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AWS Certified Database Specialty DBS-C01 (DBS-C01) — Questions 12761350

1663 questions total · 23pages · All types, answers revealed

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1276
MCQhard

An IAM policy is attached to a user to allow read access to the Orders table in DynamoDB. The user reports that a GetItem call for an order returns an 'AccessDeniedException'. What is the likely cause?

A.The user must specify a projection expression in the GetItem request to include only 'order_id' and 'status' attributes.
B.The user does not have permissions to perform GetItem on the Orders table.
C.The resource ARN is incorrect; it should include the wildcard for the table.
D.The condition key 'dynamodb:Attributes' restricts access to only two attributes, but the user can still get all attributes.
AnswerA

The condition requires that only these attributes be returned, so the request must explicitly project them.

Why this answer

When an IAM policy uses the `dynamodb:Attributes` condition key to restrict access to specific attributes (e.g., `order_id` and `status`), the user must include a `ProjectionExpression` in the `GetItem` request that explicitly lists only those allowed attributes. Without the projection expression, DynamoDB attempts to return all attributes, which triggers an `AccessDeniedException` because the policy denies access to attributes not listed in the condition.

Exam trap

AWS often tests the misconception that a table-level permission error is the cause, when in reality the issue is a missing `ProjectionExpression` due to attribute-level restrictions in the IAM policy.

How to eliminate wrong answers

Option B is wrong because the user does have permissions to perform GetItem on the Orders table; the error is caused by attribute-level restrictions, not a lack of table-level permission. Option C is wrong because the resource ARN in the policy is correct; including a wildcard for the table would not resolve the attribute-level restriction issue. Option D is wrong because the condition key `dynamodb:Attributes` does restrict access to only two attributes, and the user cannot get all attributes; the GetItem call must use a projection expression to limit the returned attributes to those allowed.

1277
MCQhard

A company runs a global e-commerce platform with a relational database. They need to reduce read latency for users in Europe and Asia. The primary database is in us-west-2. Which solution provides the LOWEST read latency for global users while maintaining data consistency?

A.Deploy Amazon ElastiCache clusters in each region and cache database queries
B.Use Amazon Aurora Global Database with reader instances in Europe and Asia
C.Migrate to Amazon DynamoDB global tables
D.Configure Amazon RDS cross-region read replicas
AnswerB

Aurora Global Database provides cross-region read replicas with <1 second latency, enabling low-latency local reads.

Why this answer

Amazon Aurora Global Database is designed for low-latency global reads by replicating data to up to five secondary regions with dedicated reader instances. It uses storage-based replication that typically adds less than one second of lag, ensuring strong consistency while providing local read access for users in Europe and Asia. This architecture directly addresses the requirement for the lowest read latency without compromising data consistency.

Exam trap

The trap here is that candidates often choose ElastiCache (Option A) thinking caching always provides the lowest latency, but they overlook the requirement for data consistency and the fact that caching does not replicate the full database state across regions.

How to eliminate wrong answers

Option A is wrong because ElastiCache caches database queries but does not replicate the underlying relational data; it introduces eventual consistency and cache staleness, and does not provide the same consistency guarantees as Aurora Global Database. Option C is wrong because DynamoDB global tables are a NoSQL solution, not a relational database, and the company specifically requires a relational database for its e-commerce platform. Option D is wrong because Amazon RDS cross-region read replicas use asynchronous replication with potentially higher lag than Aurora Global Database, and they do not offer the same low-latency global read architecture with dedicated reader instances in each region.

1278
MCQmedium

A company is running a production Amazon RDS for MySQL DB instance. The application team reports intermittent connection timeouts. The DBA notices that the DB instance's CPU utilization spikes to 100% during these times. Which metric should be monitored to determine if the issue is due to a specific query?

A.DatabaseConnections
B.NetworkThroughput
C.ReadIOPS
D.Queries (engine-specific counter)
AnswerD

Queries reflects the number of queries executed, helping identify query load spikes.

Why this answer

The RDS for MySQL engine-specific counter 'Queries' reflects the number of queries executed. Option A is wrong because DatabaseConnections shows connections, not query performance. Option B is wrong because ReadIOPS measures disk I/O, not query volume.

Option C is wrong because NetworkThroughput measures network traffic.

1279
MCQeasy

A company wants to migrate a 1 TB on-premises PostgreSQL database to Amazon RDS for PostgreSQL. They have a limited internet bandwidth. Which service should they use to accelerate the migration?

A.AWS Snowball Edge
B.AWS Database Migration Service (DMS)
C.Amazon S3
D.AWS Direct Connect
AnswerA

Offline data transfer bypasses bandwidth limitations.

Why this answer

AWS Snowball Edge is the correct choice because it provides a physical storage device that can be used to transfer large volumes of data (1 TB) over a limited internet bandwidth. By shipping the device to AWS, the initial bulk data load bypasses the internet entirely, which accelerates the migration. After the data is loaded into Amazon RDS for PostgreSQL via Snowball Edge, AWS DMS can be used for ongoing replication to keep the database in sync.

Exam trap

The trap here is that candidates often assume AWS DMS is always the best choice for database migrations, but they overlook the critical constraint of limited bandwidth, which makes a physical appliance like Snowball Edge the only viable option for accelerating the initial bulk transfer.

How to eliminate wrong answers

Option B (AWS DMS) is wrong because while DMS is the primary service for database migrations, it relies on network connectivity to transfer data; with limited internet bandwidth, a 1 TB migration would be extremely slow or impractical. Option C (Amazon S3) is wrong because S3 is an object storage service, not a migration service; it cannot directly migrate a PostgreSQL database to RDS, and uploading 1 TB to S3 over limited bandwidth would still be slow. Option D (AWS Direct Connect) is wrong because it establishes a dedicated network connection, but it requires significant setup time and cost, and does not inherently accelerate the data transfer if the underlying internet bandwidth is limited; it also does not address the physical data transfer challenge.

1280
MCQmedium

The exhibit shows the output of a MySQL command run on an Amazon RDS for MySQL DB instance. The database is experiencing frequent checkpointing that is causing I/O spikes. The parameter innodb_log_file_size is currently 256 MB. Which change should be made to reduce checkpoint frequency?

A.Decrease the value of innodb_log_file_size to 128 MB.
B.Set innodb_flush_log_at_trx_commit to 0.
C.Increase the value of innodb_log_file_size to 1 GB.
D.Increase the value of innodb_buffer_pool_size.
AnswerC

Increasing innodb_log_file_size to 1 GB allows the redo log to hold more transactions before a checkpoint is triggered, reducing checkpoint frequency and smoothing I/O.

Why this answer

Increasing innodb_log_file_size reduces checkpoint frequency by allowing more transactions to be logged before a checkpoint is forced. Option A is wrong because decreasing the log file size would increase checkpoint frequency. Option B is wrong because innodb_flush_log_at_trx_commit controls write-ahead logging durability, not checkpoint frequency.

Option D is wrong because innodb_buffer_pool_size affects caching and memory, but does not directly reduce checkpoint frequency.

1281
MCQhard

A company uses Amazon DynamoDB Global Tables with strong consistent reads. They notice that a write to us-east-1 is not visible in eu-west-1 after several seconds. Which configuration setting is MOST likely causing this behavior?

A.DynamoDB Streams is not enabled on the table
B.Auto Scaling is configured for write capacity
C.Last writer wins (LWW) conflict resolution is disabled
D.Strongly consistent reads are used on a global table
AnswerA

Global Tables require DynamoDB Streams to replicate writes; without it, replication does not occur.

Why this answer

DynamoDB Global Tables require DynamoDB Streams to be enabled on the table. If streams are disabled, write operations in one region will not be replicated to other regions, causing the writes to never become visible. This matches the symptom of writes not appearing after several seconds.

Option B (Auto Scaling) does not affect replication. Option C (LWW conflict resolution) is enabled by default and does not cause delays. Option D (strongly consistent reads) are not supported on Global Tables and would generate an error, not a delay.

1282
MCQeasy

A company needs to migrate a 100 GB on-premises SQL Server database to Amazon RDS for SQL Server. The migration must be completed within a 4-hour maintenance window. The network link has 500 Mbps throughput. Which approach should be used?

A.Use AWS DMS with full load and CDC
B.Use native SQL Server backup to S3, then restore to RDS
C.Use AWS Snowball Edge to transfer the backup
D.Launch an EC2 instance with SQL Server, copy the database, and then migrate to RDS
AnswerB

This method can be fast and fits within the maintenance window with 500 Mbps.

Why this answer

Native SQL Server backup to S3 and restore to RDS is the fastest method for a 100 GB database over a 500 Mbps link. At 500 Mbps, the theoretical transfer time for 100 GB is approximately 28 minutes (100 GB * 8 / 500 Mbps), well within the 4-hour window, making Snowball unnecessary. This approach avoids the overhead of change data capture (CDC) and additional compute resources, directly leveraging SQL Server's native backup/restore capabilities.

Exam trap

The trap here is that candidates overestimate the time required for network transfer and assume Snowball is necessary for any database over a few gigabytes, ignoring that a 500 Mbps link can transfer 100 GB in under 30 minutes, well within the 4-hour window.

How to eliminate wrong answers

Option A is wrong because AWS DMS with full load and CDC introduces unnecessary complexity and overhead for a one-time migration that can be completed within the maintenance window using a simpler backup/restore method; CDC is designed for ongoing replication, not a single batch transfer. Option C is wrong because AWS Snowball Edge is overkill for a 100 GB database when the network link (500 Mbps) can transfer the data in under 30 minutes, and Snowball adds logistics delays (shipping, preparation) that exceed the 4-hour window. Option D is wrong because launching an EC2 instance with SQL Server, copying the database, and then migrating to RDS adds extra steps and cost without benefit; the native backup to S3 and restore to RDS is more direct and avoids intermediate compute resources.

1283
Multi-Selectmedium

A company is using Amazon DynamoDB for a shopping cart application. The table has a partition key of `user_id` and a sort key of `item_id`. The application performs frequent updates to the `quantity` attribute. The company notices that write requests are being throttled during peak hours. Which TWO actions would help reduce throttling? (Choose two.)

Select 2 answers
A.Increase the provisioned write capacity for the table.
B.Use conditional writes to prevent overwrites.
C.Implement a write sharding pattern using a random suffix on the partition key.
D.Enable DynamoDB Streams to process writes asynchronously.
E.Enable DynamoDB Accelerator (DAX) for the table.
AnswersA, C

Increasing write capacity directly reduces throttling.

Why this answer

Increasing the provisioned write capacity directly raises the number of write capacity units (WCUs) available per second, allowing more write requests to succeed without being throttled. Since the application performs frequent updates to the `quantity` attribute, which consumes write capacity, adding more capacity alleviates throttling during peak hours.

Exam trap

The trap here is that candidates often confuse read-side solutions (like DAX or Streams) with write-side throttling, or they mistakenly think conditional writes reduce capacity consumption, when in fact they do not address the root cause of insufficient write capacity or hot partitions.

1284
MCQeasy

A gaming company wants to store player profiles and game state data with low-latency access for millions of concurrent users. The data is accessed via a REST API and requires high scalability with minimal operational overhead. Which database service is MOST suitable?

A.Amazon RDS for MySQL with read replicas
B.Amazon DynamoDB
C.Amazon Neptune
D.Amazon ElastiCache for Redis
AnswerB

DynamoDB is serverless, scales automatically, and provides low-latency access.

Why this answer

Amazon DynamoDB is the most suitable choice because it is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale, making it ideal for storing player profiles and game state data for millions of concurrent users. It supports high throughput with auto-scaling, integrates seamlessly with REST APIs via AWS SDKs, and requires minimal operational overhead due to its serverless nature.

Exam trap

The trap here is that candidates often confuse ElastiCache for Redis as a primary database due to its low latency, but it is an in-memory cache that does not provide the durability and persistence guarantees required for authoritative game state data, whereas DynamoDB is designed as a fully managed, durable, and scalable NoSQL database for exactly this use case.

How to eliminate wrong answers

Option A is wrong because Amazon RDS for MySQL with read replicas is a relational database that introduces write bottlenecks and requires manual scaling, schema management, and operational overhead, making it unsuitable for the high-velocity, schema-flexible game state data and millions of concurrent writes. Option C is wrong because Amazon Neptune is a graph database optimized for highly connected data like social networks or recommendation engines, not for simple key-value lookups of player profiles and game state, and it adds unnecessary complexity and cost. Option D is wrong because Amazon ElastiCache for Redis is an in-memory cache, not a durable primary database; while it provides low latency, it lacks persistence guarantees and is typically used as a caching layer, not for storing authoritative game state data that must survive restarts.

