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AWS Certified Database Specialty DBS-C01 (DBS-C01) — Questions 226–300

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

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226
MCQmedium

A company is migrating a 10 TB Oracle database to Amazon RDS for Oracle. The migration window is limited to 24 hours. The source database is running on-premises with a 500 Mbps network connection. Which migration approach should be used?

A.Use AWS DMS with full load and ongoing replication
B.Create an RDS read replica from the on-premises database
C.Take a physical backup of the source database and restore to RDS
D.Use Oracle Data Pump to export and import the database
AnswerA

DMS supports large data volumes and ongoing replication to minimize downtime.

Why this answer

AWS DMS with full load and ongoing replication is the correct approach because it can handle the 10 TB migration within the 24-hour window by using the 500 Mbps connection for the initial full load (which takes approximately 48 hours at full bandwidth, but DMS can compress data and use parallel tasks to reduce time), and then switch to ongoing replication to minimize downtime. The ongoing replication captures changes via Oracle LogMiner or binary logs, allowing the source to remain operational during the migration.

Exam trap

The trap here is that candidates often assume Oracle Data Pump or physical backups are faster for large databases, but they overlook the network bandwidth constraint and the need for ongoing replication to meet the 24-hour window, while DMS's ability to compress and replicate changes makes it the only viable option.

How to eliminate wrong answers

Option B is wrong because Amazon RDS for Oracle does not support creating a read replica from an on-premises database; read replicas are only available within RDS itself, typically for cross-Region or cross-AZ replication, not for external sources. Option C is wrong because taking a physical backup of the source database and restoring to RDS requires transferring the entire 10 TB backup file over the 500 Mbps link, which would take over 48 hours (10 TB * 8 / 500 Mbps = 160,000 seconds ≈ 44.4 hours) and exceed the 24-hour window, plus RDS does not support native physical restore from on-premises backups without additional tools like AWS Backup or S3. Option D is wrong because Oracle Data Pump export/import is a logical dump that would require transferring the entire 10 TB export file over the network, taking similar time as the physical backup, and does not support ongoing replication to minimize downtime, making it unsuitable for the tight 24-hour window.

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227
Multi-Selectmedium

A company is migrating a MySQL database to Amazon Aurora MySQL. The migration must be completed with minimal downtime. Which TWO methods can achieve this? (Choose two.)

Select 2 answers
A.Create an Aurora MySQL read replica from the external MySQL instance using binlog replication
B.Take a physical backup of the source database and restore to Aurora
C.Create an Aurora clone from the source database
D.Use AWS Database Migration Service (AWS DMS) with ongoing replication
E.Enable binlog replication on the source MySQL instance
AnswersA, D

This allows near-zero downtime replication.

Why this answer

You can set up an external MySQL instance as a replication source for an Amazon Aurora MySQL read replica using binary log (binlog) replication. This allows the Aurora cluster to stay synchronized with the source database with minimal downtime, as you only need to stop writes on the source and promote the Aurora replica when ready. Option D is correct because AWS Database Migration Service (AWS DMS) supports ongoing replication using change data capture (CDC) to keep the target Aurora database continuously synchronized with the source MySQL database, enabling a migration with minimal downtime.

Options B, C, and E are incorrect: taking a physical backup and restoring (B) or creating an Aurora clone from the source (C) would require downtime; enabling binlog replication alone (E) is not sufficient—it must be used with a replication setup or a service like DMS.

Exam trap

The trap here is that candidates may think enabling binlog replication alone (Option E) is sufficient for migration, but it is only a prerequisite; the actual migration requires a replication channel or a service like DMS to consume the binlog stream.

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228
Drag & Dropmedium

Arrange the steps to migrate an on-premises Oracle database to Amazon RDS for Oracle using AWS DMS (Database Migration Service) in the correct order.

Drag steps to the numbered slots on the right, or tap a step then tap a slot.

Steps
Order
1Step 1
2Step 2
3Step 3
4Step 4

Why this order

DMS migration requires setting up the replication instance, configuring endpoints with proper source database settings for CDC, creating a migration task, and monitoring for completion.

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229
MCQmedium

An administrator is deploying an Amazon RDS for MySQL DB instance and needs to ensure that all connections use SSL. Which parameter should be set on the RDS DB instance?

A.Set ssl_cipher in the DB parameter group
B.Set require_secure_transport=ON in the DB parameter group
C.Set tls_version in the DB parameter group
D.Set rds.force_ssl=1 in the DB parameter group
AnswerB

This parameter forces all connections to use SSL/TLS.

Why this answer

Setting `require_secure_transport=ON` in the DB parameter group enforces that all connections to the RDS MySQL DB instance must use SSL/TLS. This parameter, supported by MySQL 5.7 and later, rejects any non-encrypted connection attempt, ensuring transport layer security for all client-server communication.

Exam trap

The trap here is that candidates confuse `require_secure_transport` with `rds.force_ssl`, which is a valid parameter for RDS SQL Server but not for RDS MySQL, leading them to select the wrong option based on familiarity with other database engines.

How to eliminate wrong answers

Option A is wrong because `ssl_cipher` only specifies the allowed cipher suites for SSL connections but does not enforce that connections must use SSL; it allows non-SSL connections to proceed. Option C is wrong because `tls_version` controls the minimum TLS protocol version (e.g., TLS 1.2) but does not mandate that connections be encrypted; unencrypted connections are still permitted. Option D is wrong because `rds.force_ssl=1` is not a valid parameter for RDS MySQL; the correct parameter to enforce SSL is `require_secure_transport`, and `rds.force_ssl` is a parameter used in Amazon RDS for SQL Server, not MySQL.

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230
MCQhard

A company runs an e-commerce platform using Amazon Aurora MySQL with Multi-AZ deployment. The application has a read-heavy workload and uses a mix of SELECT and UPDATE queries. Recently, the company migrated from a db.r5.large to a db.r5.2xlarge instance class to handle increased traffic. However, after the migration, the CPU utilization remains high during peak hours, and the application's page load times have increased. The DBA notices that the 'Read IOPS' metric is high, but the 'Read Latency' metric is low. There is also a high number of 'Select' queries in the database. The application uses a single database endpoint. What should the DBA do to reduce CPU utilization and improve read performance?

A.Enable Multi-AZ with one standby replica.
B.Enable Performance Insights and analyze the top SQL.
C.Upgrade the instance class to db.r5.4xlarge.
D.Create one or more Aurora Replicas and modify the application to use read-only endpoints for SELECT queries.
AnswerD

Read replicas offload read traffic, reducing CPU on primary.

Why this answer

Creating Aurora Replicas offloads read-only SELECT queries from the primary instance, reducing CPU utilization on the primary and improving overall read throughput. Option A is incorrect because enabling Multi-AZ with one standby replica provides high availability but does not help with read scaling; the standby is not used for reads. Option B is incorrect because Performance Insights is a monitoring tool that helps identify performance bottlenecks but does not directly reduce CPU utilization.

Option C is incorrect because simply upgrading to a larger instance class may temporarily alleviate the issue but is not cost-effective and does not address the root cause of read-heavy workload imbalance; adding read replicas scales reads horizontally.

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231
MCQmedium

A company is migrating an on-premises MongoDB database to AWS. They need a managed database service that is compatible with MongoDB and supports automated backups, scaling, and high availability. Which service should they use?

A.Amazon DynamoDB
B.Amazon RDS for MySQL
C.Amazon Neptune
D.Amazon DocumentDB
AnswerD

DocumentDB is MongoDB-compatible and offers the required managed features.

Why this answer

Amazon DocumentDB is a fully managed, MongoDB-compatible document database service designed for workloads that require MongoDB's document model, query patterns, and APIs. It supports automated backups (continuous backups to S3 with point-in-time recovery), automatic scaling of storage and compute, and multi-AZ high availability with synchronous replication across three Availability Zones, making it the correct choice for migrating an on-premises MongoDB database to a managed AWS service.

Exam trap

The trap here is that candidates often confuse Amazon DynamoDB's document support (JSON-like items) with MongoDB compatibility, but DynamoDB does not support MongoDB's wire protocol, query operators, or aggregation pipeline, making it a non-trivial migration requiring significant application rewrites.

How to eliminate wrong answers

Option A is wrong because Amazon DynamoDB is a key-value and document database that uses a proprietary API and is not compatible with MongoDB's wire protocol or query language; it requires application code changes to use its own SDK and data model. Option B is wrong because Amazon RDS for MySQL is a relational database service using SQL and does not support MongoDB's document model, BSON data format, or MongoDB-specific operations like aggregation pipelines or geospatial queries. Option C is wrong because Amazon Neptune is a graph database service optimized for highly connected data (e.g., social networks, fraud detection) and does not support MongoDB's document storage or query interface.

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232
MCQmedium

A company has an Amazon RDS for MySQL DB instance that is publicly accessible. The security team wants to restrict access to only specific IP addresses. Which configuration should be used?

A.Create a VPC endpoint for RDS and attach a policy that allows only the specific IP addresses.
B.Use an IAM policy with a condition that restricts the source IP address.
C.Configure a security group associated with the RDS instance to allow inbound traffic only from the specific IP addresses.
D.Configure a network ACL to allow inbound traffic from the specific IP addresses.
AnswerC

Security groups can restrict inbound traffic by IP address.

Why this answer

A security group associated with the RDS instance can be configured to restrict inbound traffic to specific IP addresses, even if the instance is publicly accessible. Option A is incorrect because a VPC endpoint is used for private connectivity from within a VPC, not for restricting public access. Option B is incorrect because IAM policies control permissions for API actions, not network-level access.

Option D is incorrect because network ACLs are stateless and applied at the subnet level, and while they can filter IP traffic, security groups are the more appropriate and granular control for individual RDS instances.

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233
MCQhard

A company runs an e-commerce platform on AWS using a multi-tier architecture. The application tier consists of Auto Scaling groups of EC2 instances behind an Application Load Balancer. The database tier uses Amazon RDS for MySQL with Multi-AZ deployment. Recently, the operations team noticed that during flash sales, the application becomes unresponsive and users receive 503 errors. The team checks CloudWatch metrics and sees that the RDS instance's CPU utilization spikes to 100%, and the `DatabaseConnections` metric also spikes to the maximum allowed value of 500. The application uses connection pooling with a maximum of 200 connections, but the metric shows 500 connections. The team suspects that the connection pooling configuration is not being honored. The application code is written in Python and uses SQLAlchemy with a connection pool size of 10 per application instance. There are 20 application instances in the Auto Scaling group during peak times. The team wants to resolve the issue without increasing the database instance size. What should the team do?

A.Reduce the Auto Scaling group's desired capacity to 10 instances during flash sales
B.Set the `max_connections` parameter in the RDS parameter group to 200 and configure the application to handle connection errors with retry logic
C.Migrate the database to Amazon Aurora MySQL with Auto Scaling enabled
D.Increase the SQLAlchemy pool size to 25 per instance to reduce connection contention
AnswerB

Limiting max_connections to 200 ensures the database does not accept more connections than the application intends, and retry logic handles connection failures.

Why this answer

Setting the `max_connections` parameter in the RDS parameter group enforces a hard limit at the database level, preventing the database from accepting more than 200 connections. With 20 application instances each using a connection pool of 10, the total intended connections are 200. By setting `max_connections` to 200, any excess connection attempts will be rejected, and the application should handle connection errors with retry logic, preventing the database from being overwhelmed.

Option A is wrong: reducing the Auto Scaling group's desired capacity to 10 instances would reduce the total connection pool to 100, which might temporarily reduce load but is not a scalable solution and does not address the root cause that the application's connection pooling is not being honored. Option C is wrong: migrating to Amazon Aurora MySQL with Auto Scaling does not directly solve the connection pooling issue. Aurora may allow more connections, but the root cause is that the application is opening more connections than configured, and a migration is a costly change that doesn't fix the configuration problem.

Option D is wrong: increasing the SQLAlchemy pool size per instance to 25 would increase the total potential connections to 500 (20 instances × 25), which would worsen the connection spike and exceed the database's maximum, increasing contention and load.

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234
MCQmedium

A company is migrating a 2 TB MySQL database to Amazon Aurora MySQL. They need to minimize downtime and ensure data consistency. Which approach should be used?

A.Use AWS DMS with ongoing replication (CDC).
B.Use mysqldump to export and import into Aurora.
C.Establish AWS Direct Connect and use MySQL replication.
D.Use AWS SCT to convert schema and data.
AnswerA

DMS with CDC minimizes downtime by replicating changes.

Why this answer

AWS DMS with ongoing replication (CDC) is the correct approach because it allows you to perform an initial full load of the 2 TB database while continuously capturing and applying changes from the source MySQL database. This minimizes downtime by keeping the target Aurora MySQL cluster nearly synchronized, and you only need to stop writes briefly during the final cutover to ensure data consistency.

Exam trap

The trap here is that candidates often assume native MySQL replication (Option C) can be used directly with Aurora, but Aurora MySQL does not support standard MySQL replication as a replica; DMS is the AWS-native service designed for this purpose.

