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CCNA Management and Operations Questions

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226

Multi-Selecteasy

A company is using Amazon DynamoDB with Auto Scaling enabled. The database specialist notices that write traffic is being throttled occasionally. Which TWO factors could cause throttling despite Auto Scaling?

Select 2 answers

A.The table has Global Tables enabled, causing cross-region replication overhead.

B.Auto Scaling is not configured to scale up quickly enough for sudden traffic spikes.

C.DynamoDB Accelerator (DAX) is not caching write operations.

D.The write traffic exceeds the maximum provisioned capacity that was set for Auto Scaling.

E.A hot partition where a single partition key receives a disproportionate amount of write traffic.

AnswersD, E

Auto Scaling cannot scale beyond the configured maximum.

Why this answer

Auto Scaling in DynamoDB operates within a maximum provisioned capacity ceiling. If write traffic exceeds this configured maximum, Auto Scaling cannot increase capacity further, leading to throttling. The service will return ProvisionedThroughputExceededException for requests that exceed the set maximum.

Exam trap

The trap here is that candidates often assume Auto Scaling eliminates all throttling, but it cannot prevent throttling caused by hot partitions or when traffic exceeds the configured maximum capacity ceiling.

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227

MCQmedium

A company uses Amazon ElastiCache for Redis to cache frequently accessed data. The cache cluster experiences high CPU utilization during peak hours. The cluster has a single node of type cache.r5.large. What is the most cost-effective way to reduce CPU utilization while maintaining performance?

A.Enable encryption at rest and in transit.

B.Upgrade to a cache.r5.xlarge node type.

C.Add a read replica to distribute read traffic.

D.Increase the maxmemory-policy parameter to 'allkeys-lru'.

AnswerC

Offloads read traffic, reducing CPU on primary.

Why this answer

Adding a read replica distributes read traffic away from the primary node, reducing its CPU utilization. This is more cost-effective than upgrading to a larger instance type (option B) because you can add a smaller replica node. Option A (enabling encryption) does not reduce CPU utilization and adds overhead.

Option D (changing maxmemory-policy) also does not reduce CPU utilization.

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228

MCQmedium

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

A.Decrease the value of innodb_log_file_size to 128 MB.

B.Set innodb_flush_log_at_trx_commit to 0.

C.Increase the value of innodb_log_file_size to 1 GB.

D.Increase the value of innodb_buffer_pool_size.

AnswerC

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

Why this answer

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

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

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229

Multi-Selecthard

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

Select 3 answers

A.Switch the table to on-demand capacity mode.

B.Reduce the provisioned read capacity units to save cost.

C.Enable auto scaling for read and write capacity.

D.Disable auto scaling to avoid cost fluctuations.

E.Implement DynamoDB Accelerator (DAX) to cache read requests.

AnswersA, C, E

On-demand mode automatically accommodates traffic spikes without throttling.

Why this answer

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

Exam trap

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

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230

MCQeasy

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

A.Decrease 'max_connections' parameter to 100.

B.Increase allocated storage to 200 GB.

C.Upgrade the DB instance to a larger class like db.t3.large.

D.Enable Performance Insights and switch to Provisioned IOPS.

AnswerC

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

Why this answer

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

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

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231

Multi-Selecthard

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

Select 3 answers

A.The backup retention period on the source must be at least 1 day.

B.The source DB instance must be in a VPC.

C.A read replica must be created in the target Region.

D.Automated backups must be enabled on the source DB instance.

E.The source DB instance must be a Multi-AZ deployment.

AnswersB, C, D

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

Why this answer

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

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

Exam trap

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

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

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232

Multi-Selectmedium

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

Select 2 answers

A.Increase the number of nodes in the cluster.

B.Analyze the tables to update statistics for the query optimizer.

C.Enable encryption for the cluster.

D.Disable compression on the tables to reduce CPU overhead.

E.Run the VACUUM command to reclaim space and re-sort data.

AnswersB, E

Updated statistics help the optimizer choose efficient query plans.

Why this answer

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

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

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233

MCQmedium

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

A.Enable Aurora Auto Scaling for read replicas and offload read-only queries to replicas.

B.Set the transaction isolation level to READ UNCOMMITTED to avoid locks.

C.Configure Multi-AZ deployment to automatically failover during deadlocks.

D.Increase the DB instance class size to handle more concurrent transactions.

AnswerA

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

Why this answer

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

Exam trap

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

How to eliminate wrong answers

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

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234

MCQmedium

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

A.Add additional reader instances to distribute the load.

B.Enable RDS Proxy for the cluster.

C.Increase the 'connect_timeout' parameter to 10 seconds.

D.Enable IAM database authentication and require TLS.

AnswerB

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

Why this answer

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

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

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235

Multi-Selecthard

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

Select 3 answers

A.Configure cross-Region read replicas.

B.Increase the instance class of the writer instance.

C.Add more reader instances to the cluster.

D.Enable Aurora Auto Scaling for the reader instances.

E.Implement Amazon ElastiCache for caching frequent queries.

AnswersC, D, E

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

Why this answer

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

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

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236

MCQeasy

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

A.AWS Config

B.Amazon RDS Automated Backups

C.AWS Systems Manager Patch Manager

D.Amazon RDS Maintenance Window

AnswerD

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

Why this answer

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

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

Exam trap

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

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237

MCQhard

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

A.The table lacks a global secondary index on game_id, causing a full table scan.

B.The query is using strongly consistent reads instead of eventually consistent reads.

C.The provisioned read capacity is too low for the query pattern.

D.A hot partition on the game_id key is causing throttling for that specific partition.

AnswerD

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

Why this answer

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

Exam trap

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

How to eliminate wrong answers

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

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238

MCQeasy

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

A.Modify the application to use an individual instance endpoint for each reader.

B.Create a custom endpoint that includes both writer and readers.

C.Modify the application to use the reader endpoint for read queries.

D.Modify the application to use the cluster endpoint for all queries.

AnswerC

The reader endpoint load balances across all read replicas.

Why this answer

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

Exam trap

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

How to eliminate wrong answers

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

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239

MCQhard

A company runs a critical e-commerce application on Amazon RDS for MySQL with Multi-AZ enabled. The database is 2 TB and uses General Purpose (gp2) storage. Recently, during peak hours, the application experienced a 5-minute outage. The CloudWatch logs show that the primary DB instance failed and an automatic failover occurred. However, the failover took 3 minutes, which is longer than the expected 1-2 minutes. The 'ReadLatency' and 'WriteLatency' metrics were elevated before the failure. The 'BurstBalance' metric was at 0% for the hour before the failure. The team suspects the issue is related to storage performance. What should the team do to prevent this issue in the future?

A.Increase the DB instance class to a larger size.

B.Change the storage type to Provisioned IOPS (io1).

C.Increase the backup retention period to 35 days.

D.Create a read replica to offload read traffic.

AnswerB

Provisioned IOPS provides consistent I/O performance and avoids burst credit exhaustion.

Why this answer

The BurstBalance at 0% indicates the gp2 volume exhausted its burst credits, causing I/O throttling and increased latency, which likely contributed to the failover delay. Switching to Provisioned IOPS (io1) provides consistent performance and avoids burst credit exhaustion. Option A is wrong because increasing the DB instance class addresses compute capacity, not storage I/O.

Option C is wrong because backup retention period does not affect storage performance. Option D is wrong because read replicas offload read traffic but do not improve write performance on the primary instance.

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240

Multi-Selectmedium

Which TWO methods can be used to reduce the read latency for an Amazon Aurora MySQL database? (Choose 2.)

Select 2 answers

A.Enable encryption at rest

B.Use Aurora Auto Scaling to add replica capacity based on load

C.Increase the write capacity of the DB instance

D.Enable Amazon ElastiCache in front of the database

E.Add Aurora Replicas to offload read traffic

AnswersB, E

Auto Scaling ensures sufficient replicas to handle read traffic.

Why this answer

Aurora Auto Scaling automatically adjusts the number of Aurora Replicas in response to changes in read workload, thereby reducing read latency by distributing read traffic across additional replicas. Option E is correct because adding Aurora Replicas offloads read queries from the primary instance, allowing parallel processing of read requests and reducing contention, which directly lowers read latency.

Exam trap

The trap here is that candidates may confuse write scaling (Option C) with read scaling, or assume that encryption (Option A) or external caching (Option D) are native Aurora methods, when the exam expects knowledge of Aurora-specific read scaling features like Aurora Replicas and Auto Scaling.

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241

MCQhard

A company runs a production Amazon RDS for PostgreSQL database with automated backups enabled. A database administrator accidentally dropped a critical table. The administrator wants to restore the table from a point in time before the drop. The database is 1 TB in size and the recovery point objective (RPO) is 5 minutes. Which approach minimizes downtime?

A.Use the point-in-time recovery feature to restore the database to a new DB instance at a time before the drop, then use pg_dump to export the table and import it into the production database.

B.Restore the automated backup from S3 to a new EC2 instance running PostgreSQL, then export the table and import it into the production database.

C.Restore the database from the most recent manual snapshot to a new instance, then use pg_dump to extract the table and import it into the production database.

D.Create a read replica from the production database, stop replication, and use pg_dump to extract the table from the replica and import it into the production database.

AnswerA

PITR allows restore to any second within the backup retention period, minimizing data loss and downtime by restoring to a new instance.

Why this answer

Amazon RDS Point-in-Time Recovery (PITR) allows restoring to any second within the backup retention window, enabling a restore to just before the table was dropped. After restoring to a new DB instance, pg_dump can export the specific table, and then pg_restore or psql can import it into the production database. This minimizes downtime by avoiding a full database restore and only moving the single dropped table.

Exam trap

The trap here is that candidates may think a read replica or manual snapshot can recover a dropped table, but they fail to realize that the drop operation is replicated to the replica and that manual snapshots may not meet the required RPO.

How to eliminate wrong answers

Option B is wrong because automated backups are stored as system snapshots and transaction logs within RDS, not as raw files accessible directly from S3; you cannot restore an RDS automated backup to an EC2 instance running PostgreSQL. Option C is wrong because restoring from the most recent manual snapshot may not capture a point in time close enough to the drop event, potentially exceeding the 5-minute RPO and requiring more data loss. Option D is wrong because creating a read replica from the production database after the table has been dropped will replicate the drop, so the replica will also be missing the table; stopping replication does not recover the dropped data.

