Systems | Development | Analytics | API | Testing

Data Streaming

How to Set Up Networking on Confluent Cloud

Setting up network connections can often seem difficult or time consuming. This video provides a wayfinding introduction to help you get networking up and running for all cluster types on Confluent Cloud, showing you your networking options for each cluster type when running on AWS, Azure, or Google Cloud, respectively.

How to migrate from Kafka to Confluent Cloud with limited downtime

In this short video, a Confluent Solutions Engineering will run through the high-level steps on how to get started with your migration. And even better, once you’re done watching, you can download our comprehensive migration kit for a step by step guide of everything I’ve talked about and more.

How to Visualize Real-Time Data from Apache Kafka using Apache Flink SQL and Streamlit

Data visualization is cool, but have you tried setting up a chart of real-time data? In this video, Lucia Cerchie shows you how to create a live visualization of market data. She starts by producing data to a topic in Confluent Cloud from an Alpaca API websocket, then processes that data with Flink SQL, and finally uses a Streamlit component for a real-time visualization.

What Made Current 2024 Unforgettable? Hear From Our Attendees | Current 2024

In this recap video from Current 2024, attendees share their favorite moments from the event. From insightful talks on data streaming innovation to hands-on workshops and networking opportunities, hear what participants found most valuable.

Windowing with Table-Valued Functions | Apache Flink SQL

Apache Flink SQL makes it easy to implement analytics that summarize important attributes of real-time data streams. There are four different types of time-based windows in Flink SQL: tumbling, hopping, cumulating, and session. Learn how these various window types behave, and how to work with the table-valued functions that are at the heart of Flink SQL’s support for windowing.

How Thrivent Uses Real-Time Data for AI-Driven Fraud Detection

In today’s fast-paced financial services landscape, customers have a shorter attention span than ever. To meet clients’ growing demands for real-time access to information and keep innovating in areas like fraud detection and personalized financial advice, Thrivent needed to overhaul its data infrastructure. With data scattered across siloed legacy systems, diverse tech stacks, and multiple cloud environments, the challenge was a bit daunting. But by adopting Confluent Cloud, Thrivent was able to unify its disparate data systems into a single source of truth.