DBS-C01 Practice Exam 58 — 20 Questions

Question 1

A retail company uses Amazon Aurora MySQL for its order processing system. The database must support high write throughput and automatic scaling of storage. The company wants to ensure that the cluster can tolerate the loss of an entire Availability Zone without data loss and with minimal downtime. Which configuration should a database specialist implement?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Deploy an Aurora MySQL cluster with a primary instance and at least one Aurora Replica in a different Availability Zone.. Aurora MySQL automatically replicates data across three Availability Zones and supports automatic failover to an Aurora Replica. Placing at least one Aurora Replica in a different Availability Zone from the primary ensures that an AZ failure triggers failover to the replica with minimal downtime and no data loss, meeting the high availability requirement.

Answer

Deploy an Aurora MySQL cluster with a primary instance and enable Aurora Global Database.

Answer

Deploy an Aurora MySQL cluster with a primary instance and enable Multi-AZ deployment on the primary instance.

Answer

Deploy a single Aurora MySQL instance in one Availability Zone with automated backups enabled.

Question 2

A media company runs an Amazon Neptune cluster to store relationships between users, content, and viewing history. The team needs to run complex graph traversals that follow edges in both directions and return all paths up to five hops. They want to use a query language that is natively supported by Neptune and optimized for property graph traversal. Which query language should they use?

Accepted Answer

Gremlin. Amazon Neptune natively supports Gremlin for property graphs and SPARQL for RDF graphs. The scenario explicitly describes a property graph with users, content, and viewing history, and requires bidirectional multi-hop traversal. Gremlin's traversal steps are purpose-built for this pattern, making it the correct choice. SPARQL targets RDF, Cypher is not Neptune's primary traversal language, and GraphQL is an API layer, not a graph query language.

Answer

SPARQL

Answer

GraphQL

Answer

Cypher

Question 3

A company is using Amazon RDS for MySQL and notices that the Read IOPS metric is consistently high during business hours. The application is read-heavy. Which configuration change would most likely reduce Read IOPS?

Accepted Answer

Create one or more read replicas and redirect read traffic to them.. Creating read replicas offloads read queries from the primary DB instance to replica instances, directly reducing the number of read I/O operations on the primary. Since the application is read-heavy and Read IOPS is high during business hours, distributing read traffic to replicas alleviates the I/O bottleneck on the primary instance without requiring a larger instance or storage changes.

Answer

Add a Multi-AZ standby instance.

Answer

Increase the DB instance size to a larger instance type.

Answer

Enable storage Auto Scaling on the RDS instance.

Question 4

A company is using Amazon RDS for Oracle with Transparent Data Encryption (TDE) enabled. They need to rotate the TDE master key. What is the correct procedure?

Accepted Answer

Use the AWS KMS RotateKey operation to rotate the customer master key (CMK) that is used for TDE.. In Amazon RDS for Oracle with TDE, the master key is stored in AWS KMS. To rotate the TDE master key, you can call the AWS KMS RotateKey operation on the customer master key (CMK) used for TDE, or use the Amazon RDS procedure rds.rds_rotate_tde_key. Option B is correct. Option A is incorrect because Oracle's ALTER SYSTEM SET ENCRYPTION KEY command rotates the Oracle-internal master key, not the KMS CMK, and RDS does not support direct Oracle TDE key rotation. Option C is incorrect because full migration is unnecessary. Option D is incorrect because modifying the DB instance to use a new KMS key changes the key, but does not rotate the existing TDE key.

Answer

Use Oracle's ALTER SYSTEM SET ENCRYPTION KEY command to rotate the key.

Answer

Create a new encrypted RDS instance and migrate the data.

Answer

Modify the DB instance to use a new KMS key.

Question 5

A company is deploying a new Amazon Aurora PostgreSQL cluster for a production workload. The security team requires that all data at rest and all data in transit be encrypted, and that the cluster be isolated from the public internet. The application servers run in private subnets of the same VPC. Which combination of actions should be taken to meet these requirements?

Accepted Answer

Enable encryption at rest when creating the cluster, set the parameter rds.force_ssl to 1, and place the cluster in private subnets with a security group that allows only the application security group.. Aurora encryption at rest must be enabled at cluster creation, and the rds.force_ssl parameter enforces TLS for all client connections, covering data in transit. Network isolation is achieved by deploying the cluster in private subnets and restricting the security group to the application security group. IAM authentication, ACM certificates, and ssl_min_protocol_version alone do not satisfy the combined encryption and isolation requirements.

Answer

Create the cluster without encryption, then use AWS Certificate Manager to enable TLS, and place the cluster in private subnets.

Answer

Enable encryption at rest when creating the cluster, set the parameter ssl_min_protocol_version to TLSv1.2, and place the cluster in a public subnet with a network ACL that blocks all traffic.

Answer

Enable encryption at rest when creating the cluster, use IAM database authentication, and place the cluster in public subnets with a restrictive security group.

Question 6

A media company stores video metadata in an Amazon DynamoDB table with a partition key of videoId (string) and a sort key of uploadTimestamp (number). The table has a provisioned read capacity of 1000 RCU and write capacity of 1000 WCU, and is used by an application that performs many queries per second for the most recent videos uploaded by a specific user. The application team reports that queries for a single user's recent videos are fast, but queries that retrieve the latest videos across all users are slow and consume a lot of capacity. Which design change should a database specialist recommend to improve the performance of the cross-user query?

Accepted Answer

Create a global secondary index (GSI) with a partition key of uploadDate (string, e.g., '2023-10-05') and a sort key of uploadTimestamp, and query that index.. The cross-user query is inefficient because it must scan all partitions. A global secondary index with a partition key based on date and a sort key on uploadTimestamp allows the query to target only the relevant date partitions and retrieve results in order. This reduces the amount of data read and consumed capacity, improving performance.

Answer

Change the table's partition key to a composite of videoId and uploadTimestamp to better distribute the data.

Answer

Increase the provisioned read capacity of the table to 5000 RCU to handle the additional load.

Answer

Enable DynamoDB Streams and use AWS Lambda to maintain a separate table containing the latest videos across all users.

Question 7

A company is designing a new Amazon Neptune graph database to model relationships between users, products, and purchases for a recommendation engine. The workload requires high throughput for read queries and frequent updates to user behavior. The company needs to choose appropriate instance types and configurations. Which TWO actions should they take to optimize performance? (Choose two.)

Accepted Answer

Enable Neptune's read replicas to distribute read queries across multiple instances.. To optimize Neptune performance for a read-heavy graph workload, the primary considerations are memory and read scaling. Using a memory-optimized instance type ensures the graph fits in memory, enabling fast traversals. Adding read replicas distributes read queries, increasing throughput and reducing load on the primary instance. These two actions directly address the performance requirements.

Answer

Enable automatic backups to improve write performance.

Answer

Configure Neptune to use a single-AZ deployment to reduce network latency.

Answer

Use Neptune's bulk loader to import data continuously for real-time updates.

Question 8

A company has an Amazon DynamoDB table with on-demand capacity mode. The table experiences a sudden spike in traffic, and the application starts receiving ProvisionedThroughputExceededException errors. What is the most likely cause?

Accepted Answer

The traffic spike exceeded the previous peak traffic by more than double in a short period. DynamoDB on-demand mode automatically scales to accommodate traffic, but it does so based on the table's previous peak traffic — it can instantly handle up to double the previous peak. If traffic spikes more than 2x the prior peak within roughly 30 minutes, the table can throttle and return ProvisionedThroughputExceededException until it scales further. This is the documented behavior of on-demand capacity and the most likely cause here.

Answer

The provisioned read capacity units are insufficient

Answer

The table has reached the maximum number of read capacity units

Answer

Auto Scaling is not configured to increase capacity

Question 9

A developer is configuring an RDS for PostgreSQL instance for a new application. The application requires automatic failover to a standby instance in a different Availability Zone. Which deployment option should be selected?

Accepted Answer

Deploy a Multi-AZ instance.. Multi-AZ deployment for RDS PostgreSQL automatically provisions and maintains a synchronous standby replica in a different Availability Zone. In the event of a failure or Availability Zone outage, Amazon RDS automatically fails over to the standby, providing high availability without manual intervention. This meets the requirement for automatic failover to a standby instance in a different AZ.

Answer

Deploy a Single-AZ instance with a read replica.

Answer

Deploy a Single-AZ instance and take frequent snapshots.

Answer

Deploy a Single-AZ instance with a cross-region read replica.

Question 10

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. The database is 500 GB in size and has a 24-hour maintenance window. Which AWS service or tool should be used for the initial data transfer with minimal downtime?

Accepted Answer

AWS Database Migration Service (DMS). AWS Database Migration Service (DMS) is the correct choice because it supports ongoing replication from a source MySQL database to Amazon RDS for MySQL, allowing you to perform a full load followed by continuous change data capture (CDC) to minimize downtime. With a 500 GB database and a 24-hour maintenance window, DMS can complete the initial load and then keep the target in sync until you cut over, achieving near-zero downtime.

