An introduction of OpenShift, its extended characteristics on Kubernetes, its use cases and its case studies | By Soumya Biswas
Introduction:
In this blog, I will provide an overview of OpenShift, the features he uses at the top of Kubernetes, some differences from it compared to Kubernetes and its user cases.
Problems with Kubernetes:
The environment configured with Kubernetes increases the workload of developers and the operational team. In Kubernertes, the pods are configured with a containerized image. Here, the developer must first create the code and with the help of the Docker file, he must convert it into an image. This image must be pushed to DockerHub or to any local repository and from their image will be extracted to create pods. Here, the developer’s task has increased to learn the Docker file writing process and the operations team must build the image manually and create the pods with it. The action will also occur when the code is updated. The developer must write Dockerfile with the code and the updated operations team must build the image, push it on Docker Hub or any other local repository, then manually, they must define the image for the relevant deployment module. Kubernetes do not use intelligence here, this process can be automated with Jenkins, Gitlabs, etc. By creating CI / CD tools, but again, the problem could manage several software (i.e. Kubernetes, Jenkins, Gitlab) to deploy and manage the application. Pods also consume resources, that is, use the processor / memory that is not automatically monitored by Kubernetes. This must be managed by monitoring tools like Prometheus / Grafana by integrating the tools in Kubernetes.
Why OpenShift:
All these manual actions are automated in OpenShift. OpenShift is the main hybrid hybrid hybrid platform in the industry powered by Kubernetes, that is to say that it uses all Kubernetes features in addition to certain smarter features and it is developed by Redhat. OpenShift will decrease the workload of developers and the operational team. It will continue to monitor the SCM tool where the code is pushed, once the new code is available, it will automatically download the code and cover it on an image with its functionality S2i that is to say an image source And will push the code to the private repository, this process is called buildconfig (British Columbia) and update deployments with a new code to automatically add new features to applications, that is to say, avoiding the use of any external tool like Jenkins, etc. OpenShift is also delivered with an integrated monitoring tool that will continue to monitor the pods and inform the OPS team for any high CPC, memory, use of the disk. All these biggest functionalities of OpenShift offer flexibility to developers, that is to say that they do not need to know Docker or the process to write the Docker file and operations engineers, that is to say that they do not need to manage a separate automation tool like Jenkins to download the image of the container and push them towards deployments or to manage surveillance tools like Prometheus / Grafana or their manual task can also be complimentary.
Note: To benefit from the functionality of the OpenShift, the service must be subscribed to Redhat.
How to access OpenShift:
Unlike Kubernetes, OpenShift is also accessible in three different ways.
- Web gate
- CLI (OC)
- API (YML file)
User case for OpenShift:
Deployment and management of native applications in the cloud: OpenShift is a native Kubernetes platform, which makes it ideal for deploying and managing native applications in the cloud. The native applications in the cloud are built using architecture microservices, which makes them very scalable and resilient.
Modernization of inherited applications: OpenShift can also be used to modernize inherited applications. By containing inherited applications, they can be made more portable and scalable.
Execution of critical mission applications: OpenShift can be used to execute critical mission applications. The integrated platform’s integrated safety features and high availability capacities make it ideal for executing applications that cannot afford to decrease.
Building and deployment of applications with high data intensity: Support for the platform for various data storage options facilitates the creation and deployment of applications with high data intensity.
Running Edge Running IT applications: EDGE computer applications are deployed on the edge of the network, closer to end users. This can improve performance and reduce latency for applications requiring access to data in real time.
Additional use cases:
DevOps: Improve the DevOps process by providing a centralized platform for construction, deployment and management of applications.
Essay: Create a stadium environment to test applications before being deployed in production.
Training: Train developers to create and deploy containerized applications.
Using OpenShift, organizations can improve the speed, agility and safety of their application delivery process.
Case study: Deutsche Bank
Face problem:
As a primary financial service provider for private customers, businesses and trustees, Deutsche Bank has adopted positive trends in digital transformation. By contesting traditional commercial approaches, the bank sought to improve the experiences of digital customers – a goal directly linked to improving its developer experience.
The specialization of restrictive infrastructure has made integration difficult and the development of slow applications. The management of thousands of servers and databases has hampered the growth and adoption of more agile technologies. Many operating systems were used on several data centers.
Solution:
The bank has seen that a new cloud -based approach was necessary to support not only its current activities, but also future data needs. Deutsche Bank also wanted to support a more innovative and devops approach to replace its traditional cascade processes and monitor the pace of rapid and iterative digital innovation. To obtain the necessary scale and flexibility, the bank sought to establish a Paas which would rationalize development and management, would reduce risks and support more agile work in all its commercial units.
To build its strategic platform as a service, Deutsche Bank has requested an open source solution. After years of success with Red Hat Enterprise Linux, the bank added Red Hat Openenshift Container Platform and Red Hat Ansible Tower to build fabric, an application development platform based on containerized microservices at the bank. The fabric runs on Red Hat Enterprise Linux in several data centers and in the Microsoft Azure Public Cloud environment. RED HAT OPENSHIFT Container Platform provides management of development -based development and microservices, scaling composition and performance capacity of servers dedicated to cloud resources as needed. The two solutions are deployed and maintained using Red Hat Ansible Tower, a framework that automates and standardized it on a business scale.
Benefits:
1 and 1 Reduce the development time for end -to -end applications from 6 to 9 months to 2 to 3 weeks
2. Simplified collaboration DevOps with flexible integration and agile approach
3. Optimized use and costs of the data center and the cloud capacity with microservices, containers and cloudbursting