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242

MCQhard

A company has an Amazon RDS for SQL Server DB instance with Multi-AZ deployment. During a recent failover test, the application experienced a longer downtime than expected. The application uses a single connection string. What change should be made to reduce failover downtime?

A.Implement connection pooling in the application.

B.Use a custom DNS CNAME record pointing to the RDS endpoint.

C.Set the DNS TTL to a higher value.

D.Configure the application to use the RDS instance ID instead of endpoint.

AnswerB

CNAME allows DNS update after failover, reducing downtime.

Why this answer

Using a custom DNS CNAME record that points to the RDS endpoint allows the application to control the DNS Time-To-Live (TTL) value independently. By setting a low TTL (e.g., 5 seconds) on the CNAME, the application's DNS resolver will refresh the IP address more quickly after a failover, reducing the time the application spends trying to connect to the old, unreachable primary instance. This minimizes downtime because the application can resolve the new primary's IP address sooner, rather than relying on the default RDS endpoint's TTL, which is typically set to 60 seconds and cannot be modified.

Exam trap

The trap here is that candidates often think connection pooling (Option A) reduces failover downtime, but it actually addresses connection overhead, not DNS resolution delays, which is the primary cause of extended downtime during a Multi-AZ failover.

How to eliminate wrong answers

Option A is wrong because connection pooling reuses existing database connections to reduce overhead, but it does not affect how quickly the application detects a DNS change or reconnects after a failover; it may even keep stale connections alive longer. Option C is wrong because setting the DNS TTL to a higher value would increase the time the application caches the old IP address, thereby extending downtime after a failover, not reducing it. Option D is wrong because the RDS instance ID is not a DNS-resolvable endpoint; the application must use the RDS endpoint (or a custom CNAME) to connect, and the instance ID alone cannot be used in a connection string.

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243

MCQmedium

A company is migrating its on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a 24-hour maintenance window. The company needs to minimize downtime during the migration. Which AWS service should be used to perform the migration with minimal downtime?

A.AWS Database Migration Service

B.Oracle Data Guard

C.AWS Schema Conversion Tool (AWS SCT)

D.AWS Data Pipeline

AnswerA

This is the same as Option D and refers to AWS Database Migration Service, which is designed for minimal downtime migrations.

Why this answer

AWS Database Migration Service (AWS DMS) can migrate the on-premises Oracle database to Amazon RDS for Oracle with minimal downtime by using ongoing replication. Option B (Oracle Data Guard) is not supported for cross-environment replication to Amazon RDS. Option C (AWS Schema Conversion Tool) is used for schema conversion, not data migration.

Option D (AWS Data Pipeline) is a data orchestration service unrelated to database migration.

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244

MCQmedium

A data engineer is troubleshooting a slow-running query on an Amazon Redshift cluster. The query involves large table joins and aggregations. Which diagnostic step should be taken FIRST to understand the query execution plan and identify bottlenecks?

A.Monitor the WLM queue metrics for the query.

B.Check the SVV_TABLE_INFO view for table distribution and sort keys.

C.Run the EXPLAIN command on the query to review the execution plan.

D.Query the STL_QUERY system table to review the query text.

AnswerC

EXPLAIN reveals how Redshift will execute the query.

Why this answer

The EXPLAIN command is the first and most direct step to understand how Redshift plans to execute a query, including join types, data distribution, and aggregation strategies. It reveals the execution plan without running the query, allowing the engineer to identify bottlenecks like nested loop joins or missing sort key optimization before any other diagnostic step.

Exam trap

The trap here is that candidates often jump to checking table design (Option B) or historical logs (Option D) first, but the EXPLAIN command is the fastest way to see the actual query execution plan and pinpoint join or aggregation bottlenecks.

How to eliminate wrong answers

Option A is wrong because WLM queue metrics show resource contention and queue wait times, not the internal execution plan or join strategies. Option B is wrong because SVV_TABLE_INFO provides table design metadata (distribution keys, sort keys, compression) but does not show how a specific query will be executed. Option D is wrong because STL_QUERY stores query text and historical execution details, but it does not show the execution plan; the EXPLAIN command is needed for that.

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245

MCQeasy

A company uses Amazon DynamoDB with provisioned capacity. The application team reports occasional ProvisionedThroughputExceededException errors. The database administrator notices that the errors occur during periods of high traffic. What is the most cost-effective way to handle these errors without over-provisioning capacity?

A.Increase the provisioned read and write capacity to the peak traffic level.

B.Use DynamoDB Accelerator (DAX) to cache frequently accessed items.

C.Implement exponential backoff and retry logic in the application.

D.Switch to on-demand capacity mode.

AnswerC

Exponential backoff retries handle throttling errors efficiently without over-provisioning.

Why this answer

Implementing exponential backoff and retry logic allows the application to handle throttling errors gracefully by retrying requests after a delay, which is the most cost-effective solution as it avoids over-provisioning capacity. Option A is incorrect because increasing capacity to peak levels is costly and inefficient. Option B is incorrect because DAX is a caching layer that reduces read load but does not help with write throttling or prevent ProvisionedThroughputExceededException errors for writes.

Option D is incorrect because switching to on-demand capacity mode can be more expensive for predictable traffic patterns, and the question asks for the most cost-effective approach without over-provisioning.

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246

MCQhard

A company is using Amazon Aurora MySQL-Compatible Edition. The database administrator notices that the Aurora cluster has a high number of binary log (binlog) files in the cluster volume, consuming significant storage. The binlog retention period is set to 24 hours. What is the most efficient way to reduce the storage consumed by binlog files without compromising point-in-time recovery (PITR)?

A.Manually delete binlog files from the DB instance using the 'PURGE BINARY LOGS' command.

B.Use the 'Binary Log Export' feature to export binlogs to Amazon S3 and delete them from the cluster.

C.Disable binary logging on the Aurora cluster by setting the binlog_format parameter to OFF.

D.Reduce the binlog retention period to 1 hour.

AnswerC

Aurora does not require binlogs for PITR; disabling them saves storage and improves performance.

Why this answer

Aurora MySQL does not rely on binlogs for point-in-time recovery (PITR); it uses its own storage-based recovery. Disabling binary logging eliminates binlog generation entirely, saving storage and reducing I/O overhead. Option A is incorrect because manually deleting binlog files is not recommended by AWS and does not address the root cause.

Option B is incorrect because exporting binlogs to Amazon S3 does not reduce the storage consumed within the cluster volume. Option D is incorrect because reducing the retention period only limits how long binlogs are kept, but binlogs still accumulate and consume storage until they expire.

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247

MCQeasy

A database administrator needs to monitor Amazon RDS for PostgreSQL connections and terminate idle connections that have been open for more than 1 hour. Which combination of steps should be taken?

A.Use Amazon RDS Performance Insights to view active connections and manually terminate idle connections via the AWS Management Console.

B.Configure an RDS event subscription for 'connection' events and send to Amazon SNS. Use SNS to notify an EC2 instance that runs a script to terminate idle connections.

C.Enable audit logging and stream to Amazon CloudWatch Logs. Create a metric filter for connection events. Use CloudWatch Alarm to trigger a Lambda function that runs a SQL query to terminate idle connections.

D.Enable RDS Enhanced Monitoring and configure a CloudWatch alarm to invoke an AWS Lambda function that terminates idle connections.

AnswerC

Audit logs capture connection events; metric filter and Lambda automate termination.

Why this answer

The correct approach is Option C. Enable audit logging (e.g., using the pgaudit extension) and stream logs to CloudWatch Logs. Create a metric filter to identify connections idle for over 1 hour based on log patterns.

Set a CloudWatch Alarm to invoke an AWS Lambda function, which executes a SQL query like pg_terminate_backend(pid) to terminate idle connections. Option A: Performance Insights provides metrics but no automated termination. Option B: RDS event subscriptions do not include idle connection details.

Option D: Enhanced Monitoring provides OS-level metrics, not connection idle time.

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248

Multi-Selecthard

Refer to the exhibit. A database engineer is assigned this IAM policy. Which of the following actions can the engineer perform? (Choose two.)

Select 2 answers

A.Describe all automated snapshots

B.Delete a manual snapshot named dev-snapshot

C.Delete a manual snapshot named prod-database-snapshot

D.Delete a manual snapshot named prod-backup

E.Create a manual snapshot named test-snapshot

AnswersA, E

The Allow statement permits DescribeDBSnapshots for all resources.

Why this answer

The IAM policy includes an Allow statement for 'rds:DescribeDBSnapshots' on all resources, so the engineer can describe any snapshot, including automated snapshots (Option A). It also includes an Allow statement for 'rds:CreateDBSnapshot' on all resources, allowing creation of a manual snapshot with any name, such as 'test-snapshot' (Option E). There is no Allow statement for 'rds:DeleteDBSnapshot', and a Deny statement explicitly blocks deletion of snapshots with names starting with 'prod-'.

Therefore, deleting any manual snapshot (Options B, C, D) is not permitted. The correct answers are A and E.

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249

MCQhard

An e-commerce company runs a multi-AZ deployment of Amazon RDS for MySQL. During a recent failover test, the application experienced a 30-second write outage. The application uses a connection pooling library. The DB instance has a 60-second TTL for DNS records. What is the MOST likely cause of the outage?

A.The connection pool had open connections to the old primary, and DNS TTL caused a delay in reconnecting to the new primary.

B.The application experienced a cold start after the failover.

C.The DNS record for the RDS endpoint was not updated after the failover.

D.The Multi-AZ failover took longer than 30 seconds to complete.

AnswerA

Stale connections and DNS caching can cause a brief outage until connections are refreshed.

Why this answer

During a Multi-AZ failover, the RDS DNS record is automatically updated to point to the new primary. However, the application's connection pool may still have open connections to the old primary IP. Because the DNS TTL is 60 seconds, the client may continue to resolve to the old (cached) IP for up to 60 seconds, causing a write outage until connections are re-established to the new primary.

