If you’re not using *CDC (Change Data Capture)* for your data pipeline architecture, you’re missing out. Debezium + Kafka = magic for real-time syncs.
Also, *observability > monitoring*. Metrics alone won’t save you—logs and traces matter too.
Tool stack:
- Orchestration: Dagster
- Monitoring: Honeycomb (for traces)
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Hey everyone, wow—didn’t expect so many killer insights! The partitioning + CDC tips are gold.
Quick follow-up: Anyone have strong opinions on *serverless* for data pipeline architecture? Like, Lambda vs. Fargate for lightweight transforms?
Also, that cost warning hit hard—gonna audit our storage formats ASAP. Thanks for the reality check!
PS: Keep the horror stories coming. Nothing like a good "what NOT to do" lesson.
Also, *observability > monitoring*. Metrics alone won’t save you—logs and traces matter too.
Tool stack:
- Orchestration: Dagster
- Monitoring: Honeycomb (for traces)
---
Hey everyone, wow—didn’t expect so many killer insights! The partitioning + CDC tips are gold.
Quick follow-up: Anyone have strong opinions on *serverless* for data pipeline architecture? Like, Lambda vs. Fargate for lightweight transforms?
Also, that cost warning hit hard—gonna audit our storage formats ASAP. Thanks for the reality check!
PS: Keep the horror stories coming. Nothing like a good "what NOT to do" lesson.