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Exploring Spring 6.0: New Features And Enhancements For Java Application Development

Overview

Spring, one of the most popular frameworks for Java application development, continues to evolve with each new version. Spring 6.0, the latest major release, introduces a plethora of new features and enhancements that further enhance the developer experience and streamline the development process. 

In this article, we will delve into the world of Spring 6.0, exploring its key features, notable improvements, and benefits for Java developers:

  • Overview
  • Introduction To Spring 6.0
  • Key Features Of Spring 6.0 
  • Notable Improvements And Enhancements
  • Benefits And Best Practices For Spring 6.0 Adoption
  • Closing Thoughts

Introduction To Spring 6.0

Spring 6.0 is the next milestone in the Spring Framework’s evolution, building upon its strong foundation of dependency injection, component-based architecture, and robust enterprise features. It aims to provide developers with an efficient and modern toolkit for building scalable, maintainable, and high-performance Java applications.

Key Features Of Spring 6.0

  1. Reactive Programming Support
  • Spring 6.0 embraces reactive programming paradigms by offering enhanced support for reactive APIs and frameworks like Project Reactor and Spring WebFlux
  • Developers can build highly responsive and scalable applications using non-blocking I/O and reactive data processing
  1. Enhanced Module System
  • Spring 6.0 introduces a modular architecture, allowing developers to build and deploy applications as smaller, self-contained modules
  • The module system promotes modularity, separation of concerns, and better isolation of application components
  1. Functional Bean Registration
  • Spring 6.0 introduces a functional API for registering beans, allowing developers to define beans programmatically using lambda expressions or method references
  • This approach provides a concise and type-safe way to configure beans without the need for traditional XML or annotation-based configurations

Notable Improvements And Enhancements

  1. Improved Testing Capabilities
  • Spring 6.0 enhances testing support with the introduction of new testing annotations and utilities
  • Developers can write more robust and concise tests using features like test slicing, improved test context caching, and simplified test setup
  1. Streamlined Dependency Management
  • Spring 6.0 simplifies dependency management by leveraging features from the latest Java versions
  • Developers can take advantage of Java’s improved module system, including JPMS (Java Platform Module System) support for managing dependencies
  1. Performance And Scalability Enhancements
  • Spring 6.0 incorporates performance optimizations and architectural enhancements to deliver faster startup times, reduced memory footprint, and improved runtime performance
  • These improvements contribute to building highly scalable and efficient Java applications

Benefits And Best Practices For Spring 6.0 Adoption

  1. Stay Updated With The Latest Documentation
  1. Plan For Seamless Migration
  • If you’re currently using an older version of Spring, plan your migration strategy carefully
  • Take advantage of Spring’s backward compatibility and gradual adoption approach to ensure a smooth transition to Spring 6.0
  1. Embrace Reactive Programming
  • Explore the power of reactive programming in Spring 6.0 and consider leveraging it for building highly responsive and scalable applications
  • Familiarize yourself with reactive programming concepts and patterns to fully harness the benefits of Spring’s reactive support

Closing Thoughts

Spring 6.0 introduces exciting features and enhancements that enhance the developer experience and empower Java developers to build robust and scalable applications. With its support for reactive programming, enhanced module system, and improved testing capabilities, Spring 6.0 sets the stage for developing modern Java applications that meet the demands of today’s fast-paced development landscape.

Stay updated with the latest Spring 6.0 documentation, leverage the new features, and embrace best practices to make the most out of this major release. Enjoy the journey of building high-quality Java applications with the power of Spring 6.0!

Why You Should Be Utilizing Docker Containers In Your Cloud Computing Workflows

Based on a Lightning Talk by: Nikhil Hiremath, Full Stack Engineer @ InRhythm on May 25th, 2023

Overview

In recent years, Docker Containers have gained immense popularity in the realm of cloud computing. Docker provides a lightweight and portable platform for packaging and deploying applications, making it an ideal choice for cloud-based environments.

