AWS AmazonS3 documentation change
Summary
Updated references from 'Amazon Quick Suite' to 'Amazon Quick' in Storage Lens export documentation
Security assessment
Change involves branding terminology updates without any security implications. No security features, vulnerabilities, or configurations were modified or added.
Diff
diff --git a/AmazonS3/latest/userguide/storage_lens_basics_metrics_recommendations.md b/AmazonS3/latest/userguide/storage_lens_basics_metrics_recommendations.md index 11a0f3039..da7890cf9 100644 --- a//AmazonS3/latest/userguide/storage_lens_basics_metrics_recommendations.md +++ b//AmazonS3/latest/userguide/storage_lens_basics_metrics_recommendations.md @@ -114 +114 @@ Storage Lens only generates metrics for [S3 general purpose buckets](./UsingBuck -When exporting Storage Lens metrics data, you can choose both an S3 general purpose bucket or an S3 table bucket as your destination. General purpose buckets provide broad compatibility with existing tools and applications, offering flexibility to process data within your account, using your preferred analytics services. This option supports standard S3 access patterns and integrations for data analysis within individual buckets in your Region. In contrast, S3 table bucket lets you run immediate queries across multiple accounts and regions, create custom dashboards with Amazon Quick Suite, and join data with other AWS services or third-party tools, without the need for additional processing infrastructure. For example, you can combine Storage Lens metrics with S3 Metadata to analyze object activity patterns across your organization. +When exporting Storage Lens metrics data, you can choose both an S3 general purpose bucket or an S3 table bucket as your destination. General purpose buckets provide broad compatibility with existing tools and applications, offering flexibility to process data within your account, using your preferred analytics services. This option supports standard S3 access patterns and integrations for data analysis within individual buckets in your Region. In contrast, S3 table bucket lets you run immediate queries across multiple accounts and regions, create custom dashboards with Amazon Quick, and join data with other AWS services or third-party tools, without the need for additional processing infrastructure. For example, you can combine Storage Lens metrics with S3 Metadata to analyze object activity patterns across your organization. @@ -122 +122 @@ Exporting Storage Lens metrics to an S3 general purpose bucket offers flexibilit -When exporting Storage Lens metrics to S3 table bucket, you can easily analyze your storage usage and activity metrics without building data pipelines. Your metrics are organized in S3 Tables that are created in an AWS-managed S3 table bucket called `aws-s3` for optimal query performance, with customizable retention periods and encryption settings to meet your data management needs. With your metrics in S3 Tables, you can run queries across multiple accounts and Regions using SQL tools and AWS analytics services (like Amazon Athena, Amazon Quick Suite, Amazon EMR, and Amazon Redshift) to create custom dashboards and generate deeper insights. For example, you can join S3 Storage Lens metrics with S3 Metadata to identify objects in prefixes that aren't showing any recent activity. Any data stored in an S3 table bucket incurs S3 Tables costs. For more information about S3 Tables pricing, see [Amazon S3 pricing](https://aws.amazon.com/s3/pricing). +When exporting Storage Lens metrics to S3 table bucket, you can easily analyze your storage usage and activity metrics without building data pipelines. Your metrics are organized in S3 Tables that are created in an AWS-managed S3 table bucket called `aws-s3` for optimal query performance, with customizable retention periods and encryption settings to meet your data management needs. With your metrics in S3 Tables, you can run queries across multiple accounts and Regions using SQL tools and AWS analytics services (like Amazon Athena, Amazon Quick, Amazon EMR, and Amazon Redshift) to create custom dashboards and generate deeper insights. For example, you can join S3 Storage Lens metrics with S3 Metadata to identify objects in prefixes that aren't showing any recent activity. Any data stored in an S3 table bucket incurs S3 Tables costs. For more information about S3 Tables pricing, see [Amazon S3 pricing](https://aws.amazon.com/s3/pricing).