{"product_id":"b09782743r","title":"Event Streams in Action: Real-time event systems with Kafka and Kinesis","description":"\u003cp\u003eSummary\u003c\/p\u003e\n\n\u003cp\u003eEvent Streams in Action  is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments.\u003c\/p\u003e\n\n\u003cp\u003eAbout the Technology\u003c\/p\u003e\n\n\u003cp\u003eMany high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications.\u003c\/p\u003e\n\n\u003cp\u003eAbout the Book\u003c\/p\u003e\n\n\u003cp\u003eEvent Streams in Action  teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain.\u003c\/p\u003e\n\n\u003cp\u003eWhat's inside Validating and monitoring event streams Event analytics Methods for event modeling Examples using Apache Kafka and Amazon Kinesis\u003cbr\u003e\nAbout the Reader\u003c\/p\u003e\n\n\u003cp\u003eFor readers with experience coding in Java, Scala, or Python.\u003c\/p\u003e\n\n\u003cp\u003eAbout the Author\u003c\/p\u003e\n\n\u003cp\u003eAlexander Dean  developed Snowplow, an open source event processing and analytics platform.  Valentin Crettaz  is an independent IT consultant with 25 years of experience.\u003c\/p\u003e\n\n\u003cp\u003eTable of Contents\u003c\/p\u003e\n\n\u003cp\u003ePART 1 - EVENT STREAMS AND UNIFIED LOGS Introducing event streams The unified log 24 Event stream processing with Apache Kafka Event stream processing with Amazon Kinesis Stateful stream processing PART 2- DATA ENGINEERING WITH STREAMS Schemas Archiving events Railway-oriented processing Commands PART 3 - EVENT ANALYTICS Analytics-on-read Analytics-on-write\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":52838199197912,"sku":"YSL68877","price":29.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0835\/3356\/2072\/files\/71fsAqvOO4L._SY1500.jpg?v=1793284871","url":"https:\/\/www.bookmebay.com\/products\/b09782743r","provider":"BookMebay","version":"1.0","type":"link"}