The Changing Role of Java in the Cloud


The Changing Role of Java in the Cloud

Cloud computing describes a new supplement, consumption and delivery model for IT services based in the Internet. Java has long been the programming language that provides structure for Web-applications, and now Java development has reached cloud applications.


Cloud computing is changing the face of application development, driven by business needs to reduce costs and increase the scalability of cloud services. The success of web service applications and Software as a Service (SaaS) has led to a growing acceptance of Platform as a Service (PaaS) and Infrastructure as a service (IaaS). Cloud computing resources provide Java developers the ability to build out new projects at a low cost and scale up quickly when those Java cloud services are successful. These services usually include some combination of programming and data – which is made available from a business’ Web server – for Web users or other Web-connected programs. Java Web services range from major services along the lines of storage management to much more limited services, something as simple as checking bids on an auction item.


The acceleration of web services development is a major trend that is completely changing the playing field, as cloud and adoption movement from Java EE 7 to Java EE 8 are increasing. Some organizations, and self-described “late adopters,” have cited security and stability concerns as key risks in moving their development platform. To counter that fear, there has been an outpouring of positive feedback from the Java community since the release of EE 8, which greatly increases code simplification features using Lambda Expressions. The latest release of official Java IDE and the open source tool NetBeans 8.0.2 are ramping up migration discussions fast. With much easier machine learning, as much as 30% less code needed with Java 8 (not to mention much more efficient code), and reduced code complexity of Spark, Java developers who may not have special expertise in Big Data before, can finally develop machine learning in about half the lines of code with similar Hadoop programs.


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