AWS Certified Solutions Architect - Associate
Get started today
Ultimate access to all questions.
Deep dive into the quiz with AI chat providers.
We prepare a focused prompt with your quiz and certificate details so each AI can offer a more tailored, in-depth explanation.
A company is migrating an on-premises application to AWS. The company wants to use Amazon Redshift as a solution.
Which use cases are suitable for Amazon Redshift in this scenario? (Choose three.)
Other
Community
UAnonymous
A
Supporting data APIs to access data with traditional, containerized, and event-driven applications
B
Supporting client-side and server-side encryption
C
Building analytics workloads during specified hours and when the application is not active
D
Caching data to reduce the pressure on the backend database
E
Scaling globally to support petabytes of data and tens of millions of requests per minute
F
Creating a secondary replica of the cluster by using the AWS Management Console
Explanation:
Explanation
Amazon Redshift is AWS's fully managed, petabyte-scale data warehouse service designed for online analytical processing (OLAP) and business intelligence (BI) applications. Let's analyze each option:
Correct Answers:
A. Supporting data APIs to access data with traditional, containerized, and event-driven applications - ✅ CORRECT
- Amazon Redshift supports Data APIs that enable access to data from various application types including traditional, containerized, and serverless applications
- This is particularly useful for migrating on-premises applications that need to access data warehouse functionality
C. Building analytics workloads during specified hours and when the application is not active - ✅ CORRECT
- Amazon Redshift supports scheduled scaling and pause/resume capabilities
- You can schedule Redshift clusters to run during specific hours (e.g., business hours) and pause them during off-hours to save costs
- This is ideal for batch analytics workloads that don't need to run 24/7
F. Creating a secondary replica of the cluster by using the AWS Management Console - ✅ CORRECT
- Amazon Redshift supports creating secondary clusters for disaster recovery and read scaling
- This can be done through the AWS Management Console, AWS CLI, or SDKs
- Secondary clusters provide cross-region or cross-AZ replication capabilities
Incorrect Answers:
B. Supporting client-side and server-side encryption - ❌ INCORRECT
- While Amazon Redshift does support encryption at rest and in transit, this is a security feature rather than a primary use case
- Encryption capabilities are common across many AWS services and not unique to Redshift's core analytics functionality
D. Caching data to reduce the pressure on the backend database - ❌ INCORRECT
- This describes Amazon ElastiCache (Redis/Memcached) or Amazon DynamoDB Accelerator (DAX), not Amazon Redshift
- Redshift is a data warehouse for analytics, not a caching layer
E. Scaling globally to support petabytes of data and tens of millions of requests per minute - ❌ INCORRECT
- While Redshift can scale to petabytes of data, it's not designed for "tens of millions of requests per minute"
- This scale of transactional requests is better suited for Amazon DynamoDB or Aurora
- Redshift is optimized for complex analytical queries on large datasets, not high-volume transactional workloads
Key Takeaways
- Amazon Redshift is best suited for analytical workloads, data warehousing, and business intelligence
- It supports scheduled operations (pause/resume) for cost optimization
- Data APIs enable integration with various application architectures
- Secondary clusters provide disaster recovery and read scaling capabilities
- Redshift is not designed for caching or extremely high-volume transactional workloads
Comments
Loading comments...