Option B is incorrect because a cold start typically refers to an application starting from scratch, which is not the case here. Option C is incorrect because the DNS record is indeed updated after failover; the issue is client-side caching. Option D is incorrect because Multi-AZ failover usually completes within 1-2 minutes, but the outage duration is determined by DNS TTL and connection pooling behavior, not the failover time itself.

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250

MCQhard

A company uses Amazon DynamoDB with On-Demand capacity for a gaming application. During a new game launch, write traffic spikes 10x normal for 30 minutes. Some write requests receive ProvisionedThroughputExceeded exceptions. What is the MOST likely cause and solution?

A.The partition key is not distributing writes evenly, causing a hot partition. Redesign the partition key for uniform access.

B.On-Demand capacity cannot handle sudden spikes. Switch to Provisioned capacity with auto scaling.

C.DynamoDB Streams is enabled, causing additional write throttling. Disable streams.

D.The table has a global secondary index with a different partition key that is unevenly accessed. Remove the GSI.

AnswerA

Hot partitions cause throttling even with On-Demand capacity.

Why this answer

On-Demand capacity can handle spikes but has per-partition throughput limits. If a hot partition exists, writes to that partition may exceed its limit. Option A is correct because uneven partition keys cause throttling.

Option B is incorrect because On-Demand does not have table-level limits. Option C is not the primary cause. Option D is incorrect as GSI writes also consume write capacity.

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251

MCQmedium

A company is running an Amazon RDS for MySQL Multi-AZ DB instance. The application experiences a brief write disruption during automatic failover. The database workload has low write latency requirements. Which configuration change would minimize application impact during failover?

A.Create a read replica in a different Availability Zone and promote it during failover.

B.Change the DB instance to use a Multi-AZ DB cluster configuration.

C.Use a single-AZ deployment and rely on automated backups for recovery.

D.Increase the DB instance class to reduce failover time.

AnswerB

Multi-AZ DB cluster provides faster failover than standard Multi-AZ.

Why this answer

Changing to a Multi-AZ DB cluster (option B) reduces application impact during failover because it uses a writer and two reader instances in separate Availability Zones. Failover to a reader is typically faster than the standard Multi-AZ standby failover, minimizing write disruption. Option A (promoting a read replica) is not automatic and introduces significant delay.

Option C (single-AZ with backups) does not address failover impact. Option D (increasing instance class) does not significantly reduce failover time.

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252

MCQeasy

A company wants to automate backups for an Amazon RDS for PostgreSQL DB instance. The backup retention period should be 35 days. Which step is required?

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

B.Use AWS Backup to schedule backups.

C.Create a manual snapshot every day and delete after 35 days.

D.Set up a cross-region snapshot copy.

AnswerA

RDS automated backups can be configured with a retention period up to 35 days.

Why this answer

Amazon RDS for PostgreSQL supports automated backups with a configurable retention period of up to 35 days. By enabling automated backups and setting the retention period to 35 days, the company meets the requirement without additional tooling or manual effort. Automated backups include transaction logs for point-in-time recovery, which is not available with manual snapshots alone.

Exam trap

The trap here is that candidates may overcomplicate the solution by choosing AWS Backup or manual snapshots, when the simplest and most direct method is to enable automated backups with the desired retention period, which is a native RDS feature.

How to eliminate wrong answers

Option B is wrong because AWS Backup can be used to schedule backups, but it is not required; RDS native automated backups already support a 35-day retention period natively, and AWS Backup adds no benefit for this specific requirement. Option C is wrong because creating a manual snapshot every day and deleting after 35 days is operationally complex and does not provide automated point-in-time recovery, which is a key feature of automated backups. Option D is wrong because cross-region snapshot copy is a separate feature for disaster recovery, not a step required to set the backup retention period to 35 days.

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253

MCQhard

A company uses Amazon ElastiCache for Redis as a caching layer for a database. The cache cluster has one primary and one replica node. During a maintenance event, the primary node fails and the replica is promoted. After promotion, the application experiences increased latency. What should a database specialist do to reduce the impact of future failovers?

A.Disable replica reads to avoid stale data.

B.Enable automatic backups with a retention period of 35 days.

C.Enable cluster mode and distribute the cache across multiple shards.

D.Add more replica nodes to the cluster.

AnswerC

Cluster mode spreads data across shards, reducing the impact of a single node failure.

Why this answer

Enabling cluster mode on the ElastiCache for Redis cluster distributes data across multiple shards, each with its own primary and replica nodes. During a failover, only the data in the failed shard's primary needs to be rebuilt, limiting the cache miss impact. Adding more replicas (Option D) does not reduce the latency impact because a single primary still serves all requests after failover, and the new primary must warm its cache from scratch.

Disabling replica reads (Option A) would not address the latency increase. Automatic backups (Option B) do not affect runtime performance after failover.

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254

MCQeasy

An application is experiencing increased latency when writing to an Amazon DynamoDB table. The table uses on-demand capacity mode. The CloudWatch metric 'WriteThrottleEvents' is zero. What is the most likely cause of the increased latency?

A.The write capacity units (WCUs) are set too low.

B.DynamoDB Accelerator (DAX) is not configured for writes.

C.A hot partition is causing excessive write traffic to a single partition.

D.The table is experiencing write throttling due to exceeding the provisioned write capacity.

AnswerC

Hot partitions can cause increased latency even when overall throughput is within limits, as a single partition's capacity is constrained.

Why this answer

On-demand DynamoDB tables can experience throttling if you exceed the previous peak traffic by more than double in a short time, but since WriteThrottleEvents is zero, the latency is likely due to a hot partition causing uneven traffic distribution. Option A is incorrect because on-demand capacity does not use WCUs; throughput is automatically scaled. Option B is incorrect because DynamoDB Accelerator (DAX) is a read cache and does not affect write latency.

Option D is incorrect because on-demand tables do not have provisioned capacity; throttling would be indicated by WriteThrottleEvents, which is zero.

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255

MCQmedium

A company is using Amazon Neptune to run graph queries. The cluster has one writer and two reader instances. After a major version upgrade, the query performance degrades for complex traversal queries. The database specialist suspects that the query optimizer is not using indexes effectively. Which action should the specialist take to identify the issue?

A.Drop and recreate all indexes to ensure they are up to date.

B.Enable the Neptune explain plan feature and review the output.

C.Add more reader instances to distribute the query load.

D.Check the CloudWatch metrics for CPU utilization and query latency.

AnswerB

Explain plan shows query execution steps and index usage.

Why this answer

Enabling the Neptune explain plan feature provides detailed information about how queries are executed, including index usage. This helps identify if the query optimizer is failing to use indexes effectively after the upgrade. Option A is incorrect because dropping and recreating indexes is unnecessary and disruptive; indexes are automatically maintained.

Option C is incorrect because adding reader instances distributes read load but does not fix query optimization issues. Option D is incorrect because CloudWatch metrics show system-level performance, not query execution details.

Exam trap

The trap is that adding readers or checking metrics might seem helpful for performance, but the question specifically asks to identify index usage—only the explain plan provides that insight.

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256

MCQeasy

A database administrator notices that Amazon RDS for MySQL is experiencing high CPU utilization during peak hours. The application is read-heavy with many SELECT queries. Which action is most cost-effective to improve performance?

A.Create one or more read replicas and direct read traffic to them.

B.Increase the DB instance class to a larger size.

C.Increase the allocated storage to improve I/O throughput.

D.Scale up the DB instance vertically to a higher vCPU count.

AnswerA

Read replicas distribute read workload, reducing primary CPU.

Why this answer

The most cost-effective solution for a read-heavy, high-CPU workload on Amazon RDS for MySQL is to create one or more read replicas and direct read traffic to them. This offloads SELECT queries from the primary DB instance, reducing CPU utilization without incurring the high cost of upgrading the primary instance. Option B (increasing DB instance class) and Option D (vertical scaling to higher vCPU) are more expensive and not cost-effective.

Option C (increasing allocated storage) improves I/O throughput but does not directly reduce CPU utilization.

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257

MCQeasy

A database specialist needs to monitor the resource utilization of Amazon RDS DB instances. Which AWS service provides OS-level metrics such as memory, disk, and CPU usage?

A.Amazon RDS Performance Insights

B.Amazon RDS Enhanced Monitoring

C.Amazon CloudWatch

D.AWS CloudTrail

AnswerB

Enhanced Monitoring provides OS-level metrics.

Why this answer

Amazon RDS Enhanced Monitoring provides OS-level metrics (e.g., memory, disk, CPU usage) by running an agent on the RDS host and delivering logs to CloudWatch Logs. This is the only service that exposes hypervisor-level and guest OS metrics for RDS instances, enabling granular troubleshooting of resource contention.

Exam trap

The trap here is that candidates confuse CloudWatch’s basic RDS metrics (which are hypervisor-level) with the OS-level metrics provided only by Enhanced Monitoring, leading them to incorrectly select CloudWatch.

How to eliminate wrong answers

Option A is wrong because Amazon RDS Performance Insights focuses on database workload analysis (e.g., wait events, SQL queries) and does not provide OS-level metrics like memory or disk usage. Option C is wrong because Amazon CloudWatch provides basic RDS metrics (e.g., CPUUtilization, FreeableMemory) at the hypervisor level, but not the detailed OS-level metrics (e.g., file system disk usage, process list) that Enhanced Monitoring offers. Option D is wrong because AWS CloudTrail records API activity for governance and auditing, not real-time OS-level resource utilization.

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258

Drag & Dropmedium

Arrange the steps to switch over from a primary Amazon RDS for Oracle DB instance to a standby in a Multi-AZ deployment (planned failover) 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

Planned failover involves verifying standby health, initiating failover, and confirming connectivity.

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259

MCQeasy

A startup is running an Amazon RDS for PostgreSQL database for its web application. The database size is 50 GB. The company wants to implement a backup strategy that allows point-in-time recovery (PITR) to any point within the last 35 days with minimal storage cost. Which backup strategy should be used?

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

B.Use AWS Backup to schedule daily snapshots with 35-day retention.

C.Enable automated backups with 7-day retention and copy snapshots to another region.

D.Take manual snapshots daily and retain 35 snapshots.

