DBS-C01 Practice Exam 57 — 20 Questions

Question 1

A company runs a production Amazon RDS for MySQL Multi-AZ DB instance. The database experiences a failover event. After the failover, the application team reports increased latency for write operations. Which action should be taken to investigate the issue?

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

Accepted Answer

Verify that the application is using the correct DB endpoint and that DNS has propagated.. After a Multi-AZ failover, the DNS record for the DB instance changes to point to the new primary. If the application caches the old IP address or has a long DNS TTL, it may still attempt to connect to the old primary (now a standby), causing write operations to be redirected or to fail, resulting in increased latency. Verifying the endpoint and DNS propagation ensures the application is connecting to the correct instance.

Answer

Increase the allocated storage for the DB instance to reduce I/O contention.

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Enable automated backups and configure a backup window.

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Modify the DB instance to a larger instance class to improve write performance.

Question 2

A company needs to store and query a graph of relationships between users for a recommendation engine. The queries involve traversing multiple edges. Which AWS database service is most suitable?

Accepted Answer

Amazon Neptune. Amazon Neptune is a fully managed graph database service purpose-built for storing and traversing highly connected data. It supports both property graph (Gremlin, openCypher) and RDF (SPARQL) models, making it ideal for recommendation engines that require multi-edge traversals across user relationships.

Answer

Amazon DynamoDB with adjacency list design

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Amazon DocumentDB (with MongoDB compatibility)

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Amazon RDS for PostgreSQL with recursive CTEs

Question 3

A company is building a content management system that stores articles, images, and user comments. Articles are text-heavy and need full-text search. Images are binary files. Comments are relational with user IDs. Which TWO AWS services should be combined to best support this workload?

Accepted Answer

Amazon OpenSearch Service for full-text search. Amazon OpenSearch Service (C) is correct because it is purpose-built for full-text search and analytics, providing inverted indexes, relevance scoring, and analyzers that make it the right fit for the text-heavy article search requirement. Amazon S3 (E) is correct because it is designed for durable, scalable object storage of binary files such as images, and it integrates well with content delivery and retrieval patterns for a CMS. Together they cover the two specialized needs: search over article text and storage of image binaries. Amazon ElastiCache for Redis (A) is only a caching layer and does not provide durable primary storage or full-text search. Amazon DynamoDB (B) is a key-value/document store that lacks native full-text search capabilities for article text. Amazon RDS for MySQL (D) is relational and could store comments, but it is not optimized for full-text search at scale nor for binary image storage, so it is not the best combination for this workload.

Answer

Amazon ElastiCache for Redis for caching

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Amazon DynamoDB for articles and comments

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Amazon RDS for MySQL for articles and comments

Question 4

Which TWO of the following are valid considerations when migrating an on-premises Oracle database to Amazon RDS for Oracle using AWS DMS? (Select TWO.)

Accepted Answer

DMS can continue to replicate changes after the full load is complete until the cutover.. Options B and E are correct because AWS DMS supports change data capture (CDC): after the initial full load completes, DMS reads the source Oracle redo/archive logs and applies ongoing changes to the RDS for Oracle target, which is exactly what option B describes, and this ongoing replication is what allows a low-downtime cutover as stated in option E. Both behaviors are core DMS capabilities for Oracle-to-RDS for Oracle migrations, using the Oracle LogMiner or Binary Reader method for CDC. Option A is wrong because DMS does not perform schema or PL/SQL code conversion; stored procedures, packages, and triggers must be handled separately with tools such as AWS SCT. Option C is wrong because DMS does not restructure partitioned tables into non-partitioned tables; it moves data, and any such schema transformation would be a manual or SCT task. Option D is wrong because RDS Custom for Oracle requires specific configuration, including the custom engine version, IAM instance profile, and VPC settings, so a migration cannot proceed with no configuration changes.

Answer

DMS automatically converts Oracle stored procedures to RDS for Oracle compatible code.

Answer

DMS automatically converts partitioned tables to non-partitioned tables.

Answer

DMS can migrate directly to Amazon RDS Custom for Oracle without any configuration changes.

Question 5

A company uses Amazon DynamoDB to store session data for a web application. The table has a partition key of 'SessionId'. The company wants to automatically expire sessions after 1 hour. Which feature should be used?

Accepted Answer

DynamoDB Time to Live (TTL). DynamoDB Time to Live (TTL) is the correct choice because it allows you to define a per-item timestamp attribute (e.g., 'expireAt') that automatically deletes items after a specified duration—in this case, 1 hour. TTL operates at no additional cost, requires no custom code, and handles expiration asynchronously in the background, making it ideal for session data management.

Answer

DynamoDB Global Tables

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AWS Lambda function that scans the table every hour and deletes old items.

