DBS-C01 Practice Test 11 — 15 Questions

Question 1

A company needs to audit access to an Amazon DynamoDB table. The audit should capture which IAM user or role performed each action. Which AWS service should be used?

Accepted Answer

AWS CloudTrail. AWS CloudTrail is the correct service because it records API calls made to DynamoDB and captures the IAM user or role that performed each action. VPC Flow Logs (Option A) capture network traffic metadata, not API calls. Amazon GuardDuty (Option C) is a threat detection service that monitors for malicious activity, not API auditing. AWS Config (Option D) tracks resource configuration changes, not API call details.

Answer

VPC Flow Logs

Answer

Amazon GuardDuty

Answer

AWS Config

Question 2

Refer to the exhibit. A developer wants to connect to the database. Which database engine is most likely being used?

Accepted Answer

MySQL. The exhibit shows a connection string using the format `jdbc:mysql://...`, which is the standard JDBC URL prefix for MySQL databases. This indicates the developer is connecting to a MySQL database engine, as Oracle, SQL Server, and PostgreSQL use different JDBC URL prefixes (`jdbc:oracle:thin:`, `jdbc:sqlserver://`, and `jdbc:postgresql://` respectively).

Answer

Oracle

Answer

SQL Server

Answer

PostgreSQL

Question 3

A company is migrating a 1 TB PostgreSQL database from on-premises to Amazon RDS for PostgreSQL. The migration must have minimal downtime. Which TWO steps should be taken to achieve this?

Accepted Answer

Configure AWS DMS with ongoing replication from the source to the target.. Option A is correct because AWS Database Migration Service (DMS) supports ongoing replication (change data capture) from an on-premises PostgreSQL source to an RDS for PostgreSQL target, allowing the bulk load to complete and then continuously applying changes so the cutover downtime is only the short final catch-up. Option C is correct because the pglogical extension provides logical replication between PostgreSQL instances, including from on-premises to RDS for PostgreSQL, so the initial data copy plus continuous streaming of changes keeps the target nearly in sync with minimal downtime. Option B is not appropriate because AWS Schema Conversion Tool is used to convert schemas between different database engines (for example, to Aurora), but this migration is PostgreSQL-to-PostgreSQL, so no engine conversion is needed. Option D would cause significant downtime because a pg_dump taken at cutover and imported into RDS requires the source to be offline for the entire dump and load of a 1 TB database. Option E is not possible because RDS Read Replicas can only be created from an existing RDS or Aurora source, not from an on-premises PostgreSQL database.

Answer

Use AWS SCT to convert the schema to Amazon Aurora.

Answer

Take a full backup using pg_dump and import it into RDS during a maintenance window.

Answer

Create an RDS Read Replica of the on-premises database.

Question 4

A company runs an Amazon ElastiCache for Redis cluster as a caching layer for a high-traffic web application. The cluster has one primary and two replica nodes. Recently, the application experienced increased latency. Monitoring shows that the CPU utilization of the primary node is consistently above 80%, while replicas are below 40%. The application uses the cluster mode disabled. The operations team needs to reduce the CPU load on the primary node. Which solution should they implement?

Accepted Answer

Configure the application to use read replicas for read queries by using the reader endpoint.. In an ElastiCache for Redis cluster with cluster mode disabled, the primary node handles all writes and reads by default. To reduce CPU load on the primary, the application should be configured to direct read queries to the replica nodes using the reader endpoint. This offloads read traffic from the primary, lowering its CPU utilization.

Answer

Implement a read-through cache pattern using DynamoDB Accelerator (DAX).

Answer

Upgrade the primary node to a larger instance type.

Answer

Add more replica nodes to the cluster.

Question 5

A security team needs to audit all SQL statements executed against an Amazon Aurora MySQL DB cluster. Which combination of actions should be taken to achieve this? (Choose TWO.)

Accepted Answer

Set the server_audit_logging parameter to 1 in the DB cluster parameter group.. Options D and E are correct. To audit SQL statements in an Aurora MySQL DB cluster, you need to enable the Aurora MySQL audit plugin. This is done by setting the `server_audit_logging` parameter to 1 in the DB cluster parameter group (option D). Then you can configure the DB cluster to publish the audit logs to Amazon CloudWatch Logs (option E) for centralized monitoring and analysis. Option A is incorrect because AWS CloudTrail captures API calls, not SQL statements. Option B is incorrect because Enhanced Monitoring captures OS-level metrics, not SQL queries. Option C is incorrect because RDS event subscriptions notify about events like DB instance changes, not SQL execution.