How to eliminate wrong answers

Option B is wrong because mysqldump creates a logical snapshot that requires the source database to be read-locked during the export, causing significant downtime for a 2 TB database, and it does not support ongoing replication to minimize cutover time. Option C is wrong because MySQL native replication to Aurora is not directly supported; Aurora MySQL uses a different storage engine and replication protocol, and establishing AWS Direct Connect alone does not solve the compatibility issue. Option D is wrong because AWS SCT is a schema conversion tool that helps convert database schemas and some data, but it does not provide ongoing replication or minimize downtime; it is typically used in conjunction with DMS for heterogeneous migrations, not for a homogeneous MySQL-to-Aurora migration.

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235
MCQeasy

A security engineer reviews the IAM policy attached to a user. The user is unable to modify any RDS DB instance, even when MFA is enabled. What is the most likely cause?

A.The policy is missing the ec2:ModifyInstance permission.
B.The policy does not include a Deny statement for RDS actions.
C.The user does not have MFA enabled, or the instance name does not match the allowed prefixes.
D.The user is trying to use the RDS console, but the policy only allows API calls.
AnswerC

Correct. The most likely cause is that the IAM policy requires MFA and matching instance name prefixes, which are not satisfied.

Why this answer

The scenario states that the user cannot modify any RDS DB instance even when MFA is enabled. This suggests that the IAM policy likely includes a condition requiring MFA or a specific resource prefix (e.g., 'prod-*' or 'dev-*'). If MFA is not actually enabled on the user's account, or if the instance name does not match the allowed prefixes, the condition would fail, denying all ModifyDBInstance actions.

Option A is incorrect because EC2 permissions are irrelevant to RDS. Option B is incorrect because the absence of a Deny statement does not cause failure; the issue is an Allow condition not being met. Option D is incorrect because the console versus API distinction does not explain the inability to modify any instance.

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236
MCQmedium

A media company uses Amazon ElastiCache for Redis to cache database query results and reduce load on the primary database. The cache hit ratio is low because the cache is purged frequently. The team wants to improve the hit ratio without increasing the cache size. Which strategy should they implement?

A.Increase the TTL for cached entries to reduce early evictions.
B.Implement lazy loading to populate cache only on demand.
C.Use write-through caching to update cache on every database write.
D.Set eviction policy to allkeys-random to spread evictions evenly.
AnswerA

Longer TTL keeps data in cache longer, improving hit ratio.

Why this answer

Increasing the TTL (Time-To-Live) for cached entries allows them to remain in the cache longer, reducing the frequency of evictions due to expiration. Since the cache is purged frequently, a low TTL is likely causing entries to expire before they can be reused, which directly lowers the hit ratio. By extending the TTL, the team can retain popular entries longer without needing to increase the cache size, as the existing memory is used more efficiently.

Exam trap

The trap here is that candidates confuse cache eviction (due to memory pressure) with cache expiration (due to TTL), and assume that changing the eviction policy or caching strategy will fix a problem caused by entries being removed too quickly by expiration.

How to eliminate wrong answers

Option B is wrong because lazy loading (populating cache on cache miss) is already the default behavior in many Redis caching patterns and does not address the root cause of frequent purging; it may even increase write traffic to the database on misses. Option C is wrong because write-through caching updates the cache on every database write, which can increase write latency and memory usage without solving the issue of entries being evicted too early due to low TTL or memory pressure. Option D is wrong because setting the eviction policy to allkeys-random spreads evictions evenly across all keys, but this does not prevent frequent purging; it only changes which keys are evicted when memory is full, and if the cache is already being purged frequently due to expiration (not memory pressure), this policy has no effect.

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237
MCQhard

A company is designing a global e-commerce application that requires a relational database with sub-10ms read latency across multiple AWS Regions. The database will store inventory and product catalog data. Which database design should they choose?

A.Use Amazon DynamoDB Global Tables with eventual consistency.
B.Deploy Multi-AZ for Amazon RDS and use Route 53 latency-based routing.
C.Set up Cross-Region Read Replicas for Amazon RDS MySQL.
D.Use Amazon Aurora Global Database with a primary cluster in one Region and secondary clusters in other Regions.
AnswerD

Aurora Global Database offers low-latency global reads.

Why this answer

Amazon Aurora Global Database is designed for low-latency global reads, with typical replication lag of under 1 second and read latency in the single-digit milliseconds from secondary clusters. It uses a dedicated storage-based replication mechanism that does not impact the performance of the primary cluster, making it ideal for a global e-commerce application requiring sub-10ms reads across multiple AWS Regions.

Exam trap

The trap here is that candidates confuse Multi-AZ or Cross-Region Read Replicas with true global low-latency read scaling, not realizing that Aurora Global Database is the only option that provides dedicated secondary clusters with storage-based replication for sub-10ms reads across Regions.

How to eliminate wrong answers

Option A is wrong because DynamoDB Global Tables is a NoSQL key-value and document database, not a relational database, and the question explicitly requires a relational database. Option B is wrong because Multi-AZ for Amazon RDS provides high availability within a single Region, not global read scaling; Route 53 latency-based routing cannot reduce cross-Region read latency when the database itself is in one Region. Option C is wrong because Cross-Region Read Replicas for Amazon RDS MySQL use asynchronous replication with typical lag of seconds or more, and read requests from secondary Regions still incur cross-Region network latency that often exceeds 10ms.

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238
MCQeasy

A gaming company needs a database to store player session data that is ephemeral and requires sub-millisecond latency. The data can be lost on failure without impact. Which service is best?

A.Amazon DynamoDB
B.Amazon RDS for PostgreSQL
C.Amazon S3
D.Amazon ElastiCache for Redis
AnswerD

ElastiCache Redis provides sub-millisecond latency and can be configured with no persistence.

Why this answer

Amazon ElastiCache for Redis is the best choice because it provides an in-memory data store with sub-millisecond latency, ideal for ephemeral player session data that can be lost on failure. Redis supports data structures like strings and hashes with TTL (time-to-live) expiration, perfectly matching the transient, low-latency requirement without needing durability.

Exam trap

The trap here is that candidates may choose DynamoDB (Option A) because it is a common choice for session data, but the question's explicit requirement for sub-millisecond latency and tolerance for data loss points to an in-memory cache like Redis, not a durable database.

How to eliminate wrong answers

Option A is wrong because Amazon DynamoDB, while fast, is a fully managed NoSQL database that persists data to disk and typically offers single-digit millisecond latency, not the sub-millisecond latency required for ephemeral session data; it also incurs higher cost and overhead for data that can be lost. Option B is wrong because Amazon RDS for PostgreSQL is a relational database with disk-based storage, offering higher latency (often 5-10+ ms) and ACID compliance, which is unnecessary and over-engineered for transient session data that can be lost. Option C is wrong because Amazon S3 is an object storage service with high latency (typically 100+ ms for first byte) and is designed for durable, persistent storage, not ephemeral, sub-millisecond access patterns.

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239
MCQhard

A company is running a production Amazon RDS for MySQL database that is experiencing performance degradation. Amazon CloudWatch metrics show high CPU utilization and high number of connections. The company has already optimized queries and implemented connection pooling. What is the MOST cost-effective solution to address the high CPU utilization?

A.Add Read Replicas to offload read traffic
B.Change the storage type to Provisioned IOPS (io1)
C.Enable RDS Proxy to reduce database connections
D.Scale up to a larger DB instance class
AnswerD

More CPU capacity directly addresses high CPU utilization.

Why this answer

Scaling up to a larger DB instance class directly increases the compute capacity (vCPUs and memory) available to the database, which addresses the root cause of high CPU utilization. Since queries are already optimized and connection pooling is in place, the remaining bottleneck is the instance's processing power, making a vertical scale-up the most cost-effective solution to handle the sustained CPU load without introducing additional architectural complexity.

Exam trap

The trap here is that candidates often choose RDS Proxy (Option C) assuming it reduces CPU utilization by lowering connection overhead, but the question explicitly states connection pooling is already implemented, so the CPU issue is from compute-bound operations, not connection management.

How to eliminate wrong answers

Option A is wrong because adding Read Replicas offloads read traffic but does not reduce CPU utilization on the primary instance; the primary still handles all write operations and the high connection count, so CPU pressure remains. Option B is wrong because changing the storage type to Provisioned IOPS (io1) improves I/O latency and throughput, but does not address high CPU utilization caused by compute-bound workloads or connection overhead. Option C is wrong because enabling RDS Proxy reduces the number of database connections by pooling them, but the company has already implemented connection pooling, and the high CPU utilization persists due to compute-intensive operations, not connection churn.

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240
MCQhard

A company runs an Amazon Aurora MySQL-compatible database cluster. The security team requires that all database credentials be rotated automatically every 30 days. Which combination of AWS services can meet this requirement with minimal operational overhead?

A.Use IAM database authentication and rotate the IAM user keys every 30 days.
B.Store the password in AWS Secrets Manager and enable automatic rotation with a 30-day interval.
C.Use AWS CloudHSM to generate a new password and a Lambda function to update the database.
D.Store the password in AWS Systems Manager Parameter Store and use a scheduled Lambda function to update the password.
AnswerB

Secrets Manager can automatically rotate RDS credentials.

Why this answer

AWS Secrets Manager provides built-in automatic rotation for RDS database credentials. Option A is incorrect because IAM database authentication does not involve password rotation. Option C is incorrect because CloudHSM does not manage password rotation.

Option D is incorrect because Systems Manager Parameter Store lacks built-in rotation capabilities for RDS credentials.

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241
MCQeasy

A developer needs to connect to an Amazon RDS for PostgreSQL DB instance from an EC2 instance in the same VPC. What is the most secure way to authenticate the connection without storing database credentials in the application code?

A.Use a hardcoded password in the application configuration file.
B.Store the database password in AWS Secrets Manager and retrieve it at runtime.
C.Enable IAM database authentication and generate an authentication token.
D.Store the password in AWS Systems Manager Parameter Store as a SecureString.
AnswerC

IAM database authentication eliminates the need for a stored password.

Why this answer

IAM database authentication for RDS PostgreSQL allows the application to connect using an IAM user or role without storing any database credentials. The authentication token is generated by the AWS SDK and is valid for 15 minutes. This eliminates the need to store credentials in the application code.

Option A is incorrect because a hardcoded password is not secure. Option B (Secrets Manager) and Option D (Systems Manager Parameter Store SecureString) both require the application to retrieve a secret at runtime, which still introduces credential management overhead and potential exposure. IAM authentication is the most secure option as it removes static credentials entirely.

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242
MCQhard

A company is using Amazon DynamoDB as the primary database for a global e-commerce application. During the holiday season, the application experiences throttling on write requests even though the read and write capacity units are well below the provisioned limits. The table uses on-demand capacity mode. What is the most likely cause of this throttling?

A.There is a hot partition due to an uneven write distribution across partition keys.
B.The table's provisioned write capacity is set too low.
C.The table has exceeded the maximum write capacity units per partition.
D.The AWS account has reached the DynamoDB write throughput limit per region.
AnswerA

Correct. Uneven write distribution creates a hot partition that exceeds the partition's throughput limit, causing throttling even in on-demand mode.

Why this answer

In DynamoDB on-demand capacity mode, throughput scales automatically based on traffic. However, throttling can still occur if a single partition receives more write requests than the partition's maximum throughput capacity (1,000 WCU per partition). This is known as a hot partition, caused by an uneven distribution of write activity across partition keys.

Option A correctly identifies this. Option B is incorrect because on-demand mode does not use provisioned capacity. Option C uses incorrect terminology—there is no 'maximum write capacity units per partition' that the table as a whole can exceed.

Option D is incorrect because DynamoDB does not have a per-region account-level write limit that causes throttling on a single table.

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243
MCQeasy

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. The company wants to minimize application changes. Which endpoint type should the application use after migration?

A.RDS reader endpoint
B.RDS cluster endpoint
C.RDS instance endpoint (DNS name)
D.RDS console endpoint
AnswerC

Application connects to the RDS instance endpoint.

Why this answer

The RDS instance endpoint (DNS name) is the standard connection endpoint for a single RDS DB instance, which is the target of a direct migration from on-premises MySQL to Amazon RDS for MySQL. This endpoint requires no application changes, as the application simply replaces the old on-premises hostname with the RDS instance DNS name, maintaining the same MySQL protocol and connection logic.

Exam trap

The trap here is that candidates confuse RDS instance endpoints with Aurora cluster endpoints, mistakenly selecting the cluster endpoint (Option B) for a standard RDS MySQL migration, even though cluster endpoints are exclusive to Aurora and not applicable to single-instance RDS deployments.

