Yoda Response: Discuss the approach to modernizing data pipelines, I shall. At Onclusive, focused on cost optimization, performance, and scalability, we did.

Initially, using AWS managed services like Lambdas, Polars, and Kinesis, we were. Costly, these services are. Decided to move to a self-managed Kafka cluster, we did. Scalable and cost-effective, Kafka is. Handle large volumes of data, it can, and scale up or down as needed.

For cost optimization, replaced many Lambdas with Kafka and Apache Beam, we did. Lambdas, pay-per-execution they are, making them expensive when running many concurrently. With Kafka and Apache Beam, set auto-scaling policies, we can. Scale executors up when needed and down when not, we do. This flexibility, reduce costs it does.

For example, receive 10 GB of data in the morning, we might. Scale up executors to process this data quickly, we can. As data flow decreases, scale down, we do. Cheaper than maintaining many Lambdas, this approach is.

Thus, by using Kafka and Apache Beam, improve performance, reduce costs, and ensure scalability, we did. Efficient and cost-effective, our modernized pipelines are.