For event streaming application developers, it is important to continuously update the streaming pipeline based on the need for changes in the individual applications in the pipeline. It is also […]
Following part 1 and part 2 of the Spring for Apache Kafka Deep Dive blog series, here in part 3 we will discuss another project from the Spring team: Spring […]
In part 1, we discussed an event streaming architecture that we implemented for a customer using Apache Kafka®, KSQL from Confluent, and Kafka Streams. Now in part 2, we’ll discuss […]
In the last year, we’ve experienced enormous growth on Confluent Cloud, our fully managed Apache Kafka® service. Confluent Cloud now handles several GB/s of traffic—a 200-fold increase in just six […]
So far in this series, we have recognized that by going back to first principles, we have a new foundation to work with. Event-first thinking enables us to build a […]
On the heels of part 1 in this blog series, Spring for Apache Kafka – Part 1: Error Handling, Message Conversion and Transaction Support, here in part 2 we’ll focus […]
With serverless being all the rage, it brings with it a tidal change of innovation. Given that it is at a relatively early stage, developers are still trying to grok […]
The requirements for fast and reliable data pipelines are growing quickly at Deliveroo as the business continues to grow and innovate. We have delivered an event streaming platform which gives […]
Part 1 of this series discussed why you need to embrace event-first thinking, while this article builds a rationale for different styles of event-driven architectures and compares and contrasts scaling, […]
In the future, data will be as automated and self-service as infrastructure is today. You’ll open a console that lists the data available in your company; define the pieces you […]
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