How to eliminate wrong answers

Option A is wrong because the RDS reader endpoint is used only with Aurora clusters to distribute read traffic across read replicas; it is not available for standard RDS for MySQL instances and would cause connection failures if used. Option B is wrong because the RDS cluster endpoint is specific to Aurora DB clusters (for write operations) and does not exist for standard RDS for MySQL instances; using it would result in a DNS resolution error. Option D is wrong because the RDS console endpoint is not a valid database connection endpoint; it refers to the AWS Management Console URL for managing RDS resources, not a MySQL protocol endpoint.

Full explanation →
244
MCQhard

A data warehouse team is migrating from Amazon Redshift to Amazon Redshift RA3 nodes. The current cluster uses 10 DC2.large nodes. The new cluster will use 4 RA3.xlarge nodes. After the migration, the team notices that query performance is significantly slower. Which factor is the MOST likely cause of the performance degradation?

A.The data distribution style is set to EVEN instead of KEY.
B.The cluster does not have enough disk space for the workload.
C.The cluster has fewer nodes, reducing parallelism.
D.RA3 nodes are not optimized for large datasets.
AnswerC

RA3 nodes separate compute and storage; fewer compute nodes reduce parallelism.

Why this answer

Reducing the number of nodes from 10 to 4 decreases the parallelism, even though RA3 nodes have more compute capacity per node. Redshift distributes data across slices, and each node has multiple slices. With fewer nodes, the total number of slices is lower, reducing the degree of parallelism for query execution, which can lead to slower performance for large queries.

Option A is incorrect because the distribution style (EVEN vs KEY) affects data distribution but is not the most likely cause here; the question does not indicate a change in distribution style. Option B is incorrect because RA3 nodes use managed storage with ample capacity; disk space is not constrained. Option D is incorrect because RA3 nodes are optimized for large datasets; the issue is not the node type but the reduction in parallelism due to fewer nodes.

Full explanation →
245
MCQmedium

A security team is auditing an Amazon RDS for SQL Server DB instance. They notice that SSL connections are not enforced. Which configuration change will enforce SSL for all connections?

A.Modify the security group to only allow inbound traffic on port 443.
B.Add the SQL Server SSL option to the option group.
C.Set the 'rds.force_ssl' parameter to 1 in the DB parameter group.
D.Change the DB subnet group to a public subnet.
AnswerC

This parameter forces SSL connections to the SQL Server DB instance.

Why this answer

For Amazon RDS for SQL Server, you can enforce SSL connections by setting the 'rds.force_ssl' parameter to 1 in the DB parameter group. This forces all connections to use SSL. Option A is incorrect because security groups control network access but do not enforce encryption.

Option B is incorrect because the option group manages features such as Transparent Data Encryption (TDE) and native backup/restore, not SSL enforcement. Option D is incorrect because changing the subnet to public would expose the instance to the internet and does not enforce SSL.

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246
MCQhard

A company is planning to migrate a 5 TB Oracle data warehouse to Amazon Redshift. The migration must be completed within a 2-day maintenance window. The source database is heavily normalized and uses complex joins. Which strategy is most appropriate?

A.Use AWS DMS to directly migrate data to Redshift with full load and ongoing replication.
B.Export data to flat files, use S3 Transfer Acceleration to upload to S3, then COPY into Redshift.
C.Use AWS SCT to convert the Oracle schema to Redshift-compatible format, then use AWS DMS to load the data.
D.Use AWS Glue to crawl the Oracle schema and create Redshift tables, then run a Glue ETL job to load data.
AnswerC

AWS SCT converts Oracle’s normalised schema and complex joins into Redshift’s columnar, denormalised format, while AWS DMS performs the continuous 5 TB load within the 2-day window using full-load plus change data capture, satisfying the tight migration deadline.

Why this answer

AWS Schema Conversion Tool (SCT) is specifically designed to convert Oracle schemas (including heavily normalized structures with complex joins) into Amazon Redshift-compatible format, which is essential for a data warehouse migration. AWS DMS then efficiently loads the converted schema and data into Redshift within the 2-day window, as it can handle large volumes with full load and ongoing replication if needed.

Exam trap

The trap here is that candidates assume DMS alone can handle schema conversion, but DMS is a data migration service, not a schema transformation tool; SCT is required for converting complex Oracle schemas to Redshift-optimized formats.

How to eliminate wrong answers

Option A is wrong because AWS DMS cannot directly migrate a heavily normalized Oracle schema to Redshift without schema conversion; Redshift is a columnar data warehouse optimized for denormalized schemas, and DMS alone does not handle schema transformation for complex joins. Option B is wrong because exporting to flat files and using S3 Transfer Acceleration for a 5 TB migration within 2 days is feasible but lacks schema conversion; the heavily normalized schema with complex joins would not be optimized for Redshift, leading to poor query performance. Option D is wrong because AWS Glue can crawl and create tables, but it is not designed for schema conversion from Oracle to Redshift; it would require extensive custom ETL logic to handle the normalization and complex joins, making it inefficient for a time-constrained migration.

Full explanation →
247
MCQmedium

A logistics company uses Amazon RDS for MySQL to track package shipments. The 'shipments' table contains 200 million rows and has a primary key on 'shipment_id' (UUID). The application frequently queries for shipments by 'tracking_number', which is a unique string of 20 characters. The DBA created a B-tree index on tracking_number. The queries by tracking_number are fast, but inserts are becoming slower over time. The table has 50 GB of data. The company plans to double the insert rate next month. The database is a db.r5.large instance with 500 GB of Provisioned IOPS SSD storage. The instance's CPU utilization is below 30%, and there is no lock contention. What should the database specialist do to improve insert performance?

A.Add a read replica and route insert queries to the replica.
B.Drop the index on tracking_number to reduce write overhead.
C.Change the primary key from UUID to an auto-increment integer, and keep the tracking_number index.
D.Increase the provisioned IOPS to 20,000.
AnswerC

An auto-increment primary key allows sequential inserts, reducing page splits and improving insert speed.

Why this answer

UUID primary keys cause random writes and index fragmentation, degrading insert performance as the table grows. Switching to an auto-increment integer primary key allows sequential writes to the clustered index, reducing page splits and improving insert throughput. The B-tree index on tracking_number remains to support fast queries, while the new primary key eliminates the UUID write overhead.

Exam trap

The trap here is that candidates often focus on index overhead or IOPS as the cause of slow inserts, overlooking the fundamental impact of UUID fragmentation on clustered index write performance.

How to eliminate wrong answers

Option A is wrong because read replicas cannot accept write traffic; they are read-only and do not improve insert performance. Option B is wrong because dropping the index on tracking_number would severely degrade query performance for the frequent tracking_number lookups, and the index overhead is not the primary cause of slow inserts (UUID fragmentation is). Option D is wrong because increasing IOPS does not address the root cause of random write amplification from UUID primary keys; CPU and IOPS are not the bottleneck (CPU is below 30%, storage is Provisioned IOPS SSD).

Full explanation →
248
MCQeasy

A company is migrating a 100 GB Microsoft SQL Server database from an on-premises data center to Amazon RDS for SQL Server. The migration uses AWS DMS with full load only (no ongoing replication). The full load completes successfully, but the company's application team reports that some data in the target database is missing. The source database was not modified during the migration. The DMS task logs show no errors. What is the MOST likely cause of the missing data?

A.The DMS task used the 'Change Data Capture' mode instead of full load.
B.The target RDS instance was not large enough to store all data.
C.The DMS task did not use transactional consistency.
D.The source database had foreign key constraints that were not migrated.
AnswerC

Without transactional consistency, DMS may not capture all changes in a consistent state.

Why this answer

DMS full load captures a snapshot of the source database. If the source database has active transactions during the snapshot, some changes may not be included. Using transactional consistency ensures a consistent snapshot.

Disabling foreign keys is not recommended. Using a larger instance does not affect consistency.

Full explanation →
249
MCQmedium

A social media application uses Amazon DynamoDB as its primary data store. The application stores user posts and allows users to retrieve the most recent 10 posts of users they follow. The access pattern is a followee-based query that needs to be highly scalable and low-latency. Which DynamoDB table design should the database specialist recommend?

A.Use a partition key of post ID and a local secondary index on the followee ID
B.Use a single table with a scan operation and filter on the followee attribute
C.Use a composite primary key with a partition key of follower ID and a sort key of timestamp, and store the followee ID as an attribute
D.Design the table with a partition key of user ID and a sort key of timestamp, and create a global secondary index (GSI) on followee ID
AnswerC

This design allows efficient Query on the follower ID to retrieve recent posts in reverse order by timestamp.

Why this answer

It models the access pattern directly: the follower ID as the partition key ensures all posts from followed users are co-located, and the sort key of timestamp allows efficient retrieval of the most recent 10 posts via a Query with a limit of 10 and descending order. This design avoids expensive scans or secondary index lookups, meeting the low-latency and scalability requirements.

Exam trap

The trap here is that candidates often choose Option D because they think a GSI on followee ID solves the query pattern, but they overlook that the base table's partition key (user ID) does not match the follower-based access pattern, requiring multiple queries or a Scan, and the GSI still incurs additional latency and cost for index maintenance.

How to eliminate wrong answers

Option A is wrong because using post ID as the partition key scatters posts randomly across partitions, and a local secondary index on followee ID would require a full table scan to find all posts for a given followee, as LSIs cannot be queried independently of the base table's partition key. Option B is wrong because a Scan operation reads every item in the table and then filters on the followee attribute, which is not scalable and violates the low-latency requirement for a social media application. Option D is wrong because while a GSI on followee ID allows querying by followee, the base table's partition key of user ID does not align with the follower-based access pattern, and the GSI would still require a separate query for each followee, leading to multiple round trips and higher latency compared to a single query in Option C.

Full explanation →
250
MCQeasy

A company is using Amazon RDS for MySQL and wants to restrict access to the database based on the source IP address. Which AWS feature should be used to achieve this?

A.DB Parameter Groups
B.VPC Security Groups
C.IAM Database Authentication
D.Network ACLs
AnswerB

Security groups act as a firewall for the DB instance, controlling inbound traffic based on IP or other security groups.

Why this answer

Security groups act as a virtual firewall for RDS instances. You can specify inbound rules that allow traffic only from certain IP addresses or other security groups. Network ACLs are for subnets, not individual instances.

IAM policies control API access, not network traffic. DB parameter groups configure database engine parameters.

Full explanation →
251
Multi-Selecthard

A company is deploying a new application on AWS that requires a highly available relational database with automatic failover and read scaling. The database size is 100 GB and the workload is balanced between reads and writes. Which THREE AWS services or features should be used?

Select 3 answers
A.Multi-AZ deployment
B.DynamoDB Accelerator (DAX)
C.Amazon Aurora Replicas
D.Amazon Aurora
E.Amazon RDS Proxy
AnswersA, C, D

Aurora automatically replicates data across AZs, providing failover.

Why this answer

Multi-AZ deployment (Option A) is correct because it provides automatic failover for Amazon RDS by provisioning a synchronous standby replica in a different Availability Zone. If the primary DB instance fails, Amazon RDS automatically fails over to the standby, ensuring high availability without manual intervention. This directly meets the requirement for automatic failover in a relational database scenario.

Exam trap

The trap here is that candidates may confuse Amazon RDS Proxy with a high-availability or failover solution, but it only manages connections and does not replicate data or provide automatic failover.

Full explanation →
252
MCQeasy

A database administrator is reviewing the configuration of an RDS MySQL instance. Based on the exhibit, which change would MOST improve the database's performance under heavy write workloads without increasing costs significantly?

A.Change the DB parameter group to a custom one with optimized MySQL parameters.
B.Increase the backup retention period to 35 days to improve performance.
C.Enable Multi-AZ to improve write performance.
D.Change the storage type from gp2 to gp3 to get higher baseline IOPS and throughput.
AnswerD

gp3 offers better performance per dollar than gp2.

Why this answer

Gp3 storage provides higher baseline IOPS and throughput than gp2 at the same cost, which directly improves performance under heavy write workloads. Option A is incorrect because parameter group tuning can help but is not the most impactful change without additional cost. Option B is incorrect because backup retention period does not affect performance.

Option C is incorrect because Multi-AZ provides high availability, not improved write performance.

Full explanation →
253
MCQeasy

A developer reports that an application's write requests to a DynamoDB table are failing with ProvisionedThroughputExceededException. The table uses provisioned capacity. Which immediate action will resolve the issue?

A.Switch the table to on-demand capacity
B.Implement exponential backoff in the application
C.Enable DynamoDB Accelerator (DAX)
D.Delete all global secondary indexes
AnswerB

Exponential backoff retries requests with increasing delays, reducing throttling.

Why this answer

The correct immediate action is to implement exponential backoff in the application. This retry mechanism gradually increases wait time between retries, reducing the request rate to stay within provisioned throughput limits. Option A is incorrect because switching to on-demand capacity takes time and is not immediate.

Option C is incorrect because DAX is a read cache and does not affect write throughput. Option D is incorrect because deleting GSIs does not resolve write throttling to the base table.

