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Question 829 - SAA-C03 discussion

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An ecommerce company runs Its application on AWS. The application uses an Amazon Aurora PostgreSQL cluster in Multi-AZ mode for the underlying database. During a recent promotional campaign, the application experienced heavy read load and write load. Users experienced timeout issues when they attempted to access the application.

A solutions architect needs to make the application architecture more scalable and highly available.

Which solution will meet these requirements with the LEAST downtime?

A.
Create an Amazon EventBndge rule that has the Aurora cluster as a source. Create an AWS Lambda function to log the state change events of the Aurora cluster. Add the Lambda function as a target for the EventBndge rule Add additional reader nodes to fail over to.
Answers
A.
Create an Amazon EventBndge rule that has the Aurora cluster as a source. Create an AWS Lambda function to log the state change events of the Aurora cluster. Add the Lambda function as a target for the EventBndge rule Add additional reader nodes to fail over to.
B.
Modify the Aurora cluster and activate the zero-downtime restart (ZDR) feature. Use Database Activity Streams on the cluster to track the cluster status.
Answers
B.
Modify the Aurora cluster and activate the zero-downtime restart (ZDR) feature. Use Database Activity Streams on the cluster to track the cluster status.
C.
Add additional reader instances to the Aurora cluster Create an Amazon RDS Proxy target group for the Aurora cluster.
Answers
C.
Add additional reader instances to the Aurora cluster Create an Amazon RDS Proxy target group for the Aurora cluster.
D.
Create an Amazon ElastiCache for Redis cache. Replicate data from the Aurora cluster to Redis by using AWS Database Migration Service (AWS DMS) with a write-around approach.
Answers
D.
Create an Amazon ElastiCache for Redis cache. Replicate data from the Aurora cluster to Redis by using AWS Database Migration Service (AWS DMS) with a write-around approach.
Suggested answer: C

Explanation:

This solution directly addresses the scalability and high availability requirements with minimal downtime.

Additional Reader Instances: Adding more reader instances to the Aurora cluster will distribute the read load, improving the performance of the application under heavy read traffic. Aurora reader instances automatically replicate the data from the writer instance, enabling you to scale out read operations.

Amazon RDS Proxy: RDS Proxy improves database availability by managing database connections more efficiently and providing a connection pool. This reduces the overhead on the Aurora cluster during peak loads, further enhancing performance and availability without requiring changes to the application code.

Why Not Other Options?:

Option A (EventBridge and Lambda): This doesn't directly address the performance and availability issues. Logging state changes and adding reader nodes on failure events doesn't provide proactive scalability.

Option B (Zero-Downtime Restart and Activity Streams): Zero-Downtime Restart (ZDR) is useful for minimizing downtime during maintenance but doesn't directly improve scalability. Database Activity Streams are more for security monitoring than for performance enhancement.

Option D (ElastiCache for Redis): While adding a caching layer can help with read performance, it introduces complexity and may not be necessary if additional reader instances can handle the load.

AWS

Reference:

Amazon Aurora Scaling - Information on scaling Aurora clusters with reader instances.

Amazon RDS Proxy - Details on how RDS Proxy can improve database performance and availability.

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asked 16/09/2024
Prashant Bari
46 questions
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