Systems | Development | Analytics | API | Testing

Ep 3 - The Connective Tissue: Shift Left to turn Data Chaos to Clarity

In the final episode of our 3-part series on the basics of data streaming, we take a deep dive into data integration—covering everything from data governance to data quality. Our guests, Mike Agnich, General Manager of Data Streaming Platform, and David Araujo, Director of Product Management at Confluent, explain why connectors are must-haves for integrating systems.

Flink AI: Hands-On FEDERATED_SEARCH()-Search a Vector Database with Confluent Cloud for Apache Flink

With the advent of modern Large Language Models (LLMs), Retrieval Augmented Generation (RAG) has become a de-facto technology choice, employed to extract insights from a variety of data sources using natural language queries. RAG combined with LLMs presents many new possibilities for integrating Generative AI capabilities within existing business applications, specifically opening up many new use cases within the data streaming and analytics space.

Cluster Linking for Azure Private Link is Now Available in Confluent Cloud

Many organizations run Apache Kafka clusters in private Azure networks to meet stringent security, compliance, and operational requirements. However, securely replicating data across clusters without exposing traffic to the public internet has traditionally been complex, requiring self-managed mirroring solutions with significant operational overhead.

Your AI Project Has a Data Liberation Problem

Generative AI has the potential to add up to $4.4 trillion annually to the global economy. But most organizations won’t see that value—not because of their models or infrastructure, but because of their data. Despite years of investment in data lakes, warehouses, and analytics tools, organizations are drowning in complexity. Data is scattered across siloed systems, riddled with duplication, and locked behind outdated batch processes.

Managing Data Contracts: Helping Developers Codify "Shift Left"

We live in a world of events. The phone in your pocket is emitting data about your location, and receiving a notification to order your morning coffee from your favorite shop en route to work. Your thermostat knows you’re out for the day, and adjusts the temperature to save energy. Your refrigerator automatically orders a replacement water filter after serving a given amount of water. Railway sensors send a location event for cars passing by.

Building AI Agents and Copilots with Confluent, Airy, and Apache Flink

From automating routine tasks to providing real-time insights to inform complex decisions, AI agents and copilots are poised to become an integral part of enterprise operations. At least that’s true for the organizations that can figure out how to supply large language models (LLMs) with real-time, contextualized, and trustworthy data in a secure and scalable way.

A Distributed State of Mind: Event-Driven Multi-Agent Systems

This article was originally published on InfoWorld on Jan. 28, 2025 While large language models (LLMs) are useful, their real power emerges when they can act on insights, automating a broader range of problems. Reasoning agents have a long history in artificial intelligence (AI) research—they refer to a piece of software that can generalize what it has previously seen to apply in situations it hasn’t seen before.

Ep 2 - Processing Without Pause: Continuous Stream Processing and Apache Flink

We’re diving even deeper into the fundamentals of data streaming to explore stream processing—what it is, the best tools and frameworks, and its real-world applications. Our guests, Anna McDonald, Distinguished Technical Voice of the Customer at Confluent, and Abhishek Walia, Staff Customer Success Technical Architect at Confluent, break down what stream processing is, how it differs from batch processing, and why tools like Flink are game changers.