DBS-C01 Practice Exam 70 — 20 Questions

Question 1

Match each DynamoDB concept to its definition.

Accepted Answer

Partition key: A simple primary key that determines the partition where the item is stored.. This matching exercise tests understanding of core DynamoDB concepts. The partition key distributes items across partitions, while the sort key enables ordering. Global secondary indexes (GSIs) allow queries on different partition keys, while local secondary indexes (LSIs) share the same partition key but different sort keys.

Answer

Sort key: A simple primary key that determines the partition where the item is stored.

Answer

Global secondary index: An index that uses the same partition key as the base table but a different sort key.

Question 2

A company is migrating an on-premises DynamoDB table to Amazon DynamoDB in another AWS region. What is the most efficient method to migrate the data?

Accepted Answer

Use DynamoDB global tables to replicate data across regions.. DynamoDB global tables provide a fully managed, multi-region, multi-master replication solution that automatically replicates data across AWS regions with low latency. This eliminates the need for custom code or external tools, making it the most efficient method for migrating an on-premises DynamoDB table to another region, as it handles ongoing replication and conflict resolution natively.

Answer

Export the table to S3 using AWS Data Pipeline, then import into DynamoDB in the target region.

Answer

Set up DynamoDB Streams and write a custom consumer to replicate data to the target region.

Answer

Use AWS DMS to replicate data from on-premises to DynamoDB.

Question 3

A company is running an Amazon RDS for SQL Server DB instance with Multi-AZ deployment. The security team wants to ensure that all data at rest is encrypted using a customer-managed key stored in AWS KMS. Which steps must be taken to achieve this? (Choose THREE.)

Accepted Answer

Copy the snapshot and specify encryption with a KMS key.. To encrypt an existing unencrypted RDS instance, you must create a manual snapshot (D), copy the snapshot with encryption using a KMS key (C), and then restore the DB instance from the encrypted snapshot (E). Option A is incorrect because you cannot enable encryption on an existing DB instance directly. Option B is incorrect because Multi-AZ deployment does not automatically encrypt data.

Answer

Modify the DB instance and enable encryption.

Answer

Enable Multi-AZ deployment to encrypt data at rest.

Question 4

A company is designing a database for a global e-commerce platform that requires low-latency reads and writes from multiple AWS Regions. The database must support ACID transactions and complex queries with joins. Which TWO services should they consider? (Choose two.)

Accepted Answer

Amazon RDS for MySQL with cross-Region read replicas. Both Amazon Aurora with Aurora Global Database and Amazon RDS for MySQL with cross-Region read replicas support ACID transactions and complex queries with joins. They can provide low-latency reads from multiple regions through read replicas in each region, though writes are directed to a single primary region, which may impact write latency from non-primary regions. Amazon DynamoDB Global Tables provide multi-region writes but do not support joins for complex queries, so they cannot fully meet the requirements. ElastiCache Redis and Amazon Redshift lack the necessary ACID and join capabilities.

Answer

Amazon DynamoDB with Global Tables

Answer

Amazon ElastiCache for Redis with global datastore

Answer

Amazon Redshift with cross-Region snapshots

Question 5

A database specialist is analyzing an Aurora MySQL error log and finds the above deadlock error. The application performs an update on the orders table and then updates the inventory table within the same transaction. The deadlock occurs when two concurrent transactions try to update orders and inventory in different orders. Which design change should the database specialist recommend to reduce deadlocks?

Accepted Answer

Ensure all transactions update tables in the same order (e.g., always update inventory first, then orders). Deadlocks in Aurora MySQL often occur when concurrent transactions acquire row-level locks on tables in different orders. By enforcing a consistent lock order (e.g., always updating inventory first, then orders), the database can avoid circular wait conditions, which are a necessary condition for deadlocks. This is a standard best practice for reducing deadlocks in InnoDB, which uses row-level locking and two-phase locking.

