InfoQ Homepage Programming Content on InfoQ
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Java (SE) State of the Union
Gil Tene presents the current state of Java SE and OpenJDK, the role of Java in the Big Data and Infrastructure components, JCP, the ecosystem, trends, etc.
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The Node.js Ecosystem in Perspective
Dan Shaw explores the implications of the decisions made while transforming application development from a Java to a JavaScript dominated environment and how they have impacted the Node.js ecosystem.
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Lessons Learnt - Migrating from Spring XD to Spring Data Cloud Flow
Katie Mooney, Dillon Woods and Cahlen Humphreys point out key differences in Spring XD that have been resolved in Spring Cloud Data Flow.
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Reactive Kafka
Rajini Sivaram talks about Kafka and reactive streams and then explores the development of a reactive streams interface for Kafka and the use of this interface for building robust applications.
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Cloud Native Streaming and Event-driven Microservices
Marius Bogoevici demonstrates how to create complex data processing pipelines that bridge the big data and enterprise integration together and how to orchestrate them with Spring Cloud Data Flow.
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Troubleshooting RabbitMQ and Microservices That Use It
Micahel Klishin talks about how one can troubleshoot a distributed service-oriented system, focusing on Java, Spring, and RabbitMQ.
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A Brief History of Unicode
Alex Blewitt discusses the origins of Unicode, why UTF8 is important, how character sets have evolved over time and the role Unicode has had in the evolution of many languages.
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Operationalizing Data Science Using Cloud Foundry
Lawrence Spracklen creates a machine learning model leveraging data within MPP databases such as Apache HAWQ or Greenplum integrated with Chorus and then deploying this as a microservice on PCF.
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Architecting for Cloud Native Data: Data Microservices Done Right Using Spring Cloud
Fred Melo introduces Spring Cloud Stream from a Data Microservices perspective.
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Spring for Apache Kafka
Gary Russell takes a look at the features of the spring-kafka project as well as the new version (2.0) of spring-integration-kafka which is now based on the Spring for Apache Kafka project.
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Spring and Big Data
Thomas Risberg discusses developing big data pipelines with Spring, focusing around the code needed and he also covers how to set up a test environment both locally and in the cloud.
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Data Science-powered Apps for the Internet of Things
Chris Rawles describes approaches to addressing the concerns around any IoT project through a deep-dive into an interactive demo centered around classification of human activities.
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