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DBS-C01 · topic practice

Monitoring and Troubleshooting practice questions

Practise AWS Certified Database Specialty DBS-C01 Monitoring and Troubleshooting practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security

20 questionsDomain: Monitoring and Troubleshooting

Practice 10 questions Browse domain →

What the exam tests

What to know about Monitoring and Troubleshooting

Monitoring and Troubleshooting questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

Watch out for

Common Monitoring and Troubleshooting exam traps

▸Answering from memory before reading the full scenario.
▸Missing a constraint such as cost, availability, security, scope or command context.
▸Choosing a broad answer when the question asks for the most specific fix.
▸Ignoring why the wrong options are tempting.

Practice set

Monitoring and Troubleshooting questions

20 questions · select your answer, then reveal the explanation

Question 1easymultiple choice

Read the full Monitoring and Troubleshooting explanation →

A company is using Amazon RDS for MySQL and notices that the Read IOPS metric is consistently high during business hours. The application is read-heavy. Which configuration change would most likely reduce Read IOPS?

Trap 1: Add a Multi-AZ standby instance.

A Multi-AZ standby is for high availability and disaster recovery, not for read offloading.

Trap 2: Increase the DB instance size to a larger instance type.

Increasing instance size may improve throughput but does not directly reduce the number of read IOPS; the workload remains.

Trap 3: Enable storage Auto Scaling on the RDS instance.

Storage Auto Scaling only adjusts storage capacity, not IOPS.

Study all Monitoring and Troubleshooting common traps →

A
Add a Multi-AZ standby instance.
Why wrong: A Multi-AZ standby is for high availability and disaster recovery, not for read offloading.
B
Create one or more read replicas and redirect read traffic to them.
Read replicas handle read queries from the primary, reducing read IOPS on the source instance.
C
Increase the DB instance size to a larger instance type.
Why wrong: Increasing instance size may improve throughput but does not directly reduce the number of read IOPS; the workload remains.
D
Enable storage Auto Scaling on the RDS instance.
Why wrong: Storage Auto Scaling only adjusts storage capacity, not IOPS.

Full breakdown with real-world context →

Question 2mediummultiple choice

Read the full Monitoring and Troubleshooting explanation →

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

Trap 1: Enable DynamoDB Accelerator (DAX) for the table.

DAX improves read performance, not write capacity.

Trap 2: Create a global secondary index on the table.

Adding a GSI does not increase write capacity; writes to the table also write to the index.

Trap 3: Switch from eventually consistent reads to strongly consistent…

Read consistency does not affect write throughput.

Study all Monitoring and Troubleshooting common traps →

A
Enable DynamoDB Accelerator (DAX) for the table.
Why wrong: DAX improves read performance, not write capacity.
B
Create a global secondary index on the table.
Why wrong: Adding a GSI does not increase write capacity; writes to the table also write to the index.
C
Increase the provisioned write capacity for the table.
Increasing write capacity units reduces throttling for write requests.
D
Switch from eventually consistent reads to strongly consistent reads.
Why wrong: Read consistency does not affect write throughput.

Full breakdown with real-world context →

Question 3hardmultiple choice

Read the full Monitoring and Troubleshooting explanation →

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

Trap 1: Create a read replica and redirect all SELECT queries to the…

While this reduces read load, the primary still handles writes and some reads; CPU may remain high if the bottleneck is not solely reads.

Trap 2: Enable Multi-AZ to offload CPU to the standby instance.

Multi-AZ does not offload CPU; the standby is not used for queries unless a failover occurs.

Trap 3: Increase the allocated storage to 1 TB to improve I/O performance.

Increasing storage does not improve CPU capacity.

Study all Monitoring and Troubleshooting common traps →

A
Create a read replica and redirect all SELECT queries to the replica.
Why wrong: While this reduces read load, the primary still handles writes and some reads; CPU may remain high if the bottleneck is not solely reads.
B
Enable Multi-AZ to offload CPU to the standby instance.
Why wrong: Multi-AZ does not offload CPU; the standby is not used for queries unless a failover occurs.
C
Increase the allocated storage to 1 TB to improve I/O performance.
Why wrong: Increasing storage does not improve CPU capacity.
D
Upgrade to a larger instance type, such as db.r5.xlarge.
A larger instance provides more CPU cores and better performance, directly addressing high CPU utilization.

