Reactive

Introduction to Resiliency4j – Part 1

Reading Time: 2 minutes This blog briefs you about the resiliency4j library.

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Passing query parameters through your WebClient

Reading Time: 5 minutes We can use spring-boot:webflux’s WebClient to invoke a third-party service from within our spring boot application. This is asynchronous and reactive method supplied by spring for invoking of unmanaged services. We also saw how we can pass query params when invoking a 3rd party service and which case to chose with our requirements. Be cautious with what you are using and always document what you want and what you created so that things like these can be caught early during the development phase.

Microservices and the Saga Pattern

Reading Time: 10 minutes Microservices have become a crucial part of any enterprise these days, no matter if it is a big or a small enterprise. When something this big is present in the market why not see some fundamentals of the same? So here we’ll go through the concepts like what is a microservice and Saga Patterns that an ideal microservice should have.

Understanding laws of scalability and the effects on a distributed system

Reading Time: 4 minutes A reactive system primarily focuses on responsiveness, elasticity, message-driven, and resiliency as its core features. Elasticity is one of the main components in the reactive manifesto. An elastic system has the ability to scale up or scale down when there is an increase/decrease in demand while remaining responsive. Scenarios where a system needs to improve the throughput or needs to handle more concurrent users, we Continue Reading

Let’s get started with Reactive Micro Services

Reading Time: 2 minutes “Unity is Strength” is what we believe is de-facto but that’s not true when it comes to behaviour of Web-Services. Monolith application (tightly encapsulated and highly inter-dependent applications) is what existed earlier but in recent time there was need of something called micro services which allows enterprise(large) applications to be broken down into independent application components which communicates to each other in case of interdependent Continue Reading

Reverse engineering using Slick 3.2 and Scala

Reading Time: < 1 minute Sometime, we have requirements for create classes corresponding to the existing database or Sometimes, in our initial phase of project, we are going to design database and tables first, after that, we are going to create classes for mapping our tables. As we know, Slick is a FRM(Functional Relational Mapping) for scala. Its a kind of ORM but for scala, it supports Functional and Reactive Continue Reading

Knoldus Partners with Confluent to Power Real Time Streams

Reading Time: 3 minutes Knoldus is pleased to announce a Consulting and System Integrator partnership with Confluent, the company founded by the creators of Apache KafkaTM Confluent, creators of the first streaming platform based on Apache KafkaTM, provides the most complete platform to build enterprise-scale streaming pipelines using Apache Kafka and simplify the development of stream processing applications. Via rapid adoption in the Fortune 500, Apache Kafka is quickly emerging as Continue Reading

Play with Reactive Slick: A Simple CRUD application in Play! framework using Slick 3.0

Reading Time: 2 minutes Recently Typesafe released Slick 3.0.0-RC1, the first release candidate for “Reactive Slick”. Reactive Slick has many new features like Support for Reactive Streams API, a new API for composing and executing database actions and many more. Before moving forward, we recommended you to go through the Slick 3.0.0-RC1 Upgrade guide. So, that you can get a hint of major changes in Slick 3.0. In this post, we will see Continue Reading

Play-Slick-PostgreSQL: Reactive Play application with Slick extensions for PostgreSQL

Reading Time: < 1 minute playing-slick-pg Building Reactive Play application with Slick extensions for PostgreSQL This is a classic CRUD application, backed by a PostgreSQL database. It demonstrates: Handling asynchronous results, Handling time-outs Achieving, Futures to use more idiomatic error handling. Accessing a JDBC database, using Slick. Achieving, table pagination and sorting functionality. Embedded JS & CSS libraries with WebJars. Play and Scala-based template engine implementation Integrating with a CSS Continue Reading

Meetup: Introduction to Play Framework !!

Reading Time: < 1 minute Reactive Application Programmers in Delhi NCR Hi Folks, Knoldus have organized an one hour session on 4th Feb 2015 at 5:00 PM. Topic is  Introduction to Play Framework. So many people have joined and enjoyed the session. I am going to share that slide here. Please let me know if you have any question related to linked slide. Slide: Introduction to Play framework

Employee-Self-Service: Reactive and Non-Blocking Database Access using Play Framework and Anorm – (Part-3)

Reading Time: 1 minute Last week, We have added Reactive and Non-Blocking behaviour in Employee-Self-Service  application. Now we have implemented Database Access as Reactive and Non-Blocking: Before def list() = Action.async { implicit request => Employee.list match { case Right(data) => Promise.timeout(Ok(html.list(data)), 1 seconds) case Left(error) => Promise.timeout(Ok(html.list(Nil)), 1 seconds) } } After def list() = Action.async { implicit request => val futureEmpList = scala.concurrent.Future { Employee.list } val timeoutFuture = Promise.timeout(“Oops”, 10.second) Continue Reading

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