Why Database CDC Pipelines Break at Scale

Failed to add items

Sorry, we are unable to add the item because your shopping cart is already at capacity.

Add to basket failed.

Please try again later

Add to wishlist failed.

Please try again later

Remove from wishlist failed.

Please try again later

Adding to library failed

Please try again

Follow podcast failed

Unfollow podcast failed

Why Database CDC Pipelines Break at Scale

Listen for free

View show details

Change Data Capture (CDC) pipelines are the backbone of modern real-time data architectures, but they often fail in production when event volume spikes or schema changes silently. Lucas and Luna walk through a real-world case from a mid-2026 fintech outage: a CDC pipeline that missed 12% of transactions during a flash sale because of unbounded log retention and missing idempotency keys. They explain the three most common failure modes—log truncation, schema drift, and backpressure stalls—and how to design for resilience. If you use Debezium, Kafka Connect, or any CDC tooling, this episode gives you concrete patterns to avoid waking up to a lagging pipeline at 3 AM. #ChangeDataCapture #CDC #DatabasePipelines #RealTimeData #KafkaConnect #Debezium #SchemaDrift #LogTruncation #Backpressure #FintechOutage #DataEngineering #StreamingData #Idempotency #DatabaseLogs #Technology #FexingoBusiness #BusinessPodcast #DatabaseTech Keep every episode free: buymeacoffee.com/fexingo

No reviews yet