DBS-C01 Monitoring and Troubleshooting Practice Test 27 — 15 Questions

Question 1

A logistics company runs an Amazon RDS for SQL Server Multi-AZ instance. During a nightly batch job, the application experiences a brief outage and the RDS console shows a failover event. After the failover, the application reconnects to the new primary, but the database specialist notices that the old primary's endpoint now resolves to the standby. Which statement correctly describes what happened and how the application should be configured?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The CNAME record for the DB instance endpoint was updated to point to the new primary, and the application should continue using the same endpoint name.. In RDS Multi-AZ, the DB instance endpoint is a DNS name that RDS repoints to the new primary after failover. Applications should connect using that endpoint rather than a fixed IP or instance-specific address, so they recover automatically. The observed behavior — the old primary's address now resolving to the standby — is exactly the expected DNS update.

Answer

The failover was triggered by the batch job exceeding the maximum allowed connections, and the application should use RDS Proxy to prevent future failovers.

Answer

The standby became the new primary only after a manual promotion, and the application must update its connection string to the standby's endpoint.

Answer

The application must be reconfigured with the new primary's IP address because the endpoint name is permanently associated with the old primary.

Question 2

A database specialist is investigating an Amazon Aurora MySQL DB cluster where the application reports intermittent connection timeouts. The specialist notices that the number of connections to the writer instance spikes dramatically every hour. Which metric in Amazon CloudWatch should be reviewed FIRST to determine if the DB cluster is hitting the maximum connection limit?

Accepted Answer

DatabaseConnections. The DatabaseConnections metric in Amazon CloudWatch tracks the number of active connections to an Aurora DB instance. Since the application experiences timeouts during hourly connection spikes, this metric will reveal if the cluster is reaching its maximum connection limit. Other metrics like CPU or memory might show secondary effects, but DatabaseConnections is the direct measure of connection count and is the first to check.

Answer

CPUUtilization

Answer

DiskQueueDepth

Answer

FreeableMemory

Question 3

A database specialist is monitoring an Amazon DynamoDB table that uses on-demand capacity mode. The table has a global secondary index (GSI) with a partition key of 'status' and a sort key of 'timestamp'. The application performs frequent queries on the GSI, and the specialist notices that the GSI's consumed read capacity is much higher than the base table's. CloudWatch metrics show that the GSI has a high number of ThrottledRequests. What is the most likely cause of the throttling on the GSI?

Accepted Answer

The GSI's partition key 'status' has a low cardinality, causing hot partitions and uneven read distribution.. In DynamoDB, a global secondary index with a low-cardinality partition key leads to hot partitions because many items share the same partition key value. Even in on-demand mode, DynamoDB applies per-partition throughput limits, and a single partition cannot exceed those limits. This results in throttling on the GSI despite the table being in on-demand mode. The high consumed read capacity on the GSI relative to the base table indicates that queries are concentrated on a few partitions.

Answer

The GSI's sort key 'timestamp' is causing all reads to target the same partition because timestamps are similar.

Answer

The GSI is using eventual consistency, which requires additional read capacity and causes throttling.

Answer

The GSI's write capacity is not provisioned separately from the base table, causing write throttling that affects reads.

Question 4

A database specialist manages an Amazon Aurora MySQL DB cluster. Users report that queries against a reader instance intermittently return stale data, even though the application connects to the reader endpoint and the cluster has two Aurora Replicas. The specialist wants to quantify the replication delay and confirm whether the replicas are lagging. Which metric should the specialist monitor in Amazon CloudWatch to directly measure Aurora replica lag?

Accepted Answer

AuroraReplicaLag. The AuroraReplicaLag metric is specifically designed to report replication delay for Aurora Replicas in milliseconds. When applications read from a reader endpoint and observe stale data, the most direct way to confirm replica lag is to monitor this metric per replica. It distinguishes replication delay from other performance issues such as storage throughput or network traffic, enabling targeted remediation.

Answer

NetworkReceiveThroughput

Answer

DiskQueueDepth

Answer

BinLogDiskUsage

Question 5

A database specialist needs to audit all login attempts and failed authentication events on an Amazon Aurora MySQL DB cluster. The events must be retained for one year and searchable for security investigations. Which approach meets these requirements?

Accepted Answer

Enable Aurora MySQL advanced auditing, publish the audit logs to Amazon CloudWatch Logs, and set a one-year retention period on the log group.. Aurora MySQL advanced auditing records connection and failed-login events, and publishing those logs to CloudWatch Logs makes them centrally searchable while a one-year retention setting preserves them for investigations. General logs, Performance Insights, and error-log exports do not capture authentication events or provide the required retention and search capability.

Answer

Enable Performance Insights with a one-year retention period and query the authentication events from its dashboard.

Answer

Enable the MySQL general_log parameter on the DB cluster and query the log tables directly in the database.

Answer

Configure the DB cluster to export error logs to Amazon S3 and enable S3 server access logging for auditing.

Question 6

A company uses Amazon ElastiCache for Redis to cache session data for a web application. The operations team reports that the cache hit ratio has dropped from 95% to 70% over the past week, and application latency has increased. The Redis cluster is running in cluster mode with 3 shards. The team needs to identify the cause of the decreased hit ratio. Which action should the team take first to diagnose the issue?

Accepted Answer

Monitor the Evictions and CurrItems CloudWatch metrics for each shard to check for increased evictions.. A drop in cache hit ratio often stems from increased evictions due to memory pressure. Monitoring Evictions and CurrItems per shard reveals whether keys are being removed prematurely. Other metrics like slow log or replication lag do not directly explain missing keys. Checking cache hits/misses confirms the symptom but not the cause.