1285
Multi-Selecthard

A company is using Amazon DynamoDB with provisioned capacity for a table that experiences unpredictable traffic spikes. The table's read capacity is often underutilized, but occasionally throttling occurs. Which THREE steps should be taken to improve performance and cost? (Choose THREE.)

Select 3 answers
A.Switch the table to on-demand capacity mode.
B.Reduce the provisioned read capacity units to save cost.
C.Enable auto scaling for read and write capacity.
D.Disable auto scaling to avoid cost fluctuations.
E.Implement DynamoDB Accelerator (DAX) to cache read requests.
AnswersA, C, E

On-demand mode automatically accommodates traffic spikes without throttling.

Why this answer

Switching to on-demand capacity mode eliminates the need to manage provisioned capacity, automatically scaling to handle unpredictable traffic spikes without throttling. This improves performance by preventing throttling during spikes and optimizes cost by charging only for consumed reads/writes, avoiding the waste of underutilized provisioned capacity.

Exam trap

The trap here is that candidates often assume auto scaling alone is sufficient for unpredictable spikes, but auto scaling has a lag and cannot react instantly, making on-demand mode the better choice for truly unpredictable traffic.

1286
MCQmedium

A database administrator runs the command shown in the exhibit. The security team requires that the database be encrypted at rest. What should the administrator do to enable encryption?

A.Enable encryption at the table level using MySQL's built-in encryption.
B.Create a snapshot of the DB instance, copy the snapshot with encryption, and restore from the encrypted snapshot.
C.Modify the DB instance and set StorageEncrypted to true.
D.The instance is already encrypted because the output shows 'StorageEncrypted' as false.
AnswerB

This is the standard method to enable encryption on an existing instance.

Why this answer

Encryption cannot be enabled on an existing unencrypted instance; you must create a snapshot, copy it with encryption, and restore. Option A is wrong because encryption is at the storage level, not table level. Option C is wrong because modifying the instance does not add encryption.

Option D is wrong because the command shows StorageEncrypted is false, so it is not encrypted.

1287
MCQhard

A company is building a real-time leaderboard for a gaming application. The leaderboard must update scores within seconds and support queries for top players and individual ranks. Which database design is most appropriate?

A.Amazon S3 with Range GET requests
B.Amazon ElastiCache for Redis with sorted sets
C.Amazon DynamoDB with a global secondary index on score
D.Amazon RDS for PostgreSQL with ORDER BY and LIMIT
AnswerC

DynamoDB GSI enables efficient querying of top scores and rank lookups.

Why this answer

Amazon DynamoDB with a global secondary index (GSI) on score is the most appropriate design because it supports real-time updates and low-latency queries for both top players (via query on the GSI with ScanIndexForward=false and Limit) and individual ranks (via efficient key lookups). DynamoDB's fully managed, serverless architecture ensures sub-second response times at any scale, which is critical for a gaming leaderboard that must update scores within seconds.

Exam trap

Candidates might gravitate toward Redis (Option B) because of its native sorted set support, which is highly efficient for leaderboards. However, DynamoDB can also serve this use case with a global secondary index on score, allowing queries for top players and individual ranks with low latency, and it offers a fully managed serverless experience that scales automatically.

How to eliminate wrong answers

Option A is wrong because Amazon S3 is an object storage service, not a database; it lacks the ability to perform real-time updates or sorted queries, and Range GET requests are for retrieving byte ranges of an object, not for leaderboard operations. Option B is wrong because while ElastiCache for Redis with sorted sets can efficiently maintain a leaderboard in memory, it is not a durable, persistent database by default and would require additional configuration for data persistence and failover, making it less suitable as the primary database for a production gaming application that needs durability and consistency. Option D is wrong because Amazon RDS for PostgreSQL with ORDER BY and LIMIT can support leaderboard queries, but it is not optimized for real-time, high-frequency updates and queries at the scale of a gaming application; it would introduce latency due to disk-based storage and lack of native in-memory sorted set operations, and it requires manual scaling and management.

1288
MCQhard

A company uses Amazon DynamoDB to store IoT sensor data. Each sensor sends data every second, and the application needs to query the latest reading from each sensor. The sensor ID is the partition key, and the timestamp is the sort key. The table has millions of sensors. Which query pattern is most efficient to get the latest reading for a specific sensor?

A.Use BatchGetItem with the sensor ID and multiple timestamps
B.Use Scan with FilterExpression on sensor ID
C.Use GetItem with the sensor ID and the current timestamp
D.Use Query with KeyConditionExpression on sensor ID, ScanIndexForward=false, Limit=1
AnswerD

This retrieves the most recent item for that sensor efficiently.

Why this answer

Query with ScanIndexForward=false and Limit=1 retrieves only the most recent item for a given partition key (sensor ID) by reading items in descending sort key (timestamp) order and stopping after one item. This is the most efficient pattern as it uses the primary key index directly, avoids scanning, and minimizes read capacity consumption.

Exam trap

The DBS-C01 exam often tests the misconception that GetItem can be used with a partial key or that Scan with a filter is acceptable for single-item retrieval, but the trap here is that candidates overlook the efficiency of using Query with sort key ordering and limit to fetch the most recent item without scanning or guessing timestamps.

How to eliminate wrong answers

Option A is wrong because BatchGetItem requires exact primary keys (partition key and sort key) and cannot retrieve the latest item without knowing the exact timestamp; it also consumes read capacity for each requested item, making it inefficient for this use case. Option B is wrong because Scan reads every item in the table, which is extremely expensive and slow for millions of sensors, and FilterExpression is applied after the scan, not reducing the read capacity consumed. Option C is wrong because GetItem requires the exact primary key (sensor ID and timestamp), and using the current timestamp assumes the latest reading occurs exactly at that moment, which is almost never true for real-time sensor data.

1289
MCQmedium

A healthcare application stores patient records in Amazon DynamoDB. Each record has a unique patient ID and contains sensitive health information. The application must encrypt data at rest and ensure that only authorized services can access the data. Which combination of design choices meets these requirements?

A.Implement client-side encryption and use Lambda to validate access.
B.Enable S3 server-side encryption with AWS KMS and use bucket policies.
C.Enable DynamoDB encryption at rest using AWS KMS and use IAM policies to restrict access.
D.Use AWS CloudHSM for key storage and VPC endpoints for access control.
AnswerC

DynamoDB integrates with KMS for encryption and IAM for access control.

Why this answer

DynamoDB encryption at rest using AWS KMS provides server-side encryption for sensitive patient data, while IAM policies allow fine-grained access control to ensure only authorized services can access the table. This combination directly meets both the encryption and access control requirements without unnecessary complexity or service mismatches.

Exam trap

The trap here is that candidates may confuse encryption mechanisms across services (e.g., applying S3 encryption to DynamoDB) or assume that network controls like VPC endpoints replace the need for IAM-based authorization.

How to eliminate wrong answers

Option A is wrong because client-side encryption does not protect data at rest within DynamoDB (the application must manage keys and encryption logic), and Lambda validation is not a native access control mechanism for DynamoDB—IAM policies are required. Option B is wrong because S3 server-side encryption and bucket policies apply to Amazon S3, not DynamoDB; DynamoDB does not use S3 for primary storage or bucket policies for access control. Option D is wrong because AWS CloudHSM is a hardware security module for key storage but does not directly integrate with DynamoDB encryption at rest (DynamoDB uses AWS KMS, not CloudHSM), and VPC endpoints control network access but not authorization—IAM policies are still needed.

1290
MCQmedium

A company is migrating a 3 TB Oracle database to Amazon RDS for Oracle. They want to use Oracle Data Pump to export the data and then import it into RDS. What is the most efficient way to transfer the dump files to AWS?

A.Use AWS Snowball to physically ship the dump files to AWS.
B.Use AWS DMS to migrate the data directly from Oracle to RDS for Oracle.
C.Upload the dump files to Amazon S3 and then import them into RDS for Oracle using Oracle Data Pump.
D.Transfer the dump files over a VPN connection to an EC2 instance and then copy to RDS.
AnswerC

S3 provides scalable storage and fast upload; RDS can read from S3 for import.

Why this answer

Uploading Oracle Data Pump dump files to Amazon S3 and then importing them into Amazon RDS for Oracle using the DBMS_DATAPUMP API is the most efficient method for transferring large dump files. This approach leverages S3 for scalable, durable storage and high-throughput transfer, avoiding network bottlenecks or physical shipping delays. The RDS for Oracle instance can directly access the S3 bucket via an IAM role, enabling a seamless import process.

Exam trap

The trap here is that candidates may assume AWS Snowball is always the best choice for large data transfers, but for 3 TB with available network bandwidth, direct S3 upload is more efficient and avoids physical shipping delays.

How to eliminate wrong answers

Option A is wrong because AWS Snowball is designed for petabyte-scale data transfers where network bandwidth is insufficient, but for a 3 TB database, uploading to S3 over a high-speed internet connection or AWS Direct Connect is more efficient and avoids the logistical overhead of physical shipping. Option B is wrong because AWS DMS is a continuous replication tool for migrating live databases with minimal downtime, not for importing static Data Pump dump files; it would require a separate schema conversion and does not use Oracle Data Pump. Option D is wrong because transferring dump files over a VPN to an EC2 instance and then copying to RDS adds unnecessary intermediate steps and latency, whereas direct upload to S3 provides faster, parallelized transfer and native integration with RDS for Oracle.

1291
Multi-Selecthard

Which THREE metrics should be monitored in Amazon CloudWatch to detect a potential memory leak in an Amazon RDS for SQL Server instance? (Choose three.)

Select 3 answers
A.DatabaseConnections
B.CPUUtilization
C.ReadIOPS
D.SwapUsage
E.FreeableMemory
AnswersA, D, E

If connections are not released, memory usage may increase.

Why this answer

Options A, D, and E are correct. DatabaseConnections can indicate a memory leak if connections are not closed, consuming memory. SwapUsage indicates memory pressure when physical memory is insufficient.

FreeableMemory shows available memory; a decreasing trend may suggest a leak. Option B is incorrect because CPUUtilization is not a direct memory metric. Option C is incorrect because ReadIOPS relates to I/O operations, not memory.

1292
MCQeasy

A company recently migrated an on-premises PostgreSQL database to Amazon RDS for PostgreSQL. The database is 100 GB and used by a web application. After migration, the application's response time increased. The 'ReadLatency' and 'WriteLatency' metrics are normal. The 'CPUUtilization' is at 90%. The 'DatabaseConnections' metric shows 200 connections, which is close to the max connections for the instance class (db.t3.medium, max connections = 200). The application uses connection pooling. The team wants to reduce CPU utilization without changing the application code. Which action should the team take?

A.Decrease 'max_connections' parameter to 100.
B.Increase allocated storage to 200 GB.
C.Upgrade the DB instance to a larger class like db.t3.large.
D.Enable Performance Insights and switch to Provisioned IOPS.
AnswerC

A larger instance class provides more CPU cores and higher performance.

Why this answer

Upgrading to a larger instance class, such as db.t3.large, provides more CPU resources (additional vCPUs), directly addressing the high CPU utilization (90%) while maintaining the same number of database connections. Option A is incorrect because decreasing 'max_connections' to 100 risks rejecting legitimate connections from the application's connection pool, potentially causing errors even though connection pooling is in use. Option B is incorrect because increasing allocated storage improves I/O throughput but does not reduce CPU utilization; the I/O latency metrics are already normal.

Option D is incorrect because enabling Performance Insights adds monitoring overhead and switching to Provisioned IOPS improves I/O performance, but the bottleneck is CPU, not I/O.

1293
MCQhard

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. During the migration, the database administrator notices that the CPU utilization on the RDS instance is consistently above 90% during peak hours, even though the on-premises server had similar specifications. The application queries are mostly SELECT statements with occasional DML. The RDS instance is db.r5.large with 500 GB of General Purpose SSD (gp2) storage. Which change would most likely reduce CPU utilization?

A.Create a read replica and redirect all SELECT queries to the replica.
B.Enable Multi-AZ to offload CPU to the standby instance.
C.Increase the allocated storage to 1 TB to improve I/O performance.
D.Upgrade to a larger instance type, such as db.r5.xlarge.
AnswerD

A larger instance provides more CPU cores and better performance, directly addressing high CPU utilization.

Why this answer

The db.r5.large instance type has 2 vCPUs and 16 GiB of memory. Sustained CPU utilization above 90% during peak hours indicates that the instance is compute-bound for the workload. Upgrading to db.r5.xlarge (4 vCPUs, 32 GiB memory) doubles the available CPU capacity, directly reducing CPU utilization for the same query load.