Full breakdown with real-world context →

Question 4easymultiple choice

Read the full Monitoring and Troubleshooting explanation →

A team manages an Amazon Aurora MySQL database. They observe that the 'Deadlocks' metric in CloudWatch is spiking. The application uses a single writer instance and multiple read replicas. Which action is most effective at reducing deadlocks?

Trap 1: Increase the instance size to handle more concurrent connections.

Concurrency is not the direct cause; deadlocks are about lock order.

Trap 2: Redirect read traffic to read replicas to reduce load on the writer.

Read replicas do not handle writes; deadlocks occur during writes.

Trap 3: Enable Multi-AZ to distribute the load.

Multi-AZ does not affect locking behavior.

Study all Monitoring and Troubleshooting common traps →

A
Increase the instance size to handle more concurrent connections.
Why wrong: Concurrency is not the direct cause; deadlocks are about lock order.
B
Redirect read traffic to read replicas to reduce load on the writer.
Why wrong: Read replicas do not handle writes; deadlocks occur during writes.
C
Enable Multi-AZ to distribute the load.
Why wrong: Multi-AZ does not affect locking behavior.
D
Review application code to ensure transactions are as short as possible and access tables in a consistent order.
Minimizing transaction duration and accessing resources in a fixed order reduces deadlock probability.

Full breakdown with real-world context →

Question 5mediummultiple choice

Read the full Monitoring and Troubleshooting explanation →

An organization is using Amazon DynamoDB with on-demand capacity. They notice that the 'ThrottledRequests' metric is non-zero during a specific hour each day. The table stores session data and has a partition key of 'user_id'. The workload is uniform. What is the most likely cause of throttling?

Trap 1: The table has on-demand capacity and cannot throttle.

On-demand tables can still throttle due to per-partition throughput limits.

Trap 2: The account-level read/write capacity limit is exceeded.

On-demand capacity can burst beyond provisioned limits, but account limits are high.

Trap 3: A global secondary index is consuming write capacity.

If no GSI exists, this is not a factor.

Study all Monitoring and Troubleshooting common traps →

A
The table has on-demand capacity and cannot throttle.
Why wrong: On-demand tables can still throttle due to per-partition throughput limits.
B
The account-level read/write capacity limit is exceeded.
Why wrong: On-demand capacity can burst beyond provisioned limits, but account limits are high.
C
A global secondary index is consuming write capacity.
Why wrong: If no GSI exists, this is not a factor.
D
The partition key is not evenly distributed.
Uneven access pattern can cause a hot partition leading to throttling even on on-demand tables.

Full breakdown with real-world context →

Question 6hardmulti select

Read the full Monitoring and Troubleshooting explanation →

A database engineer is troubleshooting slow query performance on an Amazon RDS for PostgreSQL instance. The instance is db.r5.large with 500 GB of General Purpose SSD (gp2) storage. CloudWatch metrics show high Read Latency and high Read IOPS, but low CPU utilization. Which TWO actions should the engineer take to improve performance?

Trap 1: Increase the DB instance class to a larger size, such as…

Larger instance provides more CPU and memory but does not directly improve storage latency.

Trap 2: Enable Multi-AZ to use the standby for read traffic.

Standby instances in Multi-AZ are not used for reads.

Trap 3: Optimize queries by adding appropriate indexes.

While indexing can reduce IOPS, the metrics suggest a storage bottleneck; indexing is application-specific and not directly indicated.

Study all Monitoring and Troubleshooting common traps →

A
Create a read replica and offload read queries to it.
Read replicas reduce the read IOPS on the primary, which can lower latency on the primary.
B
Increase the DB instance class to a larger size, such as db.r5.2xlarge.
Why wrong: Larger instance provides more CPU and memory but does not directly improve storage latency.
C
Enable Multi-AZ to use the standby for read traffic.
Why wrong: Standby instances in Multi-AZ are not used for reads.
D
Optimize queries by adding appropriate indexes.
Why wrong: While indexing can reduce IOPS, the metrics suggest a storage bottleneck; indexing is application-specific and not directly indicated.
E
Switch from General Purpose SSD (gp2) to Provisioned IOPS SSD (io1) with a higher IOPS rate.
Provisioned IOPS provides consistent low latency for I/O-intensive workloads.

Full breakdown with real-world context →

Question 7mediummulti select

Read the full Monitoring and Troubleshooting explanation →

A company is using Amazon DynamoDB with autoscaling enabled. The table has a partition key of 'order_id' and a sort key of 'order_date'. The application performs both point queries and range queries. Recently, the 'ConsumedReadCapacityUnits' metric shows that the table is consistently using 100% of the provisioned capacity. Which THREE factors should the database engineer investigate to determine the cause?