AnswerA

Automated backups support PITR up to 35 days.

Why this answer

Automated backups in Amazon RDS provide point-in-time recovery (PITR) within the retention period, and the maximum retention period is 35 days. Enabling automated backups with a 35-day retention period meets the requirement for PITR to any point within the last 35 days with minimal storage cost, as the backup storage is charged only for the incremental changes. Option B (AWS Backup) introduces additional cost and complexity without adding value for this scenario.

Option C (7-day retention with cross-region copy) does not achieve 35-day PITR and incurs cross-region transfer costs. Option D (daily manual snapshots) does not provide PITR and results in higher storage costs due to full snapshots.

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260

Multi-Selecthard

A company uses Amazon DynamoDB with provisioned capacity for a critical application. During a traffic spike, the table experiences throttling on write requests. The DBA needs to resolve the issue quickly. Which THREE actions should the DBA take? (Choose THREE.)

Select 3 answers

A.Switch the table to on-demand capacity mode.

B.Implement exponential backoff in the application's write requests.

C.Temporarily increase the write capacity units (WCU) using the AWS Console or CLI.

D.Enable auto scaling for the table to automatically adjust capacity.

E.Enable DynamoDB Accelerator (DAX) to cache writes.

AnswersB, C, D

Exponential backoff reduces retry collisions.

Why this answer

Uses exponential backoff to handle throttling by retrying requests with increasing delays. Option C temporarily increases write capacity units (WCU) to handle the spike. Option D enables auto scaling to automatically adjust capacity.

Option A is incorrect because switching to on-demand may resolve throttling but is not one of the three correct actions; the question asks for three specific actions, and B, C, D are the correct combination. Option E is wrong because DAX is a caching layer for reads, not writes, and does not resolve write throttling.

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261

MCQhard

A company is using Amazon DynamoDB with auto scaling enabled. The table's read capacity is set to a minimum of 100 and maximum of 1000 read capacity units (RCUs). The actual consumed read capacity is consistently at 200 RCUs. What should the database specialist do to optimize costs without impacting performance?

A.Lower the minimum read capacity to 200 RCUs.

B.Decrease the maximum read capacity to 500 RCUs.

C.Disable auto scaling and set the read capacity to 200 RCUs.

D.Increase the minimum read capacity to 500 RCUs.

AnswerA

Correct: Setting the minimum to 200 RCUs matches the actual consumption, avoiding paying for unused capacity while allowing auto scaling to handle spikes.

Why this answer

Lowering the minimum to 200 RCUs ensures auto scaling does not scale below the actual usage, reducing provisioned capacity costs. Option B is wrong because decreasing the maximum could cause throttling during spikes. Option C is wrong because disabling auto scaling would require manual management and may lead to over-provisioning or under-provisioning.

Option D is wrong because increasing the minimum would increase costs unnecessarily.

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262

MCQeasy

A company is using Amazon DynamoDB with auto scaling enabled. The table's write capacity is set to a minimum of 50 and maximum of 500 write capacity units (WCUs). The actual consumed write capacity is consistently at 100 WCUs. What should the database specialist do to optimize costs without impacting performance?

A.Increase the minimum write capacity to 200 WCUs.

B.Disable auto scaling and set the write capacity to 100 WCUs.

C.Lower the minimum write capacity to 100 WCUs.

D.Decrease the maximum write capacity to 200 WCUs.

AnswerC

Matches actual consumption.

Why this answer

Lower the minimum write capacity to 100 WCUs. With auto scaling enabled and actual consumed write capacity consistently at 100 WCUs, the minimum should match the actual usage to avoid over-provisioning. Setting it to 100 WCUs ensures that baseline capacity is just enough for normal operations, while auto scaling can still scale up to 500 WCUs during traffic spikes.

Option A (increasing minimum to 200 WCUs) would raise costs without benefit. Option B (disabling auto scaling and fixing at 100 WCUs) removes the ability to scale up, risking throttling during spikes. Option D (decreasing maximum to 200 WCUs) limits scalability and could cause throttling if traffic exceeds 200 WCUs.

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263

MCQmedium

A company has an Amazon Redshift cluster that is running slowly on complex queries. The cluster has 10 dc2.large nodes. The 'QueryDuration' metric shows high values for several queries. The team wants to improve performance without changing queries. Which action is MOST likely to help?

A.Add more nodes of the same type to the cluster.

B.Enable compression on all columns.

C.Enable Redshift Spectrum to offload queries to Amazon S3.

D.Increase the workload management (WLM) concurrency level.

AnswerA

Adding more nodes increases the cluster's compute capacity, allowing complex queries to process more data in parallel without any changes to the queries themselves.

Why this answer

Adding more nodes (scaling out) increases the cluster's compute capacity, allowing complex queries to process data in parallel without any query changes. Option C is incorrect because Redshift Spectrum requires data to be in S3 and external tables to be defined, which would require modifying queries to reference those tables. Option B reduces storage I/O but not CPU-bound complex queries.

Option D increasing concurrency can cause resource contention, slowing queries.

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264

Multi-Selecthard

A company runs a production Amazon RDS for PostgreSQL instance with Multi-AZ deployment. The DB instance has a large number of connections from application servers. The operations team wants to monitor the number of database connections and receive an alert when it exceeds 80% of the maximum connections. Which combination of steps should be taken to set up this monitoring? (Choose two.)

Select 2 answers

A.Set the alarm threshold to 80 and the evaluation period to 5 minutes

B.Enable Enhanced Monitoring and create a CloudWatch alarm on the 'database_connections' metric

C.Set the alarm threshold to (0.8 * max_connections) and the evaluation period to 1 minute

D.Create a CloudWatch alarm on the 'DatabaseConnections' metric for the RDS instance

E.Enable Performance Insights and create a CloudWatch alarm using the 'DBLoad' metric

AnswersC, D

This ensures the alarm triggers when connections exceed 80% of the maximum.

Why this answer

Correct answers are C and D. C: Set the alarm threshold to (0.8 * max_connections) and the evaluation period to 1 minute ensures the alarm triggers when connections reach 80% of the maximum. D: Create a CloudWatch alarm on the 'DatabaseConnections' metric for the RDS instance to monitor the actual number of connections.

A is wrong because the threshold should be based on max_connections, not a fixed value of 80. B is wrong because Enhanced Monitoring provides OS-level metrics, not database connection counts. E is wrong because Performance Insights provides DBLoad, not connection counts.

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265

MCQeasy

A company has an Amazon DynamoDB table that stores IoT sensor data. The table has a partition key of device_id and a sort key of timestamp. The team wants to efficiently retrieve the latest reading for each device. Which query pattern should be used?

A.Scan with FilterExpression to get the latest timestamp for each device

B.Query with ScanIndexForward=true and Limit=1

C.GetItem with the device_id and timestamp values

D.Query with ScanIndexForward=false and Limit=1

AnswerD

This retrieves the most recent item for a given partition key by ordering the sort key in descending order and limiting to one result.

Why this answer

Setting ScanIndexForward=false on a Query returns items in descending sort-key order. By querying with the device_id as the partition key and limiting results to 1, you retrieve the most recent timestamp for that device efficiently without scanning the entire table.

Exam trap

The trap here is confusing ScanIndexForward=true with false, leading candidates to pick Option B, which retrieves the oldest rather than the latest record.

How to eliminate wrong answers

Option A is wrong because a Scan reads every item in the table, which is expensive and slow for large datasets; FilterExpression is applied after the scan, so it does not reduce the read cost. Option B is wrong because ScanIndexForward=true returns items in ascending order, so Limit=1 would give the oldest timestamp, not the latest. Option C is wrong because GetItem requires both the partition key and sort key to retrieve a specific item, but the team does not know the exact timestamp of the latest reading in advance.

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266

MCQmedium

A company is experiencing increased latency on their Amazon RDS for PostgreSQL instance. The application team reports that queries are taking longer than usual. The database metrics show high CPU utilization and a spike in write operations. Which initial step should the database specialist take to diagnose the issue?

A.Enable Performance Insights on the DB instance to analyze the workload.

B.Create a read replica to offload read traffic from the primary instance.

C.Modify the DB instance to a larger instance class to handle the load.

D.Enable enhanced monitoring to get OS-level metrics of the DB instance.

AnswerA

Performance Insights provides a comprehensive view of database performance and helps pinpoint the bottleneck.

Why this answer

Enabling Performance Insights provides a detailed performance analysis and helps identify the root cause of the latency. It is the recommended first step for diagnosing database performance issues.

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267

MCQmedium

A database administrator is creating an IAM policy to allow a DevOps engineer to manage production RDS instances. The policy above is attached to the engineer's IAM role. The engineer reports that they cannot create a new DB instance with the identifier 'prod-analytics'. What is the most likely reason?

A.The policy does not allow the 'rds:CreateDBInstance' action on the required resource because the resource ARN pattern is incorrect.

B.The policy does not include the 'rds:CreateDBSecurityGroup' action.

C.The engineer does not have permissions to pass an IAM role to the DB instance if one is specified.

D.The policy does not include the 'rds:CreateDBInstance' action for all regions.

AnswerC

When creating a DB instance with an IAM role, the 'iam:PassRole' permission is required. This is a common missing permission.

Why this answer

The most likely reason is that when creating the DB instance, the engineer specified an IAM role to be associated with the instance (e.g., for backup or monitoring). The attached policy does not include an 'iam:PassRole' action, which is required to pass the role to RDS. Without it, the CreateDBInstance call fails due to insufficient permissions to pass the specified role.

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268

Multi-Selecteasy

A company is using Amazon DynamoDB with provisioned capacity. The table's read capacity is consistently underutilized, but the write capacity is frequently maxed out. The team wants to optimize costs while maintaining performance. Which TWO actions should be taken?

Select 2 answers

A.Switch the table to on-demand capacity mode.

B.Enable DynamoDB Accelerator (DAX) to offload reads.

C.Use DynamoDB Auto Scaling for write capacity.

D.Increase the provisioned write capacity to handle spikes.

E.Reduce the provisioned read capacity to match actual usage.

AnswersC, E

Auto Scaling adjusts write capacity to match demand, reducing throttling and cost.