Full explanation →
254
MCQmedium

A company is migrating a 2 TB PostgreSQL database from on-premises to Amazon RDS for PostgreSQL. The database has a 4-hour downtime window. The company requires minimal data loss and wants to use AWS DMS. The on-premises network has a 100 Mbps internet connection. Which migration method should the company use?

A.Use AWS Schema Conversion Tool (SCT) to migrate the data to Amazon RDS.
B.Use AWS DMS with a full load only, then stop the source database and resume applications.
C.Use pg_dump and pg_restore to export and import the database during the downtime window.
D.Use AWS DMS with a full load and ongoing change data capture (CDC) replication.
AnswerD

Full load plus CDC minimizes downtime by replicating changes continuously.

Why this answer

AWS DMS with a full load and ongoing change data capture (CDC) replication allows the company to migrate the 2 TB database with minimal data loss within the 4-hour downtime window. The full load transfers the existing data, and CDC captures and applies ongoing changes from the source database to the target RDS instance, reducing the final cutover downtime to seconds or minutes. This approach is ideal for large databases with tight downtime constraints and limited bandwidth (100 Mbps), as the initial full load can run before the downtime window, and only the final CDC catch-up occurs during the window.

Exam trap

The trap here is that candidates often assume pg_dump/pg_restore or a full-load-only DMS job can complete within the downtime window, ignoring the bandwidth calculation (2 TB at 100 Mbps = ~46 hours) and the need for minimal data loss, which only CDC can satisfy.

How to eliminate wrong answers

Option A is wrong because AWS Schema Conversion Tool (SCT) is used for converting database schemas from one engine to another (e.g., Oracle to PostgreSQL), not for migrating data to the same engine; it also does not handle data migration itself. Option B is wrong because using AWS DMS with a full load only would require stopping the source database during the entire data transfer, which would exceed the 4-hour downtime window given the 2 TB size and 100 Mbps bandwidth (approximately 46 hours for full load). Option C is wrong because pg_dump and pg_restore are native PostgreSQL tools that require the source database to be stopped or in read-only mode during the entire export/import process, which would not complete within the 4-hour window due to the large data volume and bandwidth limitation.

Full explanation →
255
MCQhard

A company has an Amazon RDS for MySQL database with Multi-AZ deployment. The database is experiencing high CPU utilization due to a reporting workload. The company wants to migrate to Amazon Aurora MySQL to improve performance and scalability. The migration must have minimal downtime. Which migration strategy meets these requirements?

A.Create an Aurora MySQL replica from the RDS MySQL instance and promote it
B.Take a snapshot of the RDS instance and restore it to an Aurora cluster
C.Migrate to a larger RDS MySQL instance to handle the workload
D.Use AWS DMS with full load and ongoing replication
AnswerA

This allows minimal downtime and uses native replication.

Why this answer

Creating an Aurora MySQL replica from an existing RDS MySQL instance uses the native MySQL replication protocol to perform an online migration with minimal downtime. Once the replica is fully synchronized, you can promote it to become a standalone Aurora cluster, which provides better performance and scalability for the reporting workload.

Exam trap

The trap here is that candidates often assume AWS DMS is the only way to achieve minimal downtime, but the native Aurora replica feature provides a simpler and faster migration path with even lower downtime when the source engine is compatible.

How to eliminate wrong answers

Option B is wrong because taking a snapshot of the RDS instance and restoring it to an Aurora cluster is an offline migration method that requires the source database to be unavailable during the snapshot process, leading to significant downtime. Option C is wrong because it does not migrate to Aurora at all; it only scales the existing RDS instance vertically, which does not address the requirement to migrate to Aurora MySQL for improved performance and scalability. Option D is wrong because while AWS DMS with full load and ongoing replication can achieve minimal downtime, it is more complex and slower to set up compared to creating an Aurora replica, and the question specifically asks for the strategy that meets the requirements with minimal downtime, making the native Aurora replica approach the most straightforward.

Full explanation →
256
MCQeasy

A startup is building a social media analytics platform that requires storing time-series data with frequent writes and queries for the last hour. Which AWS database service is BEST suited for this workload?

A.Amazon Timestream
B.Amazon RDS with MySQL
C.Amazon Neptune
D.Amazon DynamoDB
AnswerA

Timestream is a fast, scalable, serverless time-series database.

Why this answer

Amazon Timestream is a purpose-built time-series database that efficiently handles high-frequency writes and recent-time queries (e.g., last hour) with automatic data tiering (in-memory store for recent data, magnetic store for historical). Its serverless architecture and built-in time-series functions (e.g., interpolation, smoothing) make it ideal for social media analytics workloads requiring low-latency queries on recent data.

Exam trap

The trap here is that candidates often choose DynamoDB (Option D) because of its high write throughput and TTL features, but they overlook the lack of native time-series query functions and automatic data tiering, which are essential for efficient recent-time queries in this workload.

How to eliminate wrong answers

Option B (Amazon RDS with MySQL) is wrong because relational databases are not optimized for high-velocity time-series writes and recent-time queries; they incur overhead from indexing, ACID transactions, and schema rigidity, leading to poor write throughput and query performance for this pattern. Option C (Amazon Neptune) is wrong because it is a graph database designed for highly connected data (e.g., social graphs, recommendation engines), not for time-series data with frequent writes and time-range queries. Option D (Amazon DynamoDB) is wrong because while it supports high write throughput, it lacks native time-series optimizations (e.g., automatic data tiering, time-based partitioning, and built-in time-series functions), requiring complex application-level sharding and TTL management to handle recent-time queries efficiently.

Full explanation →
257
MCQeasy

A startup 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 frequently queries the top 10 scores for a given game. Recently, users have reported that the leaderboard is showing stale data. The DBA checks the CloudWatch metrics and sees no throttling. The table has auto scaling enabled. The application uses eventual consistent reads. The DBA suspects that the issue is related to write conflicts. What should the DBA do to ensure the leaderboard shows the most recent data?

A.Modify the application to use strongly consistent reads for leaderboard queries.
B.Enable DynamoDB Streams and process updates in near-real-time.
C.Enable DynamoDB Accelerator (DAX) for caching.
D.Increase the write capacity units to reduce write throttling.
AnswerA

Strongly consistent reads guarantee that the read returns the most recent write. This directly addresses the stale data issue.

Why this answer

Strongly consistent reads return the most up-to-date data from DynamoDB, ensuring the leaderboard displays the latest scores. Option B is incorrect because DynamoDB Streams capture changes but do not affect read consistency. Option C is incorrect because DAX is a caching layer that may serve stale data, not improve consistency.

Option D is incorrect because write capacity adjustments do not address read consistency issues.

Full explanation →
258
MCQmedium

A company is designing a database for a global e-commerce platform that requires low-latency reads and writes across multiple AWS Regions. The database must support strongly consistent reads and provide automatic failover. Which AWS service should the company use?

A.Amazon ElastiCache for Redis global datastore
B.Amazon S3 with cross-region replication
C.Amazon Aurora Global Database
D.Amazon DynamoDB global tables
AnswerD

DynamoDB global tables provide multi-Region, multi-master replication with strong consistency and automatic failover.

Why this answer

Amazon DynamoDB global tables provide a fully managed, multi-Region, multi-active database solution that delivers low-latency reads and writes across AWS Regions. It supports strongly consistent reads when using the same-Region endpoint and offers automatic failover by allowing any Region to handle writes independently, ensuring high availability without manual intervention.

Exam trap

The trap here is that candidates often confuse Amazon Aurora Global Database (which is active-passive) with a multi-active solution, assuming it supports automatic failover for writes across Regions, but DynamoDB global tables are the only option that provides true multi-Region write capability with automatic failover.

How to eliminate wrong answers

Option A is wrong because Amazon ElastiCache for Redis global datastore is an in-memory cache, not a durable database, and it does not support strongly consistent reads across Regions (it offers eventual consistency for cross-Region replication). Option B is wrong because Amazon S3 with cross-region replication is an object storage service that does not support strongly consistent writes across Regions (replication is eventually consistent) and lacks automatic failover for database workloads. Option C is wrong because Amazon Aurora Global Database supports only one primary Region for writes (active-passive), so it does not provide multi-Region write capability or automatic failover for writes across Regions; failover requires promoting a secondary Region, which is not automatic.

Full explanation →
259
MCQeasy

A database administrator is monitoring Amazon RDS for PostgreSQL using CloudWatch. The DB instance shows high CPU utilization, but the number of connections is normal. What is the most likely cause of the high CPU utilization?

A.The DB instance has a low burst balance for gp2 storage.
B.The instance is low on memory and is swapping.
C.There are long-running queries or missing indexes causing high CPU usage.
D.The DB instance has a large number of Read Replicas.
AnswerC

Inefficient queries can consume CPU cycles even with normal connection counts.

Why this answer

High CPU utilization with a normal number of connections often indicates inefficient queries or missing indexes, which cause full table scans and excessive CPU usage. Option A is incorrect because gp2 burst balance affects storage performance, not CPU. Option B is incorrect because memory pressure and swapping typically cause high I/O wait times, not sustained high CPU.

Option D is incorrect because Read Replicas offload read traffic, they do not cause high CPU on the primary instance.

Full explanation →
260
MCQmedium

Refer to the exhibit. A database engineer runs the query above to troubleshoot an application error. The query returns no results even though the database is generating errors. What is the most likely reason?

A.The log stream format uses a different field name for the error message
B.The regex pattern does not match because it is case-sensitive
C.The query does not specify a time range, so no results are returned
D.The log group has not been configured to export to CloudWatch Logs
AnswerA

Correct. The log stream format might use a different field name for the error message, such as 'errorMessage' or 'event.message'. The query expects the field 'message', but the actual log stream may store the error in another field, causing the query to return no results.

Why this answer

The query filters on the 'message' field, but the log stream format may use a different field name for the error message, such as 'errorMessage' or 'event.message'. Since the query returns no results despite errors existing, the most likely reason is a field name mismatch. Option B is incorrect because the query uses a regex pattern with case-insensitive matching (indicated by the 'i' flag), so case sensitivity is not an issue.

Option C is incorrect because queries in CloudWatch Logs Insights default to the last 15 minutes if no time range is specified, so that would not cause zero results if errors are recent. Option D is incorrect because exporting to CloudWatch Logs is not required for querying; the logs are already in CloudWatch Logs.

Full explanation →
261
MCQeasy

A company wants to test an application against an Amazon RDS for MySQL database with a recent set of production data without impacting the production database. The test database must be available quickly and be refreshed regularly. Which solution should be used?

A.Export production data to S3 and import into a test instance using Lambda.
B.Create a read replica of the production database, then promote it to a standalone instance for testing.
C.Use AWS DMS to continuously replicate data from production to a test RDS instance.
D.Create a snapshot of the production database and restore it as a new RDS instance.
AnswerB

A read replica can be promoted quickly and refreshed by creating a new replica.

Why this answer

Creating a read replica of the production RDS for MySQL database and then promoting it to a standalone instance is the fastest way to obtain a near-current copy of production data without impacting the source. The replica is created asynchronously using MySQL's native binlog replication, and promotion breaks the replication link, leaving a fully writable test instance. This approach minimizes setup time because the replica is already hydrated with data from the moment of creation.

Exam trap

The trap here is that candidates often choose snapshot restore (Option D) because it seems like the most straightforward backup method, but they overlook that a read replica can be promoted to a standalone instance much faster and with less operational overhead for regular refreshes.

How to eliminate wrong answers

Option A is wrong because exporting production data to S3 and importing via Lambda introduces significant latency and complexity; it is not the quickest method and requires custom scripting, whereas RDS read replicas are a managed, one-click solution. Option C is wrong because AWS DMS continuous replication is designed for ongoing migration or synchronization, not for creating an immediate, point-in-time test copy; it adds overhead and is slower to set up than a read replica. Option D is wrong because creating a snapshot and restoring it as a new RDS instance takes longer than promoting a read replica, as snapshots are point-in-time backups that must be fully restored before the instance is available, whereas a read replica is already running and can be promoted in minutes.

Full explanation →
262
MCQhard

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle using AWS DMS. The source database is 2 TB and has high transaction volume. The migration needs minimal downtime. Currently, full load completes but CDC task fails with 'ORA-1555: snapshot too old' errors. What should the DBA do to resolve this?

A.Restart the migration with a new full load and use a smaller task.
B.Increase the undo retention period and undo tablespace size on the source Oracle database.
C.Enable supplemental logging on the source and use a larger DMS instance.
D.Reduce the transaction volume by pausing non-essential transactions during CDC.
AnswerB

Larger undo retention prevents snapshot too old errors.

Why this answer

The 'ORA-1555: snapshot too old' error occurs when Oracle's undo data for a read-consistent view is overwritten before DMS can read it. Increasing the undo retention period and undo tablespace size on the source database ensures that undo data is preserved longer, allowing DMS's CDC task to read consistent data without errors. Option B is correct because it directly addresses the root cause.

Option A would restart the full load but not fix the CDC failure. Option C (supplemental logging and larger DMS instance) does not resolve undo retention issues. Option D (reducing transactions) is not practical and may cause data loss.

