CCNA Deployment and Migration Questions — Page 5 of 5

301

MCQeasy

A company wants to migrate a 10 GB PostgreSQL database from an on-premises server to Amazon RDS for PostgreSQL. The migration can tolerate several hours of downtime. Which migration method is the MOST straightforward?

A.Use AWS Database Migration Service (AWS DMS) with ongoing replication

B.Use AWS Schema Conversion Tool (AWS SCT) to migrate the data

C.Create an Amazon RDS Read Replica from the on-premises database

D.Use pg_dump to export the database and pg_restore to import into RDS

AnswerD

This is the simplest method for a one-time migration with downtime tolerance.

Why this answer

Pg_dump and pg_restore are native PostgreSQL utilities that provide a straightforward, reliable method for migrating a 10 GB database with acceptable downtime. The 10 GB size is well within the practical limits of a logical dump, and the process requires no additional AWS services or complex configuration, making it the simplest approach for a migration that can tolerate several hours of downtime.

Exam trap

The trap here is that candidates may over-engineer the solution by choosing AWS DMS with ongoing replication, assuming it is always the best migration tool, when the question explicitly states that several hours of downtime are acceptable, making the simpler native pg_dump/pg_restore approach the most straightforward.

How to eliminate wrong answers

Option A is wrong because AWS DMS with ongoing replication is designed for minimal-downtime migrations and introduces unnecessary complexity (e.g., setting up a replication instance, source/target endpoints, and change data capture) for a scenario where several hours of downtime are acceptable. Option B is wrong because AWS SCT is used for schema conversion when migrating between different database engines (e.g., Oracle to PostgreSQL), not for migrating data between two PostgreSQL databases where the schema is already compatible. Option C is wrong because an Amazon RDS Read Replica cannot be created from an on-premises database; read replicas in RDS are only supported between RDS instances or from an RDS instance to an external source, not the reverse.

Practice this question →

302

MCQhard

A company is migrating a 5 TB SQL Server database to Amazon RDS for SQL Server using AWS DMS. They are using Full LOB mode. The migration is failing with an error about memory allocation. What should they do to resolve this?

A.Decrease the MaxLobSize setting.

B.Increase the DMS replication instance class.

C.Split the migration into multiple DMS tasks.

D.Enable BatchApply on the DMS task.

AnswerB

More memory resolves allocation errors.

Why this answer

The memory allocation error in AWS DMS Full LOB mode occurs when the replication instance lacks sufficient memory to buffer LOB data. Increasing the replication instance class (option B) directly provides more memory, resolving the issue. Decreasing MaxLobSize (A) would truncate data, not fix allocation.

Splitting the task (C) does not increase memory per instance. Enabling BatchApply (D) improves commit efficiency but does not address memory allocation for LOBs. Therefore, B is correct.

Exam trap

The trap here is that candidates might confuse memory allocation errors with network or throughput issues and incorrectly choose to split the task or adjust LOB settings, rather than recognizing that the root cause is insufficient instance memory for Full LOB mode.

How to eliminate wrong answers

Option A is wrong because decreasing MaxLobSize would truncate LOB data, potentially causing data loss or migration failure if LOBs exceed the reduced limit; Full LOB mode is designed to handle LOBs of any size without truncation. Option C is wrong because splitting the migration into multiple tasks does not address the underlying memory constraint on the replication instance; each task still runs on the same instance and would encounter the same memory limitation. Option D is wrong because BatchApply optimizes target commit behavior for high-volume transactions but does not affect the memory allocation for LOB processing during the read phase; it is irrelevant to the memory error.

Practice this question →

303

MCQhard

A company is migrating a 10 TB Oracle database to Amazon Aurora PostgreSQL. The migration uses AWS DMS with CDC. After the full load, the CDC phase is falling behind by several minutes. The source Oracle database generates 500 MB of redo logs per minute. Which action will most likely improve CDC performance?

A.Disable CDC and perform a full load only

B.Increase the number of parallel apply threads on the DMS task

C.Reduce the batch size in the DMS task settings

D.Increase the source Oracle redo log size

AnswerB

More parallel apply threads can increase throughput for applying changes to the target.

Why this answer

Increasing the number of parallel apply threads on the DMS task allows the target Aurora PostgreSQL database to apply changes concurrently, reducing the bottleneck caused by sequential apply. With 500 MB/min of redo logs, the single-threaded default apply cannot keep pace, so parallel apply directly addresses the lag by distributing the load across multiple threads.

Exam trap

The trap here is that candidates often confuse batch size with parallelism, assuming reducing batch size will speed up apply, when in fact it increases overhead and slows down CDC, while the correct solution is to increase parallelism to match the high redo log generation rate.

How to eliminate wrong answers

Option A is wrong because disabling CDC and performing only a full load would not capture ongoing changes, defeating the purpose of a migration with minimal downtime; the issue is CDC performance, not the full load. Option C is wrong because reducing the batch size in DMS task settings would decrease the number of changes applied per transaction, increasing the number of round trips and likely worsening the lag, not improving it. Option D is wrong because increasing the source Oracle redo log size does not affect DMS CDC performance; DMS reads redo logs at the rate they are generated, and larger logs do not change the volume of data or the apply speed on the target.

Practice this question →

304

MCQmedium

A company is migrating a 2 TB Oracle database from on-premises to Amazon RDS for Oracle using AWS DMS. The migration completes successfully, but the new RDS instance shows higher CPU utilization than the on-premises database for the same workload. Which action is MOST likely to reduce CPU utilization on RDS?

A.Disable automated backups to free resources

B.Enable Oracle Multitenant architecture

C.Increase the allocated storage to improve IOPS

D.Change the RDS instance to a burstable class

AnswerC

Increasing allocated storage improves IOPS, which reduces I/O wait times and can significantly lower CPU utilization if the database is I/O-bound. This is often the most straightforward first step.

Why this answer

Increasing allocated storage on Amazon RDS for Oracle directly improves the provisioned IOPS (if using Provisioned IOPS) or baseline IOPS (for gp2/gp3). Higher IOPS reduces I/O wait time, which is a common cause of high CPU utilization when the database is I/O-bound. Query optimization or instance resizing may also help, but increasing storage is a simple, low-risk action that often alleviates I/O-related CPU pressure.

Option B is incorrect because Oracle Multitenant (CDB/PDB) architecture adds container management overhead and is not designed to reduce CPU utilization; also, converting an existing non-CDB RDS instance to CDB is not supported.

Exam trap

The trap is assuming that CPU utilization is always due to compute limits and overlooking the impact of I/O wait. Candidates may also incorrectly believe Oracle Multitenant reduces CPU, but it actually adds overhead and is not applicable to existing RDS instances.

How to eliminate wrong answers

Option A is wrong because disabling automated backups does not significantly reduce CPU utilization; backups primarily affect I/O and storage, not CPU, and disabling them would compromise recovery capabilities without addressing the root cause. Option C is wrong because increasing allocated storage to improve IOPS addresses I/O bottlenecks, not CPU utilization; higher IOPS can reduce wait times but does not lower CPU usage for the same workload. Option D is wrong because changing to a burstable class (e.g., db.t3) may reduce cost but can actually increase CPU utilization due to CPU credits and throttling under sustained load, making it unsuitable for reducing CPU usage.

Practice this question →

305

MCQmedium

A company is migrating an on-premises PostgreSQL database to Amazon RDS for PostgreSQL. The database is 2 TB in size and has a high write volume. The migration window is limited to 4 hours. Which migration approach provides the fastest initial load with minimal downtime?

A.Use pg_dump to export the database and pg_restore to import into RDS.

B.Create a read replica of the on-premises database and promote it to a standalone database in RDS.