Why this answer

The correct answers are C and E. DynamoDB Auto Scaling for write capacity (C) dynamically adjusts the provisioned write capacity based on traffic, preventing throttling during spikes without over-provisioning. Reducing provisioned read capacity (E) to match actual usage saves costs because reads are underutilized.

Option A (on-demand) can be more expensive for predictable workloads, and Auto Scaling is often more cost-effective. Option B (DAX) offloads reads, not writes, so it does not address the write bottleneck. Option D (increasing provisioned writes) would raise costs without dynamic scaling, as capacity would remain high even when not needed.

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269

MCQeasy

A company wants to automate the creation of a new Amazon RDS for SQL Server instance with specific configurations, including VPC, subnet, and security group settings. Which AWS service should be used to deploy this infrastructure as code?

A.AWS CodeDeploy

B.AWS Elastic Beanstalk

C.AWS CloudFormation

D.AWS OpsWorks

AnswerC

CloudFormation templates can define RDS instances along with VPC, subnets, and security groups.

Why this answer

AWS CloudFormation is the correct service because it allows you to define your entire infrastructure, including Amazon RDS for SQL Server instances, VPCs, subnets, and security groups, as code using a JSON or YAML template. This enables automated, repeatable deployments and version control of your infrastructure, which is the core requirement for infrastructure as code (IaC).

Exam trap

The trap here is that candidates often confuse AWS CloudFormation with AWS Elastic Beanstalk, thinking Elastic Beanstalk can also deploy infrastructure as code, but Elastic Beanstalk is a higher-level service that manages the environment automatically and does not give you fine-grained control over VPC and subnet configurations via code.

How to eliminate wrong answers

Option A is wrong because AWS CodeDeploy is a service for automating code deployments to running instances (e.g., EC2, Lambda), not for provisioning infrastructure like RDS or VPCs. Option B is wrong because AWS Elastic Beanstalk is a PaaS service that abstracts underlying infrastructure management and does not provide direct control over specific VPC, subnet, and security group configurations as code. Option D is wrong because AWS OpsWorks is a configuration management service based on Chef and Puppet, designed for managing application configurations and server states, not for declaratively provisioning infrastructure resources like RDS instances or network components.

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270

MCQhard

A company is using Amazon ElastiCache for Redis as a caching layer for a high-traffic web application. The cache hit ratio has dropped from 95% to 70% after a recent deployment that changed the cache key structure. The application team wants to improve the hit ratio without increasing the cache memory. Which action should they take?

A.Disable Cluster Mode and use a single node.

B.Implement a consistent hashing algorithm for key distribution.

C.Increase the TTL (time-to-live) for all cache keys.

D.Use random TTLs to spread out expiration times.

AnswerB

Consistent hashing minimizes key redistribution when nodes change and ensures even distribution, reducing evictions and improving hit ratio.

Why this answer

A drop in cache hit ratio after changing the key structure indicates that the new keys are not being distributed evenly across the cluster nodes, causing some nodes to be overloaded with misses. Implementing a consistent hashing algorithm (e.g., using the Redis Cluster hash slot mechanism or a client-side library like libketama) ensures that keys are distributed uniformly across shards, minimizing cache misses and improving the hit ratio without adding memory.

Exam trap

The trap here is that candidates often confuse TTL management (options C and D) with key distribution issues, mistakenly believing that extending or randomizing expiration times will fix a hit ratio drop caused by poor key placement across cluster nodes.

How to eliminate wrong answers

Option A is wrong because disabling Cluster Mode and using a single node would remove the ability to scale horizontally and could lead to memory exhaustion, but it does not address the root cause of poor key distribution; in fact, a single node would still have the same key structure issue. Option C is wrong because increasing the TTL for all cache keys would only keep stale data longer, not improve the hit ratio caused by key distribution problems; it could also increase memory pressure by holding onto unused keys. Option D is wrong because using random TTLs to spread out expiration times helps avoid thundering herd problems but does not fix the uneven key distribution that leads to a low hit ratio; random TTLs do not affect how keys are mapped to nodes.

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271

MCQeasy

A company is using Amazon RDS for SQL Server with Multi-AZ and automated backups enabled. The database administrator needs to restore the database to a specific point in time that is within the retention period. What is the correct procedure?

A.Use the RDS console to perform a point-in-time recovery to the desired time

B.Restore from a manual snapshot taken at the desired time

C.Use the native SQL Server backup and restore functionality

D.Restore from the latest automated snapshot

AnswerA

Correct. Point-in-time recovery via the RDS console or API allows restoring to any time within the backup retention period.

Why this answer

The correct procedure for performing a point-in-time recovery within the retention period for an Amazon RDS for SQL Server instance with Multi-AZ and automated backups is to use the RDS console or API to specify the desired point in time. This restores the database to the specified time using the automated backup logs. Option B is incorrect because manual snapshots capture a specific point and cannot be used for arbitrary point-in-time recovery.

Option C is incorrect because native SQL Server backup is not supported for RDS instances; AWS manages backups. Option D is incorrect because restoring from the latest automated snapshot does not give a specific point in time.

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272

MCQhard

A company has a production Amazon DynamoDB table with on-demand capacity. The table experiences occasional throttling due to hot partitions. The operations team wants to implement a solution to identify the specific partition keys causing the throttling. What is the MOST efficient approach?

A.Enable AWS X-Ray tracing on the application and analyze traces.

B.Enable VPC Flow Logs and use CloudWatch Logs Insights to query the logs.

C.Enable Amazon CloudWatch Contributor Insights for DynamoDB.

D.Enable DynamoDB Streams and process the stream records to identify hot keys.

AnswerC

Contributor Insights analyzes access patterns and identifies top partition keys.

Why this answer

Amazon CloudWatch Contributor Insights for DynamoDB is the most efficient solution because it automatically analyzes DynamoDB request metadata to identify the most frequently accessed partition keys, including those causing throttling. It provides near real-time top-N contributor reports without requiring application changes, custom logging, or additional stream processing, making it purpose-built for diagnosing hot partition issues.

Exam trap

The trap here is that candidates often confuse DynamoDB Streams (which capture change data) with a tool for monitoring read traffic or access patterns, leading them to choose Option D despite Streams being designed for event-driven processing, not diagnostic analysis of hot partitions.

How to eliminate wrong answers

Option A is wrong because AWS X-Ray traces application-level requests but does not directly identify DynamoDB partition keys causing throttling; it focuses on end-to-end latency and service maps, not per-key access patterns. Option B is wrong because VPC Flow Logs capture network traffic metadata (IP addresses, ports, protocols) and cannot reveal DynamoDB partition keys or item-level access patterns, as DynamoDB uses HTTPS and the partition key is embedded in the request payload, not in network headers. Option D is wrong because DynamoDB Streams capture item-level changes (inserts, updates, deletes) but do not provide read request data or access frequency per partition key; processing streams to infer hot keys would require complex custom logic and still miss read-heavy hot partitions.

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273

MCQeasy

A database specialist needs to capture SQL queries executed against an Amazon Aurora MySQL DB cluster for performance analysis. The capture should have minimal performance impact and be stored in Amazon CloudWatch Logs. Which feature should the specialist use?

A.Enable Performance Insights and configure the Performance Insights log export to CloudWatch Logs.

B.Enable the slow query log and export to CloudWatch Logs.

C.Enable database audit logs and export to CloudWatch Logs.

D.Enable the general log and publish to CloudWatch Logs.

AnswerA

Performance Insights captures SQL queries with minimal impact.

Why this answer

Performance Insights captures SQL queries with minimal overhead by sampling the database engine's internal wait states and query activity, then exports this data to CloudWatch Logs for analysis. This approach is designed for performance monitoring without the significant performance impact of enabling full logging (like the general log), making it ideal for capturing queries for performance analysis.

Exam trap

The trap here is that candidates often confuse the purpose of the general log (capturing all queries) with performance analysis, overlooking that Performance Insights provides a low-overhead alternative specifically designed for this task.

How to eliminate wrong answers

Option B is wrong because the slow query log only captures queries that exceed a specified execution time threshold, not all SQL queries, and enabling it can still add overhead. Option C is wrong because database audit logs are designed for compliance and security auditing (e.g., tracking login attempts, schema changes), not for capturing all SQL queries for performance analysis, and they can generate high volume. Option D is wrong because the general log captures all SQL queries but has a high performance impact on the database, especially under heavy load, and is not recommended for production use.

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274

MCQmedium

A company is running an Amazon RDS for MySQL DB instance. The database performance has degraded over time. The DBA suspects that the issue is due to a high number of connections that are in a 'sleep' state from a legacy application. What is the MOST effective solution to automatically terminate idle connections?

A.Modify the 'wait_timeout' parameter in the DB parameter group to a lower value.

B.Increase the 'max_connections' parameter to accommodate more idle connections.

C.Enable Amazon RDS Proxy to manage connection pooling and automatically close idle connections.

D.Use a script to run 'SHOW PROCESSLIST' and manually kill idle connections.

AnswerA

This parameter controls how long the server waits for activity on a non-interactive connection before closing it.

Why this answer

The 'wait_timeout' parameter in MySQL automatically closes idle connections after the specified number of seconds. Reducing this value from the default (28800 seconds) will terminate sleeping connections sooner and free up resources. Option B is incorrect because increasing 'max_connections' does not terminate idle connections; it only allows more connections, which could worsen the problem.

Option C is incorrect because Amazon RDS Proxy manages connection pooling and reduces connection overhead but does not automatically terminate idle connections; it reuses connections but does not kill them. Option D is incorrect because running 'SHOW PROCESSLIST' and manually killing connections is not automated and requires human intervention, so it is not the most effective solution.

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275

MCQhard

A company uses Amazon Aurora MySQL-Compatible Edition. The database specialist notices that the DB cluster's failover time is longer than expected. The primary instance is using a db.r5.large instance class. Which change would most likely reduce the failover time?

A.Enable Backtrack on the DB cluster.

B.Use a larger instance class for the Aurora Replicas.

C.Increase the number of Aurora Replicas.

D.Enable Multi-AZ deployment for the DB cluster.