Answer

Enable AWS CloudTrail for the Aurora DB cluster.

Answer

Enable Enhanced Monitoring for the DB cluster.

Answer

Enable RDS event subscription for the DB cluster.

Question 6

A company is deploying a new application that uses Amazon RDS for MySQL. The database must be highly available with automatic failover. Which deployment configuration meets these requirements?

Accepted Answer

Multi-AZ deployment with a standby replica in a different Availability Zone. A Multi-AZ deployment for Amazon RDS for MySQL automatically provisions and maintains a synchronous standby replica in a different Availability Zone. In the event of a failure, Amazon RDS automatically fails over to the standby, providing high availability without manual intervention. This configuration meets the requirement for automatic failover and high availability within a single AWS region.

Answer

Single-AZ with a Read Replica in the same region

Answer

Multi-AZ deployment with synchronous replication to a cross-region replica

Answer

Single-AZ with automated backups

Question 7

A company is using Amazon DynamoDB with on-demand capacity mode. The company notices that during a flash sale, the write requests are throttled. What is the most likely cause of the throttling?

Accepted Answer

A hot partition is causing throttling even though the table uses on-demand capacity.. Even in on-demand capacity mode, DynamoDB partitions data by partition key, and a single partition has a hard throughput ceiling (roughly 1,000 WCUs and 3,000 RCUs per partition). During a flash sale, if writes concentrate on one partition key (a hot partition), that partition throttles regardless of the table's on-demand capacity. On-demand mode scales table-level capacity but cannot split a single hot partition instantly.

Answer

The table has reached its maximum throughput limit for on-demand mode.

Answer

The table is not configured for auto scaling.

Answer

The provisioned write capacity units (WCUs) are set too low.

Question 8

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. They used AWS SCT to convert the schema, but some stored procedures failed to convert automatically. What is the best course of action?

Accepted Answer

Manually rewrite the unconverted stored procedures to PostgreSQL-compatible code based on SCT's assessment report.. AWS SCT provides an assessment report that identifies unconverted stored procedures and suggests manual rewrites. Since Oracle and PostgreSQL have fundamentally different procedural languages (PL/SQL vs. PL/pgSQL), automated conversion cannot handle all syntax and semantic differences. Manually rewriting the unconverted procedures based on SCT's report ensures compatibility and correctness, as SCT highlights the specific lines and constructs that need attention.

Answer

Use AWS Lambda to automatically convert the stored procedures.

Answer

Use AWS DMS to replicate the Oracle stored procedures as-is to Aurora.

Answer

Switch to Amazon RDS for Oracle to avoid conversion issues.

Question 9

A company runs an OLTP workload on an RDS for MySQL instance. The database has a table with 50 million rows. The application frequently runs queries that join this table with a small lookup table (1000 rows) using a foreign key. The queries are slow. Which design change would most improve performance?

Accepted Answer

Add an index on the foreign key column in the large table.. The query joins a large table (50M rows) with a small lookup table (1000 rows) on a foreign key column. Without an index on the foreign key column in the large table, MySQL must perform a full table scan for each join, leading to slow performance. Adding an index on that column allows MySQL to use an index lookup (e.g., B-tree) to quickly locate matching rows, dramatically reducing query time.

Answer

Partition the large table by the foreign key column.

Answer

Scale up the RDS instance to a larger size.

Answer

Create a read replica and direct all read queries to it.

Question 10

A company uses Amazon Redshift for data warehousing. They run a query that joins a large fact table (10 billion rows) with a small dimension table (1 million rows). The query is slow. The distribution style of the fact table is AUTO, and the dimension table has DISTSTYLE ALL. The join key is user_id. What is the MOST likely reason for the poor performance?

Accepted Answer

The fact table's distribution key is not user_id, causing redistribution. When the fact table uses DISTSTYLE AUTO, Redshift may choose a distribution key that is not user_id. When the fact table is distributed on a different key, joining on user_id requires Redshift to redistribute the fact table rows across nodes to match the dimension table's distribution, causing significant network traffic and slower performance. The dimension table with DISTSTYLE ALL is already replicated to all nodes, so the bottleneck is the fact table's distribution mismatch.

