Machine learning on AWS Lambda has a new best friend

Amazon Web Services (AWS) has introduced a new integration between AWS Lambda and Amazon Elastic File System (Amazon EFS), which allows for persistent storage capabilities that can enhance the functionality of serverless computing. This integration provides Lambda functions with the ability to store and access data concurrently, leveraging EFS's distributed file storage system, which is beneficial for tasks such as machine learning, virus scanning, and other use cases requiring large data storage. However, despite this advancement, AWS Lambda remains a stateless service, and using it to create stateful applications could lead to challenges, including potential failures in function chaining and service fragility. Security and configuration are critical when using EFS with Lambda, as it involves setting up a Virtual Private Cloud (VPC), managing access controls, and ensuring network visibility. Tools like New Relic's Infrastructure monitoring and Amazon Cloudwatch offer metrics to monitor the performance and security of the EFS-Lambda setup, providing insights into IOPS consumption and connection stability.