Apache Flink

Introduction to Flink SQL FEDERATED_SEARCH() on Confluent cloud. FEDERATED_SEARCH() along with ML_PREDICT() enables developers to execute GenAI use cases with data streaming technologies.

Learn how Flink enables developers to connect real-time data to external models through remote inference, enabling seamless coordination between data processing and AI/ML workflows.

FLIP 304 lets you customize and enrich your Flink failure messaging: Assign types to failures, emit custom metrics per type, and expose your failure data to other tools.

Confluent’s Create Embeddings Action for Flink helps you generate vector embeddings from real-time data to create a live semantic layer for your AI workflows.

This blog details an end-to-end real-time prediction project leveraging the combined capabilities of Confluent Cloud stacks and Google Cloud Vertex AI. This project aims to deliver a streamlined solution for real-time prediction applications, catering to the evolving needs and challenges of moder...

The blog post provides a comprehensive overview of the Flink Table API, demonstrating how it enables developers to express complex data processing logic using Java or Python in a user-friendly manner. It also includes practical examples and guidance, making it a valuable resource for anyone...

With AI model inference in Flink SQL, Confluent allows you to simplify the development and deployment of RAG-enabled GenAI applications by providing a unified platform for both data processing and AI tasks. Learn how you can use it to build a RAG-enabled Q&A chatbot using real-time airline data.

The Apache Flink® community released Apache Flink 1.20 this week. In this blog post, we highlight some of the most interesting additions and improvements.

Confluent Cloud for Apache Flink®️ supports AI model inference and enables the use of models as resources in Flink SQL, just like tables and functions. You can use a SQL statement to create a model resource and invoke it for inference in streaming queries.

Part two in the series on using FlinkSQL, Kafka, and Streamlit dives into async.io, FlinkSQL syntax, and Streamlit barchart component structure.

In part 1 of this series, we’ll make an app, powered by Kafka and FlinkSQL in Confluent Cloud and visualized with Streamlit, that allows a user to select a stock, in this case SPY, or the SPDR S&P 500 ETF Trust. Upon selection, a live chart of the stock’s bid prices, calculated every five seconds...

We're thrilled to announce the general availability of Confluent Cloud for Apache Flink across all three major clouds. This means that you can now experience Kafka and Flink as a unified, enterprise-grade platform to connect and process your data in real time.

Check out all the highlights from the Apache Flink® 1.19 release!

Several key new features have been added to Confluent Cloud for Apache Flink this year including Topic Actions, Terraform support, and expansion into GCP and Azure. Let's take a look at these enhancements and how they empower users to harness the full potential of streaming data.