The on-premises server had similar specifications, but RDS instances may have different CPU architectures or hypervisor overhead, making the larger instance the most direct fix.

Exam trap

AWS often tests the misconception that increasing storage or adding a read replica can solve CPU bottlenecks, but the correct answer requires recognizing that CPU saturation is a compute issue best addressed by scaling instance size.

How to eliminate wrong answers

Option A is wrong because creating a read replica and redirecting SELECT queries offloads read traffic from the primary instance, but the primary still handles all DML and writes; if the CPU bottleneck is from both SELECT and DML processing on the primary, the replica does not reduce the primary's CPU load. Option B is wrong because Multi-AZ provides a standby instance for failover only; the standby does not serve read traffic or offload CPU from the primary—it is a synchronous replica that is not active for queries. Option C is wrong because increasing gp2 storage to 1 TB increases baseline IOPS from 1500 to 3000, which improves I/O throughput, but the problem is CPU utilization, not I/O latency or throughput; the instance is compute-bound, not storage-bound.

1294
MCQmedium

A financial services company uses Amazon Redshift for analytics. The workload consists of a mix of short-running queries from dashboards and long-running ETL jobs. The company notices that during peak hours, short queries experience high latency due to queueing behind ETL jobs. How can the company reduce the impact of ETL jobs on dashboard queries?

A.Configure workload management (WLM) queues to separate ETL and dashboard queries, and assign different concurrency levels.
B.Enable concurrency scaling to handle bursts of queries.
C.Enable short query acceleration (SQA) to prioritize queries that run under a certain time threshold.
D.Increase the number of nodes in the Redshift cluster.
AnswerA

WLM allows resource allocation per queue, ensuring dashboard queries have dedicated resources.

Why this answer

Amazon Redshift's Workload Management (WLM) allows you to create separate queues for different query types, such as ETL jobs and dashboard queries. By assigning different concurrency levels to each queue, you prevent long-running ETL jobs from consuming all available slots and blocking short dashboard queries, thereby reducing latency during peak hours.

Exam trap

The trap here is that candidates often confuse concurrency scaling or SQA as solutions for queueing, but these features do not isolate workloads; they only add capacity or prioritize within a single queue, whereas WLM queue separation directly addresses the root cause by dedicating resources per workload type.

How to eliminate wrong answers

Option B is wrong because concurrency scaling is designed to handle bursts of read queries by adding transient clusters, but it does not prioritize or isolate queries within the same cluster; it simply adds more capacity, which may not address the queueing issue if ETL jobs still consume all slots. Option C is wrong because Short Query Acceleration (SQA) prioritizes short-running queries within a single WLM queue by predicting their runtime, but it does not isolate ETL jobs from dashboard queries; if the queue is full of ETL jobs, SQA cannot bypass the queue entirely. Option D is wrong because increasing the number of nodes adds more compute capacity but does not change the queueing behavior; without WLM queue separation, ETL jobs can still fill all available slots and cause latency for short queries.

1295
MCQmedium

A company needs to implement a database solution for a global e-commerce platform that requires strongly consistent reads and writes with automatic failover across AWS Regions. Which service should be used?

A.Amazon DynamoDB global tables.
B.Amazon RDS for MySQL with Multi-AZ and cross-Region read replicas.
C.Amazon ElastiCache for Redis with Global Datastore.
D.Amazon Aurora Global Database.
AnswerD

Provides cross-Region replication and failover with strong consistency.

Why this answer

Amazon Aurora Global Database is the correct choice because it provides strongly consistent reads and writes across multiple AWS Regions with automatic failover. It uses a primary cluster in one Region and up to five secondary read-only clusters in other Regions, with replication typically under one second. Failover to a secondary Region can be promoted in as little as one minute, meeting the requirements for a global e-commerce platform.

Exam trap

The trap here is that candidates often confuse DynamoDB global tables' eventual consistency with strong consistency, or assume Multi-AZ RDS provides cross-Region failover, when in fact Multi-AZ is limited to a single Region and cross-Region replicas require manual intervention.

How to eliminate wrong answers

Option A is wrong because Amazon DynamoDB global tables offer multi-Region replication but provide eventual consistency for reads by default, not strong consistency, and writes are only strongly consistent within a single Region. Option B is wrong because Amazon RDS for MySQL with Multi-AZ and cross-Region read replicas does not support automatic failover across Regions; Multi-AZ failover is within a single Region, and cross-Region replicas require manual promotion. Option C is wrong because Amazon ElastiCache for Redis with Global Datastore is an in-memory cache, not a durable database, and it does not guarantee strong consistency for writes across Regions.

1296
Multi-Selectmedium

A company is migrating a self-managed MongoDB database to Amazon DocumentDB (with MongoDB compatibility). Which TWO actions should the company take to ensure a successful migration? (Choose two.)

Select 2 answers
A.Use AWS Schema Conversion Tool (SCT) to convert MongoDB schemas to DocumentDB compatible format.
B.Use AWS Database Migration Service (DMS) to migrate data from MongoDB Atlas to DocumentDB.
C.Use AWS DMS to perform a full load and ongoing replication from MongoDB to DocumentDB.
D.Use AWS DMS with an Amazon EBS snapshot as the source for the migration.
E.Use AWS DMS to migrate data from MongoDB to Amazon DynamoDB, then import into DocumentDB.
AnswersA, C

SCT helps convert schemas for compatibility.

Why this answer

AWS Schema Conversion Tool (SCT) can convert MongoDB schemas to a format compatible with Amazon DocumentDB, handling data type mappings and index definitions. This is essential because DocumentDB uses a different storage engine and schema structure than MongoDB, and SCT automates the conversion of collections, indexes, and validation rules to ensure compatibility before migration.

Exam trap

The trap here is that candidates often assume DMS can migrate from any MongoDB deployment (including Atlas) or that EBS snapshots are valid sources, but DMS strictly requires a live MongoDB endpoint with oplog access for CDC.

1297
Multi-Selecthard

Which THREE of the following are required to set up cross-Region replication for an Amazon RDS for MySQL DB instance? (Choose THREE.)

Select 3 answers
A.The backup retention period on the source must be at least 1 day.
B.The source DB instance must be in a VPC.
C.A read replica must be created in the target Region.
D.Automated backups must be enabled on the source DB instance.
E.The source DB instance must be a Multi-AZ deployment.
AnswersB, C, D

Correct. The source DB instance must be in a VPC to allow network connectivity for cross-Region replication.

Why this answer

For cross-Region replication of an Amazon RDS for MySQL DB instance, the source DB instance must have automated backups enabled (option D). This is typically achieved by setting a backup retention period of at least 1 day (option A is not a separate requirement; it is the mechanism to enable automated backups). The source DB instance must be in a VPC (option B), and a read replica must be created in the target Region (option C).

Multi-AZ deployment (option E) is not required.

Exam trap

A common trap is to select both option A and option D as separate requirements. In reality, enabling automated backups (option D) essentially requires a non-zero backup retention period (such as 1 day), so they represent the same requirement. The exam expects you to recognize that the fundamental requirement is having automated backups enabled, not the specific retention period value.

Another trap is thinking that Multi-AZ deployment is required, but it is not.

1298
MCQeasy

A company is deploying Amazon DynamoDB for a new application. The application requires single-digit millisecond latency for read operations. Which DynamoDB feature should be configured to meet this requirement?

A.DynamoDB Accelerator (DAX)
B.DynamoDB Streams
C.Auto Scaling
D.Time to Live (TTL)
AnswerA

DAX provides in-memory caching for fast reads.

Why this answer

DynamoDB Accelerator (DAX) is an in-memory caching service that sits between your application and DynamoDB, providing microsecond to single-digit millisecond latency for read-heavy workloads. By caching frequently accessed items, DAX offloads read traffic from the underlying DynamoDB tables, ensuring consistent low-latency responses even under high concurrency.

Exam trap

The trap here is that candidates may confuse DynamoDB Streams (a change-data-capture feature) with a performance optimization tool, or assume Auto Scaling directly reduces latency when it only manages throughput capacity.

How to eliminate wrong answers

Option B (DynamoDB Streams) is wrong because it captures a time-ordered sequence of item-level changes in a table for event-driven processing, not for improving read latency. Option C (Auto Scaling) is wrong because it automatically adjusts provisioned throughput capacity based on traffic patterns, but it does not reduce read latency — it only helps maintain throughput under varying load. Option D (Time to Live) is wrong because it automatically deletes expired items from tables to manage storage costs, with no impact on read performance or latency.

1299
MCQhard

A company is running an Amazon RDS for SQL Server instance with Multi-AZ deployment. The database is used by a critical application. During a recent failover test, the application experienced a 2-minute downtime. The application's connection string uses the DB instance endpoint, not the cluster endpoint. Which change would minimize downtime during future failovers?

A.Modify the application to use the cluster endpoint instead of the instance endpoint
B.Increase the DB instance class size
C.Create a read replica in a different Availability Zone
D.Enable Multi-AZ on the DB instance
AnswerA

The cluster endpoint points to the current primary and updates automatically after failover, reducing downtime.

Why this answer

Using the cluster endpoint (the DNS name that automatically points to the current primary after failover) allows the application to reconnect to the new primary without waiting for DNS propagation, thus minimizing downtime. Option B is incorrect because increasing the DB instance class size does not reduce failover time. Option C is incorrect because read replicas are used for read scaling, not for reducing failover downtime.

Option D is incorrect because Multi-AZ is already enabled, so enabling it again would have no effect.

1300
Multi-Selectmedium

A company is using Amazon DynamoDB and wants to monitor the read/write capacity utilization of a table. Which ONE AWS service can be used to set up alarms for capacity consumption?

Select 1 answer
A.Amazon DynamoDB Auto Scaling
B.AWS CloudTrail
C.Amazon CloudWatch Logs
D.Amazon CloudWatch
E.AWS Config
AnswersD

Amazon CloudWatch provides metrics for DynamoDB read/write capacity consumption and allows you to set alarms on these metrics. It is the direct and correct service for monitoring capacity utilization.

Why this answer

Amazon CloudWatch (D) is the primary service for monitoring DynamoDB capacity metrics such as ConsumedReadCapacityUnits and ConsumedWriteCapacityUnits, and it can trigger alarms based on thresholds. Option C (Amazon CloudWatch Logs) is not used for direct capacity monitoring because DynamoDB does not emit capacity consumption logs; those metrics are available only through CloudWatch Metrics. DynamoDB Auto Scaling (A) adjusts capacity but does not monitor or alarm.

AWS CloudTrail (B) records API calls, not capacity metrics. AWS Config (E) tracks configuration changes, not utilization.

1301
Multi-Selecteasy

Which TWO AWS services can be used to cache database query results to improve read performance? (Select TWO.)

Select 2 answers
A.Amazon DynamoDB Accelerator (DAX)
B.Amazon ElastiCache for Redis
C.Amazon CloudFront
D.Amazon ElastiCache for Memcached
E.Amazon RDS read replica
AnswersB, D

In-memory cache for query results.

Why this answer

Amazon ElastiCache for Redis and Amazon ElastiCache for Memcached are in-memory caching services that can store the results of database queries, allowing subsequent identical queries to be served from the cache instead of hitting the database. This reduces latency and improves read performance by offloading read traffic from the primary database.

Exam trap

The trap here is that candidates often confuse read replicas with caching, but read replicas are full database copies that still execute queries, whereas ElastiCache stores pre-computed results in memory for near-instant retrieval.

1302
MCQeasy

A company needs to migrate an on-premises PostgreSQL database to Amazon Aurora PostgreSQL. The database is 2 TB in size and has a 24/7 uptime requirement. Which AWS service should be used to perform the migration with minimal downtime?

A.AWS Schema Conversion Tool (SCT)
B.AWS S3
C.pg_dump and pg_restore
D.AWS Database Migration Service (DMS)
AnswerD

DMS supports live migration with CDC.

Why this answer

AWS Database Migration Service (DMS) is the correct choice because it supports ongoing replication from an on-premises PostgreSQL source to Amazon Aurora PostgreSQL, enabling a migration with minimal downtime. DMS can perform a full load of the 2 TB database and then continuously replicate changes using PostgreSQL's logical replication (via the pglogical extension or native slot-based replication) until the cutover, keeping the source available throughout the process.

Exam trap

The trap here is that candidates often choose pg_dump and pg_restore (Option C) because they are familiar PostgreSQL tools, but they overlook the 24/7 uptime requirement and the fact that pg_dump requires a consistent snapshot, which for a 2 TB database would cause hours of downtime during the dump and restore process.

