Life doesn't happen in batch mode, which is why for several years now, we see a very strong tendency towards stream processing throughout various industries. Companies need, or least partially have to rethink their existing data architectures in order to enable near real-time business cases. Besides traditional database systems and batch-driven tooling, many companies put Apache Kafka® - the de facto standard for robust and scalable event streaming - to good use.
This talk explores the following four different ways to run Kafka on Azure:
* Kafka on HDInsight (open-source core Kafka)
* EventHubs (Microsoft's very own "Kafka look-alike")
* Confluent Cloud (a vendor-backed Kafka distribution)
* Kafka in Azure Kubernetes Service
You will walk away with a better understanding about the most important benefits, drawbacks and implications for each of the discussed alternatives.
Hans-Peter (@hpgrahsl) is a technical trainer at NETCONOMY. As an independent engineer and consultant he helps customers to build cloud-based or on-premises data architectures using modern technology stacks and NoSQL data stores. He is also an associate lecturer for Software Engineering at CAMPUS 02 and is speaking at tech-related and developer conferences. For his code contributions, conference talks and blog post writing at the intersection of the Apache Kafka and MongoDB ecosystems, Hans-Peter received the Confluent Community Catalyst award twice and became one of the founding members of the MongoDB Champions Program.
Event Page: https://globalazure.at/sessions/kafka/