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Amazon Redshift Managed Storage

5 minutes 5 Questions

Amazon Redshift Managed Storage (RMS) is a managed storage solution that seamlessly scales with the size of your Redshift cluster, providing you with cost-effective and high-performance storage for your data warehouse. RMS automatically manages your data's placement, migration, and compression, fre…

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AWS Certified Solutions Architect - Amazon Redshift Managed Storage Example Questions

Test your knowledge of Amazon Redshift Managed Storage

Question 1

A company is migrating its historical dataset into an Amazon Redshift cluster and wants to keep the data in Redshift managed storage (not external tables). They require the ability to increase storage capacity without adding or resizing compute nodes. Which Amazon Redshift feature enables this?

Correct Answer: Redshift RA3 nodes

Redshift RA3 nodes use Redshift Managed Storage to decouple storage from compute, allowing storage to scale independently to petabytes while you size compute based on performance needs. Redshift Spectrum enables querying data in Amazon S3 but does not increase the cluster’s managed storage. DC2 nodes couple storage with compute capacity, requiring more nodes for more storage. Concurrency Scaling adds transient clusters to handle query load spikes and does not address storage scaling.

Question 2

Your Amazon Redshift cluster receives daily bulk loads into large tables. Over time, queries slow down due to table bloat and unsorted data. Which operational task should you schedule to reclaim space and re-sort data to maintain query performance?

Correct Answer: Implement a regular Vacuum process

VACUUM reclaims disk space from deleted or updated rows, re-sorts table data according to the sort key, and merges small blocks. This restores data locality and zone map effectiveness, reducing the amount of data scanned and improving query performance after frequent bulk loads. Scaling the cluster or changing WLM does not address fragmentation and unsorted data, and increasing the number of queries is irrelevant. Best practice is to schedule VACUUM after large loads (often along with ANALYZE to refresh statistics).

Question 3

A company has a nightly ETL process that extracts data from an Amazon RDS instance, loads it into an Amazon Redshift cluster, and then reports are generated. Recently, the reports take longer than usual to generate. Which approach is the MOST cost-effective in improving the Redshift query performance?

Correct Answer: Modify the sort keys to better align with the WHERE clause in the queries

The best approach to improve the Redshift query performance is to modify the sort keys so they better align with the WHERE clause in the queries. This helps in minimizing the amount of data scanned from the disks and can improve query performance. The other answer choices either add significant cost (additional nodes & RDS read replica) or may require significant design changes (Redshift Spectrum, move to EMR or Aurora).

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