C.Use AWS Schema Conversion Tool (AWS SCT) to convert the schema and then use AWS DMS for ongoing replication.

D.Use AWS DMS with PostgreSQL as source and target, using native logical replication for full load and ongoing replication.

AnswerD

DMS with logical replication can perform a full load quickly and then keep the target in sync with minimal downtime.

Why this answer

AWS DMS with native logical replication (using PostgreSQL's built-in logical replication slots) performs a full load of the 2 TB database while simultaneously capturing ongoing changes, enabling near-zero downtime during the migration window. This approach is optimized for high-write volumes and limited windows, as it avoids the need for a separate export/import step and minimizes the time the source database is unavailable.

Exam trap

The trap here is that candidates often confuse AWS DMS with schema conversion tools (AWS SCT) or assume that traditional dump/restore tools are sufficient for large, high-write databases, overlooking DMS's native logical replication capability for same-engine migrations with minimal downtime.

How to eliminate wrong answers

Option A is wrong because pg_dump/pg_restore requires a full export and import of the 2 TB database, which typically takes longer than 4 hours for high-write workloads and incurs significant downtime during the final cutover. Option B is wrong because creating a read replica of an on-premises PostgreSQL database is not supported; read replicas are a feature of Amazon RDS, not on-premises instances, and promoting a replica to a standalone database does not apply to cross-environment migrations. Option C is wrong because AWS SCT is used for schema conversion when migrating between different database engines (e.g., Oracle to PostgreSQL), not for same-engine PostgreSQL migrations, and using DMS with SCT adds unnecessary complexity without improving speed.

Practice this question →

306

MCQeasy

A company is deploying Amazon RDS for MySQL in a Multi-AZ configuration for high availability. The database must be able to automatically failover to a standby in another Availability Zone. Which RDS feature enables this?

A.Multi-AZ deployment

B.Automated backups

C.Enhanced Monitoring

D.Read Replicas

AnswerA

Multi-AZ automatically fails over to standby in another AZ.

Why this answer

Multi-AZ deployment for Amazon RDS automatically provisions and maintains a synchronous standby replica in a different Availability Zone. When a failure is detected, Amazon RDS automatically fails over to the standby, ensuring high availability without manual intervention. This is the native RDS feature designed specifically for automatic failover across AZs.

Exam trap

The trap here is confusing Read Replicas (asynchronous, manual promotion) with Multi-AZ (synchronous, automatic failover), as both involve replicas in different AZs but serve fundamentally different purposes.

How to eliminate wrong answers

Option B is wrong because Automated backups are for point-in-time recovery and retention of database snapshots, not for automatic failover or synchronous replication. Option C is wrong because Enhanced Monitoring provides real-time OS-level metrics for performance analysis, not failover capabilities. Option D is wrong because Read Replicas are asynchronous replicas used for read scaling and can be promoted manually, but they do not provide automatic failover or synchronous replication for high availability.

Practice this question →

307

MCQmedium

A company is migrating a 1 TB SQL Server database to Amazon RDS for SQL Server. They need to minimize downtime and support ongoing replication. Which combination of AWS services should they use?

A.AWS SCT and AWS DMS

B.AWS S3 and AWS Glue

C.AWS DMS alone

D.Native SQL Server backup and restore to RDS

AnswerA

SCT converts schema, DMS migrates data with ongoing replication.

Why this answer

AWS DMS (Database Migration Service) can perform a full load of the 1 TB SQL Server database and then continuously replicate ongoing changes using change data capture (CDC) to minimize downtime. AWS SCT (Schema Conversion Tool) is used to assess and convert any incompatible schema objects (e.g., stored procedures, indexes) from the source SQL Server to the target RDS for SQL Server, ensuring a smooth migration. Together, they provide a complete solution for heterogeneous or homogeneous migration with minimal downtime and ongoing replication.

Exam trap

The trap here is that candidates often assume AWS DMS alone is sufficient for any migration, forgetting that schema conversion (via AWS SCT) is critical when moving to a different SQL Server version or when source objects are incompatible with RDS, which the exam tests as a required combination for minimizing downtime and supporting ongoing replication.

How to eliminate wrong answers

Option B is wrong because AWS S3 and AWS Glue are designed for data lakes and ETL (Extract, Transform, Load) workflows, not for continuous database replication with minimal downtime; Glue cannot perform ongoing CDC from SQL Server to RDS. Option C is wrong because AWS DMS alone can handle the migration and replication, but without AWS SCT, schema conversion issues (e.g., unsupported data types, deprecated features) may cause failures or require manual intervention, especially if the source and target SQL Server versions differ. Option D is wrong because native SQL Server backup and restore to RDS is a one-time, offline process that does not support ongoing replication and would require significant downtime to restore a 1 TB database.

Practice this question →

308

MCQeasy

A company wants to migrate a 500 GB MySQL database from an on-premises server to Amazon RDS for MySQL. The migration must be completed within a 2-hour downtime window. Which migration approach is MOST suitable?

A.Use AWS Database Migration Service (DMS) with a full load.

B.Use mysqldump to export the database and then import it into RDS.

C.Create an RDS Read Replica of the on-premises database and promote it.

D.Create a compressed backup using Percona XtraBackup, upload it to S3, and restore it to RDS.

AnswerD

Percona XtraBackup creates a fast physical backup; restoring from S3 is efficient and can complete within 2 hours.

Why this answer

Percona XtraBackup allows you to create a physical backup of the MySQL database that can be compressed and uploaded to Amazon S3, then restored directly to an Amazon RDS for MySQL instance. This approach is significantly faster than logical backups (like mysqldump) for a 500 GB database, as it bypasses SQL parsing and rebuilds the data files directly, enabling completion within a 2-hour downtime window.

Exam trap

The trap here is that candidates often assume mysqldump (Option B) is the simplest and fastest method for a one-time migration, but they overlook the massive performance penalty of logical backups for large datasets, and they may not realize that Percona XtraBackup is the only option among these that can reliably complete a 500 GB migration within a 2-hour window.

How to eliminate wrong answers

Option A is wrong because AWS DMS with a full load alone does not meet the 2-hour downtime requirement for a 500 GB database; the initial full load can take hours depending on network bandwidth and database size, and DMS is designed for ongoing replication, not a one-time fast migration with strict downtime. Option B is wrong because mysqldump performs a logical export that serializes all data into SQL statements, which is extremely slow for 500 GB due to parsing, network transfer, and import overhead, often exceeding the 2-hour window. Option C is wrong because you cannot create an RDS Read Replica of an on-premises database; RDS Read Replicas only work within the RDS ecosystem (cross-Region or cross-AZ) and require an existing RDS source instance, not an external on-premises server.

Practice this question →

309

Multi-Selectmedium

Which THREE factors should be considered when choosing between a native database migration tool (e.g., pg_dump) and AWS DMS for migrating a database to Amazon RDS? (Choose three.)

Select 3 answers

A.Whether the target database is in a different AWS region

B.Downtime tolerance during migration

C.Requirement for ongoing replication to keep the target in sync

D.Need to perform complex data transformations during migration

E.Total size of the database and network bandwidth

AnswersB, C, E

Native tools typically require full downtime; DMS can minimize downtime with ongoing replication.

Why this answer

Downtime tolerance directly influences the choice between a one-time logical dump (pg_dump) and AWS DMS, which supports minimal-downtime migrations via ongoing replication. pg_dump requires the source database to be read-consistent during the dump, often necessitating a read-only or quiesced state, whereas DMS can perform a full load followed by continuous change data capture (CDC) to keep the target nearly in sync with minimal application downtime.

