Implementing cloud-native applications
Here in this blog, we will learn about how to implement cloud-native applications.
The significance of application transformation
Businesses face a critical challenge in today’s rapidly changing digital landscape: how to embrace the potential of cloud-native architecture and free themselves from the limitations of legacy systems, all the while protecting existing investments where necessary. Why are cloud-native solutions so important? They provide increased agility, scalability, and security posture.
First, think about the usual challenges that conventional systems present. They frequently have intricate, monolithic codebases that impede deployment and development processes and make it challenging for businesses to react quickly to changes in the market. Maintaining regulatory compliance can be a difficult task, and addressing security vulnerabilities can be more difficult.
Cloud-native architecture is useful in this situation. Essentially, cloud-native computing is about utilizing containers and microservices to their full potential. By dividing applications into smaller, easier-to-manage components, microservices can speed up development and deployment. These microservices can be operated in a more standardized and isolated environment across various infrastructures thanks to containers.
OpenShift provides a unified platform that supports both traditional and cloud-native applications for enterprises looking to integrate their current applications with cloud-native architectures in an efficient manner. Organizations can transition to a cloud-native future while retaining their current workloads operating in virtual machines (VMs) on a single platform thanks to features like OpenShift Virtualization. OpenShift Virtualization, in conjunction with Red Hat Application Foundations and other middleware products and services, assists enterprises in establishing data connections between legacy and contemporary applications. This enables them to take advantage of cloud-native practices without causing any disturbances to their current systems.
Moreover, OpenShift facilitates the automation of workloads related to continuous integration and continuous deployment (CI/CD), which simplifies operations. This facilitates the faster development, modernization, and large-scale deployment of both cloud-native and traditional applications, enabling businesses to better adapt to changes in the market and increase their development agility.
Scalability is an area where cloud-native solutions excel. Businesses can more readily scale their applications to meet increasing demands by implementing orchestration and containerization. For highly distributed cloud architectures, Red Hat Runtimes (part of Red Hat Application Foundations) provides lightweight runtimes and frameworks that may shorten deployment cycle times.
Finally, security is a constant worry. Thorough testing and security inspections are integral to the process of development. Through image vulnerability scanning, tools like Red Hat Quay, a private container registry, improve security. When used in conjunction with Red Hat OpenShift, it can store built images from the automated CI/CD workflow in addition to pulls from authorized external image registries. This enhances the image lifecycle’s overall security posture.
To put it briefly, cloud-native technology is about enabling teams to overcome legacy limitations and innovate more quickly in order to advance the business.
Now let’s put this into practice.
Using Red Hat products, we deconstruct the important stages of this cloud-native application journey—from development to testing to production.
Step 1: Creation and preliminary integration
- Grow locally or virtually: Set up your development environment first. This can be done remotely or locally. For source code management and containerization that complies with the Open Container Initiative (OCI), use programs like Git or Maven. Red Hat Application Foundations includes Red Hat Runtimes, which you should also take into consideration. It provides lightweight frameworks and runtimes that are ideal for highly distributed cloud architectures, such as Quarkus and Spring Boot. This method makes the development process more uniform and gets the application ready for a comparable operating environment.
- Push to pipeline for CI/CD: You can integrate your code into OpenShift’s continuous integration and delivery pipeline once the initial development phase is complete. Investigate methods for automating the beginning of image builds using hooks, plugins, or uploads in order to optimize the pipeline’s transition from development to testing. Enhancing the efficiency and reliability of your software delivery pipeline is possible with hooks that can start builds automatically when changes are made to the code, plugins that make it easier to integrate with container registries, and manual uploads that give you exact control over the build process.
Step 2: Container management and ongoing integration
- Build container images automatically: With every code revision, OpenShift’s CI/CD pipeline automatically creates container images, following predetermined build configurations through source-to-image workflows. This automation integrates testing procedures and helps ensure that the container images for your application are updated with the most recent code changes. To identify the version or purpose of these images, label or tag them with specific terms (e.g., devImage, v1.0, latest).
- Organize pictures using Red Hat Quay: The container images marked for development are automatically built, stored, and managed within Red Hat Quay. Following this, they are pushed to the development infrastructure for additional deployment and testing. These container images are always ready for deployment because Red Hat Quay is the repository for them.
Step 3: Validation and testing
- For development testing, deploy: Red Hat Quay deploys the container images designated as devImages for testing within the OpenShift development environment. The purpose of this preliminary testing stage is to ensure that the application’s fundamental features are operating as intended. Unit tests, integration tests, and other tests that verify the application’s individual components are usually included. Finding and fixing problems early in the development process is the main objective.
- Carry out advanced testing: The container images marked for testing can be promoted to the OpenShift testing environment for more thorough and in-depth testing after the first round of development testing is finished. A wider variety of tests, including system integration, performance, security, and other tests, are typically included in this phase. The objective is to fully verify the functionality and performance of the application in a range of scenarios. Potential problems that might not have been discovered during the first development testing stage are identified with the aid of advanced testing.
Step 4: Production readiness and deployment
- Complete for production: The container images are tagged for production deployment once tests in the testing infrastructure pass. This entails confirming that the application satisfies all operational and scaling requirements before putting it into production.
- Implement in a live environment: The fully tested program is then put into use in the live environment. This indicates that the application’s development and initial deployment phases of its life cycle are finished, and it is now ready for end users.
Conclude
An overview framework for developing cloud-native applications with Red Hat products and solutions is given by these steps. We invite you to read Building Your Cloud Native Applications for a more thorough investigation and comprehension, as it provides a more in-depth analysis of its design.
Solution like “Telco 5G N6 LAN Consolidation with F5” and “Telco Service Assurance on Public Cloud” are especially pertinent for companies looking to incorporate cutting-edge technologies into their operations on a cloud-native basis. These showcase the use of Red Hat OpenShift and Red Hat Ansible Automation Platform and are appropriate for telecom companies investigating edge computing. “Intelligent Automation Workflow for Claims” demonstrates how businesses can improve operational effectiveness and enable data-driven decision-making by fusing automation and data science. When combined, these solutions show how cutting-edge technology and cloud-native methodologies can promote operational creativity and agility.