Answer

Amazon S3 with AWS Glue

Answer

AWS Snowball Edge

Answer

mysqldump and restore to RDS

Question 11

A retail company runs an order-processing application on AWS. The application writes each order to an Amazon DynamoDB table and must retrieve orders by order ID with single-digit millisecond latency. The table currently uses order ID as the partition key and has no sort key. The company wants to add the ability to query all orders for a specific customer without scanning the entire table. Which design change should a database specialist recommend?

Accepted Answer

Create a global secondary index with customer ID as the partition key and order ID as the sort key. To query orders by customer without scanning, you need an index whose partition key is customer ID. A global secondary index supports a different partition key from the base table and can be added at any time. The base table continues to serve order ID lookups. Local secondary indexes and sort key changes are not viable because they require the same partition key or table recreation.

Answer

Enable DynamoDB Streams on the table and process the stream with an AWS Lambda function

Answer

Add a sort key to the existing table using customer ID

Answer

Create a local secondary index with customer ID as the sort key

Question 12

A healthcare company needs to store patient records in a database that must be highly durable and available across multiple Availability Zones. The database must support complex joins and transactions, and the company wants to use a managed service to reduce operational burden. The data is highly sensitive and must be encrypted at rest and in transit. Which AWS service should the company use?

Accepted Answer

Amazon RDS for PostgreSQL with Multi-AZ. Amazon RDS for PostgreSQL with Multi-AZ is the correct choice because it is a fully managed relational database that supports complex joins and transactions, provides high durability and availability across multiple Availability Zones, and offers encryption at rest and in transit, meeting the healthcare company's requirements.

Answer

Amazon S3 with bucket encryption

Answer

Amazon ElastiCache for Memcached

Answer

Amazon DynamoDB with global tables

Question 13

A media company is building a real-time recommendation engine. The workload consists of millions of small, independent read and write operations per second, each accessing a single item by its unique identifier. Latency must remain under 10 milliseconds at the 99th percentile, and the data model is a simple key-value structure with no complex joins or transactions. The company wants a fully managed AWS database that scales horizontally without manual sharding. Which database design choice BEST meets these requirements?

Accepted Answer

Use Amazon DynamoDB with a partition key that distributes writes evenly and on-demand capacity mode.. The workload demands a horizontally scalable, fully managed key-value store with consistent single-digit millisecond latency for millions of independent operations. DynamoDB is purpose-built for this pattern, and an evenly distributed partition key avoids hot partitions while on-demand mode handles unpredictable traffic. Relational and analytical engines lack the write scalability and latency characteristics required here.

Answer

Use Amazon Redshift with a distribution key on the unique identifier and concurrency scaling enabled.

Answer

Use Amazon Aurora MySQL with a single writer instance and read replicas in multiple Availability Zones.

Answer

Use Amazon RDS for PostgreSQL with a Multi-AZ deployment and Provisioned IOPS storage.

Question 14

A healthcare company is building a new patient records system on AWS. The system must store structured data with complex relationships, support ACID transactions, and scale read traffic independently from write traffic as the patient base grows. The database must also provide a managed experience with automated backups and point-in-time recovery. Which AWS database solution should the company choose?

Accepted Answer

Amazon RDS for MySQL with Multi-AZ deployment and read replicas. The scenario requires a managed relational database that supports complex relationships, ACID transactions, and independent read scaling. Amazon RDS for MySQL fits because it is a relational database service that supports Multi-AZ for high availability and read replicas to scale read traffic. It also provides automated backups and point-in-time recovery. Other options are either non-relational, in-memory, or object storage, which do not meet the transactional and relational requirements.

Answer

Amazon DynamoDB with global secondary indexes

Answer

Amazon ElastiCache for Redis with cluster mode enabled

Answer

Amazon S3 with S3 Glacier Deep Archive for storage

Question 15

A company is designing a database for an IoT application that ingests time-series data from millions of sensors. The data is used for real-time monitoring and historical analysis. The company needs a solution that can handle high write throughput, store data efficiently, and support time-based queries. Which TWO AWS services are MOST appropriate for this use case? (Choose two.)

Accepted Answer

Amazon Timestream. The scenario requires handling high write throughput, efficient storage, and time-based queries for IoT data. Amazon Timestream is purpose-built for time-series data, offering scalability and built-in time-series functions. Amazon S3 with Glue and Athena provides a scalable data lake solution for historical analysis. Together, they cover real-time and historical needs. Other options lack the specialized time-series capabilities or are not cost-effective for long-term storage.

Answer

Amazon RDS for PostgreSQL with TimescaleDB extension

Answer

Amazon ElastiCache for Redis with streams

Answer

Amazon DynamoDB with TTL

Question 16

A media company stores user-uploaded video metadata in an Amazon DynamoDB table. The table has a partition key of videoId (string) and no sort key. The company needs to efficiently query all videos uploaded by a specific user within a given date range, without scanning the entire table. The dataset is expected to grow to several terabytes with millions of users. Which design change should a database specialist implement to meet these requirements with the LEAST operational overhead?

