InfoQ Homepage Infrastructure Content on InfoQ
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Using Bayesian Optimization to Tune Machine Learning Models
Scott Clark introduces Bayesian Global Optimization as an efficient way to optimize ML model parameters, explaining the underlying techniques and comparing it to other standard methods.
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Machine Learning and End-to-End Data Analysis Processes in Spark Using Python and R
Debraj GuhaThakurta discusses ML and data analysis processes in Spark using examples written in Python and R.
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Scaling the Data Infrastructure @Spotify
Mārtiņš Kalvāns and Matti Pehrs overview the Data Infrastructure at Spotify, diving into some of the data infrastructure components, such us Event Delivery, Datamon and Styx.
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Scaling Counting Infrastructure @Quora
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
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Orchestrate All the Things! with Spring Cloud Data Flow
Eric Bottard and Ilayaperumal Gopinathan discuss easy composition of microservices with Spring Cloud Data Flow.
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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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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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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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Mesos: A State-of-the-art Container Orchestrator
Jie Yu discusses how containers are managed in Mesos, the future of container support in Mesos, and shows some of the new container networking and storage features.
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Uses of Big Data by a Non-Profit Engaged in Conducting Events Funded in Part by Third Party Sponsors
Thomas Grilk discusses how a non-profit can efficiently use data from customers/athletes in its marketing and sponsorship activities while respecting the privacy and confidentiality of its customers.
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Scaling Dropbox
Preslav Le talks about how Dropbox’s infrastructure evolved over the years, how it looks today, as well the challenges and lessons learned on the way.
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TensorFlow: A Flexible, Scalable & Portable System
Rajat Monga talks about why Google built TensorFlow, an open source software library for numerical computation using data flow graphs, and what were some of the technical challenges in building it.
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