AWS Certified Data Analytics Specialty 2021 - Hands-On! - Kinesis - Handling Duplicate Records

The video tutorial explains how duplicates can occur in Kinesis Data Streams on both the producer and consumer sides. On the producer side, network timeouts can lead to duplicate records being created. The solution is to embed a unique record ID to deduplicate data. On the consumer side, retries can cause the same data to be read twice, especially during worker restarts or shard changes. Making consumer applications idempotent is recommended to handle duplicates. The video also provides exam tips related to these scenarios.

How can you make a consumer application idempotent to handle duplicates?

What is the recommended approach to handle duplicates at the final destination in Kinesis Data Streams?