AnswerB

Larger replicas can process transactions faster during promotion, reducing failover time.

Why this answer

Using a larger instance class for Aurora replicas ensures they can handle the workload after failover, potentially reducing failover time. However, the key factor is that Aurora failover is typically fast, but if replicas are undersized, the time to promote and become fully operational increases. Using a larger instance class for the replicas (or all instances) can help.

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276

MCQhard

A company runs an e-commerce platform using Amazon DynamoDB as the database. The table has a provisioned capacity of 5000 WCU and 3000 RCU. During a flash sale, the write traffic spikes to 8000 WCU for 10 minutes, causing significant throttling. The operations team notices that the table's WriteCapacityUnits metric shows 5000, but the ConsumedWriteCapacityUnits metric peaks at 4500. The application is experiencing errors and slow response times. The team wants to handle such spikes automatically without manual intervention and without over-provisioning. Which solution should be implemented?

A.Enable DynamoDB Auto Scaling with a target utilization of 70% and a minimum capacity of 5000 WCU

B.Increase the provisioned WCU to 8000 permanently

C.Implement an Amazon SQS queue to buffer write requests and process them asynchronously

D.Switch the table to on-demand capacity mode

AnswerA

Auto Scaling dynamically adjusts capacity to handle spikes while minimizing cost.

Why this answer

DynamoDB Auto Scaling can adjust capacity based on demand, and setting a target utilization of 70% allows headroom for spikes. Option B is wrong because increasing provisioned WCU to 8000 permanently would be costly and result in over-provisioning during normal traffic. Option C is wrong because while SQS can buffer requests, it adds latency and does not solve the real-time throttling issue; it changes the architecture to async processing, which may not be acceptable for an e-commerce platform.

Option D is wrong because switching to on-demand capacity mode would handle the spikes automatically but can be significantly more expensive for a workload with a predictable baseline, and the team wants to avoid over-provisioning costs.

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277

MCQmedium

A company uses Amazon DynamoDB to store IoT sensor data. Each sensor writes a record every second. The table has a partition key of 'sensor_id' and a sort key of 'timestamp'. Over time, the team notices that write performance degrades for certain sensors that generate more data. The table uses provisioned capacity with auto scaling enabled. The application uses eventual consistency. The team needs to ensure consistent write performance without throttling. Which action should be taken?

A.Modify the partition key to include a random number or prefix to distribute writes evenly.

B.Increase the provisioned write capacity units (WCU) to a higher value.

C.Switch the table to on-demand capacity mode.

D.Create a global secondary index (GSI) with a different partition key to handle writes.

AnswerA

Write sharding evens out the load across partitions, preventing any single partition from being overloaded.

Why this answer

Adding a random number or prefix to the partition key distributes writes across multiple partitions, preventing hot partitions that cause throttling. Option B (increasing WCU) does not resolve the underlying hot partition issue, as each partition still has a maximum write capacity. Option C (on-demand mode) still has per-partition throughput limits and does not fix uneven write distribution.

Option D (creating a GSI) does not affect the base table's write distribution; GSIs are for read efficiency, not write distribution.

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278

Multi-Selectmedium

A company is designing a disaster recovery plan for an Amazon RDS for MySQL database. The database must have a Recovery Point Objective (RPO) of less than 5 minutes and a Recovery Time Objective (RTO) of less than 1 hour. Which TWO actions should be taken? (Choose two.)

Select 2 answers

A.Use a single-AZ instance with automated backups to S3.

B.Deploy the database in a Multi-AZ configuration.

C.Create a cross-region read replica with automated backups enabled.

D.Take daily manual snapshots and copy them to another region.

E.Use AWS DMS for continuous replication to a standby instance.

AnswersB, C

Multi-AZ configuration provides automatic synchronous replication to a standby instance in a different Availability Zone. Automatic failover occurs within minutes, achieving RTO < 1 hour and RPO near zero.

Why this answer

(Multi-AZ configuration) provides automatic synchronous replication to a standby instance in a different Availability Zone. In the event of a failure, automatic failover occurs within minutes, achieving an RTO of less than 1 hour and an RPO of effectively zero. Option C (cross-region read replica with automated backups enabled) replicates data asynchronously to another AWS region, allowing promotion to a standalone database for disaster recovery. With continuous replication, the RPO can be less than 5 minutes, and promotion time is typically under 1 hour, meeting both objectives.

Option A is incorrect because a single-AZ instance with automated backups requires restoring from a backup, which takes longer than 1 hour, failing the RTO requirement. Option D is incorrect because daily manual snapshots have an RPO of up to 24 hours, exceeding the 5-minute requirement. Option E is incorrect because AWS DMS is primarily a migration service and is not optimized for continuous replication for DR; it adds complexity and does not provide the same RTO/RPO guarantees as native RDS replication features.

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279

MCQeasy

An IAM policy is attached to a user who needs to restore an Amazon RDS DB instance from a DB snapshot. The user attempts to restore and receives an 'Access Denied' error. Which missing permission is MOST likely causing the failure?

A.rds:DescribeDBSnapshots

B.rds:DescribeDBInstances

C.rds:CreateDBInstance

D.rds:CreateDBSubnetGroup

AnswerC

Restoring from snapshot creates a new DB instance, requiring CreateDBInstance.

Why this answer

To restore an Amazon RDS DB instance from a DB snapshot, the user must have the `rds:CreateDBInstance` permission. This is because the restore operation internally calls the CreateDBInstance API to create a new DB instance from the specified snapshot. Without this permission, the request fails with an 'Access Denied' error, even if the user has permissions to describe snapshots or instances.

Exam trap

The trap here is that candidates often assume describing snapshots is sufficient for restoration, but AWS requires the write-level `CreateDBInstance` permission because restoring creates a new DB instance, not just reads existing data.

How to eliminate wrong answers

Option A is wrong because `rds:DescribeDBSnapshots` only allows listing or viewing snapshot metadata, not performing the restore action. Option B is wrong because `rds:DescribeDBInstances` only allows viewing existing DB instance details, which is unrelated to creating a new instance from a snapshot. Option D is wrong because `rds:CreateDBSubnetGroup` is needed only if a custom subnet group must be created; the restore can use an existing subnet group, and the missing permission is the core CreateDBInstance action.

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280

MCQhard

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a high transaction rate. The migration must have minimal downtime. Which migration strategy should a database specialist recommend?

A.Use AWS DMS with ongoing replication to capture changes.

B.Copy the data files to Amazon S3 and then load into RDS.

C.Use Oracle Data Pump to export and import the database.

D.Perform an RMAN backup and restore to RDS.

AnswerA

DMS with CDC allows near-zero downtime migration.

Why this answer

AWS DMS with ongoing replication allows for minimal downtime by continuously replicating changes from the source Oracle database to the target Amazon RDS for Oracle, allowing a cutover with only a brief pause. Option B is incorrect because copying data files to S3 and loading into RDS is not a supported migration path for RDS for Oracle and would require significant downtime. Option C is incorrect because Oracle Data Pump export and import requires the source database to be offline or in read-only mode during export, causing downtime.

Option D is incorrect because RMAN backup and restore is not natively supported for RDS for Oracle and would involve complex manual steps and downtime.

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281

MCQmedium

A database administrator notices that an Amazon Aurora MySQL DB cluster's primary instance is experiencing high CPU utilization due to a long-running analytical query. The application can tolerate eventual consistency. What is the MOST cost-effective solution to reduce CPU load on the primary instance?

A.Configure an Auto Scaling policy for Aurora Replicas and modify the application to use the reader endpoint.

B.Create a read replica in a different region and route read traffic there.

C.Increase the instance size of the primary instance.

D.Enable Aurora Parallel Query on the cluster.

AnswerA

Aurora Replicas share the same storage and can offload SELECT queries.

Why this answer

Offloading read queries to Aurora Replicas is cost-effective and reduces primary load without additional infrastructure.

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282

Multi-Selecthard

A company is running an Amazon RDS for MySQL Multi-AZ DB instance. The company wants to implement a backup strategy that meets a recovery point objective (RPO) of 5 minutes and a recovery time objective (RTO) of 1 hour. Which THREE steps should the company take to meet these objectives?

Select 3 answers

A.Configure AWS Backup to copy automated backups to another region.

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

C.Change the DB instance to a Single-AZ configuration to reduce costs.

D.Create a cross-region read replica to use for failover in another region.

E.Take daily manual snapshots and copy them to another region.

AnswersA, B, D

AWS Backup can copy backups cross-region for disaster recovery.

Why this answer

Automated backups with a 35-day retention period (B) enable point-in-time recovery within the last 35 days, supporting an RPO of 5 minutes. Configuring AWS Backup to copy automated backups to another region (A) provides cross-region disaster recovery, helping meet the RTO of 1 hour by restoring in a different region. Creating a cross-region read replica (D) allows for quick failover by promoting the replica, which can significantly reduce RTO.

Option C (Single-AZ) is less resilient and does not help meet RPO/RTO. Option E (daily manual snapshots) cannot achieve a 5-minute RPO due to manual timing.

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283

Multi-Selecthard

A company is using Amazon DynamoDB with on-demand capacity mode. The application experiences occasional throttling during traffic spikes. The database administrator wants to implement a solution to reduce throttling. Which THREE actions should the administrator take? (Choose THREE.)

Select 3 answers

A.Use DynamoDB Accelerator (DAX) to cache frequently accessed items.

B.Enable auto scaling for the table.

C.Switch the table to provisioned capacity mode with auto scaling.

D.Implement exponential backoff and retry logic in the application.

E.Design the application to handle throttling by retrying with backoff.

AnswersA, D, E

DAX reduces read traffic to the table, decreasing the chance of read throttling.

Why this answer

Options A, D, and E are correct. Using DynamoDB Accelerator (DAX) caches frequently accessed items, offloading read capacity from the table and reducing read throttling. Implementing exponential backoff and retry logic in the application (option D) and designing the application to handle throttling by retrying with backoff (option E) both ensure that requests are retried gracefully during spikes, reducing the impact of throttling.

Option B is incorrect because auto scaling is not applicable to on-demand capacity mode, which scales automatically. Option C is incorrect because switching to provisioned capacity does not inherently reduce throttling; on-demand already handles sudden spikes, but throttling may still occur if the workload exceeds table limits momentarily.