Trap 1: Whether autoscaling is configured correctly to add capacity.

Autoscaling adjusts provisioned capacity, not consumed capacity.

Trap 2: Whether a global secondary index is being used for queries.

GSI usage does not affect the table's consumed read capacity directly.

Study all Monitoring and Troubleshooting common traps →

A
Whether autoscaling is configured correctly to add capacity.
Why wrong: Autoscaling adjusts provisioned capacity, not consumed capacity.
B
Whether the application is using Scan operations instead of Query operations.
Scans consume more read capacity than queries.
C
Whether the partition key is evenly distributed across partitions.
Uneven distribution leads to hot partitions and throttling.
D
Whether a specific 'order_id' is being accessed frequently, creating a hot key.
Hot keys can cause high consumption on a single partition.
E
Whether a global secondary index is being used for queries.
Why wrong: GSI usage does not affect the table's consumed read capacity directly.

Full breakdown with real-world context →

Question 8mediummultiple choice

Read the full Monitoring and Troubleshooting explanation →

A company is using Amazon RDS for MySQL and notices that database connections are being rejected intermittently. The application logs show 'Too many connections' errors. The DB instance has 1000 max_connections. Which action should the DBA take to troubleshoot and resolve this issue without impacting performance?

Trap 1: Increase the max_connections parameter to 5000 in the DB parameter…

Increasing max_connections can cause memory pressure and performance degradation.

Trap 2: Create a read replica to offload read traffic

Read replicas do not reduce the number of connections to the primary instance.

Trap 3: Set the 'wait_timeout' parameter to a lower value to close idle…

Reducing wait_timeout may cause active queries to be terminated prematurely.

Study all Monitoring and Troubleshooting common traps →

A
Increase the max_connections parameter to 5000 in the DB parameter group
Why wrong: Increasing max_connections can cause memory pressure and performance degradation.
B
Create a read replica to offload read traffic
Why wrong: Read replicas do not reduce the number of connections to the primary instance.
C
Enable Performance Insights and review the 'DB Connections' metric to identify spikes and troubleshoot application connection pooling
Performance Insights helps identify the source of connection bursts and allows tuning of the application's connection pooling behavior.
D
Set the 'wait_timeout' parameter to a lower value to close idle connections faster
Why wrong: Reducing wait_timeout may cause active queries to be terminated prematurely.

Full breakdown with real-world context →

Question 9hardmultiple choice

Read the full Monitoring and Troubleshooting explanation →

A database engineer is troubleshooting a production Amazon Aurora MySQL DB cluster. The application is experiencing high latency on write operations. The engineer checks the Amazon CloudWatch metrics and sees that the 'AuroraBinlogReplicaLag' metric is high. What is the most likely cause of the write latency?

Trap 1: The DB cluster has insufficient storage capacity for the binlog…

Insufficient storage would cause errors, not binlog lag.

Trap 2: The DB cluster has a high CPU utilization that is causing…

CPU utilization is a separate metric; binlog lag is specific to replication.

Trap 3: A recent failover event caused the binlog to be replayed from the…

Failover does not cause binlog lag; it may cause a brief stall but not sustained high lag.

Study all Monitoring and Troubleshooting common traps →

A
The DB cluster has insufficient storage capacity for the binlog files
Why wrong: Insufficient storage would cause errors, not binlog lag.
B
The DB cluster has a high CPU utilization that is causing replication lag
Why wrong: CPU utilization is a separate metric; binlog lag is specific to replication.
C
The binlog replication to a downstream MySQL instance is falling behind
High binlog lag means the downstream replica cannot keep up, causing write delays if the source waits for acknowledgment.
D
A recent failover event caused the binlog to be replayed from the last checkpoint
Why wrong: Failover does not cause binlog lag; it may cause a brief stall but not sustained high lag.

Full breakdown with real-world context →

Question 10easymultiple choice

Read the full Monitoring and Troubleshooting explanation →

A company is running a production Amazon DynamoDB table with on-demand capacity. The application is experiencing increased latency and throttled requests during peak hours. Which monitoring tool should the database specialist use to identify the specific partition keys causing the throttling?

Trap 1: Amazon Inspector

Amazon Inspector is a vulnerability management service, not for DynamoDB monitoring.

