Solution Pattern: Event-driven intelligent applications
Event-driven Sentiment Analysis using Kafka, Knative and AI/ML
Event-driven Sentiment Analysis using Kafka, Knative and AI/ML
Open source is at the heart of everything Red Hat works on. Learn how Red Hat engineers contribute to data streaming projects such as Apache Kafka and Strimzi.
Get tips on managing and preserving Kafka Connect offsets smoothly starting from AMQ Streams 2.6 (Kafka 3.6).
Discover the importance of encryption of data at rest in Apache Kafka and examine one approach to encrypting data at rest using the Kroxylicious Kafka proxy.
Explore an approach to load testing against Red Hat 3scale API Management using Hyperfoil and Ansible on Red Hat OpenShift.
Dive into the inaugural edition of Camel integration quarterly, covering the
Without data, software has no value. Data needs to be created, stored, updated
Learn how to develop applications using Quarkus, .NET Core 7, and Golang that
Learn how to deploy an application on a cluster using Red Hat OpenShift Service
Data integration patterns help create a unified, accurate, and consistent view