DBS-C01 Practice Exam 69 — 20 Questions

Question 1

A company is migrating an on-premises MongoDB database to Amazon DocumentDB. They need to ensure that the migration is completed with minimal downtime and that data remains consistent. Which tool should they use?

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

Accepted Answer

Use AWS DMS with MongoDB as source and DocumentDB as target. AWS DMS supports continuous change data capture (CDC) from MongoDB to Amazon DocumentDB, enabling near-zero downtime migration by replicating ongoing changes after the initial full load. This ensures data consistency without requiring application downtime, unlike batch export/import methods.

Answer

Use mongoexport and mongoimport

Answer

Export data to Amazon S3 and load into DocumentDB

Answer

Use MongoDB Atlas Live Migration

Question 2

An Amazon RDS for SQL Server instance is running out of storage space. The instance uses 500 GB of Magnetic storage. The database specialist needs to increase storage to 1 TB with minimal downtime. Which solution meets these requirements?

Accepted Answer

Modify the DB instance and increase the allocated storage to 1 TB.. Modifying the DB instance to increase allocated storage is the correct approach because it can be done with minimal downtime. Amazon RDS for SQL Server supports dynamic storage scaling, allowing you to increase the allocated storage size without requiring a snapshot or migration. The instance remains available during the modification, although a brief performance impact may occur. Option A is incorrect because restoring from a snapshot requires significant downtime and does not offer a direct storage increase on the existing instance. Option B is incorrect because converting storage type (e.g., from Magnetic to General Purpose) is a separate modification that also incurs downtime, and it is not necessary to change storage type before increasing size; you can modify storage size directly. Option D is incorrect because using AWS DMS is overkill for a simple storage increase and introduces additional complexity and potential downtime during the migration process.

Answer

Create a snapshot of the DB instance and restore it with larger storage.

Answer

Convert the storage type to General Purpose (gp2) and then increase size.

Answer

Use AWS DMS to migrate the database to a new instance with 1 TB storage.

Question 3

A company uses Amazon Aurora MySQL for its e-commerce platform. The DB cluster has one writer and two readers. Recently, the application started showing occasional deadlock errors during order processing. The error logs show: 'Transaction (Process ID 123) was deadlocked on lock resources with another process and has been chosen as the deadlock victim. Rerun the transaction.' The application retries three times before failing. The development team wants to reduce the likelihood of deadlocks. Which three actions should the team take? (Choose three.)

Accepted Answer

Shorten the duration of transactions by committing frequently.. Reduces the time locks are held, decreasing contention. Option C uses a weaker isolation level (READ COMMITTED) that reduces locking overhead compared to REPEATABLE READ. Option E ensures transactions request locks in a consistent order, preventing cycle dependencies. Option B is incorrect because READ UNCOMMITTED can cause dirty reads and is not suitable for e-commerce order processing. Option D is incorrect because increasing retry attempts does not reduce the likelihood of deadlocks; it only allows more retries after a deadlock occurs.

Answer

Switch to READ UNCOMMITTED isolation level to reduce locking.

Answer

Increase the number of retry attempts to 10.

Question 4

A company has an Amazon Aurora MySQL DB cluster with one writer and two readers. The application is experiencing high read latency. CloudWatch shows that the 'AuroraBinlogReplicaLag' metric is high for one of the reader instances. What is the most likely cause?

Accepted Answer

The reader instance is not keeping up with the write workload from the writer. The 'AuroraBinlogReplicaLag' metric measures the lag between the writer and a reader when using binary log replication. A high value indicates that the reader is not applying changes from the writer quickly enough, causing read latency. This is typically because the reader instance is not keeping up with the write workload from the writer. Option A is incorrect because Aurora storage is shared and not the cause of replication lag. Option C is incorrect; while an undersized reader can contribute to lag, the primary cause is the reader not keeping pace with writes, not necessarily size. Option D is incorrect because parameter groups affect settings but not replication lag directly.

Answer

The Aurora cluster storage is experiencing high I/O latency

Answer

The reader instance is undersized and needs to be scaled up

Answer

The DB cluster parameter group is misconfigured

Question 5

A company has a production Amazon RDS for PostgreSQL Multi-AZ DB instance. The company's security team requires that all database connections use IAM database authentication. The company also needs to ensure that connections from a specific application server are allowed only if the server has a valid IAM role. Which combination of steps should the database administrator take to meet these requirements?