Answer

Combine the orders and inventory tables into a single table to avoid multiple table locks

Answer

Use SELECT ... FOR UPDATE on both tables before updating

Answer

Change the transaction isolation level to READ UNCOMMITTED

Question 6

A company is deploying a new Amazon Aurora MySQL database. The development team requires a separate database instance for testing that is a clone of the production database but does not require the same level of performance. What is the MOST cost-effective way to create this test database?

Accepted Answer

Use the Aurora cloning feature to create a clone of the production cluster. The Aurora cloning feature creates a copy of the production cluster that is both fast and storage-efficient, using copy-on-write technology. This clone can be created with a different (smaller) DB instance class than the source, meeting the requirement for lower performance at minimal cost, as no additional storage is provisioned until data is modified.

Answer

Create a new Aurora cluster from the latest snapshot of the production cluster

Answer

Create a read replica of the production cluster and promote it to a standalone cluster

Answer

Create a new Aurora cluster and use a smaller DB instance class

Question 7

Which THREE of the following are key considerations when designing a time-series database using Amazon DynamoDB? (Select THREE.)

Accepted Answer

Enable Time to Live (TTL) to automatically expire old data. Amazon DynamoDB's Time to Live (TTL) feature automatically deletes expired items without consuming write throughput, making it ideal for managing data retention in time-series workloads. This eliminates the need for custom cleanup scripts and reduces storage costs over time.

Answer

Always use strongly consistent reads for accurate time-series data

Answer

Use local secondary indexes for aggregating data across partitions

Question 8

Which THREE steps should be taken to troubleshoot high replica lag in an Amazon Aurora MySQL DB cluster? (Choose THREE.)

Accepted Answer

Review network latency between the writer and replica. Options A, C, and E are correct. High replica lag in Amazon Aurora MySQL can be caused by network latency (A), resource contention on the replica (C), or issues with the replication process itself (E). Option B (increasing instance size) is a mitigation, not a troubleshooting step—you diagnose first. Option D (disabling binary logging) would break replication entirely.

Answer

Increase the instance size of the replica

Answer

Disable binary logging on the writer

Question 9

Which TWO actions can be used to encrypt an existing unencrypted Amazon RDS for MySQL DB instance? (Choose 2.)

Accepted Answer

Create a new encrypted DB instance and migrate data using database dump and restore.. To encrypt an existing unencrypted RDS for MySQL DB instance, you cannot modify the instance directly (option E is incorrect). You can either take a snapshot, copy it with encryption enabled, and restore from the encrypted snapshot (option D), or create a new encrypted DB instance and migrate data using database dump and restore (option C). Option A is incorrect because creating a read replica with encryption enabled does not encrypt the source instance. Option B is incorrect because enabling SSL encrypts data in transit, not at rest.

Answer

Create a read replica with encryption enabled.

Answer

Enable SSL on the DB instance.

Answer

Modify the DB instance and enable encryption.

Question 10

An application uses Amazon ElastiCache for Redis as a session store. Users report that sessions are being lost intermittently. The ElastiCache cluster has replication enabled with one replica. CloudWatch metrics show 'Evictions' spiking during peak hours. What is the MOST likely cause?

Accepted Answer

The cache's memory is full and the eviction policy is removing keys. A spike in 'Evictions' CloudWatch metric indicates that the cache's memory is full, and ElastiCache is evicting keys based on the configured eviction policy (e.g., allkeys-lru). This removal of keys directly causes session data to be lost. Option A is incorrect: replication lag can cause stale reads but not evictions or loss of keys. Option B is incorrect: encryption in transit does not affect memory usage or evictions. Option D is incorrect: automatic snapshots may cause a brief latency spike but do not result in evictions.

Answer

Replication lag between primary and replica is causing read failures

Answer

Encryption in transit is enabled and causes decryption errors

Answer

The cluster is performing automatic snapshots that block writes

Question 11

A company has an Amazon RDS for MySQL DB instance that is running low on storage. The current allocated storage is 500 GB, and the free space is down to 10 GB. The database administrator wants to increase storage with minimal downtime. Which action should be taken?

