AWS SAA-C03 #49

A company stores call transcript files on a monthly basis. Users access the files randomly within 1 year of the call, but users access the files infrequently after 1 year. The company wants to optimize its solution by giving users the ability to query and retrieve files that are less than 1-year-old as quickly as possible. A delay in retrieving older files is acceptable.

Which solution will meet these requirements MOST cost-effectively?

A. Store individual files with tags in Amazon S3 Glacier Instant Retrieval. Query the tags to retrieve the files from S3 Glacier Instant Retrieval.

B. Store individual files in Amazon S3 Intelligent-Tiering. Use S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year. Query and retrieve the files that are in Amazon S3 by using Amazon Athena. Query and retrieve the files that are in S3 Glacier by using S3 Glacier Select.

C. Store individual files with tags in Amazon S3 Standard storage. Store search metadata for each archive in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Instant Retrieval after 1 year. Query and retrieve the files by searching for metadata from Amazon S3.

D. Store individual files in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Deep Archive after 1 year. Store search metadata in Amazon RDS. Query the files from Amazon RDS. Retrieve the files from S3 Glacier Deep Archive.


The most cost-effective solution would be Option B.

Storing individual files in Amazon S3 Intelligent-Tiering allows for automatic cost savings as the access patterns change, without performance impact or operational overhead. Using S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year is a cost-effective solution for infrequently accessed data where retrieval times of a few minutes to hours are acceptable.

You can query and retrieve the files that are in Amazon S3 by using Amazon Athena , which is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. For the files that are in S3 Glacier, you can use S3 Glacier Select to retrieve only the data you need from an archive, which can further save costs.

This solution meets the requirement of quick retrieval for files less than 1-year-old and acceptable delay for older files, while optimizing costs.

相关推荐
陈天伟教授3 小时前
人工智能训练师认证教程(2)Python os入门教程
前端·数据库·python
Elastic 中国社区官方博客4 小时前
Elasticsearch:在分析过程中对数字进行标准化
大数据·数据库·elasticsearch·搜索引擎·全文检索
聪明努力的积极向上4 小时前
【MYSQL】字符串拼接和参数化sql语句区别
数据库·sql·mysql
代码or搬砖4 小时前
RBAC(权限认证)小例子
java·数据库·spring boot
神仙别闹4 小时前
基于QT(C++)实现学本科教务系统(URP系统)
数据库·c++·qt
2301_768350234 小时前
MySQL为什么选择InnoDB作为存储引擎
java·数据库·mysql
上海蓝色星球4 小时前
迈向智慧电网新纪元:上海蓝色星球数字孪生变电主子站系统
运维·数据库
是大芒果4 小时前
数据库表设计
数据库
哥哥还在IT中4 小时前
MySQL order by 如何优化
数据库·mysql
积跬步,慕至千里5 小时前
postgre数据库大批量快速导出方法总结
数据库·postgres