Exam trap

The trap here is that candidates often assume AWS DMS can perform complex data transformations like an ETL tool, when in fact DMS only supports simple column mappings and transformations, not multi-table joins or business logic rewrites.

Practice this question →

310

MCQhard

Refer to the exhibit. You run the command and get the output shown. The database is an RDS for MySQL instance. You need to connect to it from an EC2 instance in the same VPC. Which connection string should be used?

A.mysql -h mydb.123456789012.us-east-1.rds.amazonaws.com -P 3306 -u admin -p

B.psql -h mydb.123456789012.us-east-1.rds.amazonaws.com -p 5432 -U admin

C.mysql -h mydb.us-east-1.rds.amazonaws.com -P 3306 -u admin -p

D.mysql -h mydb.123456789012.us-east-1.rds.amazonaws.com -P 5432 -u admin -p

AnswerA

Correct endpoint and port.

Why this answer

The command uses the MySQL client (`mysql`) with the correct fully qualified domain name (FQDN) of the RDS instance, which includes the AWS account ID and region, and the default MySQL port 3306. The `-u admin -p` flags specify the master username and prompt for a password, which is the standard way to connect to an RDS for MySQL instance from an EC2 instance in the same VPC.

Exam trap

The trap here is that candidates may confuse the default ports for MySQL (3306) and PostgreSQL (5432) or omit the account ID from the RDS endpoint, leading them to choose an option with an incorrect port or an incomplete hostname.

How to eliminate wrong answers

Option B is wrong because it uses `psql`, which is the PostgreSQL client, not the MySQL client, and port 5432 is the default PostgreSQL port, not MySQL. Option C is wrong because the hostname `mydb.us-east-1.rds.amazonaws.com` is missing the AWS account ID (`123456789012`), which is required in the FQDN for RDS instances; without it, DNS resolution will fail. Option D is wrong because it uses port 5432, which is the PostgreSQL default port, not the MySQL default port 3306.

Practice this question →

311

MCQhard

A company is migrating a 5 TB PostgreSQL database from on-premises to Amazon RDS for PostgreSQL. The database has a 24/7 uptime requirement and must be migrated with minimal downtime. The on-premises network bandwidth is 100 Mbps. The migration must be completed within 48 hours. The team has chosen to use AWS Database Migration Service (DMS) with ongoing replication from a change data capture (CDC) source. After setting up the source endpoint, target endpoint, and replication instance, the initial full load takes 30 hours. However, during the CDC phase, the target falls behind by over 2 hours and continues to lag. The replication instance is a dms.c5.large (2 vCPUs, 4 GB memory). The source database is heavily utilized with frequent updates. What should the team do to reduce the CDC lag and meet the migration deadline?

A.Increase the replication instance size to dms.c5.2xlarge.

B.Enable Multi-AZ on the replication instance for better performance.

C.Split the migration into multiple DMS tasks for parallel processing.

D.Disable ongoing replication and use a one-time full load migration.

AnswerA

Increasing the replication instance size provides more CPU and memory, allowing it to process CDC changes faster and reduce lag.

Why this answer

Increasing the replication instance size to dms.c5.2xlarge provides more CPU and memory, which can handle higher transaction throughput, reducing CDC lag. Option B is wrong because enabling Multi-AZ on a replication instance does not directly improve performance; it adds redundancy and can even introduce latency. Option C is wrong because splitting the migration into multiple tasks for a single source database adds overhead and may cause conflicts, and it does not necessarily reduce lag.

Option D is wrong because disabling ongoing replication would result in data loss and does not meet the minimal downtime requirement.

Practice this question →

312

Multi-Selectmedium

A company is migrating a 1 TB Oracle database to Amazon Aurora PostgreSQL using AWS DMS. They need to ensure minimal downtime and data consistency. Which TWO actions should the company take?

Select 2 answers

A.Increase the target Aurora storage to 2 TB to avoid storage issues

B.Enable change data capture (CDC) on the source Oracle database

C.Enable data validation on the DMS task

D.Disable foreign key constraints on the target during migration

E.Use AWS Schema Conversion Tool to convert the schema

AnswersB, C

CDC captures ongoing changes to minimize downtime.

Why this answer

Enabling Change Data Capture (CDC) on the source Oracle database allows AWS DMS to capture ongoing changes after the full load, enabling a near-zero downtime migration by continuously replicating transactions to the target Aurora PostgreSQL. Option C is correct because enabling data validation on the DMS task ensures that the data migrated is consistent between the source and target, verifying that no data loss or corruption occurred during the migration process.

Exam trap

The trap here is that candidates often confuse the AWS Schema Conversion Tool (SCT) with DMS, thinking it is part of the migration process for minimizing downtime, when in fact SCT is used for schema assessment and conversion before migration, not for ongoing replication or consistency checks.

Practice this question →

313

MCQhard

A company is migrating a 10 TB Oracle data warehouse to Amazon Redshift. They want to use AWS DMS for continuous replication. However, the migration is taking longer than expected due to LOB columns. What optimization should be applied?

A.Use AWS SCT to compress LOBs.

B.Enable FullLobMode to transfer all LOBs.

C.Set MaxLobSize to a value like 64 KB to limit inline LOB transfer.

D.Increase the number of DMS tasks.

AnswerC

This optimizes performance.

Why this answer

Setting MaxLobSize to a value like 64 KB instructs AWS DMS to treat LOBs smaller than that threshold as inline data, which is transferred more efficiently in the batch stream. This avoids the performance penalty of using FullLobMode, which transfers each LOB individually and can dramatically slow down continuous replication for large tables with many LOB columns.

Exam trap

The trap here is that candidates assume FullLobMode is always the safest or fastest choice, not realizing that its per-LOB API call overhead is the very cause of the slowdown, while LimitedLobMode with a properly tuned MaxLobSize dramatically improves throughput for LOB columns.

How to eliminate wrong answers

Option A is wrong because AWS SCT (Schema Conversion Tool) does not compress LOBs; it converts schema and can assess migration complexity, but data compression during transfer is handled by DMS settings, not SCT. Option B is wrong because enabling FullLobMode forces DMS to transfer every LOB in its entirety using a separate API call per LOB, which is the default behavior that causes the slow performance described in the scenario. Option D is wrong because simply increasing the number of DMS tasks does not address the root cause of LOB transfer overhead; it may lead to resource contention or task conflicts without improving per-LOB throughput.

Practice this question →

314

MCQmedium

A company is migrating a 500 GB MongoDB database to Amazon DocumentDB. The migration must have minimal impact on the source database. Which approach should the company take?

A.Use mongodump to export the data, then use mongorestore to import into DocumentDB.

B.Use mongoexport to export CSV, then use the DocumentDB import tool.

C.Use AWS Database Migration Service (DMS) with MongoDB as source and DocumentDB as target.

D.Use AWS Schema Conversion Tool (SCT) to convert schema, then copy data.

AnswerC

DMS allows online migration with minimal impact.

Why this answer

AWS DMS supports ongoing replication from MongoDB to Amazon DocumentDB, enabling a live migration with minimal impact on the source database. DMS uses the MongoDB oplog to capture changes continuously, so the source is only read during the initial load and then tailed for CDC, avoiding heavy locks or performance degradation.

Exam trap

The trap here is that candidates assume native MongoDB tools (mongodump/mongoexport) are always the best for migration, but they fail to consider the requirement for minimal impact and the need for ongoing replication, which only AWS DMS provides for DocumentDB.