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DynamoDB Streams

Question 6

An Amazon RDS for Oracle instance is experiencing high swap usage. Which metric should be monitored to determine if the instance is memory-constrained?

Accepted Answer

SwapUsage. SwapUsage measures the amount of swap space used by the RDS instance. High swap usage indicates that the instance is memory-constrained because the operating system is paging memory to disk, which severely degrades performance. Monitoring SwapUsage directly identifies memory pressure.

Answer

CPUUtilization

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WriteIOPS

Answer

FreeableMemory

Question 7

A database specialist is trying to connect to an Amazon RDS for MySQL instance from an EC2 instance but receives a 'Connection timed out' error. The security group for the RDS instance allows inbound traffic on port 3306 from the security group of the EC2 instance. What should the specialist check next?

Accepted Answer

Check the network ACL associated with the subnet of the RDS instance to ensure it allows inbound traffic on port 3306 and outbound traffic on ephemeral ports.. The 'Connection timed out' error suggests the packet is being dropped at the network layer, likely by a network ACL. Since the security group allows inbound on port 3306, the next step is to check the network ACL associated with the RDS instance's subnet. Network ACLs are stateless, so they must allow both inbound traffic on port 3306 and outbound traffic on ephemeral ports for the response. Option B is incorrect because a timed out error occurs before the TCP handshake completes, so DNS resolution is not the issue. Option C is incorrect because an internet gateway and public route are irrelevant if both instances are in the same VPC or connected privately. Option D is incorrect because the security group for the EC2 instance can be stateful and typically allows outbound traffic by default; the timeout is not caused by missing outbound rules on the EC2 side.

Answer

Check that the RDS instance has a public DNS name and the EC2 instance can resolve it.

Answer

Ensure that the VPC has an internet gateway attached and the route table has a route to it.

Answer

Verify that the security group for the EC2 instance allows outbound traffic on port 3306.

Question 8

A company is running an Amazon RDS for Oracle database in Multi-AZ. The primary instance fails over unexpectedly. The DBA wants to determine the cause of the failover. What should the DBA do?

Accepted Answer

View the RDS events in the AWS Management Console.. RDS events in the AWS Management Console (or via the describe-events API) capture Multi-AZ failover events, including the reason and timestamp, such as 'Multi-AZ failover started' or 'DB instance restarted.' This is the authoritative source for determining why a failover occurred, because RDS logs the failover trigger (e.g., primary instance failure, storage issue, or manual reboot) as an event. Reviewing these events gives the DBA the exact cause without needing to dig into OS-level metrics or database logs.

Answer

Review the Enhanced Monitoring metrics for the primary instance.

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Query the database error logs for the failover time.

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Check AWS CloudTrail for any database-related API calls.

Question 9

A company uses Amazon Redshift for data warehousing. They run a daily ETL job that loads data into the cluster. Recently, the job started failing with 'Disk Full' errors. The cluster has 5 RA3 nodes. Which step should be taken to resolve the issue?

Accepted Answer

Resize the cluster to a larger node type or add more nodes. Resize the cluster to a larger node type or add more nodes. RA3 nodes use managed storage with a local cache, and a 'Disk Full' error typically indicates that the local cache or the overall storage limit for the cluster is exhausted. Resizing adds more local cache and increases the total managed storage capacity, resolving the disk full error. Option A is incorrect because disabling concurrency scaling does not free up disk space; it only affects query concurrency. Option B is incorrect because VACUUM reclaims space from deleted rows, but it requires temporary disk space; if the disk is already full, VACUUM may fail or not help. Option D is incorrect because Redshift Spectrum allows querying data directly from S3 without loading it into Redshift, but it does not resolve a disk full error on the Redshift cluster itself.

Answer

Disable concurrency scaling to free up resources

Answer

Run a VACUUM command to reclaim space from deleted rows

Answer

Enable Redshift Spectrum to offload queries to S3

Question 10

A company has an Amazon RDS for PostgreSQL DB instance with automated backups enabled. The retention period is set to 7 days. A developer accidentally performed a DROP TABLE operation on a critical table 2 days ago. How can the table be recovered with minimal data loss?

Accepted Answer

Perform a point-in-time restore to a time just before the DROP TABLE operation.. RDS automated backups with a 7-day retention enable point-in-time restore (PITR) to any second within that window using continuous transaction log archiving. Since the DROP TABLE occurred 2 days ago, restoring to a time just before the statement replays the database to that exact moment, recovering the table with minimal data loss. The restored instance is a new DB instance, and the table can then be exported and re-imported into the original.

Answer

Use the pg_dump utility to create a manual backup and restore it.

Answer

Create a read replica of the DB instance and promote it to a standalone instance.

