DBS-C01 Practice Test 14 — 15 Questions

Question 1

Refer to the exhibit. An application team notices that the MySQL RDS instance 'mydb' is running at 80% CPU utilization during peak hours. They need to improve read performance without increasing the CPU load on the primary instance. Which action should they take?

Accepted Answer

Create a Read Replica in the same region. Creating a Read Replica offloads read traffic from the primary MySQL RDS instance, reducing CPU load on the primary while improving read performance for applications. Read Replicas asynchronously replicate data using MySQL’s native binlog-based replication, allowing the primary to focus on write operations without additional CPU overhead from serving reads.

Answer

Increase the DB instance class to db.r5.xlarge

Answer

Change storage type to io1 with higher IOPS

Answer

Enable Multi-AZ deployment

Question 2

A company is building a real-time chat application using Amazon DynamoDB. Each message has a conversation ID, timestamp, sender, and content. The primary access pattern is to retrieve the most recent 50 messages for a given conversation, ordered by timestamp. Which table design minimizes cost and latency?

Accepted Answer

Use conversation ID as partition key and timestamp as sort key; query with ScanIndexForward=false and Limit=50.. Option C is correct because using conversation ID as the partition key and timestamp as the sort key allows a single Query operation with ScanIndexForward=false to retrieve items in reverse chronological order, and Limit=50 ensures only the most recent 50 messages are returned. This design minimizes cost by avoiding full table scans or additional indexes, and minimizes latency by leveraging DynamoDB's native sort key ordering without needing external caching or streams.

Answer

Use a composite primary key of conversation ID and message ID, and enable DynamoDB Streams to process messages.

Answer

Use DynamoDB Accelerator (DAX) to cache the most recent messages.

Answer

Use conversation ID as partition key and a GSI on timestamp.

Question 3

A company uses Amazon DynamoDB as the primary database for a global gaming application. The application requires single-digit millisecond latency for user profile lookups by user ID. However, some queries need to retrieve all active users in a region (e.g., 'us-east-1') for administrative dashboards, and these queries currently perform full table scans, causing high costs and throttling. What design approach should be taken to optimize this?

Accepted Answer

Create a global secondary index (GSI) on the region attribute.. Option C is correct because creating a Global Secondary Index (GSI) on the 'region' attribute allows the administrative dashboard queries to retrieve all active users in a specific region using an efficient index scan instead of a full table scan. This reduces read capacity consumption, avoids throttling, and maintains single-digit millisecond latency for the indexed queries, while the base table remains optimized for user ID lookups.

Answer

Implement DynamoDB Accelerator (DAX) to cache the dashboard queries.

Answer

Increase the read capacity units (RCUs) on the base table.

Answer

Create a local secondary index (LSI) on the region attribute.

Question 4

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database is 1 TB and has complex stored procedures. The migration must be completed within a 4-hour downtime window. Which migration approach is most efficient?

Accepted Answer

Use AWS SCT to convert schema and code, then AWS DMS for data migration.. Option B is correct because AWS SCT converts the Oracle schema and complex stored procedures to Aurora PostgreSQL-compatible code, while AWS DMS performs the full data migration within the 4-hour window. This combination handles both schema/code conversion and bulk data transfer efficiently, meeting the time constraint.

Answer

Use AWS Schema Conversion Tool (SCT) to convert schema only.

Answer

Use Oracle Data Pump to export and pg_restore to import.

Answer

Use AWS DMS with ongoing replication.

Question 5

A company is migrating an on-premises MongoDB database to AWS. The application uses MongoDB's aggregation pipeline for real-time analytics. Which AWS database service is most compatible and provides the least application changes?

Accepted Answer

Amazon DocumentDB (with MongoDB compatibility).. Amazon DocumentDB is designed to be MongoDB-compatible, supporting the MongoDB aggregation pipeline with minimal changes. This allows the company to migrate the existing MongoDB database and continue using the same aggregation pipeline for real-time analytics without rewriting application code, making it the most compatible option.

Answer

Amazon ElastiCache for Redis with RedisJSON module.

Answer

Amazon DynamoDB with DynamoDB Streams and Lambda for aggregation.