How to eliminate wrong answers

Option A is wrong because mongodump/mongorestore performs a full dump that can cause significant read load and locking on the source MongoDB, and it does not support ongoing replication, requiring downtime for the cutover. Option B is wrong because mongoexport to CSV is a single-threaded export that cannot capture the full BSON data types (e.g., ObjectId, ISODate) and does not support continuous change data capture, making it unsuitable for a minimal-impact migration. Option D is wrong because AWS SCT is designed for schema conversion between relational databases (e.g., Oracle to Aurora) and does not support MongoDB or DocumentDB; it cannot handle NoSQL document models or migrate data.

Practice this question →

315

MCQmedium

A company is migrating a 1 TB SQL Server database to Amazon RDS for SQL Server using backup and restore. The database has high transaction volume. Which backup type should be used to minimize downtime?

A.Perform a full backup, then transaction log backups, and restore the full backup with the last log backup.

B.Perform only transaction log backups and restore them to RDS.

C.Perform a differential backup and restore it to RDS.

D.Perform a full backup and restore it to RDS.

AnswerA

Allows point-in-time recovery, minimizing data loss.

Why this answer

A full backup followed by transaction log backups allows point-in-time recovery and minimizes downtime during migration. You restore the full backup to RDS, then apply the latest transaction log backup to capture all changes up to the migration cutover, ensuring data consistency without requiring the database to be offline for the entire duration.

Exam trap

The trap here is that candidates assume a full backup alone is sufficient for migration, overlooking the need for transaction log backups to capture ongoing changes and minimize downtime in a high-transaction environment.

How to eliminate wrong answers

Option B is wrong because transaction log backups alone cannot be restored without a prior full backup; SQL Server requires a full backup as the base for log chain restoration. Option C is wrong because a differential backup only captures changes since the last full backup, but without the full backup it cannot be restored, and it does not provide point-in-time recovery to minimize downtime. Option D is wrong because a full backup alone would require the database to be offline for the entire backup duration, and any transactions after the backup would be lost, increasing downtime and data loss risk.

Practice this question →

316

MCQhard

A team is setting up a DMS migration task. The IAM policy above is attached to the DMS replication instance's IAM role. The team is unable to modify the target RDS instance's maintenance window during the migration. Which additional permission is missing?

A.Add 'rds:ModifyDBInstance' permission for the target RDS instance.

B.Add 'rds:ModifyOptionGroup' permission for the target RDS instance.

C.Add 'dms:ModifyReplicationInstance' permission for the DMS replication instance.

D.Add 'ec2:DescribeVpcs' permission to the policy.

AnswerA

The DMS replication instance's IAM role needs the `rds:ModifyDBInstance` permission on the target RDS instance to change its maintenance window. Without this permission, the migration task cannot adjust the window.

Why this answer

Modifying the target RDS instance's maintenance window requires the `rds:ModifyDBInstance` permission. The DMS replication instance's IAM role must have this permission for the target RDS instance to allow the migration task to adjust the maintenance window, which is necessary to prevent conflicts during ongoing replication. Without this permission, the DMS task cannot alter the maintenance window, even if the IAM role has other RDS permissions.

Exam trap

The trap here is that candidates may confuse the permissions needed for modifying the target RDS instance's maintenance window with permissions for modifying the DMS replication instance or RDS option groups, leading them to select options B or C instead of the correct `rds:ModifyDBInstance` permission.

How to eliminate wrong answers

Option B is wrong because `rds:ModifyOptionGroup` is used to modify option groups (e.g., enabling Oracle TDE or SQL Server native backup/restore), not the maintenance window of an RDS instance. Option C is wrong because `dms:ModifyReplicationInstance` is an action on the DMS replication instance itself, not on the target RDS instance, and does not grant the ability to modify the RDS maintenance window. Option D is wrong because `ec2:DescribeVpcs` is a read-only permission for describing VPCs, which is unrelated to modifying RDS instance maintenance windows.

Practice this question →

317

MCQmedium

A company is migrating a 100 GB Oracle database to Amazon RDS for Oracle. They want to use AWS DMS. The source database is in a different AWS account. What is required to allow DMS to connect to the source?

A.Establish VPC peering or VPN between the source and target VPCs, and configure security group rules.

B.Assign an IAM role to the source database to allow DMS access.

C.Configure an S3 VPC gateway endpoint for the source VPC.

D.Create a VPC endpoint for DMS in the source account.

AnswerA

DMS requires network connectivity between the replication instance and the source database.

Why this answer

AWS DMS requires network connectivity between the replication instance and the source database. Since the source is in a different AWS account, VPC peering or a VPN connection must be established to route traffic between the VPCs. Additionally, security group rules in both VPCs must allow inbound/outbound traffic on the Oracle listener port (default 1521) from the DMS replication instance's IP or security group.

Exam trap

The trap here is that candidates confuse IAM roles (which handle authorization for AWS services) with network connectivity requirements, assuming a role can grant DMS access to a database in another account, when in fact DMS needs direct network layer access via VPC peering or VPN.

How to eliminate wrong answers

Option B is wrong because IAM roles are used to grant AWS services (like DMS) permissions to access other AWS resources (e.g., S3, RDS), not to authenticate a database user or provide network connectivity to a source database in a different account. Option C is wrong because an S3 VPC gateway endpoint is used for private connectivity to S3, not for connecting DMS to an Oracle database; it does not solve cross-account network routing. Option D is wrong because a VPC endpoint for DMS (a DMS VPC endpoint) is not a valid AWS resource; DMS uses a replication instance within a VPC, and cross-account connectivity requires VPC peering or VPN, not a VPC endpoint.

Practice this question →

318

MCQmedium

A company is migrating a 2 TB Oracle database to Amazon Aurora PostgreSQL. They need to minimize downtime. Which AWS service should they use?

A.AWS Database Migration Service (DMS)

B.AWS Schema Conversion Tool (SCT)

C.AWS Data Pipeline

D.AWS Snowball

AnswerA

DMS supports heterogeneous migrations and ongoing replication to minimize downtime.

Why this answer

AWS DMS can perform a live migration from Oracle to Aurora PostgreSQL with minimal downtime by continuously replicating ongoing changes from the source database to the target using Change Data Capture (CDC). For a 2 TB database, DMS supports full-load plus CDC, allowing the source to remain operational during the initial load and then switching over with only a brief outage to apply final changes.

Exam trap

The trap here is that candidates often confuse AWS SCT (schema conversion) with DMS (data migration), assuming SCT handles the actual data transfer, or they overestimate Snowball's suitability for minimizing downtime when the database is still being actively written to.

How to eliminate wrong answers

Option B is wrong because AWS Schema Conversion Tool (SCT) is used for converting the database schema and code objects (like stored procedures) from Oracle to PostgreSQL, but it does not perform the actual data migration or handle ongoing replication to minimize downtime. Option C is wrong because AWS Data Pipeline is a workflow orchestration service for moving and transforming data between AWS services and on-premises sources, but it lacks native support for continuous CDC replication from Oracle to Aurora PostgreSQL and is not designed for near-zero-downtime database migrations. Option D is wrong because AWS Snowball is a physical data transfer device intended for large-scale offline data movement (typically 10 TB or more) when network bandwidth is limited, but it cannot provide minimal downtime since it requires stopping writes to the source, shipping the device, and then loading data—resulting in significant downtime.

Practice this question →

319

MCQmedium

A company is migrating a 500 GB MongoDB database to Amazon DocumentDB. The migration is done using AWS DMS with full load and ongoing replication. The full load completes successfully, but during CDC, the DMS task logs show 'Memory limit exceeded' errors and the task fails repeatedly. The DMS replication instance is a dms.r5.large. The source MongoDB has a write-heavy workload with many small updates. The DBA needs to fix the migration without restarting from scratch. Which action should the DBA take?

A.Increase the DMS replication instance size to a larger instance class with more memory.

