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Enterprise-ready event streaming with Apache Kafka

The amount of data the world produces grows exponentially every year and many companies are realizing the potential of harnessing this data. A lot of this data is generated as a never-ending stream of events, with publishers creating the events and subscribers consuming them in various ways. This is where Apache Kafka comes in, more than a messaging system—it’s an event streaming platform. Get an introduction to Kafka and concepts like topic partitioning, consumer groups, and exactly-once semantics. Plus, learn about the different libraries and frameworks available, like Kafka Streams and Connect. Then, understand how the Confluent Platform for IBM Cloud Pak for Integration can take your enterprise Kafka deployment to the next level.

Kate Stanley

Software Engineer – IBM Cloud Pak for Integration

Kate Stanley is a Software Engineer based in the UK. Through her work on IBM Event Streams, she has gained experience running Apache Kafka on Kubernetes and running enterprise Kafka applications. In her previous role she specialized in cloud-native Java applications and microservices architectures. Kate has co-authored an IBM Redbook on Java microservices and has contributed to the open-source microservice project Game On and the open-source Kafka operator Strimzi. She enjoys sharing her experiences and has presented at conferences around the world, including the Kafka Summits in San Francisco, New York and London; JavaLand in Germany; and JFokus in Sweden. She is also a Confluent Community Catalyst for 2020/21.

Jeremy Hogan

Cloud Partner Solutions Architect at Confluent

Jeremy comes to Confluent most recently from Citigroup. In his role as a Vice President, he directed a team of cloud engineers and architects responsible for enabling Citigroup’s digital transformation from legacy systems, leveraging data in motion on an event driven architecture on a daily basis. In addition, Jeremy has over 20 years of experience in enterprise open source technology at companies like Red Hat and VMware.