Answer

Amazon Aurora with JSON data type.

Question 6

A company is using Amazon DynamoDB for a gaming leaderboard that updates frequently. They need to maintain a sorted list of top 100 players by score. Which THREE design patterns can achieve this efficiently?

Accepted Answer

Use a Global Secondary Index (GSI) with score as the sort key and query with ScanIndexForward=false and Limit=100.. Option A is correct because a Global Secondary Index (GSI) with score as the sort key allows you to query items in descending order using ScanIndexForward=false and limit the result to the top 100 players. This pattern efficiently retrieves the highest scores without scanning the entire table, leveraging DynamoDB's index query capabilities.

Answer

Use DynamoDB Accelerator (DAX) to cache query results.

Answer

Scan the entire table and sort the results in memory.

Question 7

A company is migrating a PostgreSQL database to Amazon Aurora PostgreSQL. The current database has complex queries that join multiple tables and performs well. After migration, the same queries are slower on Aurora. What is the most likely cause?

Accepted Answer

The DB instance class does not have enough memory for the buffer cache.. Option A is correct because after migrating to Aurora PostgreSQL, the same complex queries are slower, which often indicates that the buffer cache is too small to hold the working set of data. Aurora uses a distributed storage system where the buffer cache is managed by the DB instance's memory; if the instance class lacks sufficient memory, frequently accessed data pages must be read from storage more often, increasing I/O latency. This is a common performance bottleneck when migrating from on-premises PostgreSQL, where the buffer cache might have been larger or the working set fit entirely in memory.

Answer

Aurora PostgreSQL does not support complex joins; the queries must be rewritten.

Answer

Aurora PostgreSQL does not support indexes on joined columns.

Answer

The default DB parameter group is optimized for write-heavy workloads, not read-heavy.

Question 8

A company is designing a data lake on Amazon S3 with Amazon Redshift Spectrum for analytics. The data includes JSON logs from web servers. Which THREE design practices should the company follow to optimize query performance and cost?

Accepted Answer

Compress files using gzip or snappy.. Option A is correct because compressing JSON files with gzip or Snappy reduces the data size stored in S3, lowering storage costs and minimizing the amount of data that Redshift Spectrum must scan over the network. Redshift Spectrum can read compressed files directly, and compression often improves query performance by reducing I/O, even though it adds a small CPU overhead for decompression.

Answer

Use many small files to maximize parallelism.

Answer

Create indexes on the S3 data using AWS Glue.

Question 9

A company is running a MySQL database on an EC2 instance and wants to migrate to Amazon RDS for MySQL with minimal downtime. The database is 500 GB in size and has a high write workload. Which migration approach is most appropriate?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication.. AWS DMS with ongoing replication (change data capture) is the most appropriate approach because it allows you to migrate the 500 GB database with minimal downtime. DMS performs a full load of the existing data and then continuously replicates ongoing changes from the source MySQL EC2 instance to the target Amazon RDS for MySQL, enabling a cutover with only a brief pause in writes.

Answer

Export data to Amazon S3 and use AWS Glue to load into RDS.

Answer

Copy the MySQL data directory to Amazon EBS and attach to RDS.

Answer

Take a mysqldump from the source and import into RDS.

Question 10

A company has a critical application that uses Amazon RDS for MySQL with Multi-AZ deployment. During a recent failure, the automatic failover took 2 minutes, causing application timeout. The company needs to reduce failover time to under 30 seconds. Which solution should the database specialist recommend?

Accepted Answer

Migrate the database to Amazon Aurora MySQL.. Amazon Aurora MySQL is designed to reduce failover time significantly compared to standard RDS MySQL Multi-AZ. Aurora typically completes failover in under 30 seconds by using a shared distributed storage volume across multiple Availability Zones, allowing the primary instance to fail over to a read replica without the need to replay redo logs or perform crash recovery. This meets the requirement of reducing failover time to under 30 seconds.

Answer

Create a read replica and promote it during failover.

Answer

Increase the DB instance class to a larger size.

Answer

Implement Amazon RDS Proxy to handle connection draining.