Accepted Answer

Use the AWS Management Console to modify the DB instance and increase the allocated storage.. RDS supports modifying storage online with minimal downtime. Increasing allocated storage from 500 GB to, for example, 600 GB can be done via a modification to the DB instance. The instance remains available during the modification, though a brief performance impact may occur. Stopping the instance is unnecessary. Creating a snapshot and restoring would cause longer downtime. Waiting for autoscaling might not be quick enough if space is critically low.

Answer

Stop the DB instance, modify the allocated storage, and start the instance.

Answer

Create a snapshot of the current DB instance, restore it to a new larger instance, and point the application to the new endpoint.

Answer

Enable storage autoscaling and wait for the automatic increase.

Question 12

A company uses Amazon Redshift for data warehousing. A nightly ETL job fails with 'Disk full' error on some nodes. The cluster has 8 dc2.large nodes. Which action will MOST efficiently resolve the issue without increasing costs?

Accepted Answer

Run a VACUUM command to reclaim space. Running a VACUUM command on Amazon Redshift reclaims storage space from deleted or updated rows without incurring additional costs. Option A is wrong because increasing the number of slices per node is not possible with dc2.large nodes; slice count is fixed per node type. Option B is wrong because adding more nodes would increase costs and is not the most efficient solution. Option C is wrong although enabling compression reduces storage usage over time, it requires a table redesign and does not immediately free space to resolve the immediate 'Disk full' error.

Answer

Increase the number of slices per node

Answer

Add more nodes to the cluster

Answer

Enable compression on all tables

Question 13

A company is running a production Amazon DynamoDB table with on-demand capacity. The application is experiencing increased latency and throttled requests during peak hours. Which monitoring tool should the database specialist use to identify the specific partition keys causing the throttling?

Accepted Answer

Amazon CloudWatch Contributor Insights for DynamoDB. Amazon CloudWatch Contributor Insights for DynamoDB is the correct tool because it analyzes DynamoDB request logs to identify the most frequently accessed partition keys, including those causing throttling. It provides top-N keys by request count or throttled events, enabling the database specialist to pinpoint hot partitions responsible for increased latency and throttled requests during peak hours.

Answer

Amazon Inspector

Answer

AWS Config

Answer

AWS CloudTrail logs

Question 14

A company uses Amazon DynamoDB to store user profiles. The access pattern is mostly GetItem by user_id. They want to reduce costs. Which design change is most effective?

Accepted Answer

Use DynamoDB Standard-IA table class for the user profiles table.. DynamoDB Standard-IA (Infrequent Access) table class offers a lower storage cost for data that is accessed infrequently, while still providing the same single-digit millisecond latency for GetItem operations. Since the access pattern is mostly GetItem by user_id, and assuming the data is not accessed frequently enough to justify the higher per-request cost of Standard, Standard-IA can significantly reduce overall costs. The trade-off is a slightly higher per-request cost, but for predominantly read-heavy workloads with low access frequency, the storage savings outweigh the request cost increase.

Answer

Increase the read capacity units to reduce throttling.

Answer

Add a Global Secondary Index on an additional attribute.

Answer

Add DynamoDB Accelerator (DAX) for caching.

Question 15

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 16

A company is deploying a new multi-AZ Aurora MySQL database. The application requires read-heavy workloads and low latency. Which configuration will best meet these requirements?

Accepted Answer

Enable Aurora Auto Scaling with a target metric of average CPU utilization.. Aurora Auto Scaling dynamically adds reader instances based on the average CPU utilization metric, which directly addresses the read-heavy workload requirement by distributing read traffic across multiple replicas. This configuration ensures low latency by scaling out read capacity automatically as demand increases, without manual intervention.

Answer

Enable Multi-AZ and use the secondary for read traffic.

Answer

Deploy a single instance with one read replica in the same AZ.

