DBS-C01 Workload-Specific Database Design Practice Test 7 — 15 Questions

Question 1

A company is running a production Amazon DynamoDB table that supports a gaming application with millions of concurrent users. The table uses on-demand capacity mode. Recently, the application started experiencing throttling (ProvisionedThroughputExceededException) during peak hours. The company wants to resolve this with minimal operational overhead. What should the company do?

Accepted Answer

Request a service quota increase for the on-demand table's maximum throughput. On-demand capacity mode in DynamoDB has a default throughput quota (typically 40,000 read/write request units per second per table, though this can vary by region and account). When traffic exceeds this soft limit, DynamoDB returns ProvisionedThroughputExceededException. Requesting a service quota increase raises this ceiling, allowing the table to handle higher bursts without throttling, and requires no architectural changes or capacity management—minimizing operational overhead.

Answer

Enable DynamoDB Accelerator (DAX) to cache reads

Answer

Partition the table across multiple tables and use application-level sharding

Answer

Switch to provisioned capacity mode with auto scaling

Question 2

A company is using Amazon DynamoDB to store session data for a web application. The session data expires after 24 hours. Which DynamoDB feature should the company use to automatically delete expired items?

Accepted Answer

DynamoDB Time to Live (TTL). DynamoDB Time to Live (TTL) is the correct choice because it provides a cost-effective, fully managed mechanism to automatically delete expired items based on a timestamp attribute in the table. TTL works by comparing the current time to the epoch time value stored in the designated TTL attribute; when the value is in the past, DynamoDB marks the item for deletion, typically within 48 hours. This eliminates the need for custom code or additional AWS services, directly addressing the requirement to remove session data after 24 hours.

Answer

A retention policy on the DynamoDB table

Answer

DynamoDB Streams

Answer

A scheduled AWS Lambda function that scans and deletes expired items

Question 3

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database is used for a financial application that requires complex joins and transactions. Which migration strategy is MOST appropriate?

Accepted Answer

Use AWS SCT to convert the schema and AWS DMS to migrate data. Option C is correct because AWS Schema Conversion Tool (SCT) is required to convert the Oracle schema (including complex joins and transaction logic) to a PostgreSQL-compatible format, and AWS Database Migration Service (DMS) performs the ongoing data migration with minimal downtime. This combination handles both schema transformation and data replication for heterogeneous migrations, which is essential for a financial application with complex joins and transactions.

Answer

Use AWS DMS with native Oracle to PostgreSQL endpoint

Answer

Use Oracle GoldenGate to replicate data to Aurora PostgreSQL

Answer

Use pg_dump to export the Oracle database and restore to Aurora PostgreSQL

Question 4

A company is running a production Amazon RDS for MySQL database that is experiencing performance degradation. Amazon CloudWatch metrics show high CPU utilization and high number of connections. The company has already optimized queries and implemented connection pooling. What is the MOST cost-effective solution to address the high CPU utilization?

Accepted Answer

Scale up to a larger DB instance class. Option D is correct because scaling up to a larger DB instance class directly increases the compute capacity (vCPUs and memory) available to the database, which addresses the root cause of high CPU utilization. Since queries are already optimized and connection pooling is in place, the remaining bottleneck is the instance's processing power, making a vertical scale-up the most cost-effective solution to handle the sustained CPU load without introducing additional architectural complexity.

Answer

Add Read Replicas to offload read traffic

Answer

Change the storage type to Provisioned IOPS (io1)

Answer

Enable RDS Proxy to reduce database connections

Question 5

Which TWO of the following are benefits of using Amazon DynamoDB Accelerator (DAX)? (Choose 2.)

Accepted Answer

Reduces read latency to microseconds for cached items. Option C is correct because Amazon DynamoDB Accelerator (DAX) is an in-memory cache that delivers up to 10x read performance improvement, reducing read latency to microseconds for cached items. It sits between your application and DynamoDB, intercepting read requests and serving them from its cluster's memory, which avoids the millisecond-level latency of reading from DynamoDB's SSD storage.

Answer

Improves write throughput by caching write operations

Answer

Reduces storage costs by compressing data

Answer

Automatically scales write capacity based on demand

Question 6

Which THREE of the following are best practices for designing a DynamoDB table for a gaming leaderboard that updates scores frequently and supports queries for top players? (Choose 3.)

Accepted Answer

Use a Global Secondary Index with score as the sort key to query top scores efficiently. Option C is correct because a Global Secondary Index (GSI) with score as the sort key allows efficient range queries (e.g., Query with ScanIndexForward=false) to retrieve top players without scanning the entire table. This leverages DynamoDB's key-value and sorted-index capabilities to minimize read throughput and latency, which is critical for frequently updated leaderboards.

Answer

Scan the entire table and sort to get top scores

Answer

Use strongly consistent reads for the leaderboard queries

Answer

Use a single partition key for all players to easily query top scores

Question 7

Which TWO use cases are best suited for Amazon RDS Multi-AZ deployments? (Choose 2.)

Accepted Answer

Ensuring database availability during an Availability Zone outage. Option E is correct because Amazon RDS Multi-AZ deployments automatically provision and maintain a synchronous standby replica in a different Availability Zone (AZ). If the primary DB instance fails or the AZ becomes unavailable, Amazon RDS automatically fails over to the standby replica, ensuring database availability with minimal downtime. This is the primary purpose of Multi-AZ: high availability and automatic failover, not performance scaling.

Answer

Offloading read traffic from the primary database

Answer

Disaster recovery across AWS Regions

Answer

Improving write performance for a write-intensive workload

Answer

Scaling read capacity for a read-heavy application

Question 8

The application uses the IAM role to access the 'orders' DynamoDB table. What is the intended effect of this policy?