Accepted Answer

Enable IAM database authentication on the RDS instance. Create a database user that matches the IAM role ARN. Grant the application server's IAM role the rds_iam role. Configure the application to generate an authentication token using the IAM role's credentials.. IAM database authentication for RDS PostgreSQL requires mapping IAM roles to database users. Steps: 1) Enable IAM database authentication on the RDS instance. 2) Create a database user that matches the IAM role ARN (the role assumed by the application server). 3) Grant the rds_iam role to the application server's IAM role to allow it to authenticate. 4) Configure the application to generate an authentication token using the IAM role's credentials. Option D is correct because it includes all these steps. Option A is wrong because it uses a password instead of an authentication token. Option B is wrong because it references an IAM user ARN instead of a role ARN. Option C is wrong because it does not enable IAM authentication and uses a password.

Answer

Create a database user with a strong password. Enable IAM database authentication. Assign the application server an IAM policy that allows rds-db:connect. Configure the application to use the password.

Answer

Enable IAM database authentication. Create a database user matching the IAM user ARN. Grant the application server's IAM user the rds_iam role. Configure the application to use an authentication token.

Answer

Enable IAM database authentication. Create a database user that matches the IAM role ARN. Configure the application to use the database master username and password.

Question 6

An e-commerce application uses Amazon DynamoDB as its primary database. The table stores order data with a partition key of 'OrderID' and a sort key of 'OrderDate'. The application frequently queries orders by customer ID (which is not a key attribute). What design change would improve query performance?

Accepted Answer

Create a Global Secondary Index on CustomerID. Creating a Global Secondary Index (GSI) on CustomerID allows efficient querying by that attribute without scanning the entire table. A GSI has its own partition and sort keys, enabling fast lookups on non-key attributes. This directly addresses the performance issue of frequent queries by CustomerID, which otherwise would require a full table scan.

Answer

Enable DynamoDB Streams and export to Amazon Elasticsearch Service

Answer

Use DynamoDB Accelerator (DAX) to cache queries

Answer

Create a Local Secondary Index on CustomerID

Question 7

A company is deploying a new application that requires a relational database with automatic failover and cross-Region disaster recovery. The application is read-heavy and expects up to 10 GB of data. Which combination of AWS services should be used?

Accepted Answer

Amazon Aurora with Multi-AZ and an Aurora global database. Amazon Aurora with Multi-AZ provides high availability within a single Region, while Aurora Global Database enables cross-Region disaster recovery with typical replication latency of under one second. Aurora is optimized for read-heavy workloads and scales automatically, making it ideal for the 10 GB dataset and the application's requirements.

Answer

Amazon RDS for MySQL with Multi-AZ and a read replica in another Region

Answer

Amazon S3 with AWS Glue and Amazon Athena

Answer

Amazon DynamoDB with global tables

Question 8

Which TWO CloudWatch metrics should be monitored to detect storage performance issues for an Amazon RDS for MySQL instance? (Choose two.)

Accepted Answer

WriteIOPS. Options C and E are correct. ReadIOPS and WriteIOPS measure the input/output operations per second, which directly indicate storage performance for an RDS MySQL instance. High or erratic IOPS can signal storage contention or saturation. Option A (NetworkReceiveThroughput) tracks network traffic, not storage. Option B (DatabaseConnections) reflects concurrent connections, unrelated to storage performance. Option D (CPUUtilization) measures CPU usage, which may impact overall performance but is not a direct storage metric.

Answer

NetworkReceiveThroughput

Answer

DatabaseConnections

Answer

CPUUtilization

Question 9

A company is deploying a new application with a PostgreSQL database on Amazon RDS. The database must be highly available across two Availability Zones. Which deployment option meets this requirement?

Accepted Answer

Multi-AZ RDS instance.. A Multi-AZ RDS instance automatically provisions and maintains a synchronous standby replica in a different Availability Zone, providing automatic failover for high availability. This ensures the database remains accessible even if the primary AZ fails, meeting the requirement for cross-AZ high availability.

Answer

RDS with a read replica in another AZ.

Answer

Single-AZ RDS instance.

Answer

Amazon Aurora Global Database.

Question 10

A company uses Amazon DynamoDB for a high-traffic leaderboard application that updates scores in real-time. The table has partition key 'game_id' and sort key 'player_id'. Queries retrieve top 10 players by score for each game. Which secondary index design is most efficient?

Accepted Answer

Create a global secondary index (GSI) with partition key 'game_id' and sort key 'score'. A global secondary index (GSI) with partition key 'game_id' and sort key 'score' allows efficient retrieval of the top 10 players per game by querying a single partition (game_id) and using the sort key to order by score descending. This avoids the 1 MB read limit per partition and provides the necessary ordering without scanning the entire table.

