In this article, you will learn how to use Spring Boot and HarperDB to create a microservice. Later on, you will also look at how to deploy the complete application on AWS Elastic Beanstalk.
You will be building an Employee Leave Management System. This application will be responsible for tracking the detailed record of employees’ leaves. You will also be implementing the functionality to add, edit, and cancel leaves.
Nowadays, with the rise of social media, fast internet, etc., the tendency to use applications is getting more and more. As a result of these behavior changes, monolithic applications need to deal with a tremendous majority of changes.
Security is one of the most important aspects of modern-day applications. As technology keeps getting advanced, keeping the security up-to-date is a challenge. How awesome would it be to find top trending articles in the Security Zone in one place so that you can always stay up to date with the latest trends in technology? We dug into Google analytics to find the top 10 most popular Security articles in August. Let’s get started!
Spring Boot applications have been a key in implementing the microservice architecture. Learn how to implement security in Spring Boot with JWT token. Follow the step-by-step tutorial and secure your Spring Boot microservice.
Microservices have crafted highly flexible and adaptable IT infrastructures. Microservices is a unique software development approach that concentrates on creating single-function modules that work jointly to execute the same tasks. It enables you to alter only one service, without modifying the rest of the infrastructure. In simple words, one can easily deploy and change every service without affecting the functional facets of other applications or services. Instead of following an old monolithic architecture (sole app with manifold functions), testers and developers use this microservice approach to build independent modules for every function.
However, the microservice architecture can also make an app extra complicated, particularly when we add several functionalities. Likewise, testing the combined functionality of numerous services is a lot more complicated due to the distributed nature of the app. As microservices follow a dissimilar architecture, we also require an exceptional strategy for testing microservices. In this article, we will explore different tools for testing microservice applications. Testing microservices can assist us in eradicating several issues by avoiding a domino effect.
« Make the world become more programmable. »
That’s the goal of Nordic APIs, which holds a series of conferences and events throughout Scandinavia and, more recently, the US, to help organizations make smarter tech decisions and streamline their operations through APIs and strategies. Their work explores the API sector and sheds to light various emerging technologies and trends through their events and blogs.
The serverless journey started with functions – small snippets of code running on-demand and a short period in Figure 1. AWS Lambda in the “1.0” phase made this paradigm very popular, but it had its limitations around execution time, protocols, and poor local development experience.
Since then, developers realized that the same serverless traits and benefits could be applied to microservices and Linux containers. This leads us into what we’re calling the “1.5” phase in Figure 1. Some serverless containers here completely abstract Kubernetes, delivering the serverless experience through an abstraction layer that sits on top of it, like Knative.
Java and the JVM more generally are widely used for services everywhere, but often challenging to debug and manually test, particularly in complicated microservice architectures.
HTTP requests and responses are the core of interactions between these services, and with their external APIs, but they’re also often invisible and inaccessible. It’s hard to examine all outgoing requests, simulate unusual responses & errors in a running system, or mock dependencies during manual testing & prototyping.
The microservice architecture pattern, which is used widely across tech companies large and small, enables businesses to distribute functionality between many small applications, instead of larger monolithic portions. Each piece has a specifically defined task, along with communications and other services, usually via a REST API channel. The benefits of utilizing a microservice architecture include, but are not limited to:
Simple development and maintenance of applications: developers and teams are able to focus on one application rather than multiple, with the benefit of faster development, and fewer hitches (such as bug and easy to miss errors) in the larger project.
In this article, we will see how to implement a data pipeline from an application to Mongo DB database and from there into an Elastic Search keeping the same document ID using Kafka connect in a Microservice Architecture. In recent days and years, all the microservices architectures are asynchronous in nature and are very loosely coupled. At the same time, the prime approach to have minimum code (minimum maintenance and cost), no batch systems (real-time data), and promising performance without data loss fear. Keeping all the features in mind Kafka and Kafka connect is the best solution so far to integrate different sources and sinks in one architecture to have very robust and reliable results.
We will Depp drive and implement such a solution using Debezium Kafka connect to achieve a very robust pipeline of data from one application into Mongo and then into Elastic cluster.
Having a lightweight protocol which delivers messages over low bandwidth or unreliable networks is the foundation for a system that can facilitate the transports of data in near real time.
MQTT is one such protocol which designed to overcome following limitations:
