For safety the script will not write any data to any /dev/ device if it has an existing partition table. This script will format the instance store on boot and enable swap, by default it formats /dev/xvdb which shouldn’t contain data on boot as ephemeral storage (what the instance store sites on top of) is wiped on shutdown. You could use this script with a second EBS volume on the T1 and T2 instances for swap to give that buffer for the small amount of memory provided (Make sure you use the EBS SSD backed storage otherwise you will be charged per million I/O’s). T1 and T2 instances don’t have instance stores or special Swap instance stores. Special swap instance stores are provided with m1.small and m1.medium instances (usually /dev/xvdb3) and mounted automatically (Unless you upgrade from a micro but that is another issue I’ll cover in another post). Additionally, they now have the flexibility to reconfigure the storage, as needed, up to 10 GB.I created this script so that I could utilise the free instance store provided with my EC2 instance as swap. With this new update in AWS Lambda, users can access a low-latency, secure temporary file system in Lambda functions. Owing to this feature, users are now able to configure temporary storage between 512 MB and 10 GB, for each execution. The newly introduced increased ephemeral storage serves as the solution for these problems. storage to store data) Instance store-backed AMI (which uses ephemeral block storage to store data) While creating an EC2 instance using a web console. Moreover, there was the general complexity arising from the need to manage several moving pieces. They also had to bear substantial extra costs for using EFS. Īlthough this solved storage issues, users still had to face lowered performance through cold start. Alternatively, they had to mount an Amazon EFS (Amazon Elastic File System) to the AWS Lambda function. If you use AWS Lambda to process large files (like images and PDFs) or carry out ETL ( extract, transform, and load ) jobs on a huge dataset, or operationalize ML models, it’s difficult to follow the runtime storage requirements.Įarlier, to increase the local storage, users needed to use Amazon S3 (Amazon Simple Storage Service) as intermediary storage for reading or writing data at the time of execution. New in AWS Lambda: Increased Ephemeral Storage with Significant Advantages The increased ephemeral storage brings several benefits to the table for users. This was regardless of memory configuration or runtime. If there’s any issue with the underlying hardware or the instance is terminated or stopped, the data on ephemeral storage will be lost.Įarlier, when using AWS Lambda functions, one could only use ephemeral storage of 512 MB, for each function executed. The temporary, volatile storage attached to instances, present only during the instance’s running lifetime, is known as ephemeral storage. What’s new in AWS Lambda, is the ability to configure ephemeral storage up to 10 GB! What is Ephemeral Storage? Ephemeral storage has always been a feature of AWS Lambda. This new feature will benefit customers running data workloads, like financial analysis, machine learning (ML) inference, or media processing. AWS recently announced that users can now configure up to 10 GB of ephemeral storage for each Lambda function instance.
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