Question 11

A security engineer created the IAM policy above for an application that reads from a DynamoDB table named UserSessions. The application reports that it cannot query the table using a Global Secondary Index (GSI). The table's GSI is named GSI_UserSessions. Why is the application unable to query the index?

Accepted Answer

The Query action is not allowed on the index because the Allow statement only applies to the table, not the index.. Option A is correct because the IAM policy's Allow statement grants the Query action on the DynamoDB table resource (arn:aws:dynamodb:...:table/UserSessions) but does not include the index resource (arn:aws:dynamodb:...:table/UserSessions/index/GSI_UserSessions). In DynamoDB, a Global Secondary Index is a separate subresource, and IAM policies must explicitly grant permissions on the index ARN to allow operations like Query on that index. Without this, the application cannot query the GSI.

Answer

The application is using GetItem instead of Query to access the index.

Answer

The policy allows Query on the table, which automatically includes the index.

Question 12

A company is migrating an on-premises MongoDB database to Amazon DocumentDB (with MongoDB compatibility). The application uses MongoDB's aggregation pipeline with $lookup and $unwind stages. What should the company verify before migration?

Accepted Answer

Check if all aggregation pipeline stages used by the application are supported in DocumentDB.. Option A is correct because Amazon DocumentDB (with MongoDB compatibility) does not support all MongoDB aggregation pipeline stages. Specifically, the `$lookup` and `$unwind` stages are supported, but other stages like `$merge`, `$facet`, `$bucket`, `$bucketAuto`, `$graphLookup`, and `$search` are not. Before migration, the company must verify that every stage used in their application's aggregation pipelines is fully supported in DocumentDB to avoid runtime failures.

Answer

Verify that DocumentDB supports sharding for the collection.

Answer

Ensure the application uses the latest MongoDB driver.

Answer

Confirm that the application's secondary indexes can be migrated.

Question 13

A company runs an e-commerce platform on Amazon RDS for PostgreSQL. During a flash sale, the database experiences high write load and read replicas lag significantly. The application uses read replicas for reporting queries. Which design change would most effectively reduce replica lag without compromising write performance?

Accepted Answer

Migrate to Amazon Aurora with read replicas.. Option C is correct because Amazon Aurora's distributed storage architecture decouples compute from storage, allowing replicas to apply redo logs with minimal overhead compared to RDS for PostgreSQL's physical replication. Aurora's replicas share the same underlying storage volume, so replica lag is significantly reduced even under heavy write loads, while write performance on the primary remains unaffected due to the asynchronous, log-based replication mechanism.

Answer

Increase the instance size of the primary database.

Answer

Add more read replicas to distribute the reporting load.

Answer

Convert the RDS instance to a Multi-AZ deployment.

Question 14

A company needs a database for a serverless web application that stores user sessions. The sessions expire after 24 hours. The database must be highly available and require no server management. Which AWS service is most appropriate?

Accepted Answer

Amazon DynamoDB with TTL.. Amazon DynamoDB with TTL is the most appropriate choice because it provides a fully managed, serverless, highly available NoSQL database that can automatically expire user sessions after 24 hours using the Time to Live (TTL) feature. DynamoDB's on-demand capacity mode eliminates server management, and its built-in replication across multiple Availability Zones ensures high availability without any manual intervention.

Answer

Amazon ElastiCache for Redis with cluster mode.

Answer

Amazon RDS for PostgreSQL with Multi-AZ.

Answer

Amazon S3 with lifecycle policies.

Question 15

Refer to the exhibit. A company uses this DynamoDB table to store user session data. The application frequently queries by user_id alone to get all sessions for a user. However, the query is slow. What is the most likely cause?

Accepted Answer

The table's partition key is session_id, not user_id, so querying by user_id requires a scan.. The table's primary key is session_id, not user_id. Querying by user_id without a secondary index forces DynamoDB to perform a full table scan, which reads every item and is significantly slower than a query operation. This is the most likely cause of the slow performance.

Answer

The table has no sort key on user_id.

Answer

The table has too many items, causing slow scans.

Answer

The provisioned read capacity is too low.