Answer

Check the ReplicationLag metric to see if replica lag is causing stale reads.

Answer

Analyze the ElastiCache Redis slow log to identify slow commands that might be causing evictions.

Answer

Review the CacheHits and CacheMisses metrics to determine if the application is requesting more unique keys.

Question 7

A company uses Amazon Aurora MySQL. They have enabled the audit log and exported it to Amazon CloudWatch Logs. A security analyst needs to search for all failed login attempts in the last 24 hours. Which approach is most efficient?

Accepted Answer

Use CloudWatch Logs Insights to query the Aurora MySQL audit log group for patterns indicating failed logins.. CloudWatch Logs Insights is a powerful query tool that can search and analyze log data in CloudWatch Logs. By querying the Aurora MySQL audit log group, the analyst can efficiently filter for failed login attempts within the last 24 hours using patterns or specific fields. Other methods either lack the data (performance_schema, CloudTrail) or are inefficient and manual (downloading and grepping). Thus, Logs Insights is the correct and most efficient approach.

Answer

Query the Aurora MySQL performance_schema tables for login failures.

Answer

Use AWS CloudTrail to search for Aurora MySQL login events in the last 24 hours.

Answer

Download the audit log files from CloudWatch Logs and grep them on an Amazon EC2 instance.

Question 8

A database specialist is monitoring an Amazon DynamoDB table that uses on-demand capacity mode. The application experiences sudden traffic surges, and the specialist observes throttling errors in CloudWatch metrics. Which of the following is the MOST likely cause of the throttling?

Accepted Answer

The table has a hot partition due to uneven access patterns.. In on-demand capacity mode, DynamoDB automatically scales to handle traffic, but it cannot instantly split a partition to handle a sudden surge on a single partition key. If the workload has a hot partition, that partition can exceed its throughput limit, causing throttling. The other options incorrectly assume provisioned capacity or item limits, which do not apply in on-demand mode.

Answer

The table has exceeded the maximum number of items allowed.

Answer

The table's global secondary index is under-provisioned.

Answer

The table's provisioned read/write capacity is set too low.

Question 9

A database administrator is managing an Amazon RDS for MySQL DB instance. They need to identify the top SQL statements that are consuming the most CPU over the past hour to optimize performance. The DB instance has Performance Insights enabled with a retention period of 7 days. Which action should the administrator take to quickly identify the top SQL statements?

Accepted Answer

Use the Performance Insights dashboard to view the Top SQL tab and sort by DB load.. Performance Insights is designed to help identify performance bottlenecks by providing a Top SQL view that ranks statements by database load, which is a proxy for resource consumption such as CPU. With Performance Insights enabled and a 7-day retention, the administrator can immediately view the top SQL statements over the past hour without additional configuration.

Answer

Query the information_schema.PROCESSLIST table to see currently running queries.

Answer

Enable the slow query log and use the mysql.slow_log table to find queries with high execution time.

Answer

Use Amazon CloudWatch Logs Insights to analyze the error log for CPU-related messages.

Question 10

A company runs an Amazon RDS for SQL Server DB instance in a Multi-AZ deployment. The database specialist needs to monitor the health and performance of the database and set up alerts for potential issues. The specialist wants to use Amazon CloudWatch metrics and alarms. Which two CloudWatch metrics should the specialist monitor to detect insufficient memory and excessive disk I/O on the RDS instance? (Choose two.)

Accepted Answer

FreeableMemory. FreeableMemory directly indicates available memory; low values signal memory pressure. DiskQueueDepth measures outstanding disk I/O requests; high values indicate disk bottlenecks. Together, they provide the necessary insight into memory and disk I/O health. Other metrics like CPUUtilization, NetworkReceiveThroughput, and DatabaseConnections are useful but do not specifically address the two issues the specialist wants to detect.

Answer

CPUUtilization

Answer

DatabaseConnections

Answer

NetworkReceiveThroughput

Question 11

A company uses Amazon DynamoDB with on-demand capacity mode for a new application. During a load test, the application occasionally receives HTTP 400 errors with the code ProvisionedThroughputExceededException, even though the table is in on-demand mode. A database specialist must explain why throttling can still occur and which factor is most likely responsible. What is the most likely cause?

Accepted Answer

The table's partition key is monotonically increasing, causing a hot partition that exceeds the per-partition throughput limit.. On-demand mode automatically scales table capacity, but it still enforces per-partition throughput limits. A monotonically increasing partition key creates a hot partition, and bursts that exceed that partition's ceiling are throttled. This explains why throttling occurs despite on-demand mode and points to partition key design as the root cause.

Answer

The application is using eventually consistent reads instead of strongly consistent reads.

Answer

The table has exceeded the maximum number of items allowed in on-demand mode.

Answer

The table's auto scaling policy is misconfigured and has set the maximum capacity too low.

Question 12

A database specialist is investigating why an Amazon RDS for SQL Server DB instance is experiencing slow query performance. The specialist notices that the CPU utilization is high and there are many PAGEIOLATCH_SH waits. Which action should the specialist take to improve performance?

Accepted Answer

Scale up the DB instance class to one with more memory and higher IOPS.. PAGEIOLATCH_SH waits indicate that SQL Server is waiting for data pages to be read from disk into memory. This is typically caused by insufficient memory or slow disk I/O. Scaling up the DB instance to a class with more memory and higher IOPS can reduce