Answer

Create a global secondary index (GSI) with partition key 'game_id' and sort key 'player_id'

Answer

Create a local secondary index (LSI) with sort key 'score'

Answer

Do not create any index; use the base table with a scan

Question 11

A company uses Amazon DynamoDB to store application logs. The logs have a TTL of 7 days. The operations team needs to run ad-hoc analytical queries on logs older than 7 days, which are automatically deleted by TTL. Which solution should the team implement to retain and analyze old logs?

Accepted Answer

Use DynamoDB Streams to export logs to Amazon S3 and query with Amazon Athena.. DynamoDB Streams can capture item deletions (including TTL-based deletions) and export them to Amazon S3. Once the logs are in S3, Amazon Athena can run ad-hoc SQL queries directly on the data, providing a cost-effective and serverless analytical solution for logs older than 7 days.

Answer

Disable TTL and use a scheduled Lambda function to archive logs to Amazon S3.

Answer

Increase the TTL to 30 days and query the logs directly in DynamoDB.

Answer

Use AWS Glue to crawl DynamoDB tables and create a data catalog for Athena queries.

Question 12

A company is designing a multi-tenant SaaS application on Amazon RDS for PostgreSQL. Each tenant's data must be isolated for security and performance. The application has millions of tenants, with most tenants having small datasets (under 100 MB). Which database design pattern is MOST cost-effective and operationally efficient?

Accepted Answer

Use a single RDS instance with a shared schema and implement Row-Level Security (RLS) policies based on tenant_id.. Using a single RDS for PostgreSQL instance with Row-Level Security (RLS) allows you to isolate tenant data at the row level based on a tenant_id column, without the overhead of managing millions of separate schemas or tables. This design is both cost-effective (single instance, no per-tenant provisioning) and operationally efficient (simple schema management, no connection pooling issues), while still meeting security and performance isolation requirements for small datasets under 100 MB.

Answer

Use Amazon DynamoDB with a separate table per tenant.

Answer

Use a single RDS instance with a separate schema per tenant.

Answer

Use a separate Amazon RDS for PostgreSQL instance per tenant.

Question 13

A company is migrating an on-premises MongoDB database to Amazon DocumentDB. The migration must be online with minimal downtime. Which AWS service should be used?

Accepted Answer

AWS DMS. AWS Database Migration Service (DMS) is the correct choice because it supports ongoing replication (change data capture) from MongoDB to Amazon DocumentDB, enabling an online migration with minimal downtime. DMS can perform a full load of existing data and then continuously replicate changes from the source MongoDB oplog to keep the target DocumentDB synchronized until cutover.

Answer

AWS DataSync

Answer

AWS S3

Answer

AWS Snowball Edge

Question 14

A company is migrating a 2 TB MySQL database to Amazon Aurora MySQL. They want to minimize downtime and ensure data consistency. Which TWO methods should they use? (Choose two.)

Accepted Answer

Use AWS DMS with ongoing replication. AWS DMS with ongoing replication (Option A) is correct because it allows continuous change data capture (CDC) from the source MySQL database to the target Aurora MySQL cluster, minimizing downtime by keeping the target synchronized during the migration. This approach ensures data consistency by applying incremental changes after the initial full load, enabling a controlled cutover with minimal service interruption.

Answer

Use AWS Schema Conversion Tool to convert the schema

Answer

Use AWS Snowball Edge to transfer backup files

Answer

Use mysqldump to export data

Question 15

A company is designing a database for a global application that requires low-latency reads and writes across multiple AWS regions. The application data is key-value and does not require complex queries. The team needs strong consistency for critical data. Which TWO services should they consider? (Choose TWO.)

Accepted Answer

Amazon DynamoDB Global Tables. Amazon DynamoDB Global Tables is correct because it provides a fully managed, multi-region, multi-active database solution that replicates data across AWS Regions with low-latency reads and writes. It supports strongly consistent reads for critical data when using the `ConsistentRead` parameter, which returns the most up-to-date data from the source region. This makes it ideal for key-value workloads requiring global scalability and strong consistency.

Answer

Amazon S3 with cross-region replication

Answer

Amazon ElastiCache for Redis with global datastore

Answer

Amazon RDS for PostgreSQL with cross-region read replicas

Question 16

An Amazon DynamoDB table is experiencing throttled write requests. The table uses provisioned capacity with auto-scaling enabled. Which THREE factors could contribute to throttling despite auto-scaling?

