matter of debate. But the potentially transformative technology is increasingly being discussed in boardroom meetings worldwide. And, it is fairly evident that the vision of an AI-driven enterprise is far too compelling for chief executives to let go and simply adopt a wait-and-watch attitude.Explore
For higher education institutions, dealing with the multiple challenges and priorities of their core mission is often a complex affair. Their primary focus always remains the same – attract the best students and provide the best education possible.Explore
Cloud computing has now become mainstream in the higher education sector. Institutions across the board are deploying different versions of the cloud to minimize capital expenditure, reduce time to market, and boost flexibility and scalability, among other objectives.Explore
Would you like to speak with an expert?x