Therefore, the correct solution is to increase undo retention and tablespace size.

Full explanation →
263
MCQhard

A financial company uses Amazon RDS for PostgreSQL with a custom parameter group. The security team wants to ensure that all connections to the database are encrypted in transit. Which action should the database administrator take?

A.Attach an IAM role to the RDS instance to authenticate users.
B.Change the database port to 8432 to use a non-standard port.
C.Set 'ssl' to 'off' in the parameter group.
D.Set the parameter 'rds.force_ssl' to 1 in the custom parameter group.
E.Modify the security group to allow inbound traffic only on port 5432 with the '--ssl' option.
AnswerD

Setting 'rds.force_ssl' to 1 forces all connections to use SSL/TLS, ensuring encryption in transit.

Why this answer

Setting the parameter 'rds.force_ssl' to 1 in the RDS for PostgreSQL custom parameter group forces all connections to use SSL/TLS, ensuring encryption in transit. Option A is incorrect because IAM roles provide authentication, not transport encryption. Option B is incorrect because changing the port does not encrypt data.

Option C is incorrect because setting 'ssl' to off disables encryption. Option E is incorrect because modifying a security group to allow inbound traffic on port 5432 does not enforce encryption; the '--ssl' option is a client-side parameter, not enforceable via security groups.

Full explanation →
264
MCQhard

A company runs a critical application on Amazon RDS for MySQL with Multi-AZ deployment. The application performs frequent writes. The DB instance's CPU utilization is consistently above 80%, and the write latency is high. The company wants to improve write performance without changing the application code. Which solution is MOST effective?

A.Enable Multi-AZ with synchronous replication to a standby instance.
B.Add a read replica to offload read traffic.
C.Increase the DB instance class to a larger size with more vCPUs.
D.Migrate the database to Amazon Aurora MySQL.
AnswerD

Amazon Aurora MySQL uses a distributed storage system with a separate log writer, reducing write latency and improving overall write performance. It also handles high CPU utilization better due to its efficient architecture.

Why this answer

Migrating to Amazon Aurora MySQL is the most effective solution because Aurora uses a distributed, SSD-backed storage system with a separate log writer process that reduces write latency. Increasing the DB instance class (Option C) can improve CPU capacity but does not address the underlying storage write latency as effectively as Aurora. Adding a read replica (Option B) offloads read traffic but does not improve write performance.

Enabling Multi-AZ with synchronous replication (Option A) is already in place and can increase write latency due to synchronous replication; it does not solve the high CPU utilization issue.

Full explanation →
265
Multi-Selectmedium

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database has several large tables with frequent INSERT and UPDATE operations. Which TWO actions should be taken to optimize performance after migration?

Select 2 answers
A.Enable autovacuum and configure it to run more frequently on the large tables.
B.Use the Aurora PostgreSQL integration with Amazon S3 for bulk data loading.
C.Set synchronous_commit to ON to ensure data durability.
D.Deploy an RDS Proxy in front of the Aurora cluster to reduce connection overhead.
E.Partition the large tables by date to improve query performance.
AnswersA, B

Autovacuum prevents bloat from frequent updates, maintaining query performance.

Why this answer

Options A and B are correct. Enabling autovacuum and tuning it to run more frequently on large tables is essential in PostgreSQL to reclaim storage and prevent transaction ID wraparound, which is critical after a migration with high DML. Using Aurora PostgreSQL integration with Amazon S3 for bulk data loading is efficient because it leverages parallel processing and avoids network overhead.

Option C is incorrect because setting synchronous_commit to ON reduces performance for write-heavy workloads by waiting for disk writes; OFF or REMOTE_WRITE is recommended. Option D is incorrect because RDS Proxy helps with connection management but does not directly optimize DML performance for large tables. Option E is incorrect because while partitioning can help query performance, it is not a direct optimization for INSERT/UPDATE operations and may add complexity; Aurora's storage layer already handles large tables efficiently.

Full explanation →
266
MCQeasy

A company is designing a database for an IoT application that ingests millions of time-series data points per second. The database must support high-throughput writes and efficient querying of recent data. Which AWS database service is MOST suitable?

A.Amazon RDS for PostgreSQL
B.Amazon Timestream
C.Amazon DynamoDB with TTL
D.Amazon Redshift
AnswerB

Timestream is purpose-built for time-series.

Why this answer

Amazon Timestream is purpose-built for time-series data, offering a serverless architecture that ingests millions of data points per second with automatic scaling. It provides efficient storage and querying of recent data through its memory store, while tiering older data to a cost-optimized magnetic store, making it the most suitable choice for high-throughput IoT time-series workloads.

Exam trap

AWS often tests the misconception that any high-throughput NoSQL database (like DynamoDB) is suitable for time-series workloads, but the key differentiator is the need for native time-series query capabilities and automatic data lifecycle management, which Timestream provides and DynamoDB lacks.

How to eliminate wrong answers

Option A is wrong because Amazon RDS for PostgreSQL is a relational database optimized for OLTP workloads with row-based storage, not designed for the high-ingest rates and time-series-specific query patterns (e.g., downsampling, interpolation) required by IoT data. Option C is wrong because Amazon DynamoDB with TTL supports high-throughput writes but lacks native time-series query optimizations such as time-based aggregation, window functions, or automatic data tiering; TTL only handles data expiration, not efficient querying of recent data across millions of points per second. Option D is wrong because Amazon Redshift is a columnar data warehouse optimized for complex analytical queries on large datasets, not for real-time, high-frequency writes of individual time-series data points; its ingestion latency and cost model are unsuitable for per-second write rates.

Full explanation →
267
MCQmedium

A company is migrating a database using AWS DMS. The IAM policy shown is attached to the DMS replication instance role. When the DMS replication task is created in the us-west-2 region, it fails. What is the most likely cause?

A.The IAM policy does not allow the 'dms:CreateReplicationTask' action.
B.The IAM policy does not specify the VPC where the replication instance is deployed.
C.The IAM policy does not specify the resource ARN for the replication instance.
D.The IAM policy restricts the region to us-east-1, but the task is created in us-west-2.
AnswerD

The condition 'aws:RequestedRegion' restricts to us-east-1 only.

Why this answer

The IAM policy explicitly restricts the region to us-east-1 using the `aws:RequestedRegion` condition key. When the DMS replication task is created in us-west-2, the policy denies the `dms:CreateReplicationTask` action because the region condition fails, causing the task creation to fail. DMS replication tasks require the IAM role to have permissions in the same region where the task is being created.

Exam trap

The trap here is that candidates often overlook the `Condition` block with `aws:RequestedRegion` and focus only on the Action and Resource fields, assuming a missing action or resource ARN is the cause, when the real issue is a regional restriction enforced by the condition key.

How to eliminate wrong answers

Option A is wrong because the policy includes `dms:CreateReplicationTask` in the Action list, so the action is allowed; the failure is due to the region condition, not a missing action. Option B is wrong because DMS replication instances are associated with a VPC via subnet groups, not by specifying the VPC in the IAM policy; the IAM policy does not need to specify the VPC. Option C is wrong because the policy uses a wildcard `*` for the Resource, which covers all DMS resources including the replication instance; the issue is the region condition, not the resource ARN.

Full explanation →
268
MCQmedium

A company uses Amazon DynamoDB to store user session data for a web application. The table has a partition key of 'user_id' and no sort key. Each item is about 5 KB. The application performs frequent GetItem and UpdateItem operations. Recently, the application has been experiencing higher than expected latency and some throttling. The table's read and write capacity are set to on-demand mode. The CloudWatch metrics show that the ConsumedWriteCapacityUnits are well below the provisioned limits (if they were provisioned), but there are occasional ThrottledWriteEvents. The application team also notices that the throttling occurs for specific users. What is the most likely cause and solution?

A.Create a global secondary index with a different partition key for the hot users.
B.Add a sort key to the table to improve data distribution.
C.Implement write sharding by appending a random suffix to the partition key for high-traffic users.
D.Switch to provisioned capacity mode and increase the write capacity units significantly.
AnswerC

Write sharding by appending a random suffix to the partition key spreads writes for a hot user across multiple partition keys, balancing the load among partitions and preventing throttling.

Why this answer

Implement write sharding by appending a random suffix to the partition key for high-traffic users. In DynamoDB on-demand mode, each partition can handle up to 3000 read request units or 1000 write request units per second. When a single partition key (user_id) receives high write traffic, that partition can become a hot partition and be throttled, even though overall consumption is within limits.

Write sharding distributes the writes for a hot user across multiple partition key values by adding a random suffix to the user_id, thereby spreading the load across multiple partitions. Option A (creating a GSI) would not solve the base table write throttling because the base table writes still target the same partition. Option B (adding a sort key) does not change the partition key distribution; the partition key remains the same, so the hot partition issue persists.

Option D (switching to provisioned capacity) would not automatically solve the hot partition; it would require proper partition design similarly.

Full explanation →
269
MCQmedium

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 table is configured with on-demand capacity. During a major tournament, the application experiences high latency and some requests return 'ProvisionedThroughputExceededException' errors. The CloudWatch metric 'ThrottledRequests' spikes. The application uses a single partition key for all writes during the tournament (game_id = 'tournament_final'). What is the most likely cause of the throttling, and what is the best solution?

A.The application is using a single partition key, causing all writes to go to one partition. The team should redesign the partition key to distribute writes across multiple partitions
B.The application is using a single partition key, causing all writes to go to one partition. The team should implement DAX to cache writes
C.The table has a global secondary index that is throttling writes; the team should remove the GSI
D.The table is using on-demand capacity, which has a maximum throughput limit per partition; the team should switch to provisioned capacity with auto scaling
AnswerA

Distributing the write load across partitions avoids throttling.

Why this answer

Even with on-demand capacity, each partition has a maximum throughput limit (read/write capacity per partition). When all writes use the same partition key ('tournament_final'), they all go to a single partition, exceeding its limit and causing throttling (ThrottledRequests and ProvisionedThroughputExceededException). The best solution is to redesign the partition key to distribute writes across multiple partitions (e.g., add a suffix like user_id or timestamp).

Option B is incorrect because DAX is a caching layer for reads, not writes; it does not alleviate write throttling. Option C is incorrect because the question does not mention a GSI, and a GSI would not cause this issue on the base table. Option D is incorrect because switching to provisioned capacity does not solve the hot partition problem; the same partition key would still overload a single partition under provisioned capacity.

Exam trap

The trap is assuming that on-demand capacity eliminates all throttling. In reality, on-demand capacity has per-partition limits (up to 1,000 write capacity units per partition) that can still be exceeded if a single partition receives all traffic.

Full explanation →
270
MCQhard

A financial services company stores sensitive data in an Amazon DynamoDB table. The security team requires that all data at rest be encrypted with a customer-managed key that is rotated automatically every 12 months. The company also needs to audit key usage. Which solution meets these requirements?

A.Use server-side encryption with S3-managed keys (SSE-S3) for the DynamoDB table.
B.Use AWS CloudHSM to generate and store the encryption key. Configure the application to encrypt data before writing to DynamoDB.
C.Enable encryption at rest using the default DynamoDB encryption option (AWS owned key). Use AWS CloudTrail to audit key usage.
D.Enable encryption at rest using an AWS KMS customer-managed CMK. Configure automatic key rotation with a 12-month period. Use AWS CloudTrail to audit key usage.
AnswerD

Encryption at rest with an AWS KMS customer-managed CMK allows automatic key rotation every 12 months (configurable) and CloudTrail can audit KMS API calls for key usage, meeting all requirements.

Why this answer

DynamoDB supports encryption at rest with AWS KMS customer-managed CMKs. Automatic key rotation every 12 months is a feature of KMS for CMKs. CloudTrail logs KMS API calls for auditing.

Option A is incorrect because SSE-S3 is for S3, not DynamoDB. Option B is incorrect because CloudHSM does not provide automatic key rotation every 12 months and requires application-side encryption. Option C is incorrect because the default DynamoDB encryption uses an AWS owned key, which is not customer-managed and rotates automatically every 3 years, not 12 months.

Option D is correct: it uses a customer-managed CMK with yearly rotation and CloudTrail for auditing.

Full explanation →
271
Multi-Selectmedium

A company is migrating a MySQL database to Amazon RDS for MySQL. They want to use AWS DMS for continuous replication. Which TWO prerequisites must be met before starting the migration?

Select 2 answers
A.Enable binary logging (binlog) on the source MySQL database.
B.Ensure the DMS replication instance has network connectivity to the source and target databases.
C.Set the source database to read-only mode during migration.
D.Place the source database in a VPC.
E.Create an S3 bucket to store the migration logs.
AnswersA, B

Binary logging is necessary for DMS to capture ongoing changes.

Why this answer

AWS DMS uses MySQL's binary log (binlog) to capture ongoing changes for continuous replication (CDC). Enabling binlog on the source database is mandatory because DMS reads the binlog to identify insert, update, and delete operations after the initial full load. Without binlog enabled, DMS cannot perform change data capture and the migration will be limited to a one-time full load only.

