Adaptive write request scheduling in Redpanda's Cloud Topics

Redpanda's Cloud Topics revolutionize data storage by allowing partitions to store data entirely in object storage, such as S3, rather than on local disks, which decouples storage cost and capacity from brokers and enhances cluster scalability and retention. This innovative approach maintains compatibility with Apache Kafka producers, requiring no client changes, but fundamentally alters the data path as write requests involve uploading every batch to S3 before acknowledgment, necessitating efficient batching and scheduling to prevent latency and cost issues. To address these challenges, Redpanda developed a dynamic write-request scheduler that adjusts upload parallelism across CPU cores, optimizing batching efficiency against latency and cost without operator tuning. The system is built on Seastar's thread-per-core framework, using a buddy allocator algorithm to manage shard scheduling, allowing shards to make local decisions about splitting or merging for upload tasks. This reduces the need for centralized coordination, thus enhancing scalability and adaptability to varying loads. Ultimately, this architecture separates the functions of writing and scheduling, enabling efficient pipeline management and allowing for future enhancements without disrupting existing systems.

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