I would like to share my experience with Kafka. At Onclusive, we implemented Kafka for data stream processing, sourcing information from various channels, including news outlets. These sources provide their data through APIs, which we then send into our Kinesis stream. From Kinesis, Lambda functions are triggered to transform the data.

To optimize costs, enhance scalability, and achieve faster processing, we transitioned to Kafka and Apache Beam. We established a Kafka cluster and directed our sources to publish data to specific Kafka topics. Apache Beam then processes and transforms the data from these topics.

We utilize Kafka for its performance, scalability, and cost benefits. Additionally, Kafka supports our analytics and monitoring efforts. We push logs of data consumption and the types of data consumed to Kafka topics, enabling us to create dashboards for improved analysis and visualization.

Overall, Kafka plays a crucial role in our data pipeline.