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
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
The Rise in Big Data Analytics According to Internet World Stats, global internet usage increased by 1,339.6% between 2000-2021. With nearly thirteen times as many people using the internet, this has resulted in a massive increase in the amount of data being processed daily. Our increased sharing and consumption of digital media also compounds this increased usage to create an enormous pool of data for big data analytics firms to process.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore