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Скачать или смотреть How to Change the /tmp Folder in AWS Lambda to EFS

  • vlogize
  • 2025-04-13
  • 6
How to Change the /tmp Folder in AWS Lambda to EFS
How to change the /tmp folder in AWS Lambda to efsamazon web servicesaws lambdaamazon efs
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Описание к видео How to Change the /tmp Folder in AWS Lambda to EFS

Looking to change your AWS Lambda's `/tmp` folder to EFS for more storage? This guide provides a step-by-step guide to accomplish that.
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This video is based on the question https://stackoverflow.com/q/73734564/ asked by the user 'MLugo' ( https://stackoverflow.com/u/17291147/ ) and on the answer https://stackoverflow.com/a/73740373/ provided by the user 'Jatin Mehrotra' ( https://stackoverflow.com/u/13126651/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

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How to Change the /tmp Folder in AWS Lambda to EFS

If you're using AWS Lambda for compiling C+ + code and have been facing the "No space left on device" error due to exceeding the /tmp directory's limit of 512 MB, you're not alone. Many developers encounter this limitation when handling multiple concurrent requests. In this guide, we will explore how to change the temporary storage from /tmp in AWS Lambda to Amazon EFS (Elastic File System) for increased storage capacity.

Understanding the Problem

AWS Lambda provides ephemeral storage in the /tmp directory which has a default limit of 512 MB. When you receive too many concurrent requests, it's common to exceed this size, leading to storage errors that can disrupt your application's functionality. The root of the problem lies in managing larger workloads while successfully utilizing Lambda's computational capabilities.

The Solution: Switching to EFS

While AWS Lambda allows you to increase the size of ephemeral storage, it can involve extensive testing and can incur additional costs. On the other hand, Amazon EFS provides persistent storage that can be shared across Lambda invocations without the same space limitations. Here’s how to make the switch to EFS for your Lambda's temporary storage.

Step 1: Set Up EFS

Create an EFS File System:

Go to the AWS Management Console and navigate to the EFS service.

Click "Create file system" and follow the prompts to set it up.

Make sure that the file system is in the same region as your Lambda function.

Configuring Access Points:

Once the EFS is created, set up access points to control how Lambda functions can access your EFS.

Step 2: Modify Lambda Configuration

Access the Lambda Function:

Open the AWS Lambda service and select the Lambda function you wish to modify.

Attach EFS to Lambda:

In the function's configuration settings, look for "File system" options under the "Configuration" tab.

Link your Lambda function to the EFS file system and specify the access point you created.

Update Lambda Code to Use EFS Path:

Modify your code to read from and write to the EFS path instead of the /tmp directory.

Replace any references to /tmp with the appropriate path to your EFS file system, typically mounted as /mnt/efs/<your-access-point>.

Step 3: Testing

After configuring the function and updating the code, run tests to ensure that your Lambda can both read from and write to the EFS successfully. Monitor the performance and adjust any settings if required.

Additional Considerations

Cost Implications:

While EFS provides more flexible storage, remember that there are costs associated with EFS based on storage used and data transfer. Be sure to evaluate these costs based on your expected workload.

Performance:

While EFS offers persistence, it may not be as fast as the ephemeral storage. Ensure that your application tolerates any potential latency when accessing data.

Conclusion

Changing your AWS Lambda's temporary storage from /tmp to EFS can significantly enhance your application’s ability to handle multiple concurrent requests. By following the steps outlined above, you can alleviate storage limitations and improve performance for memory-intensive computational tasks. Remember to monitor and adjust settings as necessary to find the right balance between speed and cost efficiency.

Happy coding!

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