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AWS DBS-C01 Free Practice Questions — Page 3

Database - Specialty • 5 questions • Answers & explanations included

Question 11

The Development team recently executed a database script containing several data definition language (DDL) and data manipulation language (DML) statements on an Amazon Aurora MySQL DB cluster. The release accidentally deleted thousands of rows from an important table and broke some application functionality. This was discovered 4 hours after the release. Upon investigation, a Database Specialist tracked the issue to a DELETE command in the script with an incorrect WHERE clause filtering the wrong set of rows. The Aurora DB cluster has Backtrack enabled with an 8-hour backtrack window. The Database Administrator also took a manual snapshot of the DB cluster before the release started. The database needs to be returned to the correct state as quickly as possible to resume full application functionality. Data loss must be minimal. How can the Database Specialist accomplish this?

A. Quickly rewind the DB cluster to a point in time before the release using Backtrack.
B. Perform a point-in-time recovery (PITR) of the DB cluster to a time before the release and copy the deleted rows from the restored database to the original database.
C. Restore the DB cluster using the manual backup snapshot created before the release and change the application configuration settings to point to the new DB cluster.
D. Create a clone of the DB cluster with Backtrack enabled. Rewind the cloned cluster to a point in time before the release. Copy deleted rows from the clone to the original database.
Show Answer & Explanation

Correct Answer: A. Quickly rewind the DB cluster to a point in time before the release using Backtrack.

Why A is correct: Aurora Backtrack allows you to quickly rewind the database to a specific point in time (within the 8-hour window) without restoring from backups. This is the fastest method with minimal data loss - you simply backtrack to before the DELETE statement (4 hours ago, well within the 8-hour window). Backtrack typically completes in minutes and doesn't require creating new clusters or copying data. Why other options are wrong: B: PITR works but requires restoration to a new cluster and manual data copying, taking much longer than Backtrack. C: Restoring from snapshot loses 4 hours of data (all changes since the snapshot) and requires application reconfiguration. D: Cloning and copying data is unnecessarily complex when Backtrack can directly rewind the cluster.

Question 12

A company is load testing its three-tier production web application deployed with an AWS CloudFormation template on AWS. The Application team is making changes to deploy additional Amazon EC2 and AWS Lambda resources to expand the load testing capacity. A Database Specialist wants to ensure that the changes made by the Application team will not change the Amazon RDS database resources already deployed. Which combination of steps would allow the Database Specialist to accomplish this? (Choose two.)

A. Review the stack drift before modifying the template.
B. Create and review a change set before applying it.
C. Export the database resources as stack outputs.
D. Define the database resources in a nested stack.
E. Set a stack policy for the database resources.
Show Answer & Explanation

Correct Answers: B. Create and review a change set before applying it.; E. Set a stack policy for the database resources.

Why B and E are correct: B (Change sets): CloudFormation change sets allow you to preview changes before applying them, showing exactly what resources will be modified, added, or deleted. E (Stack policy): Stack policies explicitly protect specific resources from being updated or deleted during stack updates. You can set a policy to prevent changes to RDS resources. Why other options are wrong: A: Stack drift detects unmanaged changes, not changes from template updates. C: Stack outputs export values but don't prevent resource changes. D: Nested stacks organize resources but don't prevent modifications during updates.

Question 13

A manufacturing company's website uses an Amazon Aurora PostgreSQL DB cluster. Which configurations will result in the LEAST application downtime during a failover? (Choose three.)

A. Use the provided read and write Aurora endpoints to establish a connection to the Aurora DB cluster.
B. Create an Amazon CloudWatch alert triggering a restore in another Availability Zone when the primary Aurora DB cluster is unreachable.
C. Edit and enable Aurora DB cluster cache management in parameter groups.
D. Set TCP keepalive parameters to a high value.
E. Set JDBC connection string timeout variables to a low value.
F. Set Java DNS caching timeouts to a high value.
Show Answer & Explanation

Correct Answers: A. Use the provided read and write Aurora endpoints to establish a connection to the Aurora DB cluster.; C. Edit and enable Aurora DB cluster cache management in parameter groups.; E. Set JDBC connection string timeout variables to a low value.

