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Overview for kafka-streams


Creating an Elastic Platform Using Kafka and Microservices in OpenShift

American Express Global Business Travel run their microservices (Docker) running in OpenShift (Kubernetes) processing Kafka Streams, running real-time anomaly detection using Kafka Streams, powering their data lake through Kafka, feeding distributed caching layer (Apache Ignite) and connecting all internal and external systems using Kafka. 

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War Stories: DIY Kafka

This talk explains some problems Zalando experienced while running Kafka brokers and Kafka Streams applications, as well as the consultations the data team had with other experts the same issue.  There are highlights on some of the decisions that were made regarding backups, monitoring and operations to minimize our time spent administering our Kafka brokers and various stream applications.

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Real-Time Market Data Analytics Using Kafka Streams

Bloomberg is building a streaming platform with Apache Kafka, Kafka Streams and Spark Streaming to handle high volume, real-time processing with rapid derivative market data. In this discussion you will learn how Bloomberg utilizes Kafka Streams Processor API to build pipelines that are capable of handling millions of market movements per second with ultra-low latency, as well as performing complex analytics like outlier detection, source confidence evaluation (scoring), arbitrage detection and other financial-related processing. 

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How Big Fish Games Developed Real-Time Analytics Using Kafka Streams and Elasticsearch

Big Fish Games a leading producer and distributor of casual and mid-core game hase distributed more than 2.5 billion games to customers in 150 countries, representing over 450 unique mobile games and over 3,500 unique PC games. Big Fish Games
uses Apache Kafka to process data generated across game play. Recently, they introduced real-time analytics of game data using Kafka Streams integrated with Elasticsearch. This allows to monitor the results of live operations and to make changes to these events after they have gone live. 

This presentation gives a detailed explanation of how Big Fish Games used Kafka Streams to transform raw data into Elasticsearch documents, and how the application was scaled to over a million daily active users. It will also touch on the limitations discovered with Kafka Connect integration with Elasticsearch and how to use Elasticsearch bulk processing with Kafka Streams. 

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