DBS-C01 Monitoring and Troubleshooting — Timed 20 Questions

Question 1

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?

Accepted Answer

Create one or more read replicas and redirect read traffic to them.. Creating read replicas offloads read queries from the primary DB instance to replica instances, directly reducing the number of read I/O operations on the primary. Since the application is read-heavy and Read IOPS is high during business hours, distributing read traffic to replicas alleviates the I/O bottleneck on the primary instance without requiring a larger instance or storage changes.

Answer

Add a Multi-AZ standby instance.

Answer

Increase the DB instance size to a larger instance type.

Answer

Enable storage Auto Scaling on the RDS instance.

Question 2

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?

Accepted Answer

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

Answer

Enable DynamoDB Accelerator (DAX) for the table.

Answer

Create a global secondary index on the table.

Answer

Switch from eventually consistent reads to strongly consistent reads.

Question 3

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?

Accepted Answer

Upgrade to a larger instance type, such as db.r5.xlarge.. The db.r5.large instance type has 2 vCPUs and 16 GiB of memory. Sustained CPU utilization above 90% during peak hours indicates that the instance is compute-bound for the workload. Upgrading to db.r5.xlarge (4 vCPUs, 32 GiB memory) doubles the available CPU capacity, directly reducing CPU utilization for the same query load. The on-premises server had similar specifications, but RDS instances may have different CPU architectures or hypervisor overhead, making the larger instance the most direct fix.

Answer

Create a read replica and redirect all SELECT queries to the replica.

Answer

Enable Multi-AZ to offload CPU to the standby instance.

Answer

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

Question 4

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?

Accepted Answer

Review application code to ensure transactions are as short as possible and access tables in a consistent order.. Deadlocks in Aurora MySQL occur when two or more transactions hold locks that the other needs, and they wait indefinitely. The most effective way to reduce deadlocks is to keep transactions short and access tables in a consistent order, which minimizes lock contention and avoids circular wait conditions. This directly addresses the root cause of deadlocks, unlike scaling or redirecting traffic, which only reduce the probability of contention without fixing the underlying locking pattern.

Answer

Increase the instance size to handle more concurrent connections.

Answer

Redirect read traffic to read replicas to reduce load on the writer.

Answer

Enable Multi-AZ to distribute the load.

Question 5

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?

Accepted Answer

The partition key is not evenly distributed.. Option D is correct because the 'ThrottledRequests' metric indicates that requests are being throttled due to partition-level capacity limits. Even with on-demand capacity, DynamoDB imposes a per-partition throughput limit (typically 1,000 WCU or 3,000 RCU per partition). If the partition key 'user_id' is not evenly distributed, a single partition can become a hot key, exceeding its limit and causing throttling despite the table having on-demand capacity.

Answer

The table has on-demand capacity and cannot throttle.

Answer

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

Answer

A global secondary index is consuming write capacity.

Question 6

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?

Accepted Answer

Create a read replica and offload read queries to it.. A is correct because creating a read replica offloads read queries from the primary instance, reducing the read IOPS and read latency on the primary. This directly addresses the high Read Latency and high Read IOPS metrics without requiring a larger instance class or storage change, especially since CPU utilization is low, indicating the bottleneck is I/O, not compute.

Answer

Increase the DB instance class to a larger size, such as db.r5.2xlarge.

Answer

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

Answer

Optimize queries by adding appropriate indexes.

Question 7

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?

Accepted Answer

Whether the application is using Scan operations instead of Query operations.. Option B is correct because Scan operations read the entire table or index before applying filters, consuming far more read capacity than Query operations, which target specific partition and sort key values. If the application is using Scans instead of Queries, it would consistently consume 100% of provisioned capacity even for small result sets, leading to throttling and high utilization.

Answer

Whether autoscaling is configured correctly to add capacity.

Answer

Whether a global secondary index is being used for queries.

Question 8

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?

Accepted Answer

Enable Performance Insights and review the 'DB Connections' metric to identify spikes and troubleshoot application connection pooling. Option C is correct because enabling Performance Insights allows the DBA to monitor the 'DB Connections' metric in near real-time, identify exactly when connection spikes occur, and correlate those spikes with application behavior. This diagnostic approach pinpoints the root cause—such as a connection leak or insufficient connection pooling—without making changes that could degrade performance. Increasing max_connections or lowering wait_timeout without understanding the usage pattern can lead to resource exhaustion or premature connection termination.

Answer

Increase the max_connections parameter to 5000 in the DB parameter group

Answer

Create a read replica to offload read traffic

Answer

Set the 'wait_timeout' parameter to a lower value to close idle connections faster

Question 9

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?

Accepted Answer

The binlog replication to a downstream MySQL instance is falling behind. Option C is correct because the 'AuroraBinlogReplicaLag' metric specifically measures the lag between the Aurora MySQL cluster and an external MySQL instance that is replicating from Aurora using binary log (binlog) replication. When this lag is high, it indicates that the downstream MySQL instance is falling behind in applying binlog events, which can cause write operations on the Aurora cluster to stall or slow down due to the synchronous nature of binlog generation and the need to retain binlogs until they are consumed by the replica.

Answer

The DB cluster has insufficient storage capacity for the binlog files

Answer

The DB cluster has a high CPU utilization that is causing replication lag

Answer

A recent failover event caused the binlog to be replayed from the last checkpoint

Question 10

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?

Accepted Answer

Amazon CloudWatch Contributor Insights for DynamoDB. Amazon CloudWatch Contributor Insights for DynamoDB is the correct tool because it analyzes DynamoDB request logs to identify the most frequently accessed partition keys, including those causing throttling. It provides top-N keys by request count or throttled events, enabling the database specialist to pinpoint hot partitions responsible for increased latency and throttled requests during peak hours.

Answer

Amazon Inspector

Answer

AWS Config

Answer

AWS CloudTrail logs

Question 11

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?

Accepted Answer

The instance has reached the IOPS limit of the gp2 volume. Option B is correct because a consistently high DiskQueueDepth (above 100) on an Amazon RDS for PostgreSQL instance with gp2 storage indicates that the volume is saturating its IOPS limit. gp2 volumes provide a baseline of 3 IOPS per GB (up to 16,000 IOPS), so a 1000 GB gp2 volume has a baseline of 3000 IOPS. When the workload exceeds this baseline, the volume relies on burst credits, and once credits are exhausted, IOPS are throttled to the baseline, causing I/O requests to queue up and the DiskQueueDepth metric to rise.

Answer

Replication lag between the primary and standby instance

Answer

Insufficient memory allocated to the instance

Answer

Network throughput limit is being exceeded

Question 12

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?

Accepted Answer

AWS Database Migration Service (AWS DMS). AWS DMS is the correct service because it is specifically designed for database migrations and provides built-in monitoring of replication lag via the 'CDC latency' metric. Amazon CloudWatch is the correct complementary service because it collects and visualizes DMS metrics, including replication lag and task status, and can trigger alarms if data integrity or latency thresholds are breached.

Answer

Amazon RDS Performance Insights

Answer

AWS Schema Conversion Tool (AWS SCT)

Answer

AWS Glue

Question 13

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?

Accepted Answer

Examine the partition key value distribution to identify hot partitions. Option A is correct because high throttling on write requests in DynamoDB often results from uneven partition key value distribution, creating 'hot partitions' that exceed the per-partition throughput limits. By examining the distribution, the specialist can identify which keys are causing the bottleneck and then apply strategies like write sharding or adjusting the partition key design to spread traffic evenly.

Answer

Change the table to provisioned capacity mode

Answer

Increase the read capacity units on the table

Question 14

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?

Accepted Answer

The user 'app_user' does not have access from host '10.0.1.50'. The error logs show authentication failures despite the password being correct, which indicates the issue is not with the password itself but with the host-based access control. In MySQL, user accounts are defined as 'user'@'host', and if the application is connecting from an IP address (e.g., 10.0.1.50) that is not included in the user's allowed hosts, MySQL will reject the connection with an authentication error even if the password is correct. This is a common misconfiguration when migrating or scaling applications across different subnets.

Answer

The password is incorrect

Answer

The 'app_user' account is locked

Answer

The database requires SSL connections

Question 15

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?

Accepted Answer

Create an Amazon RDS Proxy and configure the application to connect to the proxy endpoint. Amazon RDS Proxy sits between the application and the database, pooling and reusing database connections. During a failover, RDS Proxy maintains the client connections and transparently reconnects to the new primary instance, so the application does not experience a connection loss and does not need to implement retry logic. This directly addresses the 10-minute outage by reducing failover downtime to seconds, meeting the 99.99% SLA without application code changes.

Answer

Increase the DB instance class to a larger size to improve performance and reduce failover time

Answer

Enable Multi-AZ deployment with automatic failover

Answer

Create a cross-Region read replica and promote it to primary during failover

Question 16

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?

Accepted Answer

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 correct answer is A. The 'CPUCreditBalance' dropping to near zero on a T3 instance indicates CPU credit exhaustion, which throttles the baseline CPU performance and causes query latency spikes. Even though 'CPUUtilization' is below 50%, T3 instances rely on CPU credits for burstable performance; when credits are exhausted, the instance is limited to the baseline (e.g., 10% for t3.medium), causing severe latency increases for simple SELECT statements. Moving to a dedicated CPU instance like db.r5.large eliminates credit-based throttling and provides consistent performance.

Answer

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.

Answer

The issue is caused by a connection pool exhaustion. Increase the max_connections parameter and use connection pooling.

Answer

The issue is caused by a missing index on the 'orders' table. Add a composite index on the columns used in the WHERE clauses.

Question 17

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.)

Accepted Answer

Review the slow query log to identify long-running queries.. Option B is correct because reviewing the slow query log directly identifies long-running queries that can cause sustained high CPU usage on RDS for PostgreSQL. Option D is correct because Performance Insights provides a visual dashboard of database load and top SQL queries, making it easy to pinpoint which queries are consuming the most CPU resources.

Answer

Enable Enhanced Monitoring and review OS process list.

Answer

Scale up the DB instance to a larger instance class.

Answer

Install pg_stat_statements extension and query it.

Question 18

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?

Accepted Answer

Implement write sharding by adding a random suffix to the partition key to distribute writes more evenly.. The correct answer is A because the throttling is caused by a hot partition: the table uses a single partition key, and writes are heavily skewed toward a few keys. By adding a random suffix to the partition key (write sharding), the writes are distributed evenly across all partitions, eliminating hot spots and reducing throttling. The on-demand capacity mode already handles overall throughput, but it cannot prevent throttling on individual partitions when access is skewed.

Answer

Increase the provisioned read capacity units to handle the load.

Answer

Switch the table to provisioned capacity mode and increase write capacity.

Answer

Enable DynamoDB Accelerator (DAX) to cache write operations.

Question 19

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

Question 20

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