Streaming Platforms Architecture: Scalable Pipelines
Streaming Platforms Architecture: Scalable Pipelines Streaming platforms power real-time apps across media, commerce, and analytics. A scalable pipeline sits between producers and consumers, handling bursts, retries, and ordering. With thoughtful patterns, you can keep latency low while data stays accurate. Core components Ingest tier: fast producers push events, with backpressure and retry logic to handle bursts. Stream broker: a durable, partitioned log that stores, preserves order within partitions, and enables parallel consumption. Processing layer: stateful or stateless stream processors that transform, enrich, or aggregate data in near real time. Storage layer: a real-time view store for fast queries and a long-term data lake or warehouse for batch analysis. Orchestration and monitoring: tools for scheduling, alerting, and visible health metrics. Data moves from producers to topics, then to processors, and finally to sinks. Partitioning is the key to parallelism: more partitions mean more concurrent workers. Messages should carry stable keys to keep related events together when needed. ...