Trap 2: AWS Config

AWS Config tracks configuration changes, not performance metrics.

Trap 3: AWS CloudTrail logs

CloudTrail records API calls but does not provide partition-level throttling analysis.

Study all Monitoring and Troubleshooting common traps →

A
Amazon CloudWatch Contributor Insights for DynamoDB
Contributor Insights analyzes access patterns and identifies throttled partition keys.
B
Amazon Inspector
Why wrong: Amazon Inspector is a vulnerability management service, not for DynamoDB monitoring.
C
AWS Config
Why wrong: AWS Config tracks configuration changes, not performance metrics.
D
AWS CloudTrail logs
Why wrong: CloudTrail records API calls but does not provide partition-level throttling analysis.

Full breakdown with real-world context →

Question 11mediummultiple choice

Read the full Monitoring and Troubleshooting explanation →

A database engineer is monitoring an Amazon RDS for PostgreSQL instance and notices that the 'DiskQueueDepth' metric is consistently above 100. The instance uses gp2 storage with 1000 GB allocated. What is the most likely cause of the high disk queue depth?

Trap 1: Replication lag between the primary and standby instance

Replication lag measures delay in data replication, not storage I/O.

Trap 2: Insufficient memory allocated to the instance

Memory issues cause swapping, not high disk queue depth.

Trap 3: Network throughput limit is being exceeded

Network limits would show in network metrics, not disk queue depth.

Study all Monitoring and Troubleshooting common traps →

A
Replication lag between the primary and standby instance
Why wrong: Replication lag measures delay in data replication, not storage I/O.
B
The instance has reached the IOPS limit of the gp2 volume
For a 1000 GB gp2 volume, baseline IOPS is 3000; sustained I/O beyond that causes queuing.
C
Insufficient memory allocated to the instance
Why wrong: Memory issues cause swapping, not high disk queue depth.
D
Network throughput limit is being exceeded
Why wrong: Network limits would show in network metrics, not disk queue depth.

Full breakdown with real-world context →

Question 12hardmulti select

Read the full Monitoring and Troubleshooting explanation →

A company is migrating its on-premises Oracle database to Amazon RDS for Oracle. The database specialist needs to monitor the migration process and ensure data consistency. Which TWO AWS services should be used together to continuously monitor the replication lag and data integrity?

Trap 1: Amazon RDS Performance Insights

Performance Insights is for database load analysis, not replication lag.

Trap 2: AWS Schema Conversion Tool (AWS SCT)

SCT converts schema, does not monitor replication.

Trap 3: AWS Glue

Glue is for ETL jobs, not real-time replication.

Study all Monitoring and Troubleshooting common traps →

A
Amazon RDS Performance Insights
Why wrong: Performance Insights is for database load analysis, not replication lag.
B
AWS Schema Conversion Tool (AWS SCT)
Why wrong: SCT converts schema, does not monitor replication.
C
AWS Database Migration Service (AWS DMS)
DMS provides replication tasks and publishes latency metrics.
D
AWS Glue
Why wrong: Glue is for ETL jobs, not real-time replication.
E
Amazon CloudWatch
CloudWatch collects DMS replication metrics for monitoring.

Full breakdown with real-world context →

Question 13mediummulti select

Read the full Monitoring and Troubleshooting explanation →

A database specialist is troubleshooting an Amazon DynamoDB table that is experiencing high throttling on write requests. The table has on-demand capacity and uses a composite primary key (partition key and sort key). Which THREE actions should the specialist take to identify and resolve the issue?

Trap 1: Change the table to provisioned capacity mode

Provisioned capacity may still have hot partition issues.

Trap 2: Increase the read capacity units on the table

Read capacity does not affect write throttling.

Study all Monitoring and Troubleshooting common traps →

A
Examine the partition key value distribution to identify hot partitions
Uneven distribution causes throttling on hot partitions.
B
Implement DynamoDB Accelerator (DAX) to offload read traffic
DAX reduces read load, freeing write capacity.
C
Change the table to provisioned capacity mode
Why wrong: Provisioned capacity may still have hot partition issues.
D
Increase the read capacity units on the table
Why wrong: Read capacity does not affect write throttling.
E
Review Amazon CloudWatch metrics for 'WriteThrottleEvents' and 'ConsumedWriteCapacityUnits'
These metrics pinpoint throttling and capacity usage.

