To meet the wide range of different file protocol use cases for file sharing, AWS launched the FSx line of shared storage services. Both options means incurring higher operational costs.ĪWS Lambda / EFS deployments do have one challenge to consider: Amazon EFS only supports NFS v4, which may cause issues if the files being used by AWS Lambda must also be accessed by SMB/ CIFS or NFS v3 clients. This can be countered by either allocating more storage space, which would give access to a larger number of credits, or moving to provisioned mode. Due to the system of burst credits used to determine AWS EFS performance, sustained high throughput activity can lead to a degradation in file access performance until credits have been replenished. On execution, the function itself simply accesses the mount as a normal directory.Īlthough it can be very easy to get started with Amazon EFS, certain issues can present themselves after any period of real usage. AWS will then ensure that the NFS file share is correctly mounted on any host that will execute the function.
Amazon introduced access to Amazon EFS file systems from AWS Lambda to address the importance of shared files to various enterprise and data-focused applications that require a conventional file system structure.Īmazon EFS file systems that must be accessed by an AWS Lambda function must be registered in advance within the function’s configuration, along with a mount point. Amazon EFSĪWS EFS is a managed solution for deploying file storage on AWS, allowing you to very quickly deploy scalable file systems that natively integrate with AWS Lambda.
But while it isn’t advisable or recommended by AWS, it is possible to use S3 as a file system solution. Also, environments that require high performance access to data will encounter problems if Amazon S3 is the primary data store, as this type of data access is not what this storage is designed for. For example, a write to an Amazon S3 object is an all-or-nothing operation, you can’t simply do a partial update. The IAM role associated with each function will govern the level of access granted to Amazon S3 buckets.Īs Amazon S3 provides object storage, it is most often not an ideal solution for file storage. In these kinds of AWS Lambda / S3 operations, in order to access files within Amazon S3, you must use the standard AWS APIs, usually via the Amazon SDK, from within your function code. It is also possible to trigger AWS Lambda functions when a new file is uploaded to Amazon S3, thereby initiating a data pipeline. Amazon S3Īmazon S3 storage is an outstanding solution for durable and cost-effective capacity storage in the cloud. In the following sections, we will examine the pros and cons of some of these approaches. There are a number of options for file storage AWS offers that can be used in serverless deployments. Different AWS Lambda functions can also be connected together and integrated with other AWS services to build complex workflows using AWS Step Functions. These functions can be written in any one of a multitude of languages, such as Java/C#, JavaScript, Python, Ruby, or Go. An AWS Lambda function is, as the name implies, simply an individual function that will be called into by AWS whenever the function’s triggering criteria has been met.
#Aws file storage code
AWS File Storage Integration with AWS LambdaĪWS File Storage Integration with AWS LambdaĪWS Lambda allows development teams to productionize new code within minutes, while keeping the actual business requirements front-and-center.Use the links below to jump down to the sections on:
In this article we will look at the benefits of deploying AWS file storage solutions in serverless architectures with the help of AWS Lambda, from Amazon EFS and S3 to the latest developments in FSx and NetApp Cloud Volumes ONTAP. It is for these reasons that the deployment of serverless microservices in cloud file sharing architectures is growing rapidly.ĭespite this focus on serverless, AWS Lambda functions will still frequently require access to persistent data stores such as databases, object storage, and shared file systems. Instead of thinking about servers and containers, you simply write the code that should be executed and deploy it, leaving it to AWS to manage high availability and to respond appropriately to changes in user demand. Serverless cloud platforms such as AWS Lambda eliminate the need to manually deploy and scale the base infrastructure used by applications and services in the cloud.
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