Accepted Answer

The role can only access items where the partition key matches the principal's identifier. The policy uses a condition key like `dynamodb:LeadingKeys` with a value referencing the principal's identifier (e.g., `${aws:userid}`). This restricts access to only those items in the 'orders' table whose partition key matches the IAM role's unique identifier, enforcing row-level security. The intended effect is fine-grained access control, not full table access or time-based restrictions.

Answer

The role can perform any DynamoDB action on the 'orders' table

Answer

The role can access all items in the table but only during specific times

Answer

The role is denied access to the 'orders' table

Question 9

Based on the CLI output, what is true about this RDS instance?

Accepted Answer

The instance is a Read Replica of another RDS instance. The CLI output shows `ReplicaLag` with a value of `0`, which is a field that only appears when the RDS instance is configured as a Read Replica. A Read Replica maintains asynchronous replication from a source DB instance, and the lag metric indicates how far behind the replica is. Since the output includes this field, the instance must be a Read Replica.

Answer

The instance runs Amazon Aurora PostgreSQL

Answer

The instance is a Multi-AZ deployment

Answer

The instance uses Provisioned IOPS (io1) storage

Question 10

What is the purpose of the 'TimeToLiveSpecification' in this template?

Accepted Answer

It enables DynamoDB to automatically delete items after the specified timestamp. The 'TimeToLiveSpecification' in an AWS DynamoDB CloudFormation template enables DynamoDB's Time to Live (TTL) feature, which automatically deletes items when the current time exceeds the epoch timestamp value stored in the specified attribute (e.g., 'expire_time'). This is a cost-effective way to manage data retention without requiring custom delete logic or additional write capacity.

Answer

It enforces that the 'expire_time' attribute must be unique

Answer

It automatically updates the 'expire_time' attribute when an item is read

Answer

It creates a backup of items that have expired

Question 11

A financial services company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database has a high volume of write transactions and requires minimal downtime during migration. Which AWS service or feature should be used to replicate data continuously to the target RDS instance during the migration?

Accepted Answer

AWS Database Migration Service (AWS DMS) with ongoing replication. AWS Database Migration Service (AWS DMS) with ongoing replication (change data capture, CDC) is the correct choice because it continuously captures and applies changes from the source Oracle database to the target Amazon RDS for Oracle instance, enabling near-zero downtime during migration. This is achieved by using Oracle's redo logs to stream transactions in real time, which meets the high write volume and minimal downtime requirements.

Answer

Amazon RDS Read Replica

Answer

Amazon RDS Multi-AZ deployment

Answer

AWS Schema Conversion Tool (AWS SCT)

Question 12

A gaming company runs a leaderboard application on Amazon DynamoDB. The application experiences sudden spikes in read traffic during tournaments. The table uses on-demand capacity and the reads are eventually consistent. However, some users report stale data for several seconds. What is the most likely cause?

Accepted Answer

The application is using eventually consistent reads.. The correct answer is A because eventually consistent reads in DynamoDB can return stale data for up to one second under normal conditions, but during sudden spikes in read traffic, the replication lag can extend to several seconds. The application is using eventually consistent reads, which trade immediate consistency for higher throughput and lower latency, making stale data more likely during high-traffic periods like tournaments.

Answer

The table is using on-demand capacity instead of provisioned capacity.

Answer

The table has a global secondary index (GSI) that is not updated synchronously.

Answer

The read capacity units are insufficient for the traffic spikes.

Question 13

A healthcare company stores patient records in Amazon DynamoDB. Each record includes a 'patient_id' (partition key) and 'visit_date' (sort key). The company needs to run ad-hoc queries to find all patients seen by a specific doctor within a date range. Which design approach minimizes cost and latency for this query pattern?

Accepted Answer

Create a global secondary index (GSI) with doctor_id as partition key and visit_date as sort key.. Option C is correct because a Global Secondary Index (GSI) with doctor_id as the partition key and visit_date as the sort key allows efficient key-based queries for all patients seen by a specific doctor within a date range. This avoids full table scans and filter operations, minimizing both cost (read capacity units) and latency. DynamoDB can directly retrieve the indexed items without scanning the base table.

Answer

Query the base table using a filter expression on doctor_id.

Answer

Create a local secondary index (LSI) with doctor_id as sort key.

Answer

Use a Scan operation with a filter expression for doctor_id and visit_date.

Question 14

A company is designing a database for an IoT application that collects sensor data every second from millions of devices. The data is time-series and must be stored for 90 days, with occasional queries for recent data. Which AWS database solution is MOST cost-effective and performant?

Accepted Answer

Amazon Timestream. Amazon Timestream is purpose-built for time-series data, offering automatic storage tiering (in-memory for recent data and magnetic for historical data) and serverless scaling, which makes it the most cost-effective and performant choice for ingesting sensor data every second from millions of devices and retaining it for 90 days with occasional queries on recent data.

Answer

Amazon Redshift

Answer

Amazon DynamoDB with TTL to expire old data

Answer

Amazon RDS for MySQL with partitioning

Question 15

A company is using Amazon RDS for PostgreSQL for its transactional database. The application generates reports that query millions of rows, causing high CPU on the primary instance. The reports are not time-sensitive. What is the MOST cost-effective way to offload the reporting queries without affecting write performance?

Accepted Answer

Create an Amazon RDS Read Replica and direct reporting queries to the replica.. Creating an Amazon RDS Read Replica offloads reporting queries to a separate read-only instance, preventing CPU contention on the primary. Since the reports are not time-sensitive, the replica can handle the large queries without impacting write performance, and it is cost-effective because you only pay for the replica's compute and storage.

Answer

Use Amazon ElastiCache to cache report results.

Answer

Enable Multi-AZ to distribute reads to the standby instance.

Answer

Migrate reporting to Amazon Redshift.