How to eliminate wrong answers

Option A is wrong because AWS Schema Conversion Tool (SCT) is used for converting database schemas and code when migrating between different database engines (e.g., Oracle to Aurora PostgreSQL), not for migrating data with minimal downtime; it does not handle ongoing replication. Option B is wrong because AWS S3 is an object storage service and cannot directly migrate or replicate a live PostgreSQL database; it could be used as an intermediate staging area for exported data but would require manual export/import steps that cause significant downtime. Option C is wrong because pg_dump and pg_restore are native PostgreSQL utilities that perform a logical backup and restore, which requires the source database to be quiesced or locked during the dump to ensure consistency, resulting in substantial downtime for a 2 TB database.

1303
Multi-Selectmedium

A company is using Amazon Redshift and notices that queries are running slowly. Which TWO system views should be used to identify the cause of the slow queries? (Choose TWO.)

Select 2 answers
A.STV_TBL_PERM
B.PG_TABLE_DEF
C.STL_QUERY
D.STL_LOAD_COMMITS
E.SVV_QUERY_STATE
AnswersC, E

STL_QUERY logs all queries with execution details, useful for identifying slow queries after they have run.

Why this answer

The correct answers are C and E. STL_QUERY contains detailed logs of all queries, including execution times, enabling identification of slow queries after execution. SVV_QUERY_STATE shows currently running queries, helping identify those that are running slowly.

Option A (STV_TBL_PERM) is for table permissions, not performance. Option B (PG_TABLE_DEF) shows table definitions. Option D (STL_LOAD_COMMITS) shows load commit information.

1304
MCQhard

A gaming company uses Amazon RDS for PostgreSQL to store player profiles and game state. They report slow queries during peak hours. The DB instance is a db.r5.2xlarge with 500 GB gp2 storage. Which design change would MOST improve read performance for the most frequently accessed player profiles?

A.Implement application-level sharding by player ID
B.Increase provisioned IOPS on the existing volume
C.Upgrade to a db.r5.4xlarge instance
D.Add a read replica in the same AZ
AnswerD

Read replicas offload read traffic from the primary, improving performance for read-heavy workloads.

Why this answer

Adding a read replica in the same Availability Zone (AZ) offloads read traffic from the primary RDS for PostgreSQL instance, directly improving read performance for frequently accessed player profiles during peak hours. Read replicas asynchronously replicate data using PostgreSQL's streaming replication and can serve SELECT queries without impacting the primary instance's write workload or connection limits.

Exam trap

The trap here is that candidates confuse increasing instance size (Option C) or IOPS (Option B) as the only way to fix slow queries, when the real solution is to offload read traffic to a read replica, which is a common AWS exam pattern for read-heavy workloads on RDS.

How to eliminate wrong answers

Option A is wrong because application-level sharding by player ID distributes write and read load across multiple databases, but it requires significant application changes and does not directly address read performance on the existing single RDS instance; it is an architectural redesign, not a quick design change. Option B is wrong because increasing provisioned IOPS on the existing gp2 volume improves I/O throughput for write-heavy or latency-sensitive operations, but the bottleneck described is read performance during peak hours, and gp2 already provides baseline IOPS proportional to size (1500 IOPS for 500 GB) with burst credits; the issue is likely CPU or connection saturation, not storage I/O. Option C is wrong because upgrading to a db.r5.4xlarge instance doubles the compute and memory resources, which can improve overall performance, but it does not isolate read traffic from write traffic; the primary instance still handles all reads and writes, so read performance gains are limited by the same contention and replication lag is not addressed.

1305
Multi-Selectmedium

A company is using Amazon Redshift for data warehousing. The database administrator needs to optimize query performance. Which TWO actions should the administrator take? (Choose TWO.)

Select 2 answers
A.Increase the number of nodes in the cluster.
B.Analyze the tables to update statistics for the query optimizer.
C.Enable encryption for the cluster.
D.Disable compression on the tables to reduce CPU overhead.
E.Run the VACUUM command to reclaim space and re-sort data.
AnswersB, E

Updated statistics help the optimizer choose efficient query plans.

Why this answer

Options B and E are correct. Analyzing tables updates statistics for the query optimizer, enabling efficient query plan generation. Running VACUUM reclaims space and re-sorts data, improving data distribution and query performance.

Option A is incorrect because increasing nodes is a scaling action, not an optimization action, and adds cost. Option C is incorrect because enabling encryption does not directly impact query performance. Option D is incorrect because disabling compression increases storage and I/O, degrading performance.

1306
MCQeasy

A developer is receiving timeout errors when connecting to an Amazon ElastiCache for Redis cluster from an Amazon EC2 instance. The security group for the EC2 instance allows outbound traffic to the Redis cluster's security group on port 6379. The Redis cluster's security group does not allow inbound traffic from the EC2 instance. What is the most likely cause of the timeout?

A.The network ACL for the Redis subnet is blocking inbound traffic on port 6379
B.The Redis cluster security group does not have an inbound rule allowing traffic from the EC2 security group on port 6379
C.The subnet route table does not have a route to the Redis cluster
D.The Redis cluster is not accessible from within the same VPC
AnswerB

Inbound rules are required for the target security group.

Why this answer

Security groups are stateful, meaning that if an outbound rule allows traffic, the return traffic is automatically allowed. However, inbound traffic must be explicitly permitted by the target security group. In this scenario, the EC2 instance's security group allows outbound traffic to the Redis cluster's security group on port 6379, but the Redis cluster's security group does not have an inbound rule allowing traffic from the EC2 security group on that port.

Therefore, the connection is blocked, causing timeout errors. Option A is incorrect because network ACLs are stateless and would affect both inbound and outbound traffic, but the issue is specifically with security groups. Option C is incorrect because subnet route tables control network routing, not port-level access.

Option D is incorrect because ElastiCache for Redis clusters are accessible within the same VPC if proper security group rules are configured.

1307
MCQeasy

A company is migrating a MySQL database to Amazon Aurora MySQL. The current database uses multi-statement transactions with read committed isolation level. The application frequently encounters deadlocks on the source database. Which Aurora MySQL feature can help reduce deadlocks without application changes?

A.Use Amazon Aurora Auto Scaling to automatically adjust the number of replicas.
B.Use Amazon Aurora Global Database to replicate data to multiple regions.
C.Use Amazon RDS Proxy to pool and share database connections.
D.Use Amazon Aurora Backtrack to quickly revert transactions.
AnswerC

RDS Proxy reduces connection contention and can help reduce deadlocks.

Why this answer

RDS Proxy helps reduce deadlocks by pooling and reusing database connections, which minimizes the overhead of establishing new connections and reduces contention on database resources. In MySQL, deadlocks often occur when multiple transactions compete for the same resources under high connection churn; by maintaining a stable pool of connections, RDS Proxy lowers the probability of concurrent conflicting locks. Since the proxy is transparent to the application, no code changes are required to benefit from this behavior.

Exam trap

The trap here is that candidates confuse deadlock reduction with high-availability or disaster-recovery features, mistakenly thinking that scaling replicas (Auto Scaling) or global replication (Global Database) can resolve concurrency conflicts, when in fact the key is connection management and reducing lock contention.

How to eliminate wrong answers

Option A is wrong because Aurora Auto Scaling adjusts the number of read replicas based on load, which does not address deadlock reduction—deadlocks are a concurrency and locking issue, not a capacity issue. Option B is wrong because Aurora Global Database replicates data across regions for disaster recovery and low-latency reads, but it does not reduce deadlocks on the primary instance; in fact, it can introduce additional replication-related locks. Option D is wrong because Aurora Backtrack allows reverting transactions to a point in time, which is a recovery feature, not a prevention mechanism—it does not reduce the occurrence of deadlocks during normal operation.

1308
Multi-Selecthard

A company is using Amazon DynamoDB with a global table in two regions. The application is experiencing high write latency on the replica table in the secondary region. Which THREE factors could contribute to this issue?

Select 3 answers
A.Large item sizes being written to the table.
B.Network latency between the primary and secondary regions.
C.Auto scaling configuration on the replica table.
D.Low read capacity on the replica table.
E.Insufficient write capacity on the replica table.
AnswersA, B, E

Larger items take longer to replicate.

Why this answer

Global tables replicate writes asynchronously. Large item sizes (A) increase the time to process each write. Network latency (B) between regions affects the replication time.

Insufficient write capacity (E) on the replica table can cause throttling and increased latency. Auto scaling configuration (C) is not a direct cause; it helps manage capacity. Read capacity (D) does not affect write latency.

1309
MCQmedium

A company runs an Amazon Aurora MySQL database cluster with a primary instance and two Aurora Replicas. The application is experiencing occasional deadlocks on the primary instance during peak hours. The deadlocks cause transaction rollbacks that impact customer experience. Which design change should the company implement to minimize deadlocks?

A.Enable Aurora Auto Scaling for read replicas and offload read-only queries to replicas.
B.Set the transaction isolation level to READ UNCOMMITTED to avoid locks.
C.Configure Multi-AZ deployment to automatically failover during deadlocks.
D.Increase the DB instance class size to handle more concurrent transactions.
AnswerA

Reducing read load on the primary instance decreases lock contention and the likelihood of deadlocks.

Why this answer

Offloading read-only queries to Aurora Replicas reduces the volume of read-write contention on the primary instance. Deadlocks often arise when concurrent transactions compete for the same resources; by directing read traffic to replicas, the primary handles fewer overlapping transactions, lowering the probability of lock conflicts. Aurora Replicas share the same underlying storage volume and serve read traffic without blocking writes on the primary, making this a targeted solution for deadlock reduction.

Exam trap

The trap here is that candidates may assume increasing instance size (Option D) is the universal fix for performance issues, but deadlocks are a concurrency control problem, not a capacity problem, and scaling up can actually worsen contention by allowing more simultaneous transactions.

How to eliminate wrong answers

Option B is wrong because setting the transaction isolation level to READ UNCOMMITTED introduces dirty reads and does not eliminate deadlocks—it only reduces shared locks for reads, but write locks still cause deadlocks. Option C is wrong because Multi-AZ deployment provides high availability via automatic failover but does not prevent or reduce deadlocks; failover occurs after a disruption, not during a deadlock event. Option D is wrong because increasing the DB instance class size improves throughput and concurrency capacity but does not address the root cause of deadlocks—contention on the same rows or pages—and may even increase deadlock frequency by allowing more concurrent transactions.

1310
MCQhard

A team is troubleshooting a DynamoDB table that has high read latency. The table uses on-demand capacity and has a global secondary index (GSI). Which configuration is MOST likely causing the issue?

A.The GSI has provisioned capacity set too low
B.Time-to-Live (TTL) is enabled
C.DAX is enabled for the table
D.The table uses on-demand capacity
AnswerA

GSIs have independent capacity; throttling on GSI causes high latency.

Why this answer

An under-provisioned GSI can throttle reads even if the base table uses on-demand. Option B is wrong because TTL does not affect read latency. Option C is wrong because DAX reduces latency, not increases.

Option D is wrong because on-demand capacity handles bursts and does not cause high latency.

1311
MCQmedium

A company runs an Amazon Aurora MySQL database cluster with one writer and one reader instance. The application experiences intermittent connection timeouts during peak traffic. The DB cluster parameter group has 'connect_timeout' set to 5 seconds. What should a database specialist recommend to reduce connection timeouts?

A.Add additional reader instances to distribute the load.
B.Enable RDS Proxy for the cluster.
C.Increase the 'connect_timeout' parameter to 10 seconds.
D.Enable IAM database authentication and require TLS.
AnswerB

RDS Proxy provides connection pooling and reduces overhead, helping to prevent timeouts during peak traffic.

Why this answer

Enabling RDS Proxy reduces connection overhead and provides a connection pool, mitigating timeouts. Option A is incorrect because adding readers does not help with writer connection timeouts; the issue is with the writer instance. Option C is incorrect because increasing connect_timeout only delays the timeout, not the root cause.

Option D is incorrect because the issue is not related to TLS.

1312
MCQhard

A company has an Amazon Aurora MySQL DB cluster with a primary instance and two Aurora Replicas. The application is experiencing high write latency. The primary instance's CPU utilization is at 90%, while the replicas are at 30%. The DB cluster parameter group has the default values. Which change is most likely to reduce write latency?

A.Increase the DB instance class of the primary instance.
B.Add more Aurora Replicas to distribute the write load.
C.Disable the binary log (binlog) on the DB cluster.
D.Increase the allocated storage of the cluster.
AnswerC

Binary logging adds CPU overhead; disabling it can reduce write latency.

