Managing streaming data can often lead to complex data pipelines. Building robust real-time processing systems traditionally requires significant effort to handle even basic tasks like filtering or data reformatting before information reaches its final destination. This adds layers of complexity, increasing development time and operational overhead. However, recent advancements in cloud messaging services are fundamentally changing this. By integrating light data processing capabilities directly into the messaging layer, it’s now possible to significantly simplify these pipelines.
Specifically, using inherent capabilities within a service like Pub/Sub, you can apply transforms directly to individual messages as they flow through the system. These Single Message Transforms allow for common manipulations such as filtering unwanted messages based on content or attributes, adding or removing fields, or flattening complex data structures before they are delivered to consuming applications. This offloads simple yet necessary data processing steps from your core application logic, making downstream consumers simpler, faster, and more focused on their primary function. Applying these transforms directly within the messaging service boosts overall pipeline efficiency, reduces end-to-end latency for filtered or modified data, and helps manage the volume and shape of data delivered, ultimately leading to more streamlined and cost-effective data pipelines.
Source: https://cloud.google.com/blog/products/data-analytics/pub-sub-single-message-transforms/
