InfoQ Homepage Infrastructure Content on InfoQ
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Solving Business Problems with Data Science
The panelists discuss how Data Science can help solve various problems for business.
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Get Off the Bus, Gus: 50 Ways to Leave Your Mainframe
Rohit Kelapure provides guidance and best practices in migrating monolithic mainframe apps and data including JCLs wrapped in CICS and IMS using Spring components like Spring Data Flow, Cloud, Batch.
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Hydrator: Open Source, Code-Free Data Pipelines
Jonathan Gray introduces Hydrator, an open source framework and user interface for creating data lakes for building and managing data pipelines on Spark, MapReduce, Spark Streaming and Tigon.
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Developing a Machine Learning Based Predictive Analytics Engine for Big Data Analytics
Ali Jalali presents how to develop a machine learning predictive analytics engine for big data analytics.
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NBCU Develops the Critical Need for Technical Agility in Media and Entertainment
Amar Sharma talks about NBC Universal Microservices infrastructure and how the new way they approach software development has equipped them to make better decisions about product investment.
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The Human Side of Microservices
John Billings talks about winning over those skeptical about the benefits of microservices along with tips on caching, failure, interface changes, etc. for building a distributed system architecture.
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The Five Stages of Cloud Native
Casey West talks about anti-patterns and corresponding best practices based on his experience building application infrastructure and platforms, as well as the applications which are deployed to them.
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Lessons Learned from Deploying Cloud Foundry on OpenStack
The authors discuss the top lessons learned from building a fully integrated developer platform, leveraging Cloud Foundry and OpenStack, answering questions from the audience.
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Exploring Wikipedia with Apache Spark: A Live Coding Demo
Sameer Farooqui demos connecting to the live stream of Wikipedia edits, building a dashboard showing what’s happening with Wikipedia datasets and how people are using them in real time.
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Understanding Hardware Transactional Memory
Gil Tene talks about new speculative and optimistic locking mechanisms enabled by HTM (Hardware Transactional Memory), HTM's benefits and limitations, speculating on its future impact on concurrency.
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Applying Big Data
Graeme Seaton discusses the drivers behind Big Data initiatives and how to approach them using the vast amounts of data available.
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Apache Beam: The Case for Unifying Streaming APIs
Andrew Psaltis talks about Apache Beam, which aims to provide a unified stream processing model for defining and executing complex data processing, data ingestion and integration workflows.
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