Full breakdown with real-world context →

Question 14hardmultiple choice

Read the full Monitoring and Troubleshooting explanation →

A database engineer is reviewing Amazon RDS for MySQL error logs and sees repeated authentication failures from the same IP address. The application team confirms the password is correct. What is the most likely cause of these errors?

Exhibit

Refer to the exhibit.

From Amazon CloudWatch Logs:

2023-04-01T12:00:00Z [ERROR] [Client] Authentication failed for user 'app_user' from host '10.0.1.50' using method 'mysql_native_password'
2023-04-01T12:01:00Z [ERROR] [Client] Access denied for user 'app_user'@'10.0.1.50' (using password: YES)
2023-04-01T12:02:00Z [ERROR] [Client] Access denied for user 'app_user'@'10.0.1.50' (using password: YES)

Trap 1: The password is incorrect

The application team confirmed the password is correct.

Trap 2: The 'app_user' account is locked

A locked account would show a different error.

Trap 3: The database requires SSL connections

SSL requirement would show a different error.

Study all Monitoring and Troubleshooting common traps →

A
The password is incorrect
Why wrong: The application team confirmed the password is correct.
B
The user 'app_user' does not have access from host '10.0.1.50'
The user may be defined as 'app_user'@'%' or from a different host, causing a mismatch.
C
The 'app_user' account is locked
Why wrong: A locked account would show a different error.
D
The database requires SSL connections
Why wrong: SSL requirement would show a different error.

Full breakdown with real-world context →

Question 15hardmultiple choice

Read the full Monitoring and Troubleshooting explanation →

A company runs a critical e-commerce application on Amazon Aurora MySQL with a single DB instance. The database has 8 TB of data and uses the default writer endpoint. Recently, the application experienced a 10-minute outage during a primary instance failover. The failover was triggered by an underlying hardware issue. The database specialist needs to minimize downtime during future failovers. The application team is unwilling to modify the application code to handle connection retries. The company has a 99.99% SLA requirement. Which solution should the database specialist implement to meet the SLA with minimal application changes?

Trap 1: Increase the DB instance class to a larger size to improve…

Instance size does not affect failover detection or recovery time.

Trap 2: Enable Multi-AZ deployment with automatic failover

Multi-AZ is already enabled; the issue is that the application does not retry connections, so failover still causes downtime.

Trap 3: Create a cross-Region read replica and promote it to primary during…

Promoting a read replica requires DNS changes and application reconnection, causing downtime.

Study all Monitoring and Troubleshooting common traps →

A
Increase the DB instance class to a larger size to improve performance and reduce failover time
Why wrong: Instance size does not affect failover detection or recovery time.
B
Enable Multi-AZ deployment with automatic failover
Why wrong: Multi-AZ is already enabled; the issue is that the application does not retry connections, so failover still causes downtime.
C
Create an Amazon RDS Proxy and configure the application to connect to the proxy endpoint
RDS Proxy handles failover seamlessly by preserving connections and reducing downtime.
D
Create a cross-Region read replica and promote it to primary during failover
Why wrong: Promoting a read replica requires DNS changes and application reconnection, causing downtime.

Full breakdown with real-world context →

Question 16hardmultiple choice

Read the full Monitoring and Troubleshooting explanation →

You are managing an Amazon RDS for PostgreSQL Multi-AZ DB instance that handles a high-traffic e-commerce application. Recently, the database has been experiencing intermittent slowdowns during peak hours. You have enabled Enhanced Monitoring and Performance Insights. After reviewing the Performance Insights dashboard, you notice that the 'db.sql.queries.avg_latency' metric spikes during the slowdowns, and the top SQL queries are all simple SELECT statements on a frequently accessed 'orders' table. The table has over 10 million rows and is indexed on 'order_id', 'customer_id', and 'order_date'. The average query latency for these SELECT statements jumps from 5 ms to over 500 ms during the spikes. You also observe that the 'ReadIOPS' metric on the DB instance is consistently below the provisioned IOPS limit of the gp2 storage. The DB instance type is db.r5.large with 16 GB memory. The 'DatabaseConnections' metric shows that the number of connections is well within the max_connections limit (set to 200). However, the 'CPUCreditBalance' for the underlying EC2 instance, which is a T3 medium, drops to near zero during the spikes. The 'CPUUtilization' metric is below 50%. Which of the following is the MOST likely cause and the appropriate action to resolve the issue?