Answer

Restore the DB instance from the oldest automated snapshot.

Question 11

A company runs an Amazon Redshift cluster with 8 dc2.large nodes for its data warehouse. The data engineering team loads data daily using COPY commands from S3. Recently, the load times have increased significantly. The cluster's CloudWatch metric 'CPUUtilization' is high during the load. The administrator runs the STL_LOAD_ERRORS table and finds no errors. The SVL_S3LOG shows that the COPY command is scanning many small files. The data in S3 is stored as 10,000 small CSV files (each ~100 KB). Which action will MOST improve the COPY performance?

Accepted Answer

Consolidate the small files into fewer, larger files (e.g., 100 files of 10 MB each). Amazon Redshift COPY performance is heavily influenced by the number and size of files in S3. Loading from many small files (10,000 files of ~100 KB) causes excessive overhead because each file is processed individually, leading to high CPU utilization and slow loads. Consolidating into fewer, larger files (e.g., 100 files of 10 MB each) allows Redshift to parallelize the load more efficiently across slices, dramatically improving performance.

Answer

Use the MANIFEST option to specify the files explicitly

Answer

Use the JSON format instead of CSV to reduce parsing overhead

Answer

Change the table's distribution style to ALL to avoid data redistribution

Question 12

Which TWO AWS services can be used to migrate an on-premises SQL Server database to Amazon RDS for SQL Server?

Accepted Answer

AWS DMS. AWS DMS (B) is correct because it is a managed migration service that supports SQL Server as a source and Amazon RDS for SQL Server as a target, using change data capture for minimal-downtime migrations. Native SQL Server backup to S3 and restore to RDS (C) is also correct because RDS for SQL Server natively supports restoring native .bak backups uploaded to Amazon S3, which is a documented migration path. AWS DataSync (A) is for moving files between storage systems, not for database-level migration to RDS. AWS Storage Gateway (D) provides hybrid storage access (file, volume, tape) and does not migrate SQL Server databases into RDS. AWS DynamoDB (E) is a NoSQL database service and cannot serve as a target for SQL Server migration.

Answer

AWS DataSync

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AWS Storage Gateway

Answer

AWS DynamoDB

Question 13

A company is deploying a new web application using Amazon RDS for PostgreSQL. The application requires read-heavy workloads and automatic failover. Which configuration should be used?

Accepted Answer

Multi-AZ deployment with one or more Read Replicas. A Multi-AZ deployment provides automatic failover to a standby instance in a different Availability Zone, ensuring high availability. Adding one or more Read Replicas offloads read-heavy workloads from the primary instance, improving performance. This combination meets both the read-heavy and automatic failover requirements for the application.

Answer

Multi-AZ deployment without Read Replicas

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Single-AZ with a Read Replica in the same region

Answer

Multiple Read Replicas in different regions

Question 14

A company uses Amazon DynamoDB for a session management system. They need to store session data with a TTL of 24 hours. However, they notice that expired items are not being deleted promptly, causing storage costs to increase. What is the most likely cause?

Accepted Answer

DynamoDB typically deletes expired items within 48 hours. DynamoDB's TTL mechanism typically deletes expired items within 48 hours, not immediately. The service processes TTL deletions as a background process, and while items are marked as expired at the TTL time, actual deletion can be delayed up to 48 hours. This explains why expired session data persists and increases storage costs despite TTL being properly configured.

Answer

The table has insufficient write capacity

Answer

TTL is not enabled on the table

Answer

The TTL attribute is set as a string instead of a number

Question 15

A company uses Amazon ElastiCache for Redis and needs to encrypt data in transit between the application and the cache cluster. Which feature should be enabled?

Accepted Answer

Enable encryption in transit on the replication group.. Amazon ElastiCache for Redis supports encryption in transit using TLS (Transport Layer Security) when enabled on the replication group. This ensures data is encrypted between the application and the cache cluster. Option B is incorrect because encryption at rest protects data stored on disk, not data in transit. Option C is incorrect because AWS KMS customer master keys are used for encryption at rest, not for transit encryption. Option D is incorrect because VPC security groups control network access at the IP/port level, not encryption; allowing HTTPS traffic does not enable encryption for ElastiCache communication.

Answer

Enable encryption at rest.

Answer

Use AWS KMS customer master keys.

Answer

Configure the VPC security group to allow only HTTPS traffic.

Question 16

A company uses Amazon DynamoDB to store session data for a web application. The application is experiencing occasional throttling (ProvisionedThroughputExceededException) during peak hours. The DynamoDB table has on-demand capacity mode. Which combination of steps should be taken to resolve the issue?