In Nikhil Hiremath’s Lightning Talk session, we will explore the advantages of using Docker Containers in Cloud Computing and discuss the benefits they bring to developers, operations teams, and businesses as a whole:

  • Overview
  • Portability And Consistency
  • Scalability And Resource Efficiency 
  • Rapid Deployment And Continuous Integration/Continuous Deployment (CI/CD)
  • Isolation And Security
  • Cost Optimization 
  • Closing Thoughts

Portability And Consistency

One of the key advantages of Docker Containers in Cloud Computing is their portability. Docker Containers encapsulate all the dependencies, configurations and runtime environment  required to run an application, making them highly portable across different environments. Docker Images which act like a blueprint of containers can be shared.  and deploy them to any cloud provider or on-premises infrastructure without worrying about compatibility issues. This portability ensures consistent behavior and eliminates the “it works on my machine” problem, leading to smoother deployments and reduced troubleshooting efforts.

Scalability And Resource Efficiency

Docker Containers provide an efficient and scalable approach to deploying applications in the Cloud. With Docker, applications can be packaged as lightweight containers that share the host operating system’s kernel, reducing resource overhead. This enables efficient utilization of cloud resources and allows for scaling applications horizontally by spinning up multiple containers. Cloud platforms like Amazon Web Services (AWS) and Google Cloud Platform (GCP) provide native support for Docker Containers, enabling seamless scaling and resource management.

Rapid Deployment And Continuous Integration/Continuous Deployment (CI/CD)

Docker Containers streamline the deployment process, allowing for rapid and consistent application deployment in cloud environments. By packaging the application and its runtime dependencies in images, deployment becomes a simple matter of running the container on the cloud platform. Docker also integrates well with CI/CD pipelines, enabling automation and continuous deployment. Developers can automate the build, test, and deployment processes, resulting in faster release cycles and improved time-to-market.

Isolation And Security

Docker Containers provide a high level of isolation between applications and the underlying host system, ensuring security in cloud environments. Each container operates in its own isolated runtime environment, with its own file system, network stack, and process space. This isolation prevents applications from interfering with each other, enhancing overall system stability and security. Docker also provides robust security features such as container image scanning, vulnerability detection, and the ability to apply access controls and restrictions.

Cost Optimization

Using Docker Containers in Cloud Computing can lead to cost optimization and resource efficiency. Containers enable efficient utilization of cloud resources by running multiple containers on a single host, reducing infrastructure costs. They also facilitate dynamic resource allocation, allowing organizations to scale resources up or down based on demand, optimizing costs, and avoiding overprovisioning.

Closing Thoughts

Docker Containers offer significant advantages in Cloud Computing, revolutionizing the way applications are developed, deployed, and managed. The portability, scalability, rapid deployment, isolation, and cost optimization benefits provided by Docker Containers make them a valuable tool for developers, operations teams, and businesses seeking to leverage the power of cloud computing.

By embracing Docker Containers in the cloud, organizations can enhance application agility, accelerate time-to-market, improve resource utilization, and strengthen security. As Cloud Computing continues to evolve, Docker Containers will play a crucial role in enabling efficient and scalable deployment of applications, revolutionizing the cloud landscape.

InRhythm Spring Quarterly Summit: Cloud Native Applications Workshop

Summary

In this workshop we will introduce you to gRPC, which is Google’s take on Remote Procedural Calls. You will learn a brief history of gRPC and Protocol Buffers. Google and other companies use gRPC to serialize data to binary which results in smaller data packets. In our presentation portion we will go over some of the pros and cons of using gRPC for your API calls.

 

In our hands-on workshop portion you will create a simple application to manage notes powered by Java running in a Docker container. We will walk you through creating a series of CRUD APIs in Java using gRPC to send/receive data packets, translate those into objects, and store them in a database.

 

Why gRPC?

