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Understanding AWS Lambda Event Source Mapping
- Understanding Event Source Mapping (ESM) is crucial for real-time and asynchronous workloads
- Partition key management in services like Amazon Kinesis and DynamoDB Streams is vital in ensuring order and scalability.
- Sequential processing ensures that events related to transactions, for instance, are handled in order.
- Routing unrecoverable errors to Dead Letter Queues (DLQs) is essential in event-driven systems to ensure failed events are analyzed or resolved manually.
- Parallelization and batch processing have become critical features for optimizing performance and error mitigation.
- Custom-building error-handling features, for instance, are required when leveraging Kafka as an alternative to Amazon Kinesis.
- Downstream traffic limits can pose scaling challenges that require throttling, backpressure mechanisms, and pre-filtering records to prevent overwhelming downstream components.
- Best practices for building resilient event-driven Architectures include error handling, DLQ configuration and monitoring, monitoring metrics, adjusting batch sizes, and graceful error handling.
- Balancing throughput, order guarantees, and error isolation is crucial in event-driven Architectures to ensure system efficiency and reliability.
- The session at AWS re:Invent provides practical knowledge for building robust, scalable event-driven systems.
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