InfoQ Homepage Streaming Content on InfoQ
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Practical Change Data Streaming Use Cases with Apache Kafka & Debezium
Gunnar Morling discusses practical matters, best practices for running Debezium in production on and off Kubernetes, and the many use cases enabled by Kafka Connect's single message transformations.
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Beyond Microservices: Streams, State and Scalability
Gwen Shapira talks about how microservices evolved in the last few years, based on experience gained while working with companies using Apache Kafka to update their application architecture.
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Real-Time Stream Analysis in Functional Reactive Programming
Riccardo Terrell discusses about a reactive approach to application design, and how to account for handling events in near real time employing the Functional Reactive Programming paradigm.
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Announcing Broadway
José Valim discusses how Broadway connects multiple stages and producers, how it leverages GenStage to provide back-pressure, and other features such as batching, rate-limiting, partitioning and more.
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A Dive into Streams @LinkedIn with Brooklin
Celia Kung talks about Brooklin, LinkedIn’s managed data streaming service, and dives deeper into its architecture and use cases, as well as their future plans.
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Streaming Log Analytics with Kafka
Kresten Thorup discusses how and why they use Kafka internally and demos how they utilize it as a straightforward event-sourcing model for distributed deployments.
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Massive Scale Anomaly Detection Framework
Guy Gerson introduces an anomaly detection framework PayPal uses, focusing on flexibility to support different types of statistical and ML models, and inspired by scikit-learn and Spark MLlib.
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Building Cloud-Native Data-Intensive Applications with Spring
Sabby Anandan and Soby Chako discuss how Spring Cloud Stream and Kafka Streams can support Event Sourcing and CQRS patterns.
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Next Generation MongoDB: Sessions, Streams, Transactions
Christoph Strobl, Jeff Yemin discuss some of the features in latest MongoDB versions: sessions, change streams, retriable writes, reactive access and transactions.
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The Whys and Hows of Database Streaming
Joy Gao talks about how database streaming is essential to WePay's infrastructure and the many functions that database streaming serves.
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Patterns of Streaming Applications
Monal Daxini talks about streaming application patterns and anti-patterns, and use cases and concrete examples using Apache Flink.
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Streaming SQL to Unify Batch & Stream Processing w/ Apache Flink @Uber
Shuyi Chen and Fabian Hueske explore SQL’s role in the world of streaming data and its implementation in Apache Flink and covering streaming semantics, event time, and incremental results.
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