Join us for our next Apache Kafka® meetup on September 26th from 6:00pm in Barcelona. The address, agenda and speaker information can be found below. See you there!
6:00pm: Doors open
6:00pm - 6:30pm: Pizza, Drinks and Networking
6:30pm - 7:15pm: Robin Moffatt, Confluent
7:15pm - 7:45pm: Nakul Mishra, Casumo
7:45pm - 8:00pm - Additional Q&A & Networking
Robin is a Developer Advocate at Confluent, the company founded by the creators of Apache Kafka, as well as an Oracle ACE Director and Developer Champion. His career has always involved data, from the old worlds of COBOL and DB2, through the worlds of Oracle and Hadoop, and into the current world with Kafka. His particular interests are analytics, systems architecture, performance testing and optimization. He blogs at http://cnfl.io/rmoffand http://rmoff.net/ (and previously http://ritt.md/rmoff) and can be found tweeting grumpy geek thoughts as @rmoff. Outside of work he enjoys drinking good beer and eating fried breakfasts, although generally not at the same time.
Apache Kafka and KSQL in Action : Let’s Build a Streaming Data Pipeline!
Have you ever thought that you needed to be a programmer to do stream processing and build streaming data pipelines? Think again! Apache Kafka is a distributed, scalable, and fault-tolerant streaming platform, providing low-latency pub-sub messaging coupled with native storage and stream processing capabilities. Integrating Kafka with RDBMS, NoSQL, and object stores is simple with the Kafka Connect API, which is part of Apache Kafka. KSQL is the open-source SQL streaming engine for Apache Kafka, and makes it possible to build stream processing applications at scale, written using a familiar SQL interface.
In this talk we’ll explain the architectural reasoning for Apache Kafka and the benefits of real-time integration, and we’ll build a streaming data pipeline using nothing but our bare hands, the Kafka Connect API, and KSQL.
Gasp as we filter events in real time! Be amazed at how we can enrich streams of data with data from RDBMS! Be astonished at the power of streaming aggregates for anomaly detection!
Senior Software engineer at Casumo and consultant around JVM and related technologies. Prefers automation over manual configurations. Keen on continuous delivery, unit testing and code simplicity. Interested in developing applications that requires creativity, imagination, fast-learning and zest for putting theory into code.
Kafka - one more arsenal in a distributed toolbox
Kafka is an open-source distributed commit log addressing low latency, high throughput, scalability, fault-tolerance, and disk-based retention. It can be used to build tracking systems, messaging systems, high performance streaming platforms, real-time analysis, audit log….you name it. In our case, it’s been used to build a scalable event-store and messaging platform that stores billions of messages. To ingest historical data in our event store, we opted for Spring Kafka due to easy integration with Spring framework and enhanced testing support introduced by it. In this talk, we’re taking a closer look at this magic combo and explain essential as well as more advanced Spring-Kafka concepts.
We will look at stuff such as producer, consumer, transactions, etc. and how Spring Kafka maps those concepts using KafkaMessageListenerContainer, Kafka template, @KafkaListener, @KafkaHandler, Kafka Transaction Manager, @SendTo, etc. in Spring's world. We will also demonstrate how to use spring-Kafka-test for developing and running your unit tests against embedded Kafka server.
Furthermore, we will dig into some of the enhancements, such as synchronizing a Kafka transaction with some other transaction, configuring generic MessageConverter bean for publishing/consuming messages and detecting asynchronous consumers when they are idle; introduced by SpringKafka.