Accepted Answer

Auto-scaling maximum capacity is set too low. Auto-scaling can prevent throttling only if the maximum capacity is set appropriately and traffic patterns are predictable. Option B is correct because if the auto-scaling maximum capacity is set too low, the table cannot scale enough to handle the write demand. Option C is correct because auto-scaling reacts to sustained traffic but cannot instantly accommodate a sudden traffic spike that exceeds the maximum capacity. Option E is correct because even with auto-scaling, an uneven partition key distribution can cause a single partition to exceed its throughput capacity, leading to throttling. Option A is incorrect; a global secondary index with the same partition key does not inherently cause throttling on the base table. Option D is incorrect because eventually consistent reads affect read capacity, not write capacity, and do not cause write throttling.

Answer

Global secondary index is defined with same partition key

Answer

Use of eventually consistent reads

Question 17

A company uses Amazon Aurora MySQL for its customer relationship management (CRM) system. The database has a table "contacts" with millions of rows. The application frequently searches for contacts by email address. The email column has a B-tree index. The DBA notices that queries are still slow, and the EXPLAIN plan shows index scans but not index-only scans. What is the most likely cause?

Accepted Answer

The query selects columns not included in the index, requiring table lookups.. An index-only scan requires that all columns referenced in the query (both in the SELECT list and WHERE clause) be present in the index. Since the query selects columns not included in the B-tree index on the email column, Aurora MySQL must perform additional table lookups (row fetches) to retrieve those missing columns, resulting in an index scan rather than an index-only scan.

Answer

The index is a composite index on (email, phone) and the query selects only email.

Answer

The index has low cardinality.

Answer

The index type is not suitable for equality searches.

Question 18

A security team needs to grant an IAM user permission to modify only the 'db_secrets' secret in AWS Secrets Manager. Which IAM policy statement is correct?

Accepted Answer

{ 'Effect': 'Allow', 'Action': 'secretsmanager:PutSecretValue', 'Resource': 'arn:aws:secretsmanager:us-east-1:123456789012:secret:db_secrets-??????' }. It grants the specific `secretsmanager:PutSecretValue` action on the exact ARN of the `db_secrets` secret, including the required six-character random suffix (`-??????`) that AWS Secrets Manager appends to secret names. This ensures the IAM user can only modify that single secret, meeting the security requirement of least privilege.

Answer

{ 'Effect': 'Allow', 'Action': 'secretsmanager:UpdateSecret', 'Resource': '*' }

Answer

{ 'Effect': 'Allow', 'Action': 'secretsmanager:*', 'Resource': '*' }

Answer

{ 'Effect': 'Allow', 'Action': 'secretsmanager:PutSecretValue', 'Resource': 'arn:aws:secretsmanager:us-east-1:123456789012:secret:*' }

Question 19

A company is migrating a 2 TB Oracle database to Amazon Aurora PostgreSQL using AWS SCT and DMS. After migration, the application reports that some queries are significantly slower than before. The database schema was converted automatically. What is the most likely cause?

Accepted Answer

The schema conversion did not create appropriate indexes. The most likely cause is that AWS Schema Conversion Tool (SCT) converted the Oracle schema to Aurora PostgreSQL but did not automatically create optimal indexes. Oracle and PostgreSQL use different query optimizers and index strategies; SCT focuses on structural compatibility, not performance tuning. Without manual review and addition of appropriate indexes (e.g., for foreign keys, composite columns, or partial indexes), PostgreSQL may resort to sequential scans on large tables, causing significant query slowdowns.

Answer

Aurora storage is slower than Oracle's storage

Answer

DMS introduced data type conversions that slow down queries

Answer

Aurora PostgreSQL does not support partitioning, causing full table scans

Question 20

A company runs a critical e-commerce application on Amazon RDS for PostgreSQL with a db.r5.2xlarge instance and 500 GB of gp2 storage. The application experiences periodic write spikes during flash sales. During these events, the WriteIOPS metric exceeds the provisioned baseline IOPS of 1,500, and the database becomes unresponsive for several seconds. The DBA has configured a CloudWatch alarm on WriteIOPS, but the alarm triggers after the performance issue occurs. The company needs to ensure that the database can handle these spikes without downtime. The budget allows for moderate cost increases. What should the DBA do?

Accepted Answer

Modify the DB instance to use gp3 storage with provisioned IOPS of 5,000.. Gp3 storage provides a baseline of 3,000 IOPS regardless of storage size, and allows provisioning up to 16,000 IOPS independently. By setting provisioned IOPS to 5,000, the database can handle write spikes without exceeding the IOPS limit, preventing unresponsiveness. This solution fits the moderate cost increase budget, as gp3 is typically 20% cheaper than gp2 for equivalent performance.

Answer

Increase the allocated storage to 1,000 GB to increase baseline IOPS to 3,000.

Answer

Enable Performance Insights to identify the problematic queries and tune them.

Answer

Add a read replica and redirect read traffic to it to reduce write contention.