InfoQ Homepage Event Stream Processing Content on InfoQ
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Key Takeaway Points and Lessons Learned from QCon San Francisco 2016
The 10th annual QCon San Francisco was the biggest yet, bringing together over 1500 team leads, architects, project managers, and engineering directors. Over 125 practitioner-speakers presented 92 full-length technical sessions and 32 in-depth tutorials, providing deep insights into real-world architectures and state of the art software development practices from a practitioner’s perspective.
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Big Data Processing with Apache Spark - Part 3: Spark Streaming
In this article, third installment of Apache Spark series, author Srini Penchikala discusses Apache Spark Streaming framework for processing real-time streaming data using a log analytics sample application.
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Storm Applied Review and Q&A with the Authors
Storm is a distributed, fault-tolerant, real-time computation system that was originally developed at BackType and later open sourced by Twitter. Storm Applied is a new book from Manning that aims to provide a practical guide on using Storm, both in a development and in a production setting. InfoQ has spoken with two of the book’s authors, Sean T. Allen and Matthew Jankowski.
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Real-Time Stream Processing as Game Changer in a Big Data World with Hadoop and Data Warehouse
This article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing makes sense, and what technologies and products you can choose from.
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Using SEDA to Ensure Service Availability
A new strategy for incorporating event driven architecture for scalability and availability of services in the context of SOA. These strategies are based on queuing research pioneered for the use of highly abailable and scalable services, initially in the Web context, but moving into the SOA and Web services context. Actual implementation is described in the context of Mule.