Answer

Use an RDS Proxy in front of the database.

Question 17

A company is migrating a 200 GB Oracle database to Amazon Aurora MySQL. They want to minimize downtime and ensure data consistency. Which two services should they use together? (Choose TWO.)

Accepted Answer

AWS Schema Conversion Tool (SCT). AWS Schema Conversion Tool (SCT) is required to convert the Oracle database schema (including stored procedures, functions, and data types) to a format compatible with Amazon Aurora MySQL. AWS Database Migration Service (DMS) then performs the continuous data replication from Oracle to Aurora MySQL, enabling near-zero downtime migration while maintaining data consistency through Change Data Capture (CDC).

Answer

AWS Snowball Edge

Answer

AWS Data Pipeline

Answer

Amazon EC2 with Oracle installed

Question 18

A company needs to store JSON documents that are frequently accessed by a web application. The documents have varying attributes and the query pattern includes filtering on multiple fields. Which AWS database service is most suitable?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is the most suitable choice because it is a fully managed NoSQL key-value and document database that natively supports JSON documents with varying attributes. Its flexible schema allows each item to have different attributes, and its support for secondary indexes (Local Secondary Indexes and Global Secondary Indexes) enables efficient filtering and querying on multiple fields without requiring predefined schemas or complex joins.

Answer

Amazon Neptune

Answer

Amazon ElastiCache for Redis

Answer

Amazon RDS for MySQL

Question 19

A company is deploying a new web application on AWS. The application uses Amazon RDS for MySQL as its database. The database must be highly available and automatically failover in the event of an AZ outage. The company also needs to offload read traffic from the primary database to improve performance. The application read-to-write ratio is 80:20. The database workload is variable, with occasional spikes. The company wants a cost-effective solution that scales read capacity automatically. The operations team has limited experience with AWS. Which solution should the company implement?

Accepted Answer

Deploy an Amazon Aurora MySQL cluster with Multi-AZ and enable Aurora Auto Scaling for read replicas. This solution is correct because Amazon Aurora is MySQL-compatible, provides high availability and automatic failover through its Multi-AZ deployment, and includes Aurora Auto Scaling which automatically adjusts the number of read replicas based on workload, scaling read capacity automatically. This is cost-effective as you pay only for the replicas you use and it requires minimal management, making it ideal for teams with limited AWS experience. Option A is incorrect because read replicas do not auto-scale automatically; Application Auto Scaling for replicas requires custom setup. Option B is incorrect because scaling instance size does not offload read traffic or provide read scaling. Option D is incorrect because it lacks automatic failover and requires manual intervention.

Answer

Deploy an RDS for MySQL instance with Multi-AZ and one or more read replicas, and use Application Auto Scaling to add replicas based on CPU utilization

Answer

Deploy an RDS for MySQL instance with Multi-AZ and enable automatic scaling of the instance size

Answer

Deploy an RDS for MySQL instance with multiple read replicas and use a custom script to promote a read replica in case of failure

Question 20

A financial services company is migrating a 2 TB Oracle database to Amazon Aurora PostgreSQL. The database uses Oracle-specific features like hierarchical queries and stored procedures. The company wants to minimize manual code changes. Which service should be used to automate schema conversion?

Accepted Answer

AWS Schema Conversion Tool (SCT).. AWS Schema Conversion Tool (SCT) is specifically designed to convert database schemas from one engine to another, including Oracle to Amazon Aurora PostgreSQL. It automates the conversion of Oracle-specific features like hierarchical queries (CONNECT BY) and stored procedures into PostgreSQL-compatible syntax (e.g., recursive CTEs and PL/pgSQL), minimizing manual code changes. This makes SCT the correct choice for schema conversion, while AWS DMS handles data migration separately.

Answer

AWS Database Migration Service (DMS) with full load and ongoing replication.

Answer

AWS Storage Gateway to cache data on-premises and then sync to S3.

Answer

AWS Lambda to execute custom scripts for schema transformation.