{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Spring Office Hours","title":"S3E32 - Streaming Data with Chris Bono","html":"","width":"100%","height":180,"duration":3394,"description":"In this episode of Spring Office Hours, hosts Dan Vega and DeShaun Carter interview Chris Bono, a Spring team member who works on Spring Cloud Dataflow and Spring Pulsar. They discuss streaming data, comparing Apache Kafka and Apache Pulsar, and explore the features and use cases of Spring Cloud Stream applications. Chris provides insights into the architecture of streaming applications, explains key concepts, and highlights the benefits of using Spring's abstraction layers for working with messaging systems.\nShow Notes:\nIntroduction to Chris Bono and his work on Spring Cloud Dataflow and Spring Pulsar\nComparison between Apache Kafka and Apache Pulsar\nOverview of Spring Cloud Stream and its binders\nExplanation of source, processor, and sink concepts in streaming applications\nIntroduction to Spring Cloud Stream Applications project\nDiscussion on Change Data Capture (CDC) and its importance in streaming\nExploration of various sources, processors, and sinks available in Spring Cloud Stream Applications\nMention of KEDA (Kubernetes Event-driven Autoscaling) and its potential use with Spring Cloud applications\nUpcoming features in Spring Pulsar 1.2 release\nImportance of community feedback and using GitHub discussions for feature requests and issue reporting\nThe podcast provides a comprehensive overview of streaming data concepts and how Spring projects can be used to build efficient streaming applications.","thumbnail_url":"https://img.transistorcdn.com/O8bcAkNs5eCdL9oApddU7M8Z4LjyY4G_kWKMufASgFg/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMDIwLzE2ODIz/ODU0MzItYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}