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.
Recently, I got my hands dirty working with Apache Flink®. The experience was a little overwhelming. I have spent years working with streaming technologies but Flink was new to me and the resources online were rarely what I needed. Thankfully, I had access to some of the best Flink experts in the business to provide me with first-class advice, but not everyone has access to an expert when they need one.