What are the best practices for designing a scalable data pipeline architecture? or How do you handle

IMO, the biggest mistake is ignoring *cost* when designing a data pipeline architecture. Scaling isn’t just about tech—it’s about $$$.

Use spot instances where possible, and *compress* your data before storage (Parquet/ORC formats FTW).

Oh, and *autoscaling* isn’t optional. If you’re manually tweaking capacity, you’re doing it wrong.