![]() ![]() More ephemeral storage allows you to download larger models from Amazon S3 to /tmp and use these in your processing. Machine learning (ML) inference: Many inference tasks rely on large reference data files, including libraries and models. More temporary space enables more complex ETL jobs to run in Lambda functions. There are several common customer use cases that can benefit from the expanded ephemeral storage.Įxtract-transform-load (ETL) jobs: Your code may perform intermediate computation or download other resources to complete processing. All data stored in /tmp is encrypted at rest with a key managed by AWS. ![]() It’s also available for Provisioned Concurrency. The behavior is identical whether you use zip or container images to deploy your functions. With this new configurable setting, ephemeral storage works in the same way. The contents are deleted when the Lambda service eventually terminates the execution environment. This is a common use case that can help reduce function duration for subsequent invocations. This means that you can use the same execution environment to cache static assets in /tmp between invocations. ![]() This storage is not shared between instances of Lambda functions and the space is guaranteed to be empty when a new instance starts. This provides a fast file system-based scratch area that is scoped to a specific instance of a Lambda function. ![]() How ephemeral storage works in LambdaĪll functions have ephemeral storage available at the fixed file system location /tmp. This blog post explains how this works and how to use this new setting in your Lambda functions. You can set this in the AWS Management Console, AWS CLI, or AWS SDK, AWS Serverless Application Model (AWS SAM), AWS Cloud Development Kit (AWS CDK), AWS Lambda API, and AWS CloudFormation. With this new feature, you can now configure ephemeral storage for up to 10 GB per function instance. This was set at 512 MB for every function, regardless of runtime or memory configuration. PD snapshots are global enabling customers to easily create PDs in any region.AWS Lambda functions have always had ephemeral storage available at /tmp in the file system. As discussed in part 2, GCE has a global scope that is independent of regions. For example, to export an EBS volume from US-EAST to US-WEST, you have to create a snapshot in US-EAST and then initiate the copy process to US-WEST to restore that. What this means to the customers? They need not deal with the manual copy of snapshots across regions. While EBS snapshots are specific to an AWS region, PD snapshots are global. Like the way EBS snapshots are stored in Amazon S3, PD snapshots are stored in Google Cloud Storage.But, the major difference between EBS snapshots and PD snapshots is at the scope. GCEcreates differential snapshots, which allow for better performance and lower storage charges. There is a lot of similarity between Amazon EBS snapshots and GCE PD snapshots. Like EBS, PD’s performance is proportional to the size of the disk. The maximum size supported by EBS is 1TB.GCE Persistent Disks can be up to 10TB. ![]()
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