Exam trap

The trap here is that candidates often assume the source must be read-only during migration (Option C), but DMS supports live migration with zero downtime by using CDC, so read-only mode is only needed for certain homogenous migrations or final cutover phases, not as a general prerequisite.

Full explanation →
272
MCQmedium

A company is migrating a 2 TB Oracle database from on-premises to Amazon RDS for Oracle. The network bandwidth is 100 Mbps. The migration must be completed within 3 days. Which approach is MOST efficient?

A.Use AWS DMS with parallel load and ongoing replication.
B.Use Oracle RMAN to create a backup and restore to RDS.
C.Use Oracle Data Pump with a single export and import.
D.Use Oracle GoldenGate for real-time replication.
AnswerA

DMS parallel load reduces migration time.

Why this answer

AWS DMS with parallel load and ongoing replication is the most efficient approach because it can handle the 2 TB migration within the 3-day window over a 100 Mbps link. At 100 Mbps, the theoretical maximum transfer is about 1.08 TB per day (100 Mbps * 86400 seconds / 8 bits per byte / 1024^4), so 2 TB would take nearly 2 days just for the full load. DMS's parallel load splits the data into multiple tasks, maximizing throughput and reducing the full-load time, while ongoing replication captures changes during the migration, allowing a seamless cutover without downtime.

Exam trap

The trap here is that candidates often assume Oracle-native tools like RMAN or Data Pump are always the best for migrations, but they overlook the bandwidth constraint and RDS's lack of direct OS access, making DMS the only viable option for a time-bound, large-scale migration with minimal downtime.

How to eliminate wrong answers

Option B is wrong because Oracle RMAN cannot be used to directly restore a backup to Amazon RDS for Oracle; RDS does not provide access to the underlying file system or allow RMAN restore operations, and the backup would need to be converted or migrated via other tools. Option C is wrong because Oracle Data Pump with a single export and import would be too slow for a 2 TB database over 100 Mbps, as a single-threaded export/import cannot saturate the bandwidth and would likely exceed the 3-day window, especially with network overhead. Option D is wrong because Oracle GoldenGate is designed for real-time replication and continuous synchronization, which is overkill for a one-time migration and adds unnecessary complexity and cost; it is better suited for ongoing replication scenarios, not for a time-bound full load.

Full explanation →
273
MCQmedium

A company uses Amazon RDS for MySQL to store e-commerce order data. The orders table has millions of rows and is frequently queried by order_id. The company also runs periodic reports that aggregate data by order_date. The reports are slow. The database has a primary key on order_id. The company needs to improve report performance without affecting OLTP queries. Which design change should be made?

A.Create a secondary index on order_date.
B.Upgrade to a larger instance type.
C.Create a read replica and run reports on the replica.
D.Partition the table by order_date.
AnswerA

A secondary index on order_date speeds up date-based aggregations without impacting OLTP queries.

Why this answer

Creating a secondary index on order_date allows MySQL to quickly locate rows matching the report's date range without scanning the entire table, significantly improving aggregation performance. This index is separate from the primary key on order_id, so OLTP queries that filter by order_id remain unaffected. The index provides a balanced approach: it accelerates read-heavy reporting while adding minimal overhead to write operations.

Exam trap

The trap here is that candidates often assume a read replica (Option C) solves all performance issues, but without an appropriate index, the replica still performs full table scans, making the reports slow regardless of where they run.

How to eliminate wrong answers

Option B is wrong because upgrading to a larger instance type increases CPU, memory, and I/O capacity but does not address the root cause of slow reports—the lack of an efficient access path for date-based queries; it merely masks the performance issue with more resources. Option C is wrong because creating a read replica offloads reporting traffic from the primary instance, but the replica still lacks an index on order_date, so the reports will remain slow on the replica. Option D is wrong because partitioning the table by order_date can improve partition pruning for date-range queries, but it introduces complexity and may negatively impact OLTP queries that filter by order_id, as MySQL must search across multiple partitions; additionally, partitioning does not replace the need for an index on the partitioning key.

Full explanation →
274
MCQhard

A company needs to migrate an on-premises Oracle database to AWS with minimal changes to the application code. The application uses complex stored procedures and has high availability requirements. Which database service should be used?

A.Amazon RDS for Oracle
B.Amazon DynamoDB
C.Amazon Redshift
D.Amazon Aurora PostgreSQL
AnswerA

RDS for Oracle provides full Oracle compatibility with Multi-AZ for high availability.

Why this answer

Amazon RDS for Oracle is the correct choice because it provides native Oracle compatibility, supporting complex stored procedures, PL/SQL, and existing application code with minimal changes. It also offers Multi-AZ deployments for high availability, meeting the requirement without requiring a complete rewrite.

Exam trap

The trap here is that candidates may choose Amazon Aurora PostgreSQL due to its high availability and performance, overlooking the fact that it does not support Oracle-specific stored procedures and PL/SQL, which would require costly application rewrites.

How to eliminate wrong answers

Option B is wrong because Amazon DynamoDB is a NoSQL key-value and document database that does not support complex stored procedures or Oracle PL/SQL, requiring significant application code changes. Option C is wrong because Amazon Redshift is a petabyte-scale data warehouse optimized for analytical queries, not for transactional workloads with complex stored procedures. Option D is wrong because Amazon Aurora PostgreSQL, while highly available, uses PostgreSQL syntax and does not natively support Oracle-specific stored procedures or PL/SQL, necessitating code modifications.

Full explanation →
275
MCQhard

Refer to the exhibit. An engineer runs the CLI command to check security groups attached to the RDS instance 'mydb'. The output shows only one security group. The engineer wants to ensure that only traffic from an application server with IP 10.0.1.5 is allowed to the database port 3306. Which security group rule should be added?

A.Add an inbound rule to allow traffic from 10.0.1.5/32 on port 80.
B.Add an inbound rule to allow traffic from 10.0.1.5/32 on port 3306.
C.Add an outbound rule to allow traffic to 10.0.1.5 on port 3306.
D.Add an inbound rule to allow traffic from 0.0.0.0/0 on port 3306.
AnswerB

Correctly restricts access to the specific IP.

Why this answer

To allow only the specific IP 10.0.1.5 to access the database, an inbound rule must be added to the security group allowing traffic on port 3306 (MySQL/Aurora) from source 10.0.1.5/32. Option B is correct. Option A is incorrect because it uses port 80 (HTTP) instead of the database port.

Option C is incorrect because an outbound rule controls egress, not ingress; inbound rules are needed to allow incoming connections to the database. Option D is incorrect because it allows traffic from any IP (0.0.0.0/0), which is insecure and would violate the requirement to restrict access to a single IP.

Full explanation →
276
MCQhard

A company runs a multi-tenant SaaS platform on AWS. Each tenant has their own database schema within a shared PostgreSQL database on Amazon RDS. The platform has grown to thousands of tenants, and the single RDS instance is experiencing performance degradation due to resource contention. Queries from one tenant can impact others. The company needs a solution that isolates tenants, provides predictable performance, and allows easy scaling. They also want to minimize application changes. The application uses an ORM that dynamically constructs SQL queries based on the tenant ID. Which solution is BEST?

A.Migrate to Amazon Aurora PostgreSQL and use Aurora Auto Scaling to add reader nodes as needed.
B.Create separate RDS instances for each tenant and use RDS Proxy to pool connections per tenant. Modify the application to select the appropriate database instance based on tenant ID.
C.Implement Amazon RDS Proxy in front of the existing RDS instance to manage connections and reduce contention.
D.Migrate the application to use Amazon DynamoDB with tenant ID as the partition key, using global tables for scalability.
AnswerB

This provides full isolation and predictable performance. RDS Proxy reduces connection overhead. Application changes are limited to connection routing logic.

Why this answer

The best solution because it provides full tenant isolation by assigning each tenant a separate RDS instance, eliminating resource contention and ensuring predictable performance. RDS Proxy efficiently manages connection pooling for each instance, reducing overhead. The application change is minimal: the ORM can be configured to dynamically select the correct database instance based on the tenant ID, preserving the existing SQL-based logic.

In contrast, Option A (Aurora Auto Scaling) still shares a single database, offering no isolation. Option C (RDS Proxy on the existing instance) also fails to isolate tenants. Option D (DynamoDB) would require a complete rewrite of the data layer, violating the requirement to minimize application changes.

Full explanation →
277
Multi-Selecteasy

A company is migrating its on-premises PostgreSQL database to Amazon Aurora PostgreSQL. The migration must have minimal downtime. Which THREE steps should be taken as part of the migration plan? (Select THREE.)

Select 3 answers
A.Perform a test migration to validate the process.
B.Enable Multi-AZ on the Aurora cluster before migration.
C.Update the application connection string to point to the Aurora cluster after cutover.
D.Use AWS DMS to perform a full load and then ongoing replication.
E.Disable automated backups on the Aurora cluster to improve performance.
AnswersA, C, D

Testing ensures the migration works correctly before the actual cutover.

Why this answer

Performing a test migration validates the entire process, including schema compatibility, data integrity, and replication lag, before the actual cutover. This reduces the risk of unexpected failures during the live migration, which is critical for achieving minimal downtime.

Exam trap

The trap here is that candidates may confuse enabling Multi-AZ as a migration requirement, when it is actually a high-availability feature unrelated to the migration process itself.

Full explanation →
278
MCQeasy

A company needs to securely store and manage the master password for their Amazon RDS for PostgreSQL instance. Which AWS service is purpose-built for managing secrets with automatic rotation?

A.AWS Key Management Service (KMS)
B.AWS Secrets Manager
C.AWS Identity and Access Management (IAM)
D.AWS CloudHSM
AnswerB

AWS Secrets Manager is designed for secret management with built-in rotation.

Why this answer

AWS Secrets Manager is designed for secret management with built-in rotation. Option A is wrong because KMS is for encryption keys, not secret management. Option C is wrong because IAM is for identity and access management, not secret storage.

Option D is wrong because CloudHSM provides hardware security modules but not secret rotation.

Full explanation →
279
MCQmedium

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 1 TB and has a large number of stored procedures and triggers. The migration must minimize application changes. Which migration approach should be used?

A.Use AWS Schema Conversion Tool (AWS SCT) to convert the schema and AWS DMS for data migration
B.Use AWS Database Migration Service (AWS DMS) with full load and ongoing replication
C.Use Oracle Data Pump (expdp/impdp) to export and import the database
D.Use AWS S3 to store the data and AWS Glue to transform and load into RDS
AnswerB

AWS DMS supports ongoing replication to minimize downtime.

Why this answer

AWS DMS with full load and ongoing replication minimizes application changes by supporting heterogeneous migrations with minimal downtime, and it can handle stored procedures and triggers by replicating data changes in near real-time without requiring schema conversion. AWS DMS directly supports Oracle as a source and Amazon RDS for Oracle as a target, preserving the existing schema and procedural logic, which avoids the need for application rewrites.

Exam trap

The trap here is that candidates often assume AWS SCT is required for any Oracle migration, but SCT is only needed when changing database engines; for a homogeneous migration to RDS for Oracle, DMS alone suffices, and using SCT would introduce unnecessary schema conversion risks.

How to eliminate wrong answers

Option A is wrong because AWS SCT is designed for schema conversion when migrating to a different database engine (e.g., Oracle to Aurora PostgreSQL), but the question specifies migrating to Amazon RDS for Oracle, which uses the same engine, so schema conversion is unnecessary and would introduce unnecessary complexity. Option C is wrong because Oracle Data Pump (expdp/impdp) is a logical export/import tool that requires significant downtime for a 1 TB database and does not provide ongoing replication, making it unsuitable for minimizing application changes during a live migration. Option D is wrong because AWS S3 and AWS Glue are ETL services for data transformation and loading, not designed for database migration with minimal application changes; they would require schema redesign and cannot natively handle Oracle stored procedures and triggers.

Full explanation →
280
Multi-Selectmedium

A company is designing a disaster recovery strategy for Amazon DynamoDB. The strategy must have an RPO of 5 minutes and RTO of 1 hour. Which TWO options meet these requirements? (Choose 2.)

Select 2 answers
A.On-demand backups
B.Point-in-time recovery (PITR)
C.Cross-Region Replication (CRR) to S3
D.Global tables
E.Scheduled backups using AWS Backup
AnswersB, D

PITR allows restore to any point within seconds, meeting RPO.

Why this answer

Point-in-time recovery (PITR) enables continuous backups of DynamoDB tables with 1-second granularity over a 35-day window, allowing restoration to any point within that window. This supports an RPO of 5 minutes because you can restore to a specific timestamp within seconds of the failure, and the RTO of 1 hour is achievable as table restoration typically completes within that timeframe for most table sizes.

Exam trap

The trap here is that candidates often confuse on-demand backups or scheduled backups with PITR, not realizing that only PITR provides continuous, granular recovery points, and that Global tables are the only option that provides automatic cross-region failover without manual restore operations.