“gRPC is a modern open source high performance Remote Procedure Call (RPC) framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking and authentication. It is also applicable in last mile of distributed computing to connect devices, mobile applications and browsers to backend services.” – grpc.io

Creating Robust Test Automation For Microservices

Overview

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Any and all projects that a software engineer joins will come in one of two forms: greenfield or legacy codebases. In the majority of cases, projects will fall into the realm of legacy repositories. As a software engineer, it is their responsibility to be able to strategically navigate their way through either type of project by looking objectively at the opportunities to improve the code base, lower the cognitive load for software engineering, and make a determination to advise on better design strategies.

But, chances are, there is a problem. Before architecture or design refactors can be taken its best to take a pulse on the health of a platform End to End (E2E). The reason being, lurking in a new or existing platform is likely a common ailment of a modern microservices approach – the inability to test the platform E2E across microservices that are, by design, commonly engineered by different teams over time.

Revitalizing Legacy Systems

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One primary challenge faced by a number of software engineers, is the adaptive work on a greenfield platform that has fallen several months behind from a quality assurance perspective. It becomes no longer possible for QA to catch up, nor was it possible for QA to engineer and execute E2E testing to complete common user journeys throughout the enterprise system.

To solve this conundrum, E2E data generation tools need to be created so that the QA team can keep upbuilding and testing every scenario and edge case.

There are three main requirements for an E2E account and data generation tool.

The tool should:

1) Create test accounts with mock data for each microservice

2) Link those accounts between up and downs stream microservices

3) Provide easy to access APIs that are self-documenting 

Using a tool like Swagger, QA can use the API description for REST API, i.e. OpenAPI Specification (formerly Swagger Specification) to view the available endpoints and operations to create accounts, generate test data, authenticate, authorize and “connect the microservices.”

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Closing Thoughts

By creating tools for E2E testing, a QA team was able to eliminate the hassle of trying to figure out which upstream and downstream microservices needed to be called to ensure that the required accounts and data were available and set up properly to ensure a successful test of all scenarios i.e. based upon the variety of different data types, user permissions, user information, and covering the negative test cases. The QA team was able to catch up and write their entire suite of test scenarios generating the matching accounts and data to satisfy those requirements. The net result of having built an E2E test generation tool was automated tests could be produced exponentially quicker and the tests themselves are more resilient to failure. 

Even though the microservices pattern continues to gain traction, developing E2E testing tools that generate accounts and test data across an enterprise platform will likely still remain a pain point.

There’s no better way to maintain a healthy system than to ensure accounts and data in the lower environments actually work and unblock testing end-to-end. 

Configuration Automation Tools: Orchestrating Successful Deployment

Overview

In the modern technology field, buzz words come and go. One day databases are being discussed as the new best thing in the world of Agile Development only for the next, to recenter the importance of programming languages, frameworks, and methodologies.

But, one unchanging aspect of this lifecycle are the people who are an irreplaceable part of the creation, demise, and popularity of any given technology. This modern day world calls for close to perfection execution, of which individuals cannot always account for.

How does this call for flawless mechanisms affect the developers and creators, when called to building perfect products? 

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Automation is the technology by which a process or procedure is performed with minimal human interference through the use of technological or mechanical devices. It is the technique of making a process or a system operate automatically. Automation crosses all functions within almost every industry from installation, maintenance, manufacturing, marketing, sales, medicine, design, procurement, management, etc. Automation has revolutionized those areas in which it has been introduced, and there is scarcely an aspect of modern life that has been unaffected by it.

Automation provides a number of high-level advantages to every aspect of practice, making it an important process to have a working knowledge of:

  • Overview
  • Removing Human Error
  • Steps To Deploy
  • No Hidden Knowledge
  • Popular Implementation Technology Options
  • Closing Thoughts

Removing Human Error

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Automation, automation, more automation – and of course throw in some orchestration deployment and configuration management. Leaving the buzz words behind the “new technology frontier”, is removing human error. This translates to removing the dependencies of tribal knowledge when it pertains to application and system administration job duties.