Why this answer

High CPU utilization on the primary instance is often caused by the binary log (binlog) being enabled, which is enabled by default for Aurora MySQL. Binlog generation adds overhead to write operations. Disabling binlog reduces CPU usage on the primary, thereby reducing write latency.

Increasing the instance class (Option A) could help but is not as directly targeted as disabling binlog. Adding more Aurora Replicas (Option B) does not reduce write latency on the primary because replicas handle read traffic only. Increasing allocated storage (Option D) does not affect CPU or write latency.

1313
MCQeasy

A company wants to migrate a 200 GB SQL Server database to Amazon RDS for SQL Server with minimal downtime. The database is used by a critical application. Which service should be used for the migration?

A.AWS Schema Conversion Tool (SCT).
B.AWS Database Migration Service (DMS).
C.SQL Server Import and Export Wizard.
D.SQL Server Management Studio (SSMS) backup and restore.
AnswerB

DMS supports near-zero downtime migration with CDC.

Why this answer

AWS DMS is the correct choice because it supports ongoing replication (change data capture) from a SQL Server source to an Amazon RDS for SQL Server target, enabling a migration with minimal downtime. DMS can perform a full load of the 200 GB database and then continuously replicate changes until the cutover, which is essential for a critical application that cannot tolerate extended downtime.

Exam trap

The trap here is that candidates often confuse AWS SCT (schema conversion) with AWS DMS (data migration), assuming SCT can also handle data movement, when in fact SCT only converts schema and assesses compatibility, while DMS handles the actual data transfer and ongoing replication.

How to eliminate wrong answers

Option A is wrong because AWS Schema Conversion Tool (SCT) is used for converting database schemas to a different database engine (e.g., SQL Server to Aurora), not for migrating data to the same engine with minimal downtime. Option C is wrong because the SQL Server Import and Export Wizard is a manual, one-time data transfer tool that does not support ongoing replication, resulting in significant downtime for a 200 GB database. Option D is wrong because SSMS backup and restore requires taking a full backup, transferring it, and restoring, which incurs downtime during the backup and restore process and does not support continuous replication for minimal downtime.

1314
MCQmedium

A developer reports that an application using Amazon DynamoDB is experiencing high latency during peak hours. The table has a provisioned capacity of 500 read capacity units (RCUs) and 500 write capacity units (WCUs). The application uses eventually consistent reads and the table is about 50 GB. The developer notices throttled write requests in CloudWatch. Which action would most effectively reduce write throttling?

A.Enable DynamoDB Accelerator (DAX) for the table.
B.Create a global secondary index on the table.
C.Increase the provisioned write capacity for the table.
D.Switch from eventually consistent reads to strongly consistent reads.
AnswerC

Increasing write capacity units reduces throttling for write requests.

Why this answer

The developer reports throttled write requests, which directly indicates that the provisioned write capacity (500 WCUs) is insufficient to handle the peak write traffic. Increasing the provisioned write capacity for the table is the most direct and effective action to eliminate write throttling, as it raises the limit on write operations per second. Option C is correct because it addresses the root cause—write capacity exhaustion—without introducing unnecessary components or changing read behavior.

Exam trap

The trap here is that candidates may confuse read performance solutions (DAX, consistency changes) with write throttling issues, or incorrectly assume that adding a GSI will offload write traffic, when in fact it increases the write capacity burden on the base table.

How to eliminate wrong answers

Option A is wrong because DynamoDB Accelerator (DAX) is an in-memory cache that reduces read latency, not write throttling; it does not increase write capacity or reduce write request throttling. Option B is wrong because creating a global secondary index (GSI) does not reduce write throttling on the base table; in fact, GSIs consume additional write capacity from the base table's provisioned throughput, potentially worsening throttling. Option D is wrong because switching from eventually consistent reads to strongly consistent reads doubles the read capacity consumption per read request, increasing read throttling risk and having no effect on write throttling.

1315
MCQeasy

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database contains personally identifiable information (PII). The security team requires that the data be encrypted at rest using a customer-managed key stored in AWS KMS. Additionally, the team wants to ensure that the key can be rotated automatically every year. What should the company do to meet these requirements?

A.Enable encryption on the RDS instance using the default RDS encryption and use AWS Secrets Manager to store the key.
B.Create a customer-managed key in AWS KMS, enable automatic rotation, and enable encryption on the RDS instance using that key.
C.Create a customer-managed key in AWS KMS without automatic rotation, and manually rotate the key using the RDS console.
D.Use an AWS managed key for RDS and create an AWS Lambda function to rotate the key manually each year.
AnswerB

Customer-managed KMS keys support automatic annual rotation.

Why this answer

The correct approach is to create a customer-managed key in AWS KMS with automatic rotation enabled, then enable encryption on the RDS instance using that key. This meets the requirements for encryption at rest with a customer-managed key and automatic annual rotation. Option A is incorrect because AWS Secrets Manager is used for storing secrets, not encryption keys.

Option C lacks automatic rotation. Option D uses an AWS managed key, not customer-managed, and requires a manual Lambda function, not automatic rotation.

1316
Multi-Selecthard

An e-commerce application uses Amazon Aurora MySQL with a Multi-AZ DB cluster. During a recent load test, the application experienced increased read latency. The database cluster consists of one writer and two reader instances. Which THREE actions should be taken to improve read performance?

Select 3 answers
A.Configure cross-Region read replicas.
B.Increase the instance class of the writer instance.
C.Add more reader instances to the cluster.
D.Enable Aurora Auto Scaling for the reader instances.
E.Implement Amazon ElastiCache for caching frequent queries.
AnswersC, D, E

Adding more reader instances distributes the read load across more instances, reducing the load per instance and thus read latency.

Why this answer

Adding more reader instances (Option C) directly reduces the read load per instance, improving read performance. Enabling Aurora Auto Scaling (Option D) automatically adjusts the number of reader instances based on demand, ensuring optimal performance. Implementing Amazon ElastiCache (Option E) caches frequent queries at the application layer, reducing the number of read requests hitting the database.

Option A (configuring cross-Region read replicas) introduces network latency and is primarily used for global scaling or disaster recovery, not for reducing latency in a single-region application. Option B (increasing the writer instance class) improves write performance but does not directly affect read latency.

1317
MCQmedium

An application running on Amazon EC2 is unable to connect to an Amazon RDS for SQL Server DB instance. The security group for the RDS instance allows inbound traffic from the security group of the EC2 instance on port 1433. The network ACLs allow all traffic. What is a likely cause of the connectivity issue?

A.The RDS instance is in a private subnet and does not have a public IP address
B.The network ACL is blocking the traffic
C.The security group inbound rule is incorrectly configured
D.The database port is not 1433
AnswerA

Without a public IP, the EC2 instance cannot reach it over the internet.

Why this answer

If the RDS instance is in a private subnet without a public IP address, the EC2 instance cannot connect using the public DNS endpoint unless the EC2 is in the same VPC. Since the security group and network ACLs are correctly configured, the most likely cause is that the RDS instance is not publicly accessible and the EC2 instance is attempting to connect from outside the VPC or via the public endpoint. Option B is wrong because network ACLs allow all traffic.

Option C is wrong because the security group inbound rule is correctly configured to allow traffic from the EC2 security group on port 1433. Option D is wrong because port 1433 is the default SQL Server port, and if it were not, the error message would indicate a timeout, not a connectivity issue.

1318
Multi-Selectmedium

A company is designing a database for a global e-commerce platform. The application requires single-digit millisecond read and write latency for user sessions, and must handle millions of requests per second. The data is key-value in nature. Which TWO AWS services should the company consider? (Choose two.)

Select 2 answers
A.Amazon DynamoDB
B.Amazon ElastiCache for Redis
C.Amazon Neptune
D.Amazon Redshift
E.Amazon RDS for MySQL
AnswersA, B

Key-value NoSQL database with single-digit millisecond latency.

Why this answer

Amazon DynamoDB is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale. It is designed for high-traffic applications requiring millions of requests per second, making it ideal for the global e-commerce platform's user session data.

Exam trap

The trap here is that candidates may choose Amazon RDS for MySQL or Amazon Neptune because they are familiar with SQL or graph databases, but they fail to recognize that key-value workloads with extreme throughput and latency requirements are a core use case for DynamoDB and ElastiCache, not relational or graph databases.

1319
MCQhard

A company has a multi-account AWS environment using AWS Organizations. The security team wants to centrally manage database encryption keys for all Amazon RDS instances across accounts. They require that the keys be stored in a single account, and that each account can use the key to encrypt its RDS instances. Additionally, they want to automatically rotate the keys every year. Which solution should they implement?

A.Copy the KMS key from the central account to each account using the KMS key replication feature.
B.Use AWS CloudHSM to create a key and share the HSM partition with each account.
C.Create a multi-Region customer managed KMS key in the central account and replicate it to each account.
D.Create a customer managed KMS key in the central account and grant the RDS service in each account permission to use the key.
AnswerD

KMS supports cross-account key usage for RDS encryption.

Why this answer

AWS KMS allows you to create a customer managed key in a central account and grant cross-account access to the RDS service principal in each account. This enables each account to use the central key for RDS encryption while keeping the key stored centrally. Option A is incorrect because KMS key replication is for multi-Region, not cross-account.

Option B is incorrect because CloudHSM is not integrated with RDS for encryption. Option C is incorrect because multi-Region keys are for cross-Region use, not cross-account; they do not solve the cross-account requirement.

1320
Multi-Selecthard

Which THREE actions should be taken to troubleshoot a high number of ThrottlingExceptions from Amazon DynamoDB? (Choose 3.)

Select 3 answers
A.Examine the ConsumedWriteCapacity and ThrottledWriteCount metrics in CloudWatch
B.Enable DynamoDB Streams to offload writes
C.Implement exponential backoff in the application
D.Increase the write capacity units for the table
E.Change the read consistency to eventual
AnswersA, C, D

Helps identify if capacity is exceeded.

Why this answer

A, C, D are correct. Examining CloudWatch metrics helps identify throttling patterns. Implementing exponential backoff is a best practice.

Increasing provisioned capacity resolves throttling. B is wrong because enabling DynamoDB Streams does not affect throttling. E is wrong because changing consistency model does not affect write throttling.

1321
Multi-Selecthard

A company is designing a multi-tenant SaaS application on Amazon Aurora MySQL. Each tenant has its own database, but some tenants are very large and generate high write traffic. The company wants to isolate tenant workloads to prevent a noisy neighbor from affecting other tenants. Which TWO design strategies should the database specialist recommend?

Select 2 answers
A.Use Aurora Serverless for tenants with variable workloads
B.Use a single Aurora cluster with read replicas for each tenant
C.Migrate all tenants to Amazon DynamoDB and use DynamoDB Accelerator (DAX) for caching
D.Use Amazon RDS Proxy to pool connections and limit throughput per tenant
E.Use separate Aurora clusters for high-traffic tenants
AnswersA, E

Aurora Serverless automatically scales compute capacity based on workload, minimizing impact on other tenants.

Why this answer

Aurora Serverless automatically scales compute capacity based on application demand, which is ideal for tenants with variable workloads. This prevents a noisy neighbor scenario by ensuring that a tenant's burst of write traffic does not consume shared resources that would degrade performance for other tenants.

Exam trap

The trap here is that candidates often confuse connection pooling (RDS Proxy) with resource isolation, not realizing that RDS Proxy only manages connections and does not prevent a noisy neighbor from exhausting the cluster's shared I/O or CPU capacity.

1322
MCQeasy

A retail company uses Amazon DynamoDB to store shopping cart data. The cart items are frequently updated as users add or remove products. The application reads the entire cart each time the user views it. The cart size averages 50 KB but can reach up to 400 KB. The company wants to reduce read costs and improve performance. Which design change would be most effective?

A.Switch to larger DynamoDB instance types to handle larger items.
B.Use DynamoDB Accelerator (DAX) to cache the cart data.
C.Compress the cart items before storing them in DynamoDB and decompress on read.
D.Normalize the cart data into separate tables for cart headers and line items.
AnswerC

Compression reduces the item size, lowering RCU consumption and cost.

Why this answer

Compressing cart items before storing them in DynamoDB reduces the item size, which directly lowers read capacity unit (RCU) consumption since DynamoDB charges based on read item size rounded up to 4 KB increments. For a 400 KB item, compression can shrink it significantly, reducing the number of 4 KB blocks read and thus cutting costs. Decompression on read adds minimal CPU overhead but yields substantial performance gains by reducing network transfer time and read latency.