B.Reduce the DMS task's 'BatchApplyEnabled' setting to apply transactions individually.

C.Stop and restart the DMS task to clear the cache.

D.Enable Multi-AZ on the DMS replication instance to distribute the load.

AnswerA

More memory allows DMS to buffer more changes and handle the workload.

Why this answer

The 'Memory limit exceeded' error during CDC with a write-heavy workload indicates the replication instance lacks sufficient memory to buffer the changes. Increasing the instance size (e.g., to dms.r5.xlarge) provides more memory. Option B is wrong because reducing BatchApplyEnabled may slow down apply but does not increase memory; it could even worsen the backlog.

Option C is wrong because restarting just clears cache temporarily; the error will recur. Option D is wrong because Multi-AZ provides high availability, not additional memory.

Practice this question →

320

Multi-Selectmedium

A company is deploying a DynamoDB table for a global application that requires low-latency reads and writes in multiple AWS Regions. Which THREE features should be enabled? (Choose three.)

Select 3 answers

A.DynamoDB Accelerator (DAX).

B.On-demand capacity mode.

C.DynamoDB Streams.

D.Time to Live (TTL).

E.DynamoDB global tables.

AnswersA, B, E

Provides in-memory caching for low-latency reads.

Why this answer

DynamoDB Accelerator (DAX) is correct because it provides an in-memory cache for DynamoDB tables, delivering microsecond latency for read-heavy workloads. For a global application requiring low-latency reads across multiple AWS Regions, DAX reduces response times by offloading read traffic from the DynamoDB table to a distributed cache, which is essential for meeting strict performance SLAs.

Exam trap

The trap here is that candidates often confuse DynamoDB Streams (a change-data-capture feature) with a performance optimization tool, when in fact Streams are for replication and event processing, not for reducing latency.

Practice this question →

321

MCQmedium

A company has an Aurora MySQL cluster with three instances. The current writer instance is 'mycluster-instance-1'. The company wants to failover to 'mycluster-instance-2' for maintenance. What is the most direct way to achieve this?

A.Change the cluster's endpoint to point to instance-2.

B.Modify 'mycluster-instance-2' to promote it to writer.

C.Reboot 'mycluster-instance-1' to trigger a failover.

D.Use the AWS CLI: aws rds failover-db-cluster --db-cluster-identifier mycluster --target-db-instance-identifier mycluster-instance-2

AnswerD

This command initiates failover to the specified instance.

Why this answer

The AWS CLI command `aws rds failover-db-cluster` with the `--target-db-instance-identifier` parameter allows you to explicitly specify which Aurora replica should become the new writer instance. This is the most direct and supported method to initiate a controlled failover to 'mycluster-instance-2' without rebooting the current writer or manually modifying endpoints.

Exam trap

The trap here is that candidates confuse rebooting an instance with triggering a failover, or assume that modifying an instance's settings can promote it, when in fact only the cluster-level failover command can explicitly designate a target replica as the new writer.

How to eliminate wrong answers

Option A is wrong because the cluster endpoint is a DNS name that automatically points to the current writer; you cannot manually change it to point to a specific instance. Option B is wrong because Aurora does not support manually promoting a replica to writer via a 'promote' action; failover is controlled by the cluster, not by modifying the instance. Option C is wrong because rebooting the writer instance does not trigger a failover; a reboot simply restarts the instance in place, and the cluster remains with the same writer unless the instance becomes unavailable.

Practice this question →

322

MCQeasy

Refer to the exhibit. A developer wants to connect to the database. Which database engine is most likely being used?

A.Oracle

B.SQL Server

C.MySQL

D.PostgreSQL

AnswerC

Port 3306 is default for MySQL.

Why this answer

The exhibit shows a connection string using the format `jdbc:mysql://...`, which is the standard JDBC URL prefix for MySQL databases. This indicates the developer is connecting to a MySQL database engine, as Oracle, SQL Server, and PostgreSQL use different JDBC URL prefixes (`jdbc:oracle:thin:`, `jdbc:sqlserver://`, and `jdbc:postgresql://` respectively).

Exam trap

The DBS-C01 exam often tests the ability to identify database engines by their JDBC connection string prefixes, and the trap here is that candidates may confuse MySQL with PostgreSQL or Oracle because all are relational databases, but each has a distinct JDBC URL format that must be matched exactly.

How to eliminate wrong answers

Option A is wrong because Oracle uses the JDBC URL prefix `jdbc:oracle:thin:@//host:port/service_name` or `jdbc:oracle:oci:@...`, not `jdbc:mysql://`. Option B is wrong because SQL Server uses `jdbc:sqlserver://host:port;databaseName=dbname`, not `jdbc:mysql://`. Option D is wrong because PostgreSQL uses `jdbc:postgresql://host:port/dbname`, not `jdbc:mysql://`.

Practice this question →

323

MCQhard

A company is migrating a self-managed Oracle database to Amazon Aurora PostgreSQL using AWS DMS. The source database has a large number of tables with foreign key constraints. During the full load phase, some tables fail to load due to foreign key violations. What is the most efficient way to resolve this?

A.Increase the DMS task memory and parallel load threads

B.Use the table preparation mode 'Do nothing' and load tables in dependency order

C.Disable foreign key constraints on the target before migration and re-enable after

D.Pre-create all target tables with the same constraints and use 'Truncate' mode

AnswerC

This allows flexible loading order and avoids violations.

Why this answer

Disabling foreign key constraints on the target Aurora PostgreSQL database before the migration allows DMS to load tables in any order without violating referential integrity. After the full load completes, re-enabling the constraints ensures data consistency. This approach is the most efficient as it avoids complex dependency ordering and reduces migration failures.

Exam trap

The trap here is that candidates may think increasing resources (Option A) or pre-creating tables (Option D) will solve the issue, but they overlook that foreign key violations are a logical dependency problem, not a performance or schema creation issue.

How to eliminate wrong answers

Option A is wrong because increasing DMS task memory and parallel load threads addresses performance bottlenecks, not foreign key constraint violations; the root cause is referential integrity, not resource contention. Option B is wrong because using 'Do nothing' table preparation mode and loading in dependency order is impractical for a large number of tables with foreign keys, as it requires manual analysis and ordering, and DMS does not automatically resolve dependencies; this approach is error-prone and time-consuming. Option D is wrong because pre-creating target tables with the same constraints and using 'Truncate' mode would still cause foreign key violations during the full load, as DMS does not guarantee insertion order; truncate mode only clears data before reloading, not resolving the dependency issue.

Practice this question →

324

MCQeasy

A team is migrating an on-premises database to Amazon RDS using AWS DMS. After the full load completed, the task stopped. The team needs to perform ongoing replication to minimize downtime. What change should the team make to the DMS task?

A.Modify the replication task to change the migration type to 'full-load-and-cdc'.

B.Restart the replication task with the same settings.

C.Create a new replication instance and start a new full-load task.

D.Use AWS Schema Conversion Tool to convert the schema again.

AnswerA

Changing to 'full-load-and-cdc' enables both full load and ongoing change data capture replication.

Why this answer

After a full load completes and the task stops, the team needs to enable ongoing replication to capture and apply changes made to the source database during the migration window. Modifying the DMS task to use the 'full-load-and-cdc' migration type allows the task to perform the initial full load and then seamlessly transition to Change Data Capture (CDC) to replicate incremental changes, minimizing downtime. This is the correct approach because DMS supports switching a completed full-load task to include CDC without re-running the full load.

Exam trap

The trap here is that candidates may think restarting the task or creating a new instance will automatically enable CDC, but DMS requires explicitly modifying the migration type to include CDC after the full load completes.