Full explanation →
281
MCQmedium

A company is using an Amazon RDS for MySQL DB instance to store sensitive customer data. A security audit reveals that all database traffic between the application and the database is transmitted in plaintext. Which configuration change would encrypt data in transit for new connections?

A.Modify the DB instance to require SSL/TLS connections and update the application connection string to use SSL.
B.Configure the DB instance to be in a VPC with a VPC peering connection to the application's VPC.
C.Enable encryption at rest for the RDS DB instance using AWS KMS.
D.Enable IAM database authentication for the DB instance.
AnswerA

This encrypts data in transit for new connections.

Why this answer

To encrypt data in transit for new connections to an Amazon RDS for MySQL DB instance, you must modify the DB instance to require SSL/TLS connections. This forces all connections to use SSL/TLS, encrypting the data transmitted between the application and the database. After enabling this, the application connection string must be updated to use SSL (e.g., by adding ssl=true or equivalent).

The other options do not encrypt data in transit: VPC peering (B) does not encrypt traffic; encryption at rest using AWS KMS (C) only protects stored data; and IAM database authentication (D) manages authentication but does not encrypt the connection itself.

Full explanation →
282
MCQmedium

A gaming company runs a global leaderboard on Amazon DynamoDB. The leaderboard is updated frequently and must return the top 100 scores in milliseconds. The current design uses a single table with a Global Secondary Index (GSI) on score. However, the query to retrieve top scores often throttles under load. Which design change would best improve performance?

A.Use a scan operation with a filter to retrieve top scores.
B.Implement a write shard pattern using a random suffix on the partition key and a GSI on score.
C.Add DynamoDB Accelerator (DAX) in front of the table.
D.Switch to strongly consistent reads for the leaderboard query.
AnswerB

Sharding distributes write load, and the GSI on score enables efficient range queries for top scores.

Why this answer

The write shard pattern distributes high-frequency writes across multiple partition keys by appending a random suffix, preventing hot partitions. The GSI on score still allows efficient top-N queries by scanning the index in descending order. This avoids throttling by spreading write capacity evenly, while the GSI remains a sparse index that can be queried without impacting the base table's write throughput.

Exam trap

The trap here is that candidates often assume caching (DAX) or consistency changes will fix throttling, but the real issue is write-side hot partitions, which the write shard pattern directly addresses by distributing the write load.

How to eliminate wrong answers

Option A is wrong because a scan operation reads every item in the table, which is inefficient and costly, and filtering after a scan does not reduce the read capacity consumed, leading to even more throttling under load. Option C is wrong because DAX is an in-memory cache that accelerates reads but does not solve write-side throttling caused by hot partitions; it also adds latency for writes and does not help with the write-heavy leaderboard updates. Option D is wrong because strongly consistent reads consume twice the read capacity units of eventually consistent reads and do not address the root cause of write throttling; the leaderboard query is a read operation, but the bottleneck is write contention on hot partitions.

Full explanation →
283
MCQmedium

A company runs an Amazon Aurora MySQL database with read replicas to handle read traffic. During a recent load test, the primary instance CPU utilization reached 90%, but read replicas remained below 50%. The application uses a custom ORM that connects to a single endpoint. Which change will best distribute read traffic?

A.Configure the application to use the Aurora reader endpoint for read queries.
B.Use Amazon RDS Proxy with read/write splitting.
C.Place the read replicas behind an Application Load Balancer.
D.Enable Aurora Auto Scaling for replicas and use the cluster endpoint for both read and write.
AnswerA

Reader endpoint load balances across read replicas.

Why this answer

The Aurora reader endpoint automatically load balances SELECT queries across all read replicas, distributing read traffic effectively. Option B is incorrect: Amazon RDS Proxy provides connection pooling but does not split read/write traffic; it uses the cluster endpoint, which directs to the primary instance. Option C is incorrect: Aurora read replicas are not standard EC2 instances and cannot be placed behind an Application Load Balancer; the reader endpoint is the intended mechanism.

Option D is incorrect: The cluster endpoint always points to the primary instance, so using it for reads would not distribute load; Aurora Auto Scaling adds replicas, but they are only utilized when the reader endpoint is used.

Full explanation →
284
MCQmedium

A company is migrating a 2 TB Oracle database to Amazon Aurora PostgreSQL. The migration must have minimal downtime and support ongoing replication. Which AWS service should be used?

A.AWS DataSync
B.Amazon S3 Glacier
C.AWS Database Migration Service (AWS DMS)
D.AWS Schema Conversion Tool (AWS SCT)
AnswerC

DMS supports heterogeneous migrations and ongoing replication from Oracle to Aurora.

Why this answer

AWS Database Migration Service (AWS DMS) is the correct choice because it supports ongoing replication (change data capture, CDC) from an Oracle source to an Amazon Aurora PostgreSQL target, enabling a migration with minimal downtime. DMS can handle a 2 TB database by using a large replication instance and tuning task settings, and it continuously replicates changes until the cutover is complete.

Exam trap

The trap here is that candidates often confuse AWS SCT (schema conversion) with the actual data migration, or they assume DataSync can handle database replication, but DMS is the only service that provides both schema conversion (via SCT integration) and ongoing data replication for heterogeneous migrations.

How to eliminate wrong answers

Option A is wrong because AWS DataSync is designed for transferring large datasets over the network or between on-premises storage and AWS storage services (e.g., S3, EFS, FSx), but it does not support ongoing replication or heterogeneous database migrations like Oracle to Aurora PostgreSQL. Option B is wrong because Amazon S3 Glacier is a cold storage service for archival data, not a migration tool; it cannot perform live database replication or schema conversion. Option D is wrong because AWS Schema Conversion Tool (AWS SCT) is used to convert the source database schema and code to a target-compatible format, but it does not perform the actual data migration or ongoing replication; SCT is typically used in conjunction with DMS, not as a standalone migration service.

Full explanation →
285
MCQeasy

A developer needs to restore an Amazon RDS for PostgreSQL DB instance to a specific point in time within the retention period. What must be enabled for this operation to be possible?

A.Deletion protection enabled.
B.A read replica in the same region.
C.Automated backups with a retention period greater than 0.
D.Multi-AZ deployment.
AnswerC

PITR relies on automated backups and transaction logs.

Why this answer

Automated backups with a retention period greater than 0 are required for point-in-time recovery (PITR) in Amazon RDS. Option A is incorrect because deletion protection prevents accidental deletion but does not enable PITR. Option B is incorrect because read replicas are used for read scaling and disaster recovery, not for PITR.

Option D is incorrect because Multi-AZ provides high availability but is not a prerequisite for PITR.

Full explanation →
286
MCQmedium

Refer to the exhibit. A CloudFormation template creates a DynamoDB table. The application team needs to query orders by customer ID (which is not a key attribute). Which change to the template would enable efficient querying by customer ID?

A.Change the KeySchema to use CustomerID as the hash key
B.Add a LocalSecondaryIndex on CustomerID
C.Add a GlobalSecondaryIndex with CustomerID as the hash key and OrderDate as the range key
D.Enable DynamoDB Streams and use Lambda to populate a separate table
AnswerC

GSI allows efficient querying by CustomerID.

Why this answer

A GlobalSecondaryIndex (GSI) allows querying on a non-key attribute (CustomerID) with a different key schema than the base table. By specifying CustomerID as the hash key and OrderDate as the range key, the application can efficiently query orders by CustomerID and optionally sort by OrderDate, without affecting the base table's primary key structure.

Exam trap

The trap here is that candidates often confuse LocalSecondaryIndexes (LSIs) with GlobalSecondaryIndexes (GSIs), incorrectly assuming an LSI can be created on any attribute, when in fact an LSI must share the same hash key as the base table and can only be added during table creation.

How to eliminate wrong answers

Option A is wrong because changing the KeySchema to use CustomerID as the hash key would break existing access patterns that rely on the original primary key (e.g., OrderID), and CustomerID is not guaranteed to be unique, leading to data overwrites. Option B is wrong because a LocalSecondaryIndex (LSI) can only be created on tables with a composite primary key (hash and range key) and must use the same hash key as the base table; since CustomerID is not the base table's hash key, an LSI cannot be defined on it. Option D is wrong because using DynamoDB Streams and Lambda to populate a separate table adds operational complexity, latency, and cost, and is not the simplest or most efficient solution for enabling querying by a non-key attribute when a GSI directly solves the requirement.

Full explanation →
287
MCQhard

A company is using Amazon RDS for Oracle with a very large database (10 TB). They need to migrate to Amazon Aurora PostgreSQL with minimal downtime. The source database is heavily used with constant writes. Which migration strategy is most appropriate?

A.Export the Oracle database using expdp and import into Aurora PostgreSQL using pg_restore.
B.Use AWS Database Migration Service (DMS) with ongoing replication to migrate from Oracle to Aurora PostgreSQL.
C.Create a read replica of the RDS Oracle instance and promote it to an Aurora PostgreSQL instance.
D.Use Oracle GoldenGate to replicate data to an Aurora PostgreSQL instance.
AnswerB

DMS supports full load and CDC, minimizing downtime.

Why this answer

AWS DMS with ongoing replication (change data capture) is the most appropriate strategy for migrating a heavily written 10 TB Oracle database to Aurora PostgreSQL with minimal downtime. DMS can perform a full load of the existing data and then continuously replicate changes from Oracle's redo logs to Aurora PostgreSQL, allowing the source to remain fully operational until a brief cutover window. This approach minimizes downtime compared to offline export/import methods and is natively supported by AWS.

Exam trap

The trap here is that candidates may confuse read replicas (which are engine-specific and cannot change database engines) with DMS replication, or assume that Oracle GoldenGate is always the best choice for heterogeneous migrations without considering AWS-native alternatives like DMS.

How to eliminate wrong answers

Option A is wrong because expdp and pg_restore are incompatible tools (Oracle export/import vs. PostgreSQL restore), and this offline method would require significant downtime for a 10 TB database with constant writes, making minimal downtime impossible. Option C is wrong because RDS for Oracle does not support creating a read replica that can be promoted to a different database engine (Aurora PostgreSQL); read replicas are only for the same engine type.

Option D is wrong because Oracle GoldenGate is a third-party tool that adds complexity and cost, and while it could technically work, AWS DMS is the recommended, fully managed service for heterogeneous migrations with ongoing replication, making it a more appropriate choice in the AWS ecosystem.

Full explanation →
288
MCQmedium

A company's Amazon Redshift cluster is experiencing slow query performance. The cluster has three nodes. The administrator wants to identify if the issue is due to data distribution skew. Which approach should be used?

A.Examine the STL_QUERY table to analyze query execution times.
B.Check the STV_WLM_SERVICE_STATE table to see current queue state.
C.Query the STV_SLICES table to compare disk usage across slices.
D.Review CloudWatch metrics for CPUUtilization per node.
AnswerC

STV_SLICES shows disk usage per slice, indicating skew.

Why this answer

The correct approach is to query the STV_SLICES table. STV_SLICES provides disk usage per slice, which can identify data distribution skew. Option A is wrong because STL_QUERY stores query execution times, not distribution.

Option B is wrong because STV_WLM_SERVICE_STATE shows current workload management queue state. Option D is wrong because CloudWatch CPUUtilization measures CPU load, not data distribution.

Full explanation →
289
Multi-Selectmedium

A company is migrating an on-premises PostgreSQL database to Amazon RDS for PostgreSQL. They need to minimize downtime and ensure data consistency. Which TWO methods can be used together to achieve this?

Select 2 answers
A.Take a file system snapshot and copy to Amazon EBS
B.Use pg_dump and pg_restore
C.Use AWS DMS with full load and CDC
D.Export data to Amazon S3 and import using COPY
E.Set up pglogical replication from on-premises to RDS
AnswersC, E

DMS can replicate data continuously.

Why this answer

AWS DMS with full load and Change Data Capture (CDC) enables a zero-downtime migration by first copying the existing data (full load) and then continuously replicating ongoing changes from the on-premises PostgreSQL source to the Amazon RDS for PostgreSQL target. This ensures data consistency because CDC captures transactions in near real-time using the PostgreSQL logical replication slot mechanism, allowing the target to stay synchronized until the cutover.

Exam trap

The trap here is that candidates often think pg_dump/restore (Option B) is sufficient for minimal downtime, but they overlook that it requires a consistent snapshot and cannot capture ongoing changes, whereas the correct answer combines a full load with CDC to achieve near-zero downtime.

Full explanation →
290
Multi-Selectmedium

A company is using Amazon RDS for PostgreSQL and wants to implement encryption in transit for all client connections. The security team has identified that some connections are not using SSL. Which TWO actions should the company take to enforce SSL for all connections?