Trap 1: The issue is due to a memory bottleneck causing queries to spill to…

Memory pressure would show high SwapUsage or low FreeableMemory, not CPU credit exhaustion. The instance is db.r5.large, not T3.

Trap 2: The issue is caused by a connection pool exhaustion

Connection count is well below max_connections, so this is not the issue. CPU credit exhaustion is the clear symptom.

Trap 3: The issue is caused by a missing index on the 'orders' table

Missing indexes would cause high ReadIOPS and sequential scans, but ReadIOPS is low and the table has indexes. The symptom points to CPU throttling.

Study all Monitoring and Troubleshooting common traps →

A
The issue is due to CPU credit exhaustion on the T3 instance. Change the DB instance class from db.t3.medium to a dedicated CPU instance type such as db.r5.large.
The T3 instance uses CPU credits; when credits are exhausted, performance is throttled. Changing to a dedicated instance eliminates credit-based performance.
B
The issue is due to a memory bottleneck causing queries to spill to disk. Increase the instance memory by moving to a db.r5.xlarge instance.
Why wrong: Memory pressure would show high SwapUsage or low FreeableMemory, not CPU credit exhaustion. The instance is db.r5.large, not T3.
C
The issue is caused by a connection pool exhaustion. Increase the max_connections parameter and use connection pooling.
Why wrong: Connection count is well below max_connections, so this is not the issue. CPU credit exhaustion is the clear symptom.
D
The issue is caused by a missing index on the 'orders' table. Add a composite index on the columns used in the WHERE clauses.
Why wrong: Missing indexes would cause high ReadIOPS and sequential scans, but ReadIOPS is low and the table has indexes. The symptom points to CPU throttling.

Full breakdown with real-world context →

Question 17mediummulti select

Read the full NAT/PAT explanation →

A database engineer is troubleshooting high CPU usage on an Amazon RDS for PostgreSQL instance. Amazon CloudWatch shows CPU Utilization consistently above 90% during business hours. Which combination of actions should the engineer take to identify the root cause? (Choose TWO.)

Trap 1: Enable Enhanced Monitoring and review OS process list.

Enhanced Monitoring shows OS-level metrics like memory and disk I/O, but not query-level CPU usage.

Trap 2: Scale up the DB instance to a larger instance class.

Scaling up addresses symptoms but does not identify the root cause; it may also increase costs unnecessarily.

Trap 3: Install pg_stat_statements extension and query it.

pg_stat_statements requires prior installation and is not available by default; Performance Insights is easier to enable and provides similar information.

Study all Monitoring and Troubleshooting common traps →

A
Enable Enhanced Monitoring and review OS process list.
Why wrong: Enhanced Monitoring shows OS-level metrics like memory and disk I/O, but not query-level CPU usage.
B
Review the slow query log to identify long-running queries.
Slow query logs can reveal queries that consume significant CPU resources.
C
Scale up the DB instance to a larger instance class.
Why wrong: Scaling up addresses symptoms but does not identify the root cause; it may also increase costs unnecessarily.
D
Enable Performance Insights and review the top SQL queries.
Performance Insights provides query-level performance data to pinpoint high-CPU queries.
E
Install pg_stat_statements extension and query it.
Why wrong: pg_stat_statements requires prior installation and is not available by default; Performance Insights is easier to enable and provides similar information.

Full breakdown with real-world context →

Question 18easymultiple choice

Read the full NAT/PAT explanation →

A company runs a production Amazon DynamoDB table with on-demand capacity. The table stores session data for a web application. Recently, users have reported occasional slow response times. The operations team notices that the table's ConsumedWriteCapacityUnits metric shows occasional spikes that exceed the provisioned throughput (though on-demand auto-scales), and ThrottledWriteEvents metrics show occasional throttling. The application uses the AWS SDK with default retry logic. The database specialist is asked to investigate. Upon reviewing the table configuration, the specialist finds that the table has a simple primary key (partition key only) and the data access pattern is heavily skewed toward a small number of partition keys. The application writes in batches of 25 items using the BatchWriteItem API. What should the specialist recommend to reduce throttling and improve performance?

Trap 1: Increase the provisioned read capacity units to handle the load.

Throttling is on writes, not reads; increasing read capacity does not help.

Trap 2: Switch the table to provisioned capacity mode and increase write…

On-demand already auto-scales; the issue is hot partitions, not overall capacity.

Trap 3: Enable DynamoDB Accelerator (DAX) to cache write operations.

