AWS lets Lambda access S3 buckets as local file systems
AWS has launched "S3 Files," a new feature enabling AWS Lambda functions to mount Amazon S3 buckets as local file systems. This allows functions to perform standard file operations on S3 objects without needing to first download the data for processing. The feature, built on Amazon EFS, is positioned as particularly valuable for multi-step AI and machine learning workloads that require state persistence and data sharing across different steps.
Key Takeaways
- The new S3 Files feature allows AWS Lambda functions to mount an S3 bucket and perform file operations directly.
- AWS highlights the value for multi-step AI/ML workflows, where functions need to persist memory and share state in a common workspace.
- Built on Amazon EFS, the feature allows multiple Lambda functions to connect to the same S3 Files system simultaneously.
- The integration is available in all regions where Lambda and S3 Files are present, with no charges beyond standard Lambda and S3 pricing.
Why It Matters
This directly addresses a common friction point in complex serverless workflows: managing data transfer between function invocations. For media processing and AI pipelines, mounting S3 as a file system simplifies code and can reduce execution latency by eliminating data download/upload cycles. The feature strengthens the AWS serverless stack for stateful applications, especially when combined with tools like Lambda durable functions that orchestrate parallel execution. Now, multiple transcoding or analysis functions can operate on a common data store without custom synchronization logic. What to watch: Performance benchmarks comparing this file-based approach against traditional S3 API Get/Put operations for typical video workflows.
Read full article at aws.amazon.com
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