InfoQ Homepage Event Driven Architecture Content on InfoQ
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Event Sourcing on the JVM
Greg Young looks at Event Sourcing as a concept as well as specific JVM-based implementations that are available. He focuses on where such an implementation would be beneficial or not.
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The Complexity That Is Hidden in Microservices and Event Sourcing
Satyajit Ranjeev shares his experience building an event sourcing system with microservices, including tips and trade-offs dealing with them.
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Spotify's Reliable Event Delivery System
Igor Maravic talks about the design and operational aspects of Spotify’s reliable event delivery system.
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Real-Time & Personalized Notifications @Twitter
Gary Lam and Saurabh Pathak talk about the hybrid push/pull-based architecture adopted by Twitter Notification platform.
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Stream Processing & Analytics with Flink @Uber
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
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Demistifying DynamoDB Streams
Akshat Vig and Khawaja Shams discuss DynamoDB Streams and what it takes to build an ordered, highly available, durable, performant, and scalable replicated log stream.
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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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ETL Is Dead, Long Live Streams
Neha Narkhede shares the experience at LinkedIn moving from ETL to real-time streams, the challenges of scaling Kafka to hundreds of billions of events/day, supporting thousands of engineers, etc.
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Event Sourcery
Sebastian von Conrad and James Ross explain how to use event sourcing in order to keep the cost of change lower.
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Server-Less Design Patterns for the Enterprise with AWS Lambda
Tim Wagner defines server-less computing, examines the key trends and innovative ideas behind the technology, and looks at design patterns for big data, event processing, and mobile using AWS Lambda.
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Handling Streaming Data in Spotify Using the Cloud
Neville Li and Igor Maravić cover the evolution of Spotify’s event delivery system, discussing lessons learned moving it into the cloud using Scio, a high level Scala API for the Dataflow SDK.
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Large-Scale Stream Processing with Apache Kafka
Neha Narkhede explains how Apache Kafka was designed to support capturing and processing distributed data streams by building up the basic primitives needed for a stream processing system.