IMPROVING COST EFFICIENCY OF DATA STREAMING PIPELINES

Summary from the TLDR Data newsletter

Streaming platforms get expensive for structural reasons, not data volume: request counts, extra copies of each message, serialization, and cross-AZ traffic often dominate the bill. Practical wins include batching producers and consumers, eliminating intermediate topics, using columnar payloads and compression, paying for low latency only where workloads truly need it, designing state deliberately, and keeping cost attribution visible per pipeline.