How to eliminate wrong answers

Option B is wrong because restarting the replication task with the same settings will simply re-run the full load from scratch, not enable ongoing replication. Option C is wrong because creating a new replication instance and starting a new full-load task would duplicate effort and waste resources, and it still does not enable CDC for ongoing replication. Option D is wrong because the AWS Schema Conversion Tool (SCT) is used for schema conversion, not for enabling CDC or managing replication tasks; it is irrelevant to the need for ongoing replication.

Practice this question →

325

Multi-Selecthard

A company is migrating a 5 TB Microsoft SQL Server database to Amazon Aurora MySQL. The migration must be completed with minimal downtime. Which THREE steps should the company take? (Select THREE.)

Select 3 answers

A.Update the application connection string to point to the Aurora reader endpoint.

B.Use AWS DMS to perform a full load and ongoing replication from SQL Server to Aurora.

C.Create a read replica of the Aurora database in the same region.

D.Use AWS SCT to convert the SQL Server schema to MySQL-compatible schema.

E.Update the application connection string to point to the Aurora writer endpoint after cutover.

AnswersB, D, E

DMS handles data migration with minimal downtime.

Why this answer

AWS DMS (Database Migration Service) supports ongoing replication (change data capture) from Microsoft SQL Server to Amazon Aurora MySQL, enabling a full load followed by continuous sync of changes. This minimizes downtime by allowing the source database to remain operational until the final cutover, at which point the application switches to the Aurora writer endpoint.

Exam trap

The trap here is that candidates often confuse the Aurora reader endpoint (for read replicas) with the writer endpoint (for primary writes), and incorrectly assume a read replica is needed during migration, when in fact the migration requires schema conversion and ongoing replication via DMS.

Practice this question →

326

Multi-Selecthard

Which TWO steps are required when migrating an on-premises Microsoft SQL Server database to Amazon RDS for SQL Server using AWS DMS with ongoing replication?

Select 2 answers

A.Create a VPC peering connection between the on-premises network and the DMS VPC.

B.Install the DMS agent on the source SQL Server instance.

C.Enable MS-CDC (change data capture) on the source database.

D.Configure MS-Replication on the source database.

E.Ensure the source database is using the full recovery model.

AnswersC, E

DMS uses CDC to capture ongoing changes from SQL Server.

Why this answer

AWS DMS requires MS-CDC (change data capture) to be enabled on the source SQL Server database when using ongoing replication (change data capture). CDC captures insert, update, and delete activity from the transaction log, allowing DMS to apply those changes to the target RDS for SQL Server instance without requiring full table reloads.

Exam trap

The trap here is that candidates often confuse MS-CDC with MS-Replication, assuming DMS requires replication agents or topology, when in fact DMS uses native CDC or log-based capture without setting up replication.

Practice this question →

327

MCQmedium

A company is migrating a PostgreSQL database to Amazon RDS for PostgreSQL. The source database uses custom functions written in PL/Python. What should the company consider?

A.Rewrite the functions in PL/pgSQL or another supported language.

B.Modify the DB parameter group to enable PL/Python.

C.Use RDS Custom for PostgreSQL to install PL/Python.

D.Migrate to Aurora PostgreSQL which supports PL/Python.

AnswerA

RDS PostgreSQL supports only specific procedural languages; PL/Python is not one of them.

Why this answer

Amazon RDS for PostgreSQL does not support PL/Python because it requires the installation of an untrusted procedural language, which poses security risks in a managed database environment. The correct approach is to rewrite the custom functions in a supported language such as PL/pgSQL, PL/Perl, or PL/Tcl, which are trusted languages available in RDS for PostgreSQL.

Exam trap

The trap here is that candidates assume RDS Custom or Aurora PostgreSQL can bypass the PL/Python limitation, but AWS does not support untrusted languages in any managed PostgreSQL offering, and RDS Custom still relies on the standard PostgreSQL engine which lacks PL/Python support.

How to eliminate wrong answers

Option B is wrong because modifying the DB parameter group cannot enable PL/Python; RDS for PostgreSQL does not include the PL/Python extension and does not allow installation of untrusted languages. Option C is wrong because RDS Custom for PostgreSQL still does not support PL/Python; RDS Custom provides OS-level access but the PostgreSQL engine itself must support the language, and PL/Python is not bundled or supported by AWS. Option D is wrong because Aurora PostgreSQL also does not support PL/Python; it shares the same limitations as RDS for PostgreSQL regarding untrusted procedural languages.

Practice this question →

328

Multi-Selecteasy

Which TWO AWS services can be used together to migrate an on-premises MySQL database to Amazon Aurora MySQL with minimal downtime? (Select TWO.)

Select 2 answers

A.AWS Schema Conversion Tool (SCT)

B.Amazon Route 53

C.AWS CloudFormation

D.AWS Database Migration Service (DMS)

E.AWS Global Accelerator

AnswersA, D

Converts schema for compatibility.

Why this answer

AWS Database Migration Service (DMS) can perform continuous replication from an on-premises MySQL source to an Amazon Aurora MySQL target using change data capture (CDC), enabling near-zero downtime. The AWS Schema Conversion Tool (SCT) is used to assess and convert the source schema, including any incompatible objects, to ensure the Aurora target is ready for migration. Together, SCT handles schema transformation while DMS handles the ongoing data replication.

Exam trap

The trap here is that candidates often assume a single service like DMS alone can handle schema conversion, but DMS does not convert incompatible schema objects — that is the specific role of SCT, and both are required for a complete migration with minimal downtime.

Practice this question →

329

MCQeasy

A startup is deploying a new web application on AWS. The application uses Amazon RDS for PostgreSQL as its database. The developers need to create the initial schema and load test data. They have a SQL script file that creates tables and inserts 10,000 rows. The DB instance is a db.t3.micro with 20 GB gp2 storage. The developers connect to the RDS instance using pgAdmin from their local machine and run the script. The script fails with a 'connection reset' error after inserting 5,000 rows. What is the MOST likely cause?

A.The DB instance ran out of memory or CPU credits due to the intensive script

B.The max_connections parameter was set too low

C.The storage volume reached its maximum capacity

D.The security group blocked the connection due to a timeout

AnswerD

Correct. A security group can have timeout settings that cause the connection to be reset if the script runs longer than the timeout, which is a common issue with long-running queries through clients like pgAdmin.

Why this answer

The most likely cause is that the connection was terminated by an idle timeout on an intermediate network component (such as a NAT Gateway, which has a default idle timeout of 350 seconds, or the client-side firewall/proxy). Security groups are stateful and do not have configurable timeout settings, so they are not directly responsible. The script's duration likely exceeded the idle timeout, causing a 'connection reset' error.

Option A is unlikely because a db.t3.micro can handle inserting 10,000 rows without exhausting memory or CPU credits; the error is network-related, not resource-related. Option B is incorrect because max_connections is sufficient for a single connection. Option C is incorrect because 20 GB storage is far more than needed for 10,000 rows.

Practice this question →

330

Multi-Selectmedium

A company is migrating a 500 GB PostgreSQL database from on-premises to Amazon Aurora PostgreSQL. They need to minimize downtime and ensure that all data changes made during migration are synchronized. Which three components are required for this migration? (Choose THREE.)

Select 3 answers

A.AWS Database Migration Service (DMS) replication instance

B.AWS Schema Conversion Tool (SCT)

C.Amazon Aurora PostgreSQL cluster as the target

D.Source PostgreSQL database configured with logical replication

E.AWS VPN connection between on-premises and AWS

AnswersA, C, D

DMS orchestrates the migration and replication.