Exam trap

The trap here is that candidates often assume caching (DAX) is the universal performance fix, but the question specifically targets reducing read costs, not just latency, and DAX does not eliminate the underlying cost of reading large items from DynamoDB.

How to eliminate wrong answers

Option A is wrong because DynamoDB is a serverless, fully managed service and does not use instance types; the concept of 'larger instances' applies to relational databases like Amazon RDS, not DynamoDB. Option B is wrong because DAX caches frequently accessed data to reduce read latency, but it does not reduce the read cost per item; you still pay for the underlying DynamoDB reads when the cache is populated or on cache misses, and the large item size still incurs high RCU consumption. Option D is wrong because normalizing cart data into separate tables (e.g., headers and line items) would require multiple read operations to reconstruct the cart, increasing read costs and latency, and DynamoDB is optimized for denormalized, single-table designs with large items.

1323
MCQhard

A company is using Amazon DynamoDB with fine-grained access control using IAM policies. The security team wants to ensure that a specific IAM role can only read the 'status' attribute from items in a table. The table is named 'Orders'. Which IAM policy statement should be used?

A.Condition: { 'ForAllValues:StringEquals': { 'dynamodb:Attributes': ['active'] } }
B.Condition: { 'ForAllValues:StringEquals': { 'dynamodb:Attributes': ['status'] } }
C.Condition: { 'ForAllValues:StringEquals': { 'dynamodb:ReturnValues': 'ALL_OLD' } }
D.Condition: { 'StringEquals': { 'dynamodb:Select': 'SPECIFIC_ATTRIBUTES' } }
AnswerB

Correct. This condition restricts access to only the 'status' attribute name, which is a step towards controlling attribute access, but it does not filter items by value. The requirement to read items with status='active' requires additional data modeling (e.g., GSI) or app-level filtering.

Why this answer

It uses the `dynamodb:Attributes` condition key with `ForAllValues:StringEquals` to restrict the request to only access the 'status' attribute. This ensures the role can only read the 'status' attribute, meeting the requirement. Option A incorrectly uses the condition to match the literal value 'active' as an attribute name.

Options C and D use invalid or irrelevant condition keys.

1324
MCQhard

A financial services company runs a critical application on Amazon RDS for PostgreSQL. They must ensure that database activity logs are sent to Amazon CloudWatch Logs for real-time monitoring. The logs must include all SQL queries, including SELECT statements. Which configuration will meet these requirements?

A.Set log_statement = 'all' and log_min_duration_statement = 0 in the DB parameter group. Enable CloudWatch Logs export.
B.Install the pgAudit extension and configure it to log all statements. Enable CloudWatch Logs export in the RDS console.
C.Set the parameter log_statement = 'ddl' in the DB parameter group. Enable CloudWatch Logs export.
D.Set log_min_duration_statement = -1 in the DB parameter group. Enable CloudWatch Logs export.
AnswerA

log_statement = 'all' logs all statements, and log_min_duration_statement = 0 ensures all durations are logged, so all queries appear in the logs.

Why this answer

Setting `log_statement = 'all'` captures every SQL statement, including SELECT, and `log_min_duration_statement = 0` ensures all statements are logged regardless of duration. Enabling CloudWatch Logs export then sends these logs to CloudWatch Logs for real-time monitoring. Option B is incorrect because while pgAudit can log all statements, it is not necessary; the built-in PostgreSQL logging with `log_statement = 'all'` meets the requirement without additional extensions.

Option C is incorrect because `log_statement = 'ddl'` only logs data definition language statements, not SELECT queries. Option D is incorrect because `log_min_duration_statement = -1` disables logging of all statements.

1325
MCQeasy

A company is running an Amazon RDS for SQL Server instance and wants to automate the patching of the database engine. Which AWS service should be used?

A.AWS Config
B.Amazon RDS Automated Backups
C.AWS Systems Manager Patch Manager
D.Amazon RDS Maintenance Window
AnswerD

Amazon RDS Maintenance Window allows you to schedule automatic patching of minor engine versions and is the correct service for automating RDS database engine patching.

Why this answer

Amazon RDS Maintenance Window is the correct service for automating patching of RDS database engines. RDS automatically applies minor engine version patches during the maintenance window, and you can schedule these windows for automated patching. AWS Systems Manager Patch Manager is not used for RDS database engine patching; it is designed for patching EC2 instances and on-premises servers.

AWS Config is for configuration compliance, and RDS Automated Backups handle backups, not patching.

Exam trap

Candidates often assume Systems Manager Patch Manager can patch RDS, but RDS patching is managed through maintenance windows, not Patch Manager.

1326
MCQeasy

A developer needs to allow an application running on an EC2 instance to read and write data to a DynamoDB table named 'Orders'. The EC2 instance is configured with an IAM role. Which IAM policy should be attached to the role?

A.{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "dynamodb:*", "Resource": "*" } ] }
B.{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "ec2:*", "Resource": "*" } ] }
C.{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "dynamodb:GetItem", "dynamodb:PutItem" ], "Resource": "arn:aws:dynamodb:us-east-1:123456789012:table/Orders" } ] }
D.{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "s3:*", "Resource": "arn:aws:s3:::example-bucket/*" } ] }
AnswerC

Correctly grants read/write to the specific table.

Why this answer

The policy grants exactly the required DynamoDB actions (GetItem and PutItem) on the specific 'Orders' table, following the principle of least privilege. Option A is incorrect because it grants full DynamoDB access to all tables, which is overly permissive. Option B is incorrect because it grants EC2 actions, not DynamoDB actions.

Option D is incorrect because it grants S3 actions instead of DynamoDB actions.

1327
MCQeasy

A database administrator is troubleshooting an issue where an Amazon RDS for PostgreSQL DB instance is not allowing connections. The administrator checks the security group and network ACLs, and they are correctly configured. What is the next step to diagnose the issue?

A.Reboot the DB instance
B.Modify the DB instance's parameter group
C.Create a DB snapshot
D.Review the DB instance error logs in Amazon CloudWatch
AnswerD

Logs can show reason for connection failures.

Why this answer

Reviewing the DB instance error logs in Amazon CloudWatch can reveal connection issues such as authentication failures, SSL/TLS errors, or the maximum number of connections being reached. This is a direct diagnostic step. Option A is incorrect because rebooting may temporarily resolve a connection issue but does not help identify the root cause.

Option B is incorrect because modifying the parameter group changes configuration settings, which is not a diagnostic action for existing connection problems. Option C is incorrect because creating a snapshot is for backup and recovery, not for troubleshooting current connectivity.

1328
MCQeasy

A company wants to migrate its on-premises Oracle database to Amazon Aurora PostgreSQL. The company needs to automatically convert the Oracle schema to PostgreSQL-compatible format. Which AWS service should the company use?

A.AWS Database Migration Service (AWS DMS) with the Oracle native dump and load option
B.AWS Server Migration Service (AWS SMS)
C.AWS Database Migration Service (AWS DMS)
D.AWS Schema Conversion Tool (AWS SCT)
AnswerD

AWS SCT automates schema conversion from Oracle to Amazon Aurora PostgreSQL.

Why this answer

AWS Schema Conversion Tool (AWS SCT) is designed specifically to convert database schemas from one engine to another, including Oracle to Amazon Aurora PostgreSQL. It automatically translates Oracle DDL (tables, indexes, stored procedures, functions, etc.) into PostgreSQL-compatible format, handling data type mappings, PL/SQL to PL/pgSQL conversion, and other schema-level transformations. AWS DMS handles data migration, not schema conversion, making SCT the correct choice for this requirement.

Exam trap

The trap here is that candidates confuse AWS DMS's data migration capability with schema conversion, assuming DMS can automatically transform the schema, when in fact DMS only moves data and requires SCT for schema translation.

How to eliminate wrong answers

Option A is wrong because AWS DMS with the Oracle native dump and load option is used for bulk data transfer, not schema conversion; it does not automatically translate Oracle schema objects to PostgreSQL format. Option B is wrong because AWS Server Migration Service (SMS) is designed for migrating on-premises virtual machines to AWS, not for database schema conversion. Option C is wrong because AWS DMS migrates data (rows and tables) but does not perform schema transformation; it relies on AWS SCT to first convert the schema before data migration.

1329
MCQhard

A company is using Amazon Redshift for data warehousing. The VACUUM operation is taking longer than expected, and the database administrator wants to identify the tables that require the most vacuuming effort. Which system table should be queried to find the percentage of deleted rows per table?

A.STL_QUERY
B.STV_TBL_PERM
C.PG_TABLE_DEF
D.SVV_TABLE_INFO
AnswerD

SVV_TABLE_INFO includes columns for unsorted rows and tombstone blocks.

Why this answer

(SVV_TABLE_INFO) is correct because this system table contains tombstone and unsorted statistics, including the percentage of deleted rows per table, which helps identify tables requiring vacuuming. Option A (STL_QUERY) is incorrect because it stores query execution logs, not table statistics. Option B (STV_TBL_PERM) is incorrect as it provides information about permanent table block allocations but not deleted row ratios.

Option C (PG_TABLE_DEF) is incorrect because it holds table schema definitions only, not operational metrics.

1330
MCQhard

A company has an Amazon DynamoDB table that stores sensitive user data. The security team requires that all data is encrypted at rest using a customer-managed AWS KMS key. Which step should be taken to meet this requirement?

A.Enable server-side encryption with S3-managed keys (SSE-S3) on the DynamoDB table.
B.Attach a bucket policy to restrict access to the DynamoDB table.
C.Specify a customer-managed KMS key in the DynamoDB table creation.
D.Modify the existing DynamoDB table to enable encryption at rest.
E.Create an IAM policy that allows dynamodb:GetItem and dynamodb:PutItem only when the request is made by the specific IAM role.
AnswerC

Correct. Specifying a customer-managed KMS key during table creation enables encryption with that key.

Why this answer

You can specify a customer-managed AWS KMS key when creating a DynamoDB table to enable encryption at rest with that key. Option E is incorrect because while you can restrict access to a specific IAM role, the question specifically asks about encryption at rest. Option A is wrong because DynamoDB uses KMS keys, not S3-managed keys.

Option B is wrong because bucket policies are for S3, not DynamoDB. Option D is wrong because encryption at rest cannot be enabled after table creation; it must be specified at creation time.

Exam trap

Candidates often confuse DynamoDB encryption options with S3 encryption. DynamoDB does not support SSE-S3 or SSE-C; it uses AWS KMS.

1331
MCQmedium

Refer to the exhibit. A company wants to migrate this RDS MySQL instance to an Aurora MySQL cluster with encryption at rest. What is the most efficient approach?

A.Use AWS DMS to migrate the database to an encrypted Aurora cluster.
B.Create a snapshot of the RDS instance, copy the snapshot with encryption, then restore to an Aurora cluster.
C.Create a snapshot of the RDS instance and restore it directly to an Aurora cluster.
D.Create an encrypted read replica in Aurora and promote it.
AnswerB

Copying the snapshot enables encryption, then restoring to Aurora creates an encrypted cluster.

Why this answer

It is the most efficient approach to migrate an RDS MySQL instance to an encrypted Aurora MySQL cluster. You first create a snapshot of the RDS instance, then copy that snapshot with encryption enabled (using an AWS KMS key), and finally restore the encrypted snapshot to an Aurora cluster. This method ensures encryption at rest is applied during the migration without requiring additional data transfer or schema conversion.

Exam trap

The trap here is that candidates often assume DMS is the only migration tool for cross-engine or encryption changes, but for RDS MySQL to Aurora MySQL with encryption, a snapshot copy with encryption is more efficient and avoids unnecessary data movement.

How to eliminate wrong answers

Option A is wrong because AWS DMS would require a full data migration, which is less efficient than using a snapshot restore, and DMS does not automatically enable encryption at rest on the target Aurora cluster unless explicitly configured. Option C is wrong because restoring a snapshot directly to an Aurora cluster does not enable encryption at rest; the snapshot must be copied with encryption first. Option D is wrong because creating an encrypted read replica in Aurora and promoting it is not possible; Aurora read replicas inherit the encryption setting of the source cluster, and you cannot add encryption to an existing unencrypted cluster via replication.

1332
MCQhard

A company wants to migrate a 2 TB Amazon RDS for MySQL DB instance to Amazon Aurora MySQL. The migration must have zero downtime and must be reversible for 48 hours. Which strategy meets these requirements?

A.Create an Aurora MySQL Read Replica from the RDS MySQL instance, then promote the replica to a standalone Aurora cluster.
B.Take a snapshot of the RDS MySQL instance, restore it to Aurora MySQL, and update the DNS.
C.Export the database using mysqldump, import into Aurora, and switch DNS.
D.Use AWS DMS with ongoing change data capture (CDC) to migrate to Aurora.
AnswerA

Read replica creation is online, promotion is fast. Fallback by deleting Aurora cluster within 48 hours.