Why A, C, E are correct: A (Use Aurora endpoints): The cluster endpoint automatically points to the current primary, and reader endpoint load-balances across replicas. Applications don't need to track individual instance endpoints. C (Cache management): Aurora DB cache management helps warm up the cache on replicas, reducing recovery time during failover. E (Low JDBC timeout): Lower connection timeouts cause applications to fail fast and retry with new connections to the new primary more quickly. Why other options are wrong: B: CloudWatch alerts for manual restoration is not automatic failover and increases downtime. D: High TCP keepalive increases the time to detect failed connections, increasing downtime. F: High Java DNS caching prevents applications from recognizing the new primary's IP address after failover (similar to Question 3).

Question 14

A company is hosting critical business data in an Amazon Redshift cluster. Due to the sensitive nature of the data, the cluster is encrypted at rest using AWS KMS. As a part of disaster recovery requirements, the company needs to copy the Amazon Redshift snapshots to another Region. Which steps should be taken in the AWS Management Console to meet the disaster recovery requirements?

A. Create a new KMS customer master key in the source Region. Switch to the destination Region, enable Amazon Redshift cross-Region snapshots, and use the KMS key of the source Region.
B. Create a new IAM role with access to the KMS key. Enable Amazon Redshift cross-Region replication using the new IAM role, and use the KMS key of the source Region.
C. Enable Amazon Redshift cross-Region snapshots in the source Region, and create a snapshot copy grant and use a KMS key in the destination Region.
D. Create a new KMS customer master key in the destination Region and create a new IAM role with access to the new KMS key. Enable Amazon Redshift cross-Region replication in the source Region and use the KMS key of the destination Region.
Show Answer & Explanation

Correct Answer: C. Enable Amazon Redshift cross-Region snapshots in the source Region, and create a snapshot copy grant and use a KMS key in the destination Region.

Why C is correct: For cross-Region snapshot copying with encrypted Redshift clusters, you must enable cross-Region snapshots in the source Region, create a snapshot copy grant in the destination Region, and specify a KMS key in the destination Region. The snapshot copy grant authorizes Redshift to use the destination Region's KMS key to encrypt the copied snapshots. Why other options are wrong: A: You need a KMS key in the destination Region, not the source Region's key (KMS keys are Region-specific). B: Cross-Region replication isn't the correct term; it's cross-Region snapshot copying. IAM roles alone don't solve the KMS encryption issue. D: Close, but the snapshot copy grant is the critical component that's missing from this option.

Question 15

A company has a production Amazon Aurora Db cluster that serves both online transaction processing (OLTP) transactions and compute-intensive reports. The reports run for 10% of the total cluster uptime while the OLTP transactions run all the time. The company has benchmarked its workload and determined that a six-node Aurora DB cluster is appropriate for the peak workload. The company is now looking at cutting costs for this DB cluster, but needs to have a sufficient number of nodes in the cluster to support the workload at different times. The workload has not changed since the previous benchmarking exercise. How can a Database Specialist address these requirements with minimal user involvement?

A. Split up the DB cluster into two different clusters: one for OLTP and the other for reporting. Monitor and set up replication between the two clusters to keep data consistent.
B. Review all evaluate the peak combined workload. Ensure that utilization of the DB cluster node is at an acceptable level. Adjust the number of instances, if necessary.
C. Use the stop cluster functionality to stop all the nodes of the DB cluster during times of minimal workload. The cluster can be restarted again depending on the workload at the time.
D. Set up automatic scaling on the DB cluster. This will allow the number of reader nodes to adjust automatically to the reporting workload, when needed.
Show Answer & Explanation

Correct Answer: D. Set up automatic scaling on the DB cluster. This will allow the number of reader nodes to adjust automatically to the reporting workload, when needed.

Why D is correct: Aurora Auto Scaling automatically adjusts the number of Aurora Replicas based on metrics like CPU utilization or connections. Since reports run only 10% of the time, Auto Scaling will add reader nodes during reporting periods and scale down during OLTP-only periods, optimizing costs without manual intervention. Why other options are wrong: A: Splitting into two clusters creates significant complexity with replication management and doesn't address the variable workload cost issue. B: This requires manual monitoring and adjustment, which doesn't meet the "minimal user involvement" requirement. C: Stop cluster functionality stops all nodes and doesn't support the OLTP transactions that run all the time.

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