~/talk

Persistent and performant ingestion using Data Prepper

Talkat OpenSearchCon Europe 2024 Β· 2024-05-06..05-07Β· [data-engineering, serverless]
links:none on file
slides:none on file

Data Prepper provides durable, pluggable ingestion: an HTTP push path can persist incoming events to a Kafka buffer which responds 200 once data lands in Kafka, then consumes and commits only after a successful write to OpenSearch. Pull sources (S3 via SQS, Kafka) use end-to-end acknowledgements with an easy acknowledgements=true flag and a visibility duplication protection option. Failures go to an S3 or file dead-letter queue that records errors for replay. Default bulk target is 5 MB; tests recommend ~20 MB for better throughput and observed higher performance than Logstash.

AI-written summary Β· about

  1. 0:00Introduction
  2. 1:04What is Data Prepper
  3. 6:32Data Prepper buffering
  4. 10:43Handling failure situations
  5. 15:19Improving performance
  6. 16:41Wrap up
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