Self-service availability, automatic infrastructure scaling, and dynamic resource pools are all advantages of cloud-native and Kubernetes-native technologies. This article will explore what it means to bring Java into the distributed, Kubernetes-first, cloud-native application development world we live in today, as well as why it is so critical. The cloud-native approach has a long history. Throughout that history, the patterns of organizations, architectures, and technologies that consistently, reliably, and at scale fully make use of the cloud’s capabilities to enable cloud-oriented business models have been defined as cloud-native. Cloud-Native can also be defined as a set of best practices that include, but are not limited to, continuous deployment, Linux container packaging, and microservices to help achieve the elastic scaling, speed of introducing new functionality, and increased automation that are required to adapt to an ever-changing competitive landscape. As a result, the ultimate goal is to be able to swiftly and cost-effectively implement cloud-native technology. However, Kubernetes-native is a category of cloud-native and is not distinct from the definition of cloud-native. A cloud-native application, for example, is designed to run in the cloud; a Kubernetes-native application, on the other hand, is designed to run on Kubernetes platforms, generating software that maximizes the functionalities of the Kubernetes API and components while also making infrastructure management easier. Additionally, all programs must be built for Linux container images such as Docker and OCI format before being launched on Kubernetes, allowing organizations to manage business applications across multiple and hybrid clouds. What’s more important, both cloud-native and Kubernetes-native solutions provide self-service access, automated infrastructure scaling, and dynamic resource pools, which distinguish them from traditional virtual machine-based applications.
What are the limitations and challenges in the Kubernetes-native infrastructure with Java?
Java was created with the goal of increasing network throughput for the most demanding enterprise applications while neglecting computational resources like memory, CPU, and disk storage. No one bothered that you had to pay a million dollars for only 2 GHz processors and 10 GBs of RAM to run business applications on 34 Java servers back then as long as the business apps were stable. Moreover, Java frameworks included sophisticated dynamic behaviors for mutable systems, implying that developers created intermediate code, or bytecode, and then deployed it to any Java virtual machine app server. These Java frameworks did a lot of acrobatics to keep apps flying in the air, and they even let developers change the app while it was flying. With the development of Kubernetes-Native infrastructure and containers, however, these dynamic behaviors and related hefty footprints of Java programs no longer match how today’s developers and operations teams desire to build and deploy applications. For example, if one of your microservices needs to be deployed to more than 100 or even 1000 pods in Kubernetes to address scalability and reliability issues, Java frameworks’ dynamic behavior will compile and create the same microservice as the number of deployments. Using Java for Kubernetes-Native infrastructure, especially at scale, may be difficult.The native Java framework for Kubernetes must include:
- Container first design
For Kubernetes-Native use cases including high data volume transactions, rapid scalability, and serverless services with event-driven executions, a new Kubernetes-Native Java framework should make it efficient for containers with minimal memory usage and a fast first response time. Native compiling for Java programs, for example, allows Kubernetes native applications to be incredibly optimized, with startup times in the milliseconds and memory footprints that are 25-30 times smaller than the memory footprint of the identical microservices on Kubernetes. After all, increased density on the same Kubernetes lets businesses save money on infrastructure. - Remote development capability
Assume you’ve already deployed a business application on Kubernetes at a remote location. And now, how would you approach changing code for new business features, bug fixes, or even performance improvements? In general, you could edit the code locally first, then rebuild, retest, then redeploy the modified code to Kubernetes while still in the development loop. What if you could make changes to the remote Kubernetes straight from your local Java editor tool, without having to rebuild, repackage, and reinstall the code? This capability will boost developer productivity while also cutting down on development time for Kubernetes-native apps. - Easy to Kubernetes integration
Software developers want to use as many Kubernetes APIs as possible when creating business functionalities on Kubernetes. Configmap or Secret, for example, can be used to store sensitive information such as database login and passwords rather than the program itself. This development methodology would be more efficient in terms of scaling applications and ensuring system reliability.