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284

MCQeasy

A company is using Amazon DynamoDB with on-demand capacity. The application experiences increased latency during peak hours. The DynamoDB table receives about 5,000 writes per second and 10,000 reads per second. The read latency is high, but write latency is acceptable. What should the company do to reduce read latency?

A.Enable DynamoDB Streams to offload read traffic.

B.Create a read replica of the DynamoDB table.

C.Enable DynamoDB Accelerator (DAX) for the table.

D.Switch to provisioned capacity and enable auto scaling.

AnswerC

DAX provides an in-memory cache that reduces read latency for DynamoDB tables.

Why this answer

DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache that significantly reduces read latency for DynamoDB tables, especially for repeated reads. DAX allows you to offload read traffic from the table and serve read requests from the cache, reducing the load on the table and improving response times. Option A is wrong because DynamoDB Streams is used to capture changes to items in the table, not to cache data or offload read traffic.

Option B is wrong because DynamoDB does not support read replicas; DAX is the caching solution for reads. Option D is wrong because switching to provisioned capacity and enabling auto scaling would help with scaling write capacity but does not directly address high read latency; DAX is specifically designed for in-memory caching to improve read performance.

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285

MCQmedium

A company is running an Amazon RDS for MySQL Multi-AZ DB instance. The primary instance in us-east-1a experiences an unexpected failure. After the automatic failover, the application team reports that write latency has increased significantly. The new primary instance is in us-east-1b. The DB instance class and storage configuration are identical. What is the MOST likely cause of the increased write latency?

A.The DB instance class in us-east-1b is a different size than the original.

B.The application is connecting to the DB instance in a different Availability Zone, increasing network latency.

C.The Multi-AZ configuration uses asynchronous replication, causing higher latency.

D.The new primary is in the same Availability Zone as the application, but the standby is in a different AZ, causing synchronous replication overhead.

AnswerB

The new primary is in us-east-1b, and if the application is in us-east-1a, cross-AZ latency increases write latency.

Why this answer

After failover, the new primary DB instance resides in us-east-1b, while the application likely continues to connect to the original endpoint or is still running in us-east-1a. This cross-AZ network hop introduces additional latency for write operations, as the application must send data over the network between Availability Zones. The DB instance class and storage are identical, so performance differences are not due to hardware changes.

Exam trap

The trap here is that candidates may assume Multi-AZ failover is transparent and does not affect performance, but cross-AZ network latency for writes can increase significantly if the application remains in the original AZ.

How to eliminate wrong answers

Option A is wrong because the question explicitly states that the DB instance class and storage configuration are identical, so a size difference is not a factor. Option C is wrong because Multi-AZ replication is synchronous, not asynchronous; asynchronous replication would be used for cross-Region read replicas, not for Multi-AZ failover. Option D is wrong because the new primary is in us-east-1b, not the same AZ as the application (which is in us-east-1a), and synchronous replication overhead applies to the standby, not to the application's write path.

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286

MCQmedium

A company runs a critical Amazon DynamoDB table with on-demand capacity. The table experiences throttling errors (ProvisionedThroughputExceededException) during peak hours. The table has a global secondary index (GSI) with a different partition key. What is the MOST likely cause of the throttling?

A.The base table's write capacity is insufficient for the workload.

B.The global secondary index is throttling due to uneven access patterns.

C.The partition key design causes hot partitions in the base table.

D.The table's read capacity is too low for the read-heavy workload.

AnswerB

GSIs on on-demand tables have their own capacity; hot partitions can cause throttling.

Why this answer

On-demand DynamoDB tables automatically scale capacity for the base table, but a GSI can throttle writes if its partition key creates hot partitions. The throttling on the base table occurs because the GSI write capacity is exceeded due to uneven access patterns. Options A, C, and D are incorrect because on-demand tables handle base table capacity scaling, hot partitions on the base table would cause throttling on the base table but the issue is with the GSI, and read capacity is not relevant given the write errors.

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287

MCQeasy

A company needs to audit all SQL queries executed on an Amazon RDS for PostgreSQL instance. Which feature should the company enable?

A.pgAudit extension

B.Advanced Audit

C.Database Activity Streams

D.Fine-Grained Auditing

AnswerA

pgAudit provides detailed audit logs.

Why this answer

PgAudit (PostgreSQL Audit Extension) is the native, supported way to log all SQL queries on Amazon RDS for PostgreSQL. It provides detailed session and object audit logging via the shared_preload_libraries parameter, capturing every executed statement without requiring external tools or additional infrastructure.

Exam trap

The trap here is that candidates confuse Database Activity Streams (a real RDS feature for streaming activity to Kinesis) with a full SQL audit log, but Database Activity Streams does not capture every SQL query in a traditional audit log format and requires additional processing, whereas pgAudit directly writes detailed SQL logs to the RDS log files.

How to eliminate wrong answers

Option B (Advanced Audit) is wrong because it is not a real feature in Amazon RDS; it is a generic term that does not correspond to any specific RDS capability. Option C (Database Activity Streams) is wrong because it streams database activity to Amazon Kinesis for near-real-time monitoring and security analysis, but it does not capture every SQL query in the same granular, logged format as pgAudit; it is designed for threat detection, not full SQL audit trails. Option D (Fine-Grained Auditing) is wrong because it is an Oracle Database feature (FGA) that does not exist in PostgreSQL or Amazon RDS for PostgreSQL; it is a common misconception carried over from Oracle environments.

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288

MCQmedium

Refer to the exhibit. A database engineer runs the command and receives the above output. The engineer wants to convert the database to Multi-AZ. Which command should be used?

A.aws rds reboot-db-instance --db-instance-identifier mydb --force-failover

B.aws rds create-db-instance --db-instance-identifier mydb --multi-az

C.aws rds modify-db-instance --db-instance-identifier mydb --multi-az

D.aws rds create-db-cluster --db-instance-identifier mydb --multi-az

AnswerC

'aws rds modify-db-instance' with the '--multi-az' flag modifies an existing DB instance to use Multi-AZ deployment.

Why this answer

'aws rds modify-db-instance' with the '--multi-az' flag modifies an existing DB instance to use Multi-AZ deployment. Option A is incorrect because 'reboot-db-instance' with '--force-failover' triggers a reboot and failover but does not change the Multi-AZ setting itself. Option B is incorrect because 'create-db-instance' is used to create a new instance, not modify an existing one.

Option D is incorrect because 'create-db-cluster' is for creating an Aurora DB cluster, not for converting a single DB instance to Multi-AZ.

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289

MCQeasy

A company has an Amazon DynamoDB table that stores session data for a web application. The table's read capacity units (RCUs) are consistently near 100% utilization during peak hours, causing throttling. The application can tolerate eventually consistent reads. Which action should the application team take to reduce throttling?

A.Decrease the provisioned RCUs for the table.

B.Enable DynamoDB Accelerator (DAX) to cache the session data.

C.Change the read consistency to eventually consistent.

D.Increase the provisioned RCUs for the table.

AnswerC

Using eventually consistent reads halves RCU consumption, doubling effective read capacity and reducing throttling.

Why this answer

Eventually consistent reads consume only half the Read Capacity Units (RCUs) compared to strongly consistent reads. Switching to eventually consistent reads effectively doubles the read capacity, reducing throttling without additional cost. Option A is incorrect because decreasing provisioned RCUs would reduce capacity and worsen throttling.

Option B is incorrect because while DAX can cache session data and reduce read load on the table, it does not directly address the RCU consumption for reads that still hit the table; moreover, implementing DAX adds complexity and cost. Option D is incorrect because increasing RCUs would solve throttling but at a higher cost, whereas eventually consistent reads provide a cost-effective solution.

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290

MCQmedium

A company is using Amazon ElastiCache for Redis to cache database query results. They notice that the cache hit ratio is low and many requests are hitting the database. The 'Evictions' metric is high. What is the MOST likely cause?

A.The replication factor is insufficient.

B.Encryption in transit is enabled.

C.The application is experiencing high network latency.

D.The cache node is too small for the workload.

AnswerD

A small cache leads to frequent evictions, reducing the cache hit ratio.

Why this answer

The high 'Evictions' metric indicates that the cache node is constantly full, causing it to evict old data to make room for new data. This leads to a low cache hit ratio because frequently accessed items are evicted and must be fetched from the database. Option D correctly identifies that the cache node is too small for the workload.

Option A is incorrect because insufficient replication factor would affect availability, not evictions. Option B is incorrect because encryption in transit does not impact cache capacity or evictions. Option C is incorrect because high network latency would affect request latency but not directly cause evictions.

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291

MCQhard

Refer to the exhibit. An application on an EC2 instance is trying to read an object from the S3 bucket 'data-lake-prod'. The instance is in a VPC with an IP address of 10.0.1.5. The application receives an Access Denied error. What is the cause?

A.An SCP is denying S3 access to the account.

B.A Deny statement with a source IP condition is blocking access.

C.The S3 bucket policy requires a specific VPC endpoint.

D.The IAM role does not have permission to read from the bucket.

AnswerB

The Deny with condition matches the IP and overrides the Allow.

Why this answer

The Deny statement applies to the source IP 10.0.1.5 (within 10.0.0.0/8), overriding the Allow. Option A is wrong because the IAM role does allow s3:GetObject on the bucket. Option C is wrong because there is no explicit condition on the Allow statement.

Option D is wrong because the policy is attached to the role, not an SCP.

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292

MCQmedium

Refer to the exhibit. A database administrator is writing an IAM policy to manage Amazon RDS snapshots. The policy allows actions on all RDS resources but denies deletion of any DB instance with the prefix 'production-'. A developer attempts to delete a snapshot named 'production-snapshot-2020'. Will this action be allowed?

A.Yes, but only if the developer has the necessary permissions.

B.No, because the Deny statement overrides the Allow statement.

C.Yes, because the Deny statement only applies to deleting DB instances, not snapshots.

D.No, because the snapshot name starts with 'production-', which matches the resource pattern in the Deny statement.