DAX caches reads, not writes; it does not reduce write throttling.

Study all Monitoring and Troubleshooting common traps →

A
Implement write sharding by adding a random suffix to the partition key to distribute writes more evenly.
Write sharding spreads writes across multiple partitions, reducing throttling.
B
Increase the provisioned read capacity units to handle the load.
Why wrong: Throttling is on writes, not reads; increasing read capacity does not help.
C
Switch the table to provisioned capacity mode and increase write capacity.
Why wrong: On-demand already auto-scales; the issue is hot partitions, not overall capacity.
D
Enable DynamoDB Accelerator (DAX) to cache write operations.
Why wrong: DAX caches reads, not writes; it does not reduce write throttling.

Full breakdown with real-world context →

Question 19mediumdrag order

Read the full Monitoring and Troubleshooting explanation →

Arrange the steps to set up cross-Region read replicas for an Amazon Aurora MySQL DB cluster 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

5Step 5

Question 20mediumdrag order

Read the full Monitoring and Troubleshooting explanation →

Arrange the steps to create an Amazon DynamoDB global table (multi-Region) 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

5Step 5

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Frequently asked questions

What does the DBS-C01 exam test about Monitoring and Troubleshooting?: Monitoring and Troubleshooting questions test whether you can apply the concept in context, not just recognise a definition.
How should I use these practice questions?: Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Monitoring and Troubleshooting questions in a focused session?: Yes — the session launcher on this page draws every question from the Monitoring and Troubleshooting domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
Where can I practise other DBS-C01 topics?: Use the topic links above to move to related areas, or go back to the DBS-C01 question bank to see all topics.
Are these real exam questions or dumps?: These are original practice questions written to test the same concepts the DBS-C01 exam covers. They are not copied from any real exam or dump site.

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Exam traps to avoid

▸Answering from memory before reading the full scenario.
▸Missing a constraint such as cost, availability, security, scope or command context.
▸Choosing a broad answer when the question asks for the most specific fix.
▸Ignoring why the wrong options are tempting.

Monitoring and Troubleshooting practice questions

What to know about Monitoring and Troubleshooting

Common Monitoring and Troubleshooting exam traps

Monitoring and Troubleshooting questions

A company is using Amazon RDS for MySQL and notices that the Read IOPS metric is consistently high during business hours. The application is read-heavy. Which configuration change would most likely reduce Read IOPS?

A team manages an Amazon Aurora MySQL database. They observe that the 'Deadlocks' metric in CloudWatch is spiking. The application uses a single writer instance and multiple read replicas. Which action is most effective at reducing deadlocks?

An organization is using Amazon DynamoDB with on-demand capacity. They notice that the 'ThrottledRequests' metric is non-zero during a specific hour each day. The table stores session data and has a partition key of 'user_id'. The workload is uniform. What is the most likely cause of throttling?

A company is running a production Amazon DynamoDB table with on-demand capacity. The application is experiencing increased latency and throttled requests during peak hours. Which monitoring tool should the database specialist use to identify the specific partition keys causing the throttling?

A database engineer is monitoring an Amazon RDS for PostgreSQL instance and notices that the 'DiskQueueDepth' metric is consistently above 100. The instance uses gp2 storage with 1000 GB allocated. What is the most likely cause of the high disk queue depth?

A company is migrating its on-premises Oracle database to Amazon RDS for Oracle. The database specialist needs to monitor the migration process and ensure data consistency. Which TWO AWS services should be used together to continuously monitor the replication lag and data integrity?

A database specialist is troubleshooting an Amazon DynamoDB table that is experiencing high throttling on write requests. The table has on-demand capacity and uses a composite primary key (partition key and sort key). Which THREE actions should the specialist take to identify and resolve the issue?

A database engineer is reviewing Amazon RDS for MySQL error logs and sees repeated authentication failures from the same IP address. The application team confirms the password is correct. What is the most likely cause of these errors?

Exhibit

A database engineer is troubleshooting high CPU usage on an Amazon RDS for PostgreSQL instance. Amazon CloudWatch shows CPU Utilization consistently above 90% during business hours. Which combination of actions should the engineer take to identify the root cause? (Choose TWO.)

Arrange the steps to set up cross-Region read replicas for an Amazon Aurora MySQL DB cluster in the correct order.

Arrange the steps to create an Amazon DynamoDB global table (multi-Region) in the correct order.

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Related DBS-C01 topic practice pages

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