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Learning Path: Microservices with Java, Scala, and Akka - learn Programming Languages
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Learning Path: Microservices with Java, Scala, and Akka - learn Programming Languages

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Learning Path: Microservices with Java, Scala, and Akka - learn Programming Languages
Best Programming Languages Course
Build smaller, lighter, and faster microservices for JVM languages
Use domain-driven design to design and implement microservices,Secure microservices using Spring Security,Consume microservices using a JavaScript web application,Build working applications using Play Framework,Explore how to use HTTP properly,Use the Reactive Manifesto to create microservices,Get to know the Core API of Akka HTTP
Experience with Java and Scala is necessary.,Microservices are an architectural method and pattern for application development. Microservices are becoming hugely popular and are being adopted by many organizations because of the advantages that it offers. It is an approach to building asynchronous, non-blocking, and failure-resilient applications.,Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.,This Learning Path begins by showing you how to build smaller, lighter, and faster services that can be implemented easily in a Java production environment. We then move on and focus on building microservices in Scala. We address the best practices and common pitfalls in microservice architecture and useful implementation strategies in Scala. Finally, we cover how to build reactive microservices using Akka and Akka HTTP, which adhere to the principles underlying the Reactive Manifesto.,Building microservices for Java, Scala, and Akka. All of it covered in this all-inclusive Learning Path.,Looking for the perfect course to get you started in the big booming world of microservices? Capitalize on this Learning Path and what it wants to teach you.,The goal of this Learning Path is to launch you on the right path to building lighter and faster microservices.,This Learning Path is authored by some of the best in their fields.,Sourabh Sharma has more than a decade of experience in product/app development. His expertise lies in developing, deploying, and testing N-tier web applications. In his career, he has successfully developed and delivered various standalone and cloud apps to happy Fortune 500 customers. He has also initiated and developed a microservice-based product for a US-based top enterprise product company.,Tomasz Lelek is a software engineer, programming mostly in Java and Scala. He is a fan of the microservices architecture and functional programming. He is passionate about nearly everything associated with software development. Recently, he was a speaker at conferences in Poland - Confitura and JDD (Java Developer Day) and also at Krakow Scala User Group. He has also conducted a live coding session at the Geecon Conference.,This Learning Path is for Java developers and DevOps engineers looking to upgrade their Java and microservice skills. The audience should also know Scala or be proficient in a recognized programming language such as Java, C#, Ruby, and so on, with some exposure to Scala. Some experience with writing web services would be ideal but is not mandatory. This last part of this Learning Path is targeted at Big Data developers and engineers who are working with and analyzing data in clusters and working with raw structured and unstructured datasets. It will appeal to data analysts who are working with Hadoop clusters and AKKA.,This Learning Path is for Java developers and DevOps engineers looking to upgrade their Java and microservice skills. The audience should also know Scala or be proficient in a recognized programming language such as Java, C#, Ruby, and so on, with some exposure to Scala. Some experience with writing web services would be ideal but is not mandatory. This last part of this Learning Path is targeted at Big Data developers and engineers who are working with and analyzing data in clusters and working with raw structured and unstructured datasets. It will appeal to data analysts who are working with Hadoop clusters and AKKA.
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