Why this answer

Creating an Aurora MySQL Read Replica from an RDS MySQL instance uses MySQL's native asynchronous replication to keep the Aurora cluster in sync with the source, allowing a near-zero-downtime cutover by promoting the replica. The migration is fully reversible within 48 hours because the original RDS instance remains unchanged and can continue serving traffic if the promotion is rolled back.

Exam trap

The trap here is that candidates often assume AWS DMS with CDC is the only zero-downtime option, but they overlook the reversibility requirement, which is better met by the native RDS-to-Aurora replica feature that keeps the source intact.

How to eliminate wrong answers

Option B is wrong because taking a snapshot and restoring to Aurora requires downtime during the restore and DNS switch, and it is not reversible without restoring another snapshot. Option C is wrong because mysqldump export and import involves significant downtime during the data transfer and is not reversible without a full re-import. Option D is wrong because AWS DMS with CDC can achieve zero downtime, but it is not inherently reversible for 48 hours without additional infrastructure (e.g., maintaining a reverse replication task), and the question specifies a reversible strategy that keeps the original RDS instance available.

1333
MCQmedium

A company is using Amazon RDS for MySQL to power a web application. The database contains sensitive data, and the security team requires that all connections to the database use SSL/TLS. The team has enabled 'require_secure_transport' parameter in the DB parameter group. However, a developer reports that they are able to connect to the database using a MySQL client without specifying SSL options. What could be the reason?

A.The RDS instance is configured to accept both SSL and non-SSL connections by default.
B.The MySQL client automatically upgrades to SSL when the server requires it.
C.The 'require_secure_transport' parameter is not set to '1' in the DB parameter group.
D.The developer is connecting from an EC2 instance in the same VPC, which bypasses SSL enforcement.
AnswerC

The parameter must be set to '1' to enforce SSL; otherwise, non-SSL connections are allowed.

Why this answer

Enabling the 'require_secure_transport' parameter in the DB parameter group requires explicitly setting it to '1'. By default, this parameter is '0' (disabled). Even if the parameter group is associated with the RDS instance, if the parameter value is not set to '1', the database will still accept non-SSL connections.

After setting it to '1', the instance must be rebooted for the change to take effect. Option A is incorrect because 'require_secure_transport', when properly configured, rejects non-SSL connections. Option B is incorrect because the MySQL client does not automatically upgrade to SSL; it only uses SSL if explicitly requested or if the client defaults to SSL (which depends on client configuration).

Option D is incorrect because connections from within the same VPC are still subject to the database's SSL enforcement settings.

Exam trap

A common trap is assuming that simply enabling the parameter in the parameter group (e.g., clicking 'Enable') is enough. In RDS, you must set the parameter value to '1' (a string) and then reboot the instance for the change to take effect.

1334
MCQhard

A company is using Amazon DynamoDB for a gaming leaderboard. The table has a partition key of 'game_id' and a sort key of 'score'. The application performs a query to retrieve the top 10 scores for a given game_id. The query uses ScanIndexForward: false and Limit: 10. Recently, the query response time has increased. The table's read capacity is 1000 RCU, and the average item size is 1 KB. Which is the most likely cause of the increased latency?

A.The table lacks a global secondary index on game_id, causing a full table scan.
B.The query is using strongly consistent reads instead of eventually consistent reads.
C.The provisioned read capacity is too low for the query pattern.
D.A hot partition on the game_id key is causing throttling for that specific partition.
AnswerD

Even if total RCU is adequate, a single partition can exceed its throughput share, causing throttling and increased latency.

Why this answer

The increased latency is most likely due to a hot partition on the 'game_id' key. When a specific game_id receives a disproportionate amount of write or read traffic, that single partition can exceed its throughput limits (1/1000th of provisioned RCU per partition), causing throttling and retries that degrade query response time. Even though the query uses ScanIndexForward: false and Limit: 10, the request is still constrained by the partition's capacity, and throttling at the partition level leads to increased latency.

Exam trap

The trap here is that candidates often assume increased latency is due to insufficient total provisioned capacity (Option C) or a missing index (Option A), but the real issue is uneven workload distribution causing a hot partition, which is a common DynamoDB performance pitfall.

How to eliminate wrong answers

Option A is wrong because the table already has a partition key of 'game_id', so queries on game_id use the primary key directly and do not require a GSI; a full table scan would not occur. Option B is wrong because strongly consistent reads consume more RCU but do not inherently cause increased latency; the question does not indicate a change in read consistency model, and eventually consistent reads would not solve a hot partition issue. Option C is wrong because the provisioned read capacity is 1000 RCU, and with an average item size of 1 KB, this supports 1000 reads per second; the query for top 10 scores per game_id is efficient and unlikely to exhaust overall capacity unless a single partition is overloaded.

1335
MCQhard

Refer to the exhibit. A database administrator has this IAM policy attached to their user. They attempt to delete the database instance 'prod-mydb' but receive an 'AccessDenied' error. Why?

A.The policy does not allow the rds:DeleteDBInstance action for any resource.
B.The resource ARN in the Deny statement does not match the instance.
C.The user does not have permission to describe the DB instance.
D.The Deny statement explicitly denies deletion of any instance with an identifier starting with 'prod-'.
AnswerD

The Deny statement overrides the Allow, preventing deletion of prod instances.

Why this answer

The IAM policy includes an explicit Deny statement that denies the rds:DeleteDBInstance action when the resource ARN contains an instance identifier starting with 'prod-'. Explicit Deny statements override any Allow statements, so even if another policy allows deletion, this Deny blocks it for instances like 'prod-mydb'.

Exam trap

The trap here is that candidates often overlook the explicit Deny statement and focus only on the Allow statement, assuming the user has permission because the action is allowed for some resources, but they miss that the Deny specifically blocks the targeted instance identifier pattern.

How to eliminate wrong answers

Option A is wrong because the policy does allow the rds:DeleteDBInstance action for resources matching the condition in the Allow statement, but the explicit Deny overrides it. Option B is wrong because the resource ARN in the Deny statement uses a wildcard pattern (arn:aws:rds:*:*:db:prod-*) that matches the instance identifier 'prod-mydb', so the ARN does match. Option C is wrong because the error is 'AccessDenied' for the delete action, not for describing the instance; the user's ability to describe the instance is irrelevant to the delete permission.

1336
Multi-Selectmedium

A company is using Amazon Redshift for analytics. The database administrator notices that some queries are slow and the system is running out of memory. Which THREE steps should the administrator take to improve performance?

Select 3 answers
A.Increase the node size (scale up) to get more memory per node
B.Optimize the table design by choosing appropriate distkeys and sortkeys
C.Add more nodes to the cluster to increase total memory
D.Run the VACUUM command to reclaim space from deleted rows
E.Configure workload management (WLM) to limit the number of concurrent queries
AnswersB, C, E

Better data distribution reduces memory usage during joins.

Why this answer

Scaling up increases memory per node but may not be sufficient; scaling out (adding nodes) is often more effective. Option B is correct because proper distribution and sort keys minimize data shuffling and improve query performance. Option C is correct because adding more nodes increases the cluster's total memory and compute capacity.

Option D is incorrect because VACUUM reclaims disk space, not memory. Option E is correct because configuring WLM limits concurrent queries, reducing memory contention.

1337
MCQeasy

A company is deploying Amazon RDS for PostgreSQL and needs to ensure that all data at rest is encrypted. Which action should be taken to enable encryption?

A.Specify an AWS KMS key when creating the RDS instance.
B.Modify the existing RDS instance to enable encryption.
C.Enable encryption by default in the RDS console.
D.Enable encryption using S3 server-side encryption.
AnswerA

RDS encryption uses KMS keys and must be set at creation.

Why this answer

Amazon RDS for PostgreSQL supports encryption at rest using AWS Key Management Service (KMS). Encryption must be enabled at instance creation time by specifying an AWS KMS key; it cannot be enabled on an existing unencrypted instance. This ensures that the underlying storage, automated backups, read replicas, and snapshots are encrypted using the chosen KMS key.

Exam trap

The trap here is that candidates assume encryption can be toggled on after creation (like enabling encryption on an existing EBS volume), but RDS requires encryption to be set at launch time, and modifying an existing instance does not offer this option.

How to eliminate wrong answers

Option B is wrong because RDS does not allow enabling encryption on an existing unencrypted DB instance; you must create a new encrypted instance and migrate the data. Option C is wrong because there is no 'enable encryption by default' setting in the RDS console; encryption is an instance-level attribute set only during creation. Option D is wrong because S3 server-side encryption is used for objects stored in Amazon S3, not for RDS database volumes; RDS encryption uses KMS keys for EBS volumes and storage.

1338
Multi-Selecthard

A company is monitoring an Amazon RDS for Oracle instance. CloudWatch alarms show that FreeableMemory is consistently below 256 MB. The database has high read and write I/O. Which THREE steps should the database specialist take to diagnose the issue?

Select 3 answers
A.Check the MemoryPressure and LogFileSyncDuration metrics in CloudWatch.
B.Review the Oracle memory advisor (V$MEMORY_TARGET_ADVICE).
C.Enable storage auto scaling to increase allocated storage.
D.Increase the DB instance class to allocate more memory.
E.Query V$SGASTAT and V$PGASTAT to understand memory allocation.
AnswersA, B, E

These metrics indicate memory pressure and potential performance impact.

Why this answer

Options A, B, and E are correct diagnostic steps. A: Checking MemoryPressure and LogFileSyncDuration helps identify memory pressure and I/O bottlenecks. B: Reviewing V$MEMORY_TARGET_ADVICE provides Oracle's memory sizing recommendations.

E: Querying V$SGASTAT and V$PGASTAT reveals detailed memory allocation within SGA and PGA. Option C (enabling storage auto scaling) addresses storage, not memory. Option D (increasing instance class) is a remediation step, not a diagnostic step.

1339
Multi-Selectmedium

Which TWO metrics should be monitored to detect a memory leak in an RDS for Oracle instance? (Choose 2.)

Select 2 answers
A.SwapUsage
B.FreeableMemory
C.DatabaseConnections
D.CPUUtilization
E.ReadIOPS
AnswersA, B

Increasing swap usage indicates the OS is paging memory to disk, sign of memory pressure.

Why this answer

Options A and B are correct because FreeableMemory shows the available memory, and SwapUsage indicates when the OS uses swap due to memory pressure, which are both signs of a memory leak. Option C is wrong because DatabaseConnections does not directly indicate a memory leak. Option D is wrong because CPUUtilization may be high but is not specific to a memory leak.

Option E is wrong because ReadIOPS relates to I/O, not memory.

1340
MCQhard

A company is deploying a new multi-AZ application that requires a relational database. The database must be highly available and must automatically failover to a standby in another Availability Zone within minutes. The database size is 500 GB and the workload is read-heavy. Which AWS RDS configuration meets these requirements?

A.Deploy Amazon Aurora with Multi-AZ
B.Deploy Amazon RDS for PostgreSQL with a cross-Region read replica
C.Deploy Amazon RDS for MySQL with Multi-AZ and a read replica in a different AZ
D.Deploy Amazon RDS for Oracle with RDS Proxy
AnswerC

Multi-AZ provides automatic failover; read replica improves read performance.

Why this answer

Deploying Amazon RDS for MySQL with Multi-AZ provides automatic failover to a standby in a different Availability Zone within minutes, meeting the high availability requirement. Adding a read replica in a different AZ offloads read traffic, which is ideal for the read-heavy workload, without affecting the primary database's performance.

Exam trap

The trap here is that candidates may confuse Aurora's built-in high availability with the explicit 'Multi-AZ' feature of RDS, or assume that a cross-Region read replica provides automatic failover, when in fact it requires manual promotion and does not meet the 'within minutes' automatic failover requirement.

How to eliminate wrong answers

Option A is wrong because Amazon Aurora with Multi-AZ is not a valid configuration; Aurora inherently provides high availability across AZs with its cluster architecture, but the term 'Multi-AZ' is specific to RDS, and Aurora uses a different failover mechanism that may not meet the 'within minutes' requirement as precisely as RDS Multi-AZ. Option B is wrong because a cross-Region read replica provides disaster recovery and read scaling, but it does not offer automatic failover within the same region; failover would require manual intervention or additional setup, and it does not meet the 'within minutes' automatic failover requirement. Option D is wrong because RDS Proxy is a connection pooling service that improves application scalability and resilience, but it does not provide database-level high availability or automatic failover; it is not a substitute for Multi-AZ deployment.

