It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

I’m excited to announce that Confluent has acquired WarpStream, an innovative Kafka-compatible streaming solution with a unique architecture. We’re excited to be adding their product to our portfolio alongside Confluent Platform and Confluent Cloud to serve customers who want a cloud-native streaming offering in their own cloud account.

I shouldn’t have to convince anyone that Apache Kafka is an incredibly useful and powerful technology. As a distributed event streaming platform, it’s adept at storing your event data and serving it up for downstream consuming applications to make sense of that information––in real time or as close to real time as your use case permits. The real beauty of Kafka as a technology is that it can do it with very little effort on your part. In effect, it’s a black box.

In just 12 short months, the Connect with Confluent (CwC) technology partner program has transformed from a new, ambitious initiative to expand the data streaming ecosystem into a thriving portfolio that’s rapidly increasing the breadth and value of real-time data. The program now provides a portfolio of 50+ integrations, each one amplifying the capabilities of Confluent's unified data streaming platform for Apache Kafka and Apache Flink.

Commercial and open source large language models (LLMs) are evolving rapidly, enabling developers to create innovative generative AI-powered business applications. However, transitioning from prototype to production requires integrating accurate, real-time, domain-specific data tailored to your business needs and deploying at scale with robust security measures.

Since its beginnings just five years ago, Apna has become the leading jobs site for tens of millions of workers in India, the largest labor market in the world. Today, Apna has more than 50 million registered users, resulting in more than 5 million interviews and 100,000 jobs activated per month.

Over the years, Amazon DynamoDB has grown into a feature-rich NoSQL database that has deep integrations with various services such as Amazon S3 and AWS Lambda. As businesses increasingly depend on data for decision-making, it is common to use data residing in DynamoDB to contextualize or even drive events at a granular level (as opposed to bulk or batch).

Hey, you! Yeah, you! The puzzled-looking Spring Boot developer, scouring the web for a guide on integrating your microservices with Apache Kafka on Confluent Cloud with Stream Governance. Admit it, you’ve been Googling nonstop for the past hour and all you’ve found are examples using StringSerializer/StringDeserializer with not even the slightest mention of "schema registry-aware" serialization methods. And I bet the examples you found are implemented in Java.

This summer marks five years since we announced our first fully managed connector on Confluent Cloud in 2019, the Amazon S3 Sink Connector. Since then, our connector offerings have not only expanded significantly but also enabled teams to send hundreds of petabytes of data throughput. Today, we support over 80 pre-built, fully managed connectors, custom connectors, and secure private networking.