Those job duties are performed in a repetitive fashion. The job duties are usually consolidated into various custom scripts, leaving a lot of those scripted actions with the ability to be boxed up and reused over and over again.

Steps To Deployment

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The primary cornerstones to prepping an automation deployment for an individual server, follow a near identical framework:

  1. Download and Install the various languages and/or framework libraries the application usages
  2. Download, Install, and Configure the Web server that the application will use
  3. Download, Install, and Configure the Database that the application will use
  4. Test to see if all the steps are installed and configured correctly

Running application tests ensure that the deployment is running as expected. Testing is crucial to the successful run of the deployment.

For example, something simplistic but highly catastrophic is the possibility of a typo. Consider the case of the following code:

  • cd /var/ect/ansible; rm -rf *

but instead a developer forgot the cd execute command and only ran

  • rm -rf /

In this case, the whole drive is at risk to be erased – which can and will make or break a product.

Taking time to ensure the correct command executions, can determine the overall success of a system.

No Hidden Knowledge

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Looking back on the steps to deploy an application to an environment, there are inevitably a number of small intermediary steps involved. A leader’s priority should be the revelation of each one of these unique sub-categories and effectively bringing all engineers around them up to speed on the associated best practices.

The information should be a source of truth maintained in a repository database, that is easy and intuitive to leverage

Popular Implementation Technology Options

What does a source of truth entail? Can one not skip the documentation of information and go straight into the execution of the steps onto a given system? Or create scripts to reconfigure the application if there was ever a need to? Those questions have been proposed several times and solutions have been formulated several times into the form of extensive and comprehensive build tools/frameworks.

These tools are used throughout the industry to solve the problem of orchestrated development, configuration automation, and management. 

Furthermore, DevOps tools such as: Puppet, Chef, and Ansible are well matured automation/orchestration tools. Each tool will provide enough architecture flexibility to virtually handle any use case presented.

Puppet

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Puppet was the first widely used Configuration Automation and Orchestration software dating back to its initial release in 2005. Puppet uses the Master and Slave paradigm to control X amount of machines. The Ruby language is the script language say, for executing commands in a destination environment. 

The “Puppet Agents” (Slave) are modularized distinct components to be deployed to a server. This can be used for the creation of the server (ie. web server, database, application) in its destination environment. The “Puppet Enterprise” (Master) is comprised of all the inner workings to manage, secure, and organize agents.

Puppet Documentation

Chef

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Chef is somewhat similar to Puppet. The core language used within Chef’s abstract module components is Ruby. Chef has several layers of management for individual infrastructure automation needs. The Chef workstation is the primary area for managing the various Chef components. The Chef components consist of “cookbooks”, “recipes”, and “nodes”.

“Recipes” are collections of configurations for a given system, virtual, bare metal, or cloud environment. Chef calls those different environments “nodes”. “Cookbooks” contains “recipes” and other configurations for application deployment and control mechanisms for the different Chef clients.

Chef Documentation

Ansible

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Ansible is the newest mainstream automation/configuration management tool on the market. Therefore, Ansible uses more modern programming languages and configurations concepts and tools. Python is the programming language used in this framework. One of the modern and fastest up-and-coming template languages is YAML. YAML is programming language agnostic and is a subset of the ever so popular JSON. YAML is used within Ansible to describe an Ansible Playbook. 

Ansible Playbook contains the steps that need to be executed on a given system. Once the Ansible Playbook is intact, configuration or further manipulation of the host can be executed through Ansible API – which is implemented in Python. There are several other components within Ansible technology such as modules, plugins, and inventory. 

Ansible Documentation

Closing Thoughts

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After covering a couple of the Configuration Automation and Development tools on the market, one can see a vast amount of flexibility available in eliminating those repeatable steps from human error. This software’s framework promotes reusable software within an organization – which is the most viable. The ability to scale an application development environment and environmental infrastructure is critical. 

The learning curve may be deeper than using plain bash scripts, but the structure and integrity of using a proven tool and ease of maintenance outweigh the learning curve.