1341
MCQmedium

A company is designing a database for an e-commerce platform that requires ACID transactions for order processing, complex joins for inventory reporting, and the ability to scale read replicas across multiple AWS regions. Which database service best meets these requirements?

A.Amazon Aurora
B.Amazon DynamoDB
C.Amazon RDS for SQL Server
D.Amazon Redshift
AnswerA

Aurora offers ACID transactions, complex joins, and cross-region read replicas.

Why this answer

Amazon Aurora is the correct choice because it provides full ACID compliance for transactional workloads, supports complex joins via its MySQL/PostgreSQL-compatible relational engine, and offers up to 15 low-latency read replicas that can be placed in multiple AWS Regions using Aurora Global Database. This combination of strong consistency, relational query capabilities, and cross-region read scaling directly matches the e-commerce platform's requirements.

Exam trap

The trap here is that candidates often choose DynamoDB for its scalability but overlook the explicit requirement for complex joins, which DynamoDB cannot perform natively, or they choose RDS for SQL Server without realizing its strict limit on read replicas and lack of native cross-region replication.

How to eliminate wrong answers

Option B (Amazon DynamoDB) is wrong because it is a NoSQL key-value/document database that does not support complex joins natively and provides only eventual consistency by default, not full ACID transactions across multiple items without additional client-side logic. Option C (Amazon RDS for SQL Server) is wrong because while it supports ACID transactions and joins, it is limited to a maximum of 5 read replicas and does not support cross-region read replicas natively, making it unsuitable for multi-region read scaling. Option D (Amazon Redshift) is wrong because it is a columnar data warehouse optimized for analytical queries, not transactional workloads, and does not support ACID transactions for OLTP order processing or real-time complex joins for inventory reporting.

1342
Multi-Selectmedium

Which TWO factors should be considered when selecting a migration method from on-premises Oracle to Amazon RDS for Oracle?

Select 2 answers
A.The size of the database and available network bandwidth
B.The version of the Oracle client used by applications
C.The required downtime tolerance
D.The number of stored procedures in the database
E.The number of indexes on the source database
AnswersA, C

Large databases may require Snowball; bandwidth affects transfer time.

Why this answer

The size of the database directly impacts the time required for data transfer, and available network bandwidth determines the maximum throughput for that transfer. For large databases over limited bandwidth, full offline migration may be impractical, requiring incremental or online methods like AWS DMS with ongoing replication to minimize transfer time.

Exam trap

The trap here is that candidates confuse factors affecting migration method selection with factors affecting post-migration performance or compatibility, such as client versions or object counts, which are not relevant to the method choice.

1343
MCQmedium

A company is migrating a MongoDB database to Amazon DocumentDB. They have a 200 GB database and need to minimize downtime. Which migration approach is most appropriate?

A.Take an EBS snapshot of the MongoDB volume and restore it to DocumentDB.
B.Set up MongoDB replication from the source to DocumentDB, then promote DocumentDB.
C.Export the database using mongodump and import using mongorestore into DocumentDB.
D.Use AWS DMS to migrate data from MongoDB to DocumentDB.
AnswerD

AWS DMS with ongoing replication (CDC) allows initial load and continuous sync, minimizing downtime. This is the recommended approach for large databases requiring minimal interruption.

Why this answer

AWS DMS with ongoing replication (change data capture) is the most appropriate migration approach for minimizing downtime when migrating a 200 GB MongoDB database to Amazon DocumentDB. DMS can perform an initial load and then continuously replicate ongoing changes from the source MongoDB to the target DocumentDB until cutover, resulting in near-zero downtime. Option B is incorrect because native MongoDB replication is not supported by DocumentDB; DocumentDB cannot join a MongoDB replica set.

Exam trap

Candidates may think that native MongoDB replication to DocumentDB is possible, but DocumentDB uses a different replication mechanism and cannot act as a MongoDB replica. The correct tool for minimal downtime migration is AWS DMS with ongoing replication.

How to eliminate wrong answers

Option A is wrong because EBS snapshots capture block-level data of an EC2 instance volume, not the logical database state, and DocumentDB does not support restoring from an EBS snapshot; it uses its own storage engine. Option C is wrong because mongodump/mongorestore is an offline, logical export/import process that requires the source database to be quiesced or read-locked during the dump, causing significant downtime for a 200 GB database. Option D is wrong because AWS DMS for MongoDB to DocumentDB migrations uses a CDC (change data capture) approach that relies on the MongoDB oplog, but DMS does not support DocumentDB as a target for MongoDB source migrations; DMS supports MongoDB to Amazon DynamoDB or Amazon S3, but not to DocumentDB.

1344
MCQeasy

A database administrator notices that an Amazon RDS for MySQL DB instance's CPU utilization is consistently above 90% during peak hours. Which initial troubleshooting step should the administrator take?

A.Increase the DB instance size to handle the load.
B.Use Amazon RDS Performance Insights to identify the queries consuming CPU.
C.Enable Multi-AZ deployment to distribute the load.
D.Disable slow query logging to reduce CPU overhead.
AnswerB

Performance Insights helps pinpoint the source of high CPU usage.

Why this answer

Amazon RDS Performance Insights provides detailed database performance metrics and helps identify the specific queries contributing to high CPU utilization, enabling targeted optimization. Option A is incorrect because increasing instance size is a reactive scaling action rather than a diagnostic step; it does not identify the root cause. Option C is incorrect because Multi-AZ deployment is designed for high availability and failover, not for distributing load or improving performance.

Option D is incorrect because disabling slow query logging removes valuable diagnostic information that could help identify problematic queries.

1345
MCQhard

A company is running an Amazon DocumentDB cluster. The application is experiencing high write latency. The cluster has a single instance. What should be done to identify the cause of the latency?

A.Upgrade the instance to a larger size.
B.Enable Performance Insights and review the top wait events.
C.Add a replica to distribute the write load.
D.Change the storage type to Provisioned IOPS.
AnswerB

Performance Insights reveals database bottlenecks and wait events.

Why this answer

Enabling Performance Insights for Amazon DocumentDB allows you to monitor the database load and review top wait events, which helps identify the specific causes of high write latency, such as lock contention or I/O bottlenecks. Option A is wrong because simply upgrading to a larger instance size addresses symptoms but does not identify the root cause. Option C is wrong because adding a replica does not reduce write latency on the primary instance; it only offloads read traffic.

Option D is wrong because changing to Provisioned IOPS may improve I/O performance but does not diagnose the underlying issue causing latency.

1346
MCQhard

A team is using Amazon DynamoDB Accelerator (DAX) to improve read performance for a table. They notice that DAX is returning stale data even though the TTL is set to 5 minutes. The table is updated frequently by multiple writers. What is the most likely cause of the stale reads?

A.The DAX cluster is not large enough to cache all items, causing cache misses
B.DAX is configured with eventual consistency, which returns stale data by design
C.The DAX cluster is deployed in a different Availability Zone than the application
D.The TTL is too long, causing cached items to remain after updates
AnswerD

Correct. DAX uses a write-through cache for reads, and when a DynamoDB item is updated, the cached version remains until TTL expiry. If TTL is longer than the update frequency, stale data is served.

Why this answer

DAX uses a write-through cache, meaning that items are cached only when they are read. When an item is updated in DynamoDB, the cached copy is not automatically invalidated; instead, it remains in the cache until the TTL expires. If the TTL is set too long (e.g., 5 minutes) and the item is updated frequently, stale data will be served from the cache until the TTL forces its removal.

Option A is incorrect because cache misses would cause slower reads, not stale reads. Option B is incorrect because DAX always uses eventual consistency for reads, but stale data occurs here due to TTL, not consistency level. Option C is incorrect because DAX clusters are deployed in a single VPC and can be accessed from any AZ with proper routing; AZ placement does not cause staleness.

1347
MCQhard

A company is using Amazon ElastiCache for Redis and notices that the cache hit ratio is low. The application is frequently reading data that is not in the cache. Which action would be most effective in improving the cache hit ratio?

A.Increase the number of replicas in the replication group.
B.Decrease the TTL of cached items to ensure freshness.
C.Pre-warm the cache by loading frequently accessed data from the database.
D.Enable Multi-AZ for automatic failover.
AnswerC

Pre-warming ensures that the most requested data is already in the cache, improving hit ratio.

Why this answer

Pre-warming the cache (option C) by loading frequently accessed data from the database into the ElastiCache cluster before it is requested increases the likelihood that subsequent reads will hit the cache. This directly improves the cache hit ratio. Increasing replicas (option A) does not add more cache capacity, it only provides read replicas for high availability.

Decreasing TTL (option B) causes items to expire sooner, potentially reducing the hit ratio. Enabling Multi-AZ (option D) provides failover but does not affect hit ratio. Therefore, option C is the most effective action.

1348
MCQeasy

A company wants to audit all API calls made to its Amazon RDS DB instances. Which AWS service should be used to capture these API calls?

A.AWS CloudTrail
B.AWS Config
C.Amazon GuardDuty
D.Amazon Inspector
AnswerA

Correct. AWS CloudTrail records API calls to AWS services, including RDS, providing an audit trail of actions.

Why this answer

AWS CloudTrail records API calls made to AWS services, including RDS, providing an audit trail of actions taken. Option B is incorrect because AWS Config tracks resource configuration changes and compliance, not API calls. Option C is incorrect because Amazon GuardDuty is a threat detection service that monitors for malicious activity, not an API audit tool.

Option D is incorrect because Amazon Inspector is a vulnerability assessment service that scans for security issues, not an audit trail of API calls.

1349
MCQeasy

A company runs an Amazon Aurora MySQL DB cluster with one writer and two readers. The application experiences increased read latency. The DBA wants to offload read traffic from the writer instance. Which configuration change should be made to the application?

A.Modify the application to use an individual instance endpoint for each reader.
B.Create a custom endpoint that includes both writer and readers.
C.Modify the application to use the reader endpoint for read queries.
D.Modify the application to use the cluster endpoint for all queries.
AnswerC

The reader endpoint load balances across all read replicas.

Why this answer

The reader endpoint for an Aurora MySQL cluster automatically load-balances read-only connections across all available reader instances. By modifying the application to use the reader endpoint for read queries, read traffic is offloaded from the writer instance, reducing read latency on the writer. This is the standard AWS-recommended pattern for separating read and write workloads in Aurora.

Exam trap

The trap here is that candidates often confuse the cluster endpoint (which always points to the writer) with the reader endpoint, assuming the cluster endpoint can handle both reads and writes without performance impact, but the writer instance is a single point of contention for read traffic.

How to eliminate wrong answers

Option A is wrong because using individual instance endpoints for each reader requires the application to manage connection distribution and failover logic manually, which is less resilient and does not automatically balance load across readers. Option B is wrong because a custom endpoint that includes both writer and readers would still route some read traffic to the writer, defeating the purpose of offloading reads from the writer. Option D is wrong because the cluster endpoint always points to the writer instance, so using it for all queries would not offload any read traffic from the writer.

1350
MCQmedium

A retail company uses Amazon DynamoDB to store product catalog data. The security team wants to ensure that only authorized applications can read and write to the table. The applications are running on Amazon EC2 instances. The current setup uses an IAM role attached to the EC2 instance with a policy that grants dynamodb:* on the specific table. However, during a security audit, it was discovered that any process on the EC2 instance can access the table because the instance has access to the temporary credentials from the instance metadata service. The security team requires that only specific processes (the application) can access the credentials, and that the credentials cannot be extracted from the instance. What should be done to meet these requirements?

A.Create a VPC endpoint for DynamoDB with a policy that restricts access to the specific IAM role, and configure the EC2 instance to use IMDSv2 with a hop limit.
B.Modify the security group to only allow traffic from the EC2 instance's private IP.
C.Store AWS access keys on the EC2 instance and use them in the application.
D.Attach a resource-based policy to the DynamoDB table allowing only the EC2 instance's IAM role.
AnswerA

VPC endpoint policy and IMDSv2 enhance security.

Why this answer

Using a VPC endpoint for DynamoDB with a policy that restricts access to the specific IAM role ensures that only requests from that role are allowed, and using IMDSv2 with a hop limit prevents credential theft by ensuring that only the intended application process on the EC2 instance can access the credentials. Option B is incorrect because security groups control network traffic but do not enforce IAM role usage. Option C is incorrect because storing AWS access keys on the instance is less secure and exposes credentials to any process.

Option D is incorrect because DynamoDB does not support resource-based policies; IAM roles are authorized via identity-based policies attached to the role.

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