AnswerC

The Deny is specific to 'rds:DeleteDBInstance', so snapshot deletion is allowed.

Why this answer

The Deny statement in the policy only applies to the 'rds:DeleteDBInstance' action, not to 'rds:DeleteDBSnapshot'. The Allow statement explicitly allows all actions including 'rds:DeleteDBSnapshot' on all resources. Since there is no explicit deny for deleting snapshots, the allow takes effect.

Option A is incorrect because the developer's permissions are not relevant; the policy allows the action. Option B is incorrect because the Deny does not apply to snapshots. Option D is incorrect because the Deny condition only matches deletions of DB instances, not snapshots.

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293

MCQeasy

A company is running an Amazon Aurora MySQL-compatible edition DB cluster. The application reports that a recent schema change caused a significant increase in the number of deadlocks. Which parameter should the DBA check and possibly adjust to reduce deadlocks?

A.innodb_lock_wait_timeout

B.autocommit

C.max_connections

D.transaction_isolation

AnswerD

transaction_isolation sets the isolation level for transactions. Lowering the isolation level (e.g., from REPEATABLE READ to READ COMMITTED) reduces the use of gap locks and other locking mechanisms, thereby decreasing the likelihood of deadlocks.

Why this answer

Adjusting the transaction isolation level can reduce deadlocks by decreasing the locking overhead. For example, using READ COMMITTED instead of REPEATABLE READ reduces the use of gap locks, which are a common source of deadlocks. Option A, innodb_lock_wait_timeout, determines how long a transaction waits for a lock before timing out; it does not prevent deadlocks but rather handles lock waits.

Option B, autocommit, affects when transactions are committed but does not directly impact deadlock occurrence. Option C, max_connections, limits concurrent connections, which can reduce overall contention but is not a direct deadlock reduction parameter.

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294

MCQmedium

A company is using Amazon DynamoDB with global tables. The company wants to monitor replication latency between regions. Which CloudWatch metric should the company use?

A.GlobalTableReplicationLag

B.ReplicaLag

C.WriteThrottleEvents

D.ReplicationLatency

AnswerD

This metric tracks replication lag.

Why this answer

The correct metric is ReplicationLatency, which measures the time elapsed between an update in the source region and its appearance in the replica region for DynamoDB global tables. This metric directly reflects the replication lag between regions, making it the appropriate choice for monitoring cross-region replication performance.

Exam trap

The trap here is confusing DynamoDB's ReplicationLatency with RDS's ReplicaLag, as both involve cross-region replication but apply to entirely different services and metrics.

How to eliminate wrong answers

Option A is wrong because GlobalTableReplicationLag is not a valid CloudWatch metric for DynamoDB; AWS uses ReplicationLatency for this purpose. Option B is wrong because ReplicaLag is a metric for Amazon RDS read replicas, not for DynamoDB global tables. Option C is wrong because WriteThrottleEvents tracks throttled write requests, not replication latency between regions.

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295

MCQeasy

A database administrator needs to monitor the number of connections to an Amazon RDS for MySQL DB instance. Which Amazon CloudWatch metric should be used?

A.NetworkThroughput

B.DatabaseConnections

C.ConnectionAttempts

D.ActiveTransactions

AnswerB

DatabaseConnections is the correct metric for monitoring the number of connections.

Why this answer

The DatabaseConnections metric in CloudWatch shows the number of current connections to the DB instance.

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296

MCQmedium

The exhibit shows the output of an AWS CLI command for an Amazon RDS DB instance. Based on the output, what is the current configuration of the DB instance?

A.It is an Amazon Aurora MySQL-Compatible DB cluster.

B.It is a MySQL DB instance that is currently in a failed state.

C.It is a Multi-AZ DB instance with a standby in a different AZ.

D.It is a Single-AZ MySQL DB instance.

AnswerD

MultiAZ is false and SecondaryAvailabilityZone is null, confirming Single-AZ.

Why this answer

The output shows engine=mysql, MultiAZ=false, SecondaryAvailabilityZone=null, and DBInstanceStatus=available. This indicates a Single-AZ MySQL DB instance, not a Multi-AZ deployment, not Aurora, and not in a failed state. Therefore, option D is correct.

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297

MCQmedium

A company uses Amazon DynamoDB for a real-time analytics application. The table is provisioned with 1000 RCU and 500 WCU. Recently, the application experienced throttling on reads during a marketing campaign. The 'ConsumedReadCapacityUnits' metric shows spikes up to 2000 RCU. The 'ReadThrottleEvents' metric is high. The table has a global secondary index (GSI) that is also throttled. The application uses eventually consistent reads. The team wants to minimize costs while preventing throttling. The campaign traffic is predictable and occurs for 2 hours each day. What should the team do?

A.Increase the provisioned RCU to 2000 permanently.

B.Implement DynamoDB Accelerator (DAX) to cache reads.

C.Enable auto scaling with a scheduled scaling action to increase RCU during the campaign.

D.Switch the table to on-demand capacity mode.

AnswerC

Auto scaling adjusts capacity automatically, and scheduled scaling ensures capacity is ready for the campaign, minimizing cost.

Why this answer

The traffic is predictable and occurs for 2 hours daily. Scheduled auto scaling can increase RCU during the campaign and reduce it afterward, minimizing cost while preventing throttling. Option A is incorrect because permanently increasing RCU to 2000 would waste capacity during the other 22 hours, increasing costs unnecessarily.

Option B is incorrect because DynamoDB Accelerator (DAX) adds cost and primarily caches base table reads, not global secondary index reads; the GSI is also throttled, so DAX may not fully resolve the issue, and scheduled scaling is more cost-effective for predictable patterns. Option D is incorrect because on-demand capacity mode is more expensive for predictable, sustained high traffic; auto scaling with a schedule is cheaper for this use case.

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298

MCQeasy

A database administrator needs to automate the backup process for an Amazon RDS for MySQL DB instance. The backups must be retained for 30 days and should be taken daily. Which AWS service should be used to implement this automation?

A.Amazon S3 lifecycle policies

B.AWS Backup

C.AWS Lambda with custom scripts

D.Amazon RDS automated backups

AnswerD

RDS automated backups can be enabled with a retention period of up to 35 days and perform daily backups automatically.

Why this answer

Amazon RDS automated backups are the native, built-in mechanism for backing up RDS DB instances. They automatically take daily snapshots during the backup window and retain transaction logs for point-in-time recovery. By default, the retention period can be set from 1 to 35 days, so configuring it to 30 days meets the requirement without any additional services or custom scripting.

Exam trap

The trap here is that candidates may over-engineer the solution by choosing AWS Backup or Lambda, not realizing that RDS automated backups natively support daily backups with a configurable retention period up to 35 days, making them the simplest and most appropriate choice.

How to eliminate wrong answers

Option A is wrong because Amazon S3 lifecycle policies manage the transition and expiration of objects stored in S3 buckets, not the scheduling or retention of RDS backups. Option B is wrong because AWS Backup is a centralized backup service that can back up RDS instances, but it is not required for this simple automation—RDS automated backups already provide daily backups with configurable retention natively. Option C is wrong because while AWS Lambda with custom scripts could be used to trigger manual snapshots, it adds unnecessary complexity and operational overhead when the built-in automated backup feature of RDS directly satisfies the requirement.

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299

MCQmedium

A company is using Amazon RDS for MySQL with Multi-AZ deployment. The database experiences a failover event, and after failover, the application reports increased latency. Which action should the database specialist take to diagnose the issue?

A.Check Amazon CloudWatch metrics for Database Connections and Latency, and verify DNS resolution.

B.Promote the secondary instance to primary manually.

C.Create a new read replica and redirect traffic.

D.Force a reboot of the DB instance to reset connections.

AnswerA

Monitoring metrics and DNS can pinpoint the cause of increased latency.

Why this answer

After a Multi-AZ failover, the DNS record for the RDS endpoint is updated to point to the new primary in a different Availability Zone. If the application's DNS cache still resolves to the old IP (which is now unreachable or in a different AZ), connections may time out or route suboptimally, increasing latency. Checking CloudWatch metrics for Database Connections and Latency helps isolate whether the issue is due to connection churn, resource contention, or DNS caching, while verifying DNS resolution confirms the application is connecting to the correct endpoint.

Exam trap

The trap here is that candidates assume increased latency after failover is always due to resource exhaustion or a need to reset connections, overlooking the common root cause of DNS caching and stale client connections routing to the wrong AZ.

How to eliminate wrong answers

Option B is wrong because manually promoting the secondary instance is unnecessary and counterproductive; Multi-AZ failover already promotes the standby automatically, and manual promotion would cause another disruption. Option C is wrong because creating a new read replica does not address the primary's latency issue; read replicas are for offloading read traffic, not for fixing failover-related latency on the primary. Option D is wrong because forcing a reboot resets connections but does not resolve the underlying cause of increased latency, such as DNS caching or a cold buffer pool on the new primary; it would only add downtime.

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300

MCQhard

A logistics company operates a fleet tracking system using Amazon DocumentDB (with MongoDB compatibility). The database stores location updates from thousands of vehicles every second. The collection has a compound index on (vehicle_id, timestamp). Recently, the company noticed that write latency has increased, and the primary instance's CPU is consistently above 80%. The storage is gp2, and the instance is a db.r5.large. The operations team suspects that index maintenance is causing high CPU. The database administrator needs to reduce write latency without sacrificing query performance for real-time location queries. What should the administrator do?

A.Remove the compound index and rely on the default _id index for queries.

B.Upgrade to a larger instance class, such as db.r5.xlarge, to provide more CPU and memory.

C.Disable journaling to reduce write I/O.

D.Shard the collection using a hash-based shard key on vehicle_id to distribute write load.

AnswerD

Sharding the collection using a hash-based shard key on vehicle_id distributes writes evenly and reduces index maintenance overhead.

Why this answer

Sharding the collection using a hash-based shard key on vehicle_id distributes writes evenly and reduces index maintenance overhead. Option A is wrong because removing the compound index harms query performance for real-time location queries. Option B is wrong because upgrading to a larger instance class adds CPU but does not address the root cause of index maintenance overhead.

Option C is wrong because disabling journaling reduces durability, not index maintenance.

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