Why this answer

AWS DMS replication instance is required because it orchestrates the continuous replication of data from the source PostgreSQL database to the target Aurora PostgreSQL cluster. It manages the connection, reads changes from the source using logical replication slots, and applies them to the target, enabling near-zero downtime migration.

Exam trap

The DBS-C01 exam often tests the misconception that AWS Schema Conversion Tool is always needed for any database migration, but it is only required when migrating between different database engines, not for homogeneous migrations like PostgreSQL to Aurora PostgreSQL.

Practice this question →

331

Multi-Selecthard

Which THREE factors should be considered when choosing between a homogeneous migration and a heterogeneous migration to Amazon RDS? (Select THREE.)

Select 3 answers

A.Network latency between source and target.

B.Performance requirements of the target database.

C.Amount of application code changes needed.

D.Schema compatibility between source and target.

E.Licensing costs of the target database engine.

AnswersB, D, E

May influence engine choice.

Why this answer

A homogeneous migration (e.g., MySQL to RDS MySQL) typically requires minimal schema changes, preserves performance characteristics, and maintains existing licensing costs. A heterogeneous migration (e.g., Oracle to RDS PostgreSQL) requires schema conversion (validating schema compatibility), may require re-architecting to meet performance requirements due to different query optimizers, and can change licensing costs (e.g., eliminating Oracle licenses). Therefore, factors B, D, and E directly influence the choice between homogeneous and heterogeneous migrations.

Exam trap

The trap here is that candidates confuse migration method factors (e.g., network latency, downtime tolerance) with migration type factors (e.g., schema compatibility, licensing, performance), leading them to select A as a relevant consideration when it only applies to the migration approach, not the choice between homogeneous and heterogeneous.

Practice this question →

332

MCQmedium

A company is migrating a 1 TB SQL Server database to Amazon RDS for SQL Server. The migration window is 4 hours. The on-premises network bandwidth is 1 Gbps. The database is not actively used during the migration window. The team wants to minimize migration time and cost. Which migration strategy is most appropriate?

A.Use SQL Server BCP utility to export data and then import using DTS.

B.Use AWS Snowball to transfer the database files.

C.Create a native backup, upload to S3, restore to RDS.

D.Use AWS DMS with full load only.

AnswerD

DMS can complete full load within 4 hours over 1 Gbps.

Why this answer

AWS DMS with full load only (Option D) is the most appropriate strategy for this migration. With a 1 Gbps network, the theoretical transfer time for 1 TB is about 2.2 hours (1 TB = 8000 Gb, 8000 Gb / 1 Gbps = 8000 seconds ≈ 2.22 hours), well within the 4-hour window. AWS DMS performs a direct, efficient full-load migration without requiring intermediate storage or additional tools.

Option A (BCP + DTS) is slower and more complex. Option B (Snowball) adds cost and logistics that are unnecessary given the network speed. Option C (native backup to S3 and restore) requires uploading the backup to S3 first, then restoring to RDS, which is typically slower than DMS's direct streaming approach.

Practice this question →

333

Multi-Selectmedium

A company is deploying an Amazon Aurora MySQL database with read replicas. They need to ensure high availability and disaster recovery across AWS Regions. Which THREE components should be included?

Select 3 answers

A.Aurora Replicas in the same Region

B.Aurora Global Database

C.Auto Scaling groups

D.Amazon Route 53 with health checks and failover policy

E.Amazon CloudFront

AnswersA, B, D

Aurora Replicas provide high availability within the region.

Why this answer

Aurora Replicas in the same Region provide read scaling and automatic failover within an AWS Region. They share the same underlying storage volume as the primary instance, so failover is fast (typically under 30 seconds) and does not require data rehydration. This is a core component for high availability within a single Region.

Exam trap

The trap here is that candidates often confuse Auto Scaling groups (which scale compute resources) with database replication or failover mechanisms, or they mistakenly think CloudFront can serve as a database-level disaster recovery solution when it only caches content at the edge.

Practice this question →

334

Multi-Selectmedium

A company is deploying a new MySQL database on Amazon RDS. The database must be highly available and support cross-Region disaster recovery. Which TWO actions should be taken? (Choose two.)

Select 2 answers

A.Enable encryption at rest using AWS KMS.

B.Deploy a Multi-AZ instance in multiple regions.

C.Enable automated backups with a retention period of 35 days.

D.Create a cross-region read replica.

E.Enable Multi-AZ for automatic failover within a region.

AnswersD, E

Provides disaster recovery in another region.

Why this answer

A cross-region read replica provides a secondary copy of the database in a different AWS Region, which can be promoted to a standalone primary in a disaster scenario, enabling cross-Region disaster recovery. Option E is correct because Multi-AZ deployment provides automatic failover within a single region by synchronously replicating data to a standby instance in a different Availability Zone, ensuring high availability. Together, these two actions satisfy both high availability (within-region failover) and cross-Region DR requirements.

Exam trap

The trap here is that candidates often confuse Multi-AZ with cross-region replication, thinking that Multi-AZ can be deployed across regions (Option B), or they overlook that automated backups (Option C) are region-bound and do not provide automatic failover or cross-Region DR.

Practice this question →

335

Multi-Selectmedium

A company is deploying a new application using Amazon RDS for PostgreSQL. They require high availability with automatic failover and the ability to offload read traffic. Which TWO features should they enable? (Choose two.)

Select 2 answers

A.Multi-AZ deployment

B.Read replicas

C.Performance Insights

D.Global Database

E.Auto Scaling for read replicas

AnswersA, B

Multi-AZ provides automatic failover to a standby in another Availability Zone.

Why this answer

Multi-AZ deployment (Option A) provides high availability by automatically provisioning and maintaining a synchronous standby replica in a different Availability Zone. If the primary DB instance fails, Amazon RDS automatically fails over to the standby, ensuring minimal downtime. Read replicas (Option B) offload read traffic by creating asynchronous copies of the database that can serve read queries, reducing load on the primary instance.

Exam trap

The trap here is that candidates may confuse Multi-AZ with read replicas, thinking they serve the same purpose, or incorrectly assume that Global Database or Auto Scaling for read replicas are available for standard RDS PostgreSQL, when they are either Aurora-specific or not supported.

Practice this question →

336

MCQeasy

A company is deploying a new application that requires a MySQL-compatible database with automatic scaling of compute and storage resources. Which AWS service should be used?

A.Amazon Aurora MySQL

B.Amazon RDS for MySQL

C.Amazon DynamoDB

D.Amazon Redshift

AnswerA

Supports automatic scaling for compute and storage.

Why this answer

Amazon Aurora MySQL is the correct choice because it is a MySQL-compatible relational database that automatically scales compute (up to 128 vCPUs and 244 GiB of memory) and storage (up to 128 TiB in 10 GiB increments) without downtime. Aurora's storage subsystem is distributed and self-healing, scaling as data grows, and its compute can be scaled via Auto Scaling policies or by modifying the instance class with minimal disruption.

Exam trap

The trap here is that candidates often confuse Amazon RDS for MySQL with Aurora MySQL, assuming both offer automatic scaling, but RDS requires manual scaling of compute and storage, while Aurora provides true automatic scaling for both.

How to eliminate wrong answers

Option B is wrong because Amazon RDS for MySQL does not support automatic scaling of compute resources; you must manually modify the DB instance class and storage, which can cause downtime. Option C is wrong because Amazon DynamoDB is a NoSQL key-value and document database, not MySQL-compatible, and it does not support SQL queries or relational features like joins and transactions. Option D is wrong because Amazon Redshift is a petabyte-scale data warehouse optimized for analytical queries, not a MySQL-compatible transactional database, and it does not provide automatic scaling of compute or storage in the same manner as Aurora.

