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Durable Function ESM and Chaining Pattern #2903
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| "description": "This serverless pattern demonstrates how to build an event-driven data processing pipeline using AWS Lambda Durable Functions with direct SQS Event Source Mapping and Lambda invoke chaining.", | ||
| "language": "Python", | ||
| "level": "200", | ||
| "framework": "SAM", |
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AWS SAM
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Done, updated
| @@ -0,0 +1,67 @@ | |||
| { | |||
| "title": "Event-Driven Data Pipeline with Lambda Durable Functions", | |||
| "description": "This serverless pattern demonstrates how to build an event-driven data processing pipeline using AWS Lambda Durable Functions with direct SQS Event Source Mapping and Lambda invoke chaining.", | |||
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Max limit for description is 150
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Updated, description is within the limit
Issue #, if available:
Description of changes:
This serverless pattern demonstrates how to build an event-driven data processing pipeline using AWS Lambda Durable Functions with direct SQS Event Source Mapping and Lambda invoke chaining.
This pattern demonstrates an event-driven data processing pipeline using AWS Lambda Durable Functions with direct SQS Event Source Mapping. When a message arrives in the SQS queue, it directly triggers the durable function (no intermediary Lambda needed). The durable function then orchestrates a series of specialized processing steps using Lambda invoke chaining - first validating the incoming data, then transforming it (converting data_source to uppercase), and finally storing the processed results in DynamoDB. Throughout this process, the durable function automatically creates checkpoints, enabling fault-tolerant execution that can recover from failures without losing progress. The entire pipeline operates within the 15-minute ESM execution limit, making it ideal for reliable batch processing workflows.
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