Learn the best approach for a SysOps administrator to automatically scale an Amazon Aurora MySQL DB cluster to handle increased read traffic from a new web application.
Table of Contents
Question
A company is preparing for a marketing campaign that will increase traffic to a new web application. The application uses Amazon API Gateway and AWS Lambda for the application logic. The application stores relevant user data in an Amazon Aurora MySQL DB cluster that has one Aurora Replica. Database queries for the application are 5% write and 95% read.
What should a SysOps administrator do to scale the database when traffic increases?
A. Configure Aurora Auto Scaling to add or remove Aurora Replicas in the cluster based on the average CPU utilization of the Aurora Replicas.
B. Configure Aurora Auto Scaling to increase or decrease the size of the Aurora Replicas based on the average CPU utilization of the Aurora Replicas.
C. Configure AWS Auto Scaling to monitor the Aurora cluster. Configure AWS Auto Scaling to add or remove Aurora Replicas in the cluster based on the average CPU utilization of the primary instance.
D. Configure AWS Auto Scaling to monitor the Aurora cluster. Configure AWS Auto Scaling to add or remove Aurora Replicas in the cluster based on the average CPU utilization of the existing Aurora Replica.
Answer
A. Configure Aurora Auto Scaling to add or remove Aurora Replicas in the cluster based on the average CPU utilization of the Aurora Replicas.
Explanation
Here’s why:
The web application is read-heavy, with 95% of the database queries being reads. To handle increased read traffic, the best approach is to scale out the number of Aurora Replicas. More Replicas will allow the read traffic to be distributed across multiple instances.
Aurora Auto Scaling can be configured to automatically adjust the number of Aurora Replicas based on the average CPU utilization of the Replicas. As CPU usage increases due to higher read traffic, Auto Scaling will add more Replicas to the cluster. Conversely, it will remove Replicas when CPU usage decreases. This provides automatic scaling to match demand.
The other options are incorrect:
B is wrong because Aurora Auto Scaling cannot change the instance size of Replicas. It can only add or remove Replicas.
C and D mention using AWS Auto Scaling to monitor the cluster and add/remove Replicas. However, AWS Auto Scaling is used for scaling EC2 instances. For Aurora, you need to use Aurora Auto Scaling specifically. Additionally, scaling should be based on the CPU of the Replicas handling the read traffic, not the primary instance, making D incorrect.
In summary, using Aurora Auto Scaling to dynamically adjust the number of Aurora Replicas based on CPU usage is the optimal way to scale the Aurora MySQL cluster for the read-heavy workload in this scenario. This approach will automatically accommodate traffic fluctuations while minimizing costs.
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