enum PerformanceMode
| Language | Type name |
|---|---|
.NET | Amazon.CDK.AWS.EFS.PerformanceMode |
Go | github.com/aws/aws-cdk-go/awscdk/v2/awsefs#PerformanceMode |
Java | software.amazon.awscdk.services.efs.PerformanceMode |
Python | aws_cdk.aws_efs.PerformanceMode |
TypeScript (source) | aws-cdk-lib » aws_efs » PerformanceMode |
EFS Performance mode.
See also: https://docs.aws.amazon.com/efs/latest/ug/performance.html#performancemodes
Example
const fileSystem = new efs.FileSystem(this, 'MyEfsFileSystem', {
vpc: new ec2.Vpc(this, 'VPC'),
lifecyclePolicy: efs.LifecyclePolicy.AFTER_14_DAYS, // files are not transitioned to infrequent access (IA) storage by default
performanceMode: efs.PerformanceMode.GENERAL_PURPOSE, // default
outOfInfrequentAccessPolicy: efs.OutOfInfrequentAccessPolicy.AFTER_1_ACCESS, // files are not transitioned back from (infrequent access) IA to primary storage by default
transitionToArchivePolicy: efs.LifecyclePolicy.AFTER_14_DAYS, // files are not transitioned to Archive by default
replicationOverwriteProtection: efs.ReplicationOverwriteProtection.ENABLED, // Set to `DISABLED` if you want to create a read-only file system for use as a replication destination
});
Members
| Name | Description |
|---|---|
| GENERAL_PURPOSE | General Purpose is ideal for latency-sensitive use cases, like web serving environments, content management systems, home directories, and general file serving. |
| MAX_IO | File systems in the Max I/O mode can scale to higher levels of aggregate throughput and operations per second. |
GENERAL_PURPOSE
General Purpose is ideal for latency-sensitive use cases, like web serving environments, content management systems, home directories, and general file serving.
Recommended for the majority of Amazon EFS file systems.
MAX_IO
File systems in the Max I/O mode can scale to higher levels of aggregate throughput and operations per second.
This scaling is done with a tradeoff of slightly higher latencies for file metadata operations. Highly parallelized applications and workloads, such as big data analysis, media processing, and genomics analysis, can benefit from this mode.

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