Practice this question →

337

Multi-Selecteasy

Which TWO AWS services can be used to migrate a MongoDB database to Amazon DocumentDB? (Choose 2.)

Select 2 answers

A.AWS DataSync

B.AWS Database Migration Service (AWS DMS)

C.Amazon S3

D.MongoDB native tools (mongodump and mongorestore)

E.Amazon Kinesis Data Streams

AnswersB, D

DMS supports MongoDB to DocumentDB migration.

Why this answer

AWS Database Migration Service (AWS DMS) supports MongoDB as a source and Amazon DocumentDB as a target, enabling continuous replication with change data capture (CDC) for minimal downtime. MongoDB native tools (mongodump and mongorestore) are also valid for offline, one-time migrations by exporting the database as BSON files and importing them directly into DocumentDB.

Exam trap

The trap here is that candidates often confuse AWS DataSync or S3 as viable migration tools for NoSQL databases, but neither supports the native MongoDB protocol or BSON format required for DocumentDB ingestion.

Practice this question →

338

MCQeasy

A company is migrating an on-premises MySQL database to Amazon RDS for MySQL. They need to validate that the schema is compatible. Which AWS service should they use?

A.AWS Schema Conversion Tool (SCT)

B.Amazon Inspector

C.AWS Database Migration Service (DMS)

D.AWS Trusted Advisor

AnswerA

SCT checks and converts schemas.

Why this answer

The AWS Schema Conversion Tool (SCT) is designed specifically to assess and convert database schemas from one engine to another, including on-premises MySQL to Amazon RDS for MySQL. It analyzes the source schema for compatibility issues, identifies unsupported features or deprecated syntax, and generates a detailed assessment report. This makes it the correct choice for validating schema compatibility before migration.

Exam trap

The trap here is that candidates often confuse AWS DMS with schema validation, assuming DMS handles both data migration and schema conversion, but DMS only moves data and requires a pre-validated schema; SCT is the dedicated tool for schema compatibility analysis.

How to eliminate wrong answers

Option B is wrong because Amazon Inspector is a vulnerability management service that scans workloads for software vulnerabilities and unintended network exposure; it does not perform database schema analysis or compatibility checks. Option C is wrong because AWS Database Migration Service (DMS) is used for migrating data (rows and tables) from a source to a target database, but it does not validate schema compatibility or convert schema objects; schema conversion is handled separately by SCT. Option D is wrong because AWS Trusted Advisor provides best-practice recommendations for cost optimization, performance, security, and fault tolerance, but it does not analyze database schema compatibility or migration readiness.

Practice this question →

339

MCQeasy

A company is deploying a new microservices application on Amazon ECS. Each microservice needs its own database. Which AWS database service should be used to minimize operational overhead?

A.Amazon DynamoDB

B.Amazon Aurora

C.Amazon Redshift

D.Amazon RDS for MySQL

AnswerA

DynamoDB is fully managed, serverless, and suitable for microservices.

Why this answer

Amazon DynamoDB is a fully managed NoSQL database that provides single-digit millisecond latency at any scale, making it ideal for microservices that each require their own isolated database. It eliminates operational overhead by handling hardware provisioning, setup, configuration, replication, and patching automatically, with no servers to manage. DynamoDB also supports on-demand capacity mode, which scales automatically based on traffic, perfectly aligning with the dynamic nature of microservices on Amazon ECS.

Exam trap

The trap here is that candidates often assume a relational database (like Aurora or RDS) is always the best choice for microservices, overlooking the operational simplicity and scalability of a fully managed NoSQL service like DynamoDB, which is specifically designed for high-traffic, schema-less, and serverless architectures.

How to eliminate wrong answers

Option B (Amazon Aurora) is wrong because while it is fully managed, it is a relational database that requires schema definition and connection management, adding operational overhead compared to a schema-less NoSQL solution like DynamoDB. Option C (Amazon Redshift) is wrong because it is a petabyte-scale data warehouse designed for analytical workloads, not for transactional microservice databases, and it introduces significant operational complexity with cluster management. Option D (Amazon RDS for MySQL) is wrong because although it reduces some operational tasks, it still requires manual scaling, connection pooling, and schema management, and does not provide the same level of automatic scaling and serverless operation as DynamoDB.

Practice this question →

340

MCQhard

A company is migrating a 5 TB Oracle database to Amazon Aurora MySQL using AWS DMS. The full load completes successfully, but the CDC phase is slow and the target Aurora cluster is consuming high CPU. The DMS instance type is dms.c4.2xlarge. Which change will most likely improve CDC performance?

A.Increase the Aurora cluster's max_connections parameter

B.Increase the number of parallel apply threads in the DMS task

C.Increase the DMS task's target storage allocation

D.Change the Aurora cluster to a larger instance class

AnswerB

More parallel apply threads can increase the rate of applying changes to Aurora, reducing CPU usage per thread.

Why this answer

Increasing the number of parallel apply threads in the DMS task allows the CDC phase to apply multiple transactions concurrently to the target Aurora cluster, reducing the backlog of changes. The high CPU on the target suggests the apply process is the bottleneck, not the source or network, and DMS's parallel apply threads directly address this by enabling multi-threaded writes, which improves throughput without requiring larger instances.

Exam trap

The trap here is that candidates often assume high CPU on the target means the instance is undersized and needs a larger class (Option D), but the real issue is the DMS apply process being single-threaded, which causes CPU to spike due to inefficient serial writes rather than insufficient compute capacity.

How to eliminate wrong answers

Option A is wrong because increasing max_connections does not improve CDC apply performance; it only allows more client connections to the Aurora cluster, but the bottleneck is the single-threaded apply of changes, not connection limits. Option C is wrong because target storage allocation affects disk space, not the rate at which DMS applies transactions; CDC performance is CPU and I/O bound, not storage capacity bound. Option D is wrong because while a larger Aurora instance class might reduce CPU pressure, the root cause is the DMS task's single-threaded apply; upgrading the cluster without enabling parallel apply threads would still leave the apply process as a bottleneck, and it is more cost-effective to tune DMS parallelism first.

Practice this question →

341

MCQeasy

A company wants to migrate an on-premises Oracle database to Amazon Aurora PostgreSQL. They need to convert the schema and code. Which AWS service should they use?

A.AWS Schema Conversion Tool (SCT)

B.AWS Lambda

C.Amazon S3

D.AWS Database Migration Service (DMS)

AnswerA

Converts schema and code.

Why this answer

AWS Schema Conversion Tool (SCT) is the correct choice because it is specifically designed to convert database schemas and code objects (such as stored procedures, functions, and triggers) from one database engine to another. For an Oracle-to-Aurora PostgreSQL migration, SCT analyzes the source schema, identifies incompatible data types and syntax, and generates equivalent PostgreSQL DDL and PL/pgSQL code, handling complex conversions like Oracle sequences to PostgreSQL sequences and Oracle packages to PostgreSQL schemas.

Exam trap

The trap here is that candidates often confuse AWS DMS with schema conversion, but DMS only moves data and requires SCT for the schema and code transformation; AWS explicitly separates these tasks in the migration process.

How to eliminate wrong answers

Option B (AWS Lambda) is wrong because Lambda is a serverless compute service for running code in response to events, not a schema or code conversion tool; it cannot translate Oracle PL/SQL to PostgreSQL PL/pgSQL. Option C (Amazon S3) is wrong because S3 is an object storage service used for storing data and backups, not for converting database schemas or code. Option D (AWS Database Migration Service) is wrong because DMS handles data migration (moving table data) but does not perform schema or code conversion; it relies on SCT to generate the target schema before DMS can migrate the data.

Practice this question →