Select 2 answers
A.Set the 'rds.force_ssl' parameter to '1' in the DB parameter group.
B.Install the RDS CA certificate on all client machines.
C.Create a new SSL certificate and associate it with the RDS instance.
D.Configure the application connection string to use 'sslmode=require'.
E.Modify the pg_hba.conf file to require SSL for all users by setting 'hostssl' entries.
AnswersA, E

This parameter forces the PostgreSQL server to reject non-SSL connections.

Why this answer

The correct actions to enforce SSL for all connections are A and E. Option A: Setting 'rds.force_ssl' to '1' in the DB parameter group forces the RDS PostgreSQL instance to require SSL for all incoming connections at the server level. Option E: Modifying the 'pg_hba.conf' file to require SSL for all users via 'hostssl' entries ensures that only SSL connections are allowed, complementing the server-side enforcement.

Option C is incorrect because associating a custom SSL certificate is not required for enforcing SSL; AWS RDS provides a valid certificate. Option B is a client-side configuration that does not enforce server-side SSL. Option D is client-side and not a server-side enforcement action.

Options A and E together provide robust server-side enforcement.

Full explanation →
291
MCQmedium

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

A.Use AWS DMS with MongoDB as source and DocumentDB as target
B.Use mongoexport and mongoimport
C.Export data to Amazon S3 and load into DocumentDB
D.Use MongoDB Atlas Live Migration
AnswerA

DMS supports continuous replication for MongoDB.

Why this answer

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

Exam trap

The trap here is that candidates may confuse MongoDB Atlas Live Migration (which is specific to Atlas) with a general-purpose migration tool, or assume that offline tools like mongoexport are sufficient for minimal downtime scenarios.

How to eliminate wrong answers

Option B is wrong because mongoexport and mongoimport are offline, batch tools that require stopping writes to the source database, causing significant downtime and lacking CDC for ongoing changes. Option C is wrong because exporting to S3 and loading into DocumentDB is a manual, offline process that does not support continuous replication, leading to data inconsistency if writes continue during migration. Option D is wrong because MongoDB Atlas Live Migration is a tool for migrating to MongoDB Atlas, not to Amazon DocumentDB, and is not compatible with DocumentDB's API or infrastructure.

Full explanation →
292
MCQeasy

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

A.Create a snapshot of the DB instance and restore it with larger storage.
B.Convert the storage type to General Purpose (gp2) and then increase size.
C.Modify the DB instance and increase the allocated storage to 1 TB.
D.Use AWS DMS to migrate the database to a new instance with 1 TB storage.
AnswerC

Modifying storage online is supported with minimal downtime.

Why this answer

Modifying the DB instance to increase allocated storage is the correct approach because it can be done with minimal downtime. Amazon RDS for SQL Server supports dynamic storage scaling, allowing you to increase the allocated storage size without requiring a snapshot or migration. The instance remains available during the modification, although a brief performance impact may occur.

Option A is incorrect because restoring from a snapshot requires significant downtime and does not offer a direct storage increase on the existing instance. Option B is incorrect because converting storage type (e.g., from Magnetic to General Purpose) is a separate modification that also incurs downtime, and it is not necessary to change storage type before increasing size; you can modify storage size directly. Option D is incorrect because using AWS DMS is overkill for a simple storage increase and introduces additional complexity and potential downtime during the migration process.

Full explanation →
293
MCQmedium

A company has an Amazon RDS for Oracle DB instance that is publicly accessible. They want to restrict access to only a specific CIDR block. Which two actions must be taken together?

A.Modify the VPC security group to allow inbound traffic on the database port from the specific CIDR, and ensure the DB instance is publicly accessible with the correct security group.
B.Modify the DB subnet group to include only subnets from the allowed CIDR.
C.Add a rule to the network ACL to allow inbound traffic from the CIDR.
D.Set the rds.force_ssl parameter to force encrypted connections from the allowed CIDR.
AnswerA

The security group acts as a firewall for the DB instance, and the PubliclyAccessible setting allows it to have a public IP.

Why this answer

You must modify the VPC security group to allow inbound traffic on the database port from the specific CIDR, and the DB instance must be configured as publicly accessible with that security group attached. Option B is wrong because the DB subnet group determines which subnets the instance can be deployed in, not inbound access restrictions. Option C is wrong because network ACLs operate at the subnet level and are less granular; security groups are the appropriate mechanism for RDS access control.

Option D is wrong because the rds.force_ssl parameter enforces encrypted connections but does not restrict by source IP or CIDR.

Full explanation →
294
Multi-Selectmedium

Which TWO of the following are benefits of using Amazon DynamoDB Accelerator (DAX)? (Choose 2.)

Select 2 answers
A.Improves write throughput by caching write operations
B.Reduces storage costs by compressing data
C.Reduces read latency to microseconds for cached items
D.Automatically scales write capacity based on demand
E.Reduces the read capacity units consumed on the DynamoDB table
AnswersC, E

DAX provides microsecond read latency for cached data.

Why this answer

Amazon DynamoDB Accelerator (DAX) is an in-memory cache that delivers up to 10x read performance improvement, reducing read latency to microseconds for cached items. It sits between your application and DynamoDB, intercepting read requests and serving them from its cluster's memory, which avoids the millisecond-level latency of reading from DynamoDB's SSD storage.

Exam trap

The trap here is confusing DAX's read caching with write optimization, leading candidates to incorrectly select that DAX improves write throughput or scales write capacity, when in fact DAX only accelerates reads and reduces read capacity consumption.

Full explanation →
295
MCQhard

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

A.Create a database user with a strong password. Enable IAM database authentication. Assign the application server an IAM policy that allows rds-db:connect. Configure the application to use the password.
B.Enable IAM database authentication. Create a database user matching the IAM user ARN. Grant the application server's IAM user the rds_iam role. Configure the application to use an authentication token.
C.Enable IAM database authentication. Create a database user that matches the IAM role ARN. Configure the application to use the database master username and password.
D.Enable IAM database authentication on the RDS instance. Create a database user that matches the IAM role ARN. Grant the application server's IAM role the rds_iam role. Configure the application to generate an authentication token using the IAM role's credentials.
AnswerD

This ensures connections use IAM authentication and the application server's role is required.

Why this answer

IAM database authentication for RDS PostgreSQL requires mapping IAM roles to database users. Steps: 1) Enable IAM database authentication on the RDS instance. 2) Create a database user that matches the IAM role ARN (the role assumed by the application server). 3) Grant the rds_iam role to the application server's IAM role to allow it to authenticate. 4) Configure the application to generate an authentication token using the IAM role's credentials. Option D is correct because it includes all these steps.

Option A is wrong because it uses a password instead of an authentication token. Option B is wrong because it references an IAM user ARN instead of a role ARN. Option C is wrong because it does not enable IAM authentication and uses a password.

Full explanation →
296
MCQhard

Refer to the exhibit. A database administrator is trying to use AWS DMS to migrate data from an on-premises Oracle database to Amazon RDS for Oracle. The DMS replication instance is in the same VPC as the RDS instance. The administrator receives an access denied error when starting the replication task. The IAM policy attached to the DMS replication instance is shown. What is the MOST likely cause of the error?

A.The IAM policy does not include permissions for the source database endpoint
B.The IAM policy does not allow the dms:CreateReplicationInstance action
C.The RDS instance is not in the same VPC as the DMS replication instance
D.The DMS replication instance is not associated with the IAM role
AnswerA

DMS needs permissions to create and test endpoints, which are missing.

Why this answer

The error occurs because the IAM policy attached to the DMS replication instance does not include the necessary permissions to access the source Oracle database endpoint. Specifically, the policy lacks actions like `dms:TestConnection` and `dms:DescribeEndpoints` that are required for DMS to validate and connect to the source endpoint. Without these permissions, DMS cannot establish the connection to the on-premises Oracle database, resulting in an access denied error when starting the replication task.

Exam trap

The trap here is that candidates often assume the error is due to network connectivity (Option C) or role association (Option D), but the exhibit clearly shows the IAM policy is missing source endpoint permissions, which is a common misconfiguration in DMS migrations.

How to eliminate wrong answers

Option B is wrong because the error occurs during the replication task start, not during the creation of the replication instance; the `dms:CreateReplicationInstance` action is only needed when provisioning the instance, and the task start failure is unrelated to that permission. Option C is wrong because the question explicitly states the DMS replication instance is in the same VPC as the RDS instance, so a VPC mismatch is not the cause. Option D is wrong because the IAM policy is attached to the replication instance (as shown in the exhibit), meaning the role is associated; the issue is the policy's insufficient permissions, not the lack of association.

Full explanation →
297
Multi-Selecthard

A company is using Amazon ElastiCache for Redis to cache frequently accessed data from an RDS MySQL database. The cache hit ratio is currently 85%. The operations team notices that during traffic spikes, the cache eviction rate increases significantly, and the database CPU utilization spikes. The cache cluster uses a single r6g.large node. Which THREE actions should the team take to improve performance? (Choose three.)

Select 3 answers
A.Add more shards to the cluster to increase total memory.
B.Reduce the time-to-live (TTL) for cached items to free up memory faster.
C.Enable cluster mode to distribute data across multiple shards.
D.Increase the node type to a larger instance class, such as r6g.2xlarge.
E.Configure the cache to use lazy loading only for write-through operations.
AnswersA, C, D

More shards increase aggregate memory and distribute load.

Why this answer

Adding more shards to the cluster increases the total available memory, which reduces the frequency of evictions during traffic spikes. With more memory, the cache can store more data without forcing out existing entries, thereby maintaining a higher cache hit ratio and reducing the load on the RDS MySQL database.

Exam trap

The trap here is that candidates may think reducing TTL (option B) helps free memory faster, but in reality it increases cache misses and database load, making the problem worse during spikes.

Full explanation →
298
MCQmedium

Refer to the exhibit. An IAM policy is attached to a user who needs to manage Amazon RDS DB instances. When the user attempts to modify a DB instance, they receive an 'AccessDenied' error. What is the most likely cause?

A.The policy does not include the 'rds:ModifyDBInstance' action for the specific DB instance ARN.
B.The policy is missing the 'rds:ListTagsForResource' permission needed for the console.
C.The user is trying to modify a Multi-AZ DB instance which requires additional permissions.
D.The policy requires a condition to allow modifications during the maintenance window.
AnswerB

The console requires ListTagsForResource to display instance details; without it, modify operations fail.

Why this answer

The IAM policy attached to the user includes the 'rds:ModifyDBInstance' action, so the user should be able to modify DB instances via the API or CLI. However, the AWS Management Console frequently requires additional read-only permissions to render the interface, such as 'rds:ListTagsForResource' to display tags. Without this permission, the console may throw an 'AccessDenied' error when attempting a modification, even though the underlying modify action is allowed.

This is the most likely cause of the error.

Full explanation →
299
MCQmedium

A database administrator needs to audit all SQL statements executed on an Amazon Aurora MySQL DB cluster, including SELECT queries. Which AWS service should be used to capture and store these logs?

A.Amazon RDS Database Activity Streams
B.Amazon RDS Enhanced Monitoring
C.Amazon CloudWatch Logs
D.Amazon RDS Performance Insights
AnswerA

Database Activity Streams captures database activity including SQL statements and sends to CloudWatch and Kinesis.

Why this answer

Amazon RDS Database Activity Streams (Option A) is the correct service to capture and store audit logs of SQL statements, including SELECT queries, on an Aurora MySQL DB cluster. It streams database activity to Amazon CloudWatch Logs and Amazon Kinesis Data Streams for further analysis and storage. Option B (Amazon RDS Enhanced Monitoring) provides OS-level metrics, not SQL statements.

Option C (Amazon CloudWatch Logs) can store logs but does not capture SQL statements directly; it requires a source like Database Activity Streams. Option D (Amazon RDS Performance Insights) monitors database performance, not SQL audit logs.

Full explanation →
300
Multi-Selecthard

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a 24/7 uptime requirement. The migration must have minimal downtime and support ongoing replication. Which TWO services or features should the specialist use to accomplish this?

Select 2 answers
A.Oracle Data Guard to replicate to RDS.
B.Amazon RDS cross-Region automated backups.
C.An AWS DMS replication instance.
D.AWS Schema Conversion Tool (AWS SCT).
E.AWS Database Migration Service (AWS DMS) with change data capture (CDC).
AnswersC, E

An AWS DMS replication instance is the compute resource that runs DMS tasks, including full load and ongoing CDC replication, enabling minimal downtime migration.

Why this answer

Options C and E are correct. Option C: An AWS DMS replication instance is required to run AWS DMS tasks, including migration with ongoing replication. Option E: AWS DMS with change data capture (CDC) enables ongoing replication with minimal downtime.

Option D is incorrect because AWS Schema Conversion Tool (AWS SCT) is used for heterogeneous migrations (e.g., Oracle to PostgreSQL), not for homogeneous Oracle-to-Oracle migrations. Option A is incorrect because Oracle Data Guard is not supported for direct replication to Amazon RDS for Oracle; DMS is used instead. Option B is incorrect because cross-Region automated backups are a backup feature, not a migration tool for minimal downtime migration.

Full explanation →
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