Systems | Development | Analytics | API | Testing

In this video, we discuss one way a business can approach decomposing a monolith using a series of clearly defined steps and robust monitoring.

Join Lucia Cerchie in a coding walkthrough, bridging the gap between REST APIs and data streaming. Together we’ll transform the OpenSky Network's live API into a data stream using Kafka and Flink SQL. Not only do we change the REST API into a data stream in this walkthrough, but we clean up the data on the way! We use Flink SQL to make it more readable and clean, and in that way we keep more of the business logic away from the client code.

#kafka #serverless #aws

In this video, Wade explores the process of decomposing a monolith into a series of microservices. You'll see how Tributary bank extracts a variety of API methods from an existing monolith. Tributary Bank wants to decompose its monolith into a series of microservices. They are going to start with their Fraud Detection service. However, before they can start, they first have to untangle the existing code. They will need to define a clean API that will allow them to move the functionality to an asynchronous, event-driven microservice.

Learn how the Data Portal and Apache Flink in Confluent Cloud can help developers and data practitioners find the data they need to quickly create new data products.

How do you prevent hallucinations from large language models (LLMs) in GenAI applications? LLMs need real-time, contextualized, and trustworthy data to generate the most reliable outputs. Kai Waehner, Global Field CTO at Confluent, explains how RAG and a data streaming platform with Apache Kafka and Flink make that possible.