If you’ve been following our news, you know we just announced free fractional GPU capabilities for open source users, enabling multi-tenancy for NVIDIA GPUs and allowing users to optimize their GPU utilization to support multiple AI workloads as part of our open source and free tier offering.

In the rapidly evolving landscape of API management, understanding the raw performance and reliability of your API gateway is not just an expectation — it's a necessity. At Kong, we're dedicated to ensuring our users have access to concrete, actionable data to guide their operational and development strategies.

Today I’m excited to announce that Kong has released six new open source AI plugins in Kong Gateway 3.6 that turn every Kong Gateway deployment into an AI Gateway. These new plugins are available today and are entirely free and open source for everyone. The six new plugins are AI Proxy, AI Request/Response Transformer, AI Prompt Guard, AI Prompt Template, and AI Prompt Decorator.

We're pleased to announce the launch of Standard Webhooks! Kong has been part of the Technical Committee of this standard with other great companies like Svix (the initiator of the project), Ngrok, Zapier, Twillio, Lob, Mux, and Supabase. This was a year-long effort of gathering feedback, use cases, and debating about what and how to define what landed. Standard Webhooks is one initiative to standardize the way producers and consumers can have a contract to communicate.

In November of 2014, when NodeSource was still a small consulting group, my teammates Dan Shaw, Rod Vagg, and I were having dinner after a customer engagement, discussing how to bring Node.js production deployments to the same level of polish and tooling capability of the other runtimes our customers were already employing.

In the first three parts of our Inside Flink blog series, we discussed the benefits of stream processing, explored why developers are choosing Apache Flink® for a variety of stream processing use cases, and took a deep dive into Flink's SQL API. In this post, we'll focus on how we’ve re-architected Flink as a cloud-native service on Confluent Cloud. However, before we get into the specifics, there is exciting news to share.

An effective data platform thrives on solid data integration, and for Kafka, S3 data flows are paramount. Data engineers often grapple with diverse data requests related to S3. Enter Lenses. By partnering with major enterprises, we've levelled up our S3 connector, making it the market's leading choice. We've also incorporated it into our Lenses 5.3 release, boosting Kafka topic backup/restore.

Apache Kafka® supports incredibly high throughput. It’s been known for feats like supporting 20 million orders per hour to get COVID tests out to US citizens during the pandemic. Kafka's approach to partitioning topics helps achieve this level of scalability. Topic partitions are the main "unit of parallelism" in Kafka. What’s a unit of parallelism? It’s like having multiple cashiers in the same store instead of one.