Accepted Answer

Create a global secondary index (GSI) with partition key userId and sort key uploadDate.. The access pattern requires querying by userId and a date range. A global secondary index with userId as partition key and uploadDate as sort key enables efficient Query operations across all partitions. It avoids full table scans and does not require custom replication code. The other options either fail to support the access pattern, require disruptive table redesign, or add unnecessary operational overhead.

Answer

Add a sort key of uploadDate to the existing table and change the partition key to userId.

Answer

Create a local secondary index (LSI) with partition key videoId and sort key uploadDate.

Answer

Enable DynamoDB Streams and use AWS Lambda to replicate data into a new table keyed by userId.

Question 17

A company is designing a new Amazon Aurora MySQL database for a high-traffic e-commerce application. The application requires low-latency reads and writes, and the database must scale horizontally for read traffic. The company wants to minimize operational overhead and ensure high availability. Which TWO design choices should the company make? (Choose two.)

Accepted Answer

Deploy the Aurora cluster with a writer instance and multiple reader instances in different Availability Zones.. Deploying a writer with multiple readers across Availability Zones provides high availability and read scaling, while Aurora Auto Scaling dynamically adjusts the number of readers based on demand. Together, these choices minimize operational overhead and ensure low-latency reads and writes. Other options either misuse Aurora features, attempt invalid write distribution, or propose an inappropriate primary data store.

Answer

Use Aurora Global Database to replicate the cluster to a second AWS Region for read scaling.

Answer

Use Amazon ElastiCache for Redis as the primary data store for the application.

Answer

Configure the application to write directly to a reader instance to distribute write load.

Question 18

A financial analytics firm stores trade data in an Amazon Redshift cluster. Analysts frequently run complex queries that join a large fact table with several dimension tables and aggregate billions of rows. The queries currently take hours because data is redistributed across nodes during joins. The fact table is 10 TB and grows by 1 TB per month. The most common join key is the customer_id column, which is used in nearly every query. Which design change will MOST improve query performance?

Accepted Answer

Set the distribution style of the fact table to KEY on customer_id and ensure dimension tables are set to ALL.. The primary performance issue is data redistribution during joins. Distributing the fact table by the common join key, customer_id, colocates matching rows on the same node, eliminating network traffic. Setting small dimension tables to ALL replicates them everywhere, avoiding broadcast. Together, these changes dramatically reduce join time for the described workload.

Answer

Set the distribution style of the fact table to EVEN and add a sort key on customer_id.

Answer

Convert the fact table to a materialized view and refresh it every hour.

Answer

Enable concurrency scaling on the Redshift cluster to add more clusters for read queries.

Question 19

A media analytics company ingests time-series sensor readings into Amazon Timestream. The data arrives with occasional delays of up to 48 hours due to intermittent network connectivity at remote sites. Queries must always return results that reflect the latest ingested data, including late-arriving records. Which Timestream configuration should the company use to ensure late-arriving data is correctly incorporated into query results?

Accepted Answer

Configure the table with a magnetic store writes setting enabled so that records older than the memory store retention can be ingested.. Timestream separates storage into a memory store for recent data and a magnetic store for long-term data. By default, writes that target time windows older than the memory store retention are rejected. Enabling magnetic store writes on the table allows records with older timestamps to be ingested and stored in the correct time partitions, so late-arriving sensor readings are still queryable alongside on-time data.

Answer

Set the memory store retention to 48 hours and the magnetic store retention to 365 days.

Answer

Create a scheduled query that runs every hour and re-ingests the previous 48 hours of data into a new table.

Answer

Increase the memory store retention to 7 days and disable the magnetic store entirely.

Question 20

A retail company needs a managed graph database to model product recommendations, where relationships between customers, products, and purchases are queried with multi-hop traversals. The team has no existing graph expertise and wants a fully managed AWS service with openCypher and Gremlin support. Which AWS service should they choose?

Accepted Answer

Amazon Neptune. Amazon Neptune is purpose-built for graph workloads and natively supports openCypher, Gremlin, and SPARQL. It handles multi-hop traversals efficiently, is fully managed, and removes the need for the team to build graph traversal logic or manage servers, which directly satisfies the recommendation engine scenario and the language requirements.

Answer

Amazon DocumentDB with $graphLookup aggregation

Answer

Amazon Aurora PostgreSQL with the pgRouting extension

Answer

Amazon DynamoDB with adjacency list modeling