Answer

The dimension table does not have a sort key on user_id

Answer

The dimension table uses DISTSTYLE ALL, which is inefficient for joins

Answer

The fact table should have column compression disabled for the join key

Question 11

A company is designing a social media application that requires storing user relationships (follows) and making graph queries like 'mutual friends.' Which database is most suitable?

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service optimized for storing and querying highly connected data. It supports both property graph and RDF models, and it uses Gremlin or SPARQL to efficiently traverse relationships like 'mutual friends' in a social media application, making it the ideal choice for graph queries.

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Answer

Amazon RDS for MySQL

Question 12

A company is running a MongoDB-compatible Amazon DocumentDB cluster with one writer and two readers. The application writes a large amount of data during batch processing, and after a batch completes, the writer's CPU is high, and the readers have significant replica lag. The team wants to reduce replica lag without affecting the batch performance. What should they do?

Accepted Answer

Increase the instance size of the readers to improve apply throughput. Replica lag in Amazon DocumentDB occurs when readers are unable to apply writes from the writer's oplog quickly enough. Increasing the instance size of the readers provides more CPU and memory resources, improving their apply throughput and reducing lag without affecting the writer's batch performance. Option A is incorrect because changing the storage type to Provisioned IOPS may improve I/O but does not directly address the reader's apply capacity. Option C is incorrect because reducing batch size would lower the write rate and degrade batch performance, which the team wants to avoid. Option D is incorrect because increasing the writer's instance size may help the writer handle more writes, but it does not help readers apply those writes faster; it could even increase the write rate and worsen replica lag.

Answer

Change the storage type to Provisioned IOPS on all instances

Answer

Reduce the batch size to lower the write rate

Answer

Increase the instance size of the writer to handle the batch faster

Question 13

A company is running a MySQL database on Amazon RDS and needs to store JSON documents that are frequently queried by fields within the JSON. The company wants to reduce development complexity and improve query performance. Which RDS MySQL feature should the database specialist recommend?

Accepted Answer

Use the JSON data type in MySQL 8.0 and utilize JSON path expressions in queries. MySQL 8.0's native JSON data type stores JSON documents in an optimized binary format, enabling efficient indexing and querying via JSON path expressions (e.g., `JSON_EXTRACT`, `->`, `->>`). This reduces development complexity by allowing direct SQL access to JSON fields without application-level parsing, and improves query performance through generated columns and virtual indexes.

Answer

Migrate the JSON data to Amazon DynamoDB and use DynamoDB's document model

Answer

Store JSON documents in a VARCHAR(MAX) column and use LIKE operations for queries

Answer

Store JSON documents as BLOBs and parse them in application code

Question 14

A company wants to centrally manage database user credentials and rotate them automatically. The database is an Amazon RDS for MySQL instance. Which AWS service should be used?

Accepted Answer

AWS Secrets Manager. AWS Secrets Manager is designed to store, retrieve, and automatically rotate database credentials. It natively supports Amazon RDS for MySQL with built-in rotation via Lambda, so it is the correct service for centrally managing and rotating RDS credentials. This minimizes custom code and integrates with IAM for access control.

Answer

AWS CloudHSM

Answer

AWS Identity and Access Management (IAM)

Answer

AWS Systems Manager Parameter Store

Question 15

A company is deploying a new application that requires low-latency reads from a relational database across multiple AWS Regions. The application is read-heavy and can tolerate eventual consistency. Which deployment option meets these requirements?

Accepted Answer

Deploy Amazon Aurora Global Database with a primary Region and read replicas in secondary Regions.. Amazon Aurora Global Database is designed for low-latency global reads and disaster recovery, allowing up to five secondary Regions with dedicated read replicas that replicate data with a typical latency of under one second. This meets the requirement for low-latency reads across multiple Regions while tolerating eventual consistency, as reads from secondary Regions are eventually consistent with the primary.

Answer

Deploy Amazon RDS for PostgreSQL with Multi-AZ and read replicas in the same Region.

Answer

Deploy a single Amazon RDS for MySQL instance with cross-Region read replicas.

Answer

Deploy Amazon DynamoDB Global Tables in multiple Regions.