Accepted Answer

Review the partition key design and consider using a write sharding pattern to distribute traffic evenly.. Even with on-demand capacity, DynamoDB applies a per-partition throughput limit (3,000 RCU or 1,000 WCU). Throttling occurs when traffic is unevenly distributed across partitions due to a suboptimal partition key. Reviewing the partition key and applying a write sharding pattern (e.g., adding a random suffix) distributes writes evenly, preventing throttling. Option B (DAX) only reduces read load and does not fix write throttling. Option C (auto scaling) is for provisioned mode, not on-demand. Option D (switching to provisioned) does not resolve uneven partition access; proper key design is still needed.

Answer

Enable DynamoDB Accelerator (DAX) to cache the frequently accessed items.

Answer

Enable auto scaling for the table and set minimum and maximum capacity.

Answer

Switch to provisioned capacity and increase the read and write capacity units.

Question 17

A company needs to migrate a 10 TB SQL Server database from on-premises to Amazon RDS for SQL Server with minimal downtime. The database is heavily used with frequent write operations. Which migration strategy should be used?

Accepted Answer

Use AWS DMS with ongoing replication from the on-premises database to RDS until cutover.. AWS DMS with ongoing replication (change data capture) allows a full load of the 10 TB database followed by continuous replication of write operations from the on-premises SQL Server to Amazon RDS for SQL Server. This minimizes downtime by keeping the target database synchronized until the cutover window, where only a brief pause is needed to apply final changes and switch traffic.

Answer

Use native SQL Server backup and restore to Amazon S3, then restore to RDS.

Answer

Export the database to CSV files, upload to S3, and use the COPY command in RDS.

Answer

Use AWS Schema Conversion Tool (SCT) to convert the schema, then use AWS DMS for full load.

Question 18

A gaming company uses Amazon DynamoDB to store player state. The table has a partition key of playerId and no sort key. The company wants to implement a leaderboard that shows the top 100 players by score. The scores are updated frequently, and the leaderboard must be updated in near real-time. Which design should a database specialist recommend to efficiently retrieve the top 100 players?

Accepted Answer

Create a global secondary index (GSI) with a partition key of leaderboardType (constant value) and a sort key of score, and query the index in descending order with a limit of 100.. A GSI with a constant partition key and score as the sort key allows the application to query the index in descending order and retrieve the top 100 players with a single, efficient query. This design scales with the table and provides near real-time results without scanning or additional processing.

Answer

Use a DynamoDB scan operation with a filter on score and sort the results in the application.

Answer

Create a local secondary index (LSI) with a sort key of score and query it in descending order.

Answer

Use DynamoDB Streams to trigger a Lambda function that writes the top 100 scores to a separate table, and query that table.

Question 19

A media company uses Amazon DynamoDB to store metadata for millions of video assets. The table has a partition key of 'AssetId' and a sort key of 'Version'. The application frequently queries for all versions of a specific asset, and also performs range queries on 'Version' for a given 'AssetId'. The table is currently provisioned with 1000 RCUs and 1000 WCUs, but the company wants to optimize costs by using on-demand capacity mode. However, they are concerned about the impact on query performance and cost predictability. Which statement is correct regarding switching to on-demand capacity mode?

Accepted Answer

On-demand capacity mode provides the same query performance as provisioned mode, but it may lead to higher costs for steady workloads and offers less control over throughput limits.. On-demand capacity mode supports all DynamoDB query operations, including range queries on the sort key, and provides the same performance as provisioned mode. However, it may be costlier for steady workloads and offers less control over throughput. The company should evaluate their traffic patterns to decide if on-demand is cost-effective.

Answer

Switching to on-demand capacity mode requires recreating the table, which would lose all data and require application downtime.

Answer

On-demand capacity mode automatically scales to handle traffic, but it may be more expensive for predictable workloads and does not support range queries on the sort key.

Answer

On-demand capacity mode is only available for tables with a partition key and no sort key, so the existing table cannot use it.

Question 20

A company is designing a new Amazon DynamoDB table to store order data for an e-commerce application. The table will have a partition key of orderId and a sort key of orderDate. The application needs to support efficient queries for orders by customer, orders by status, and orders within a date range for a specific customer. Which two additional design elements should a database specialist implement to meet these query requirements? (Choose two.)

Accepted Answer

Create a global secondary index (GSI) with a partition key of status and a sort key of orderDate.. To support queries by customer and by status, two GSIs are needed: one with customerId as partition key and orderDate as sort key, and another with status as partition key and orderDate as sort key. These indexes allow efficient, sorted retrieval of orders for each access pattern without scanning the base table.

Answer

Use a scan operation with a filter expression on customerId and status, and sort the results in the application.

Answer

Enable DynamoDB Streams and use AWS Lambda to maintain a separate table for orders by customer and status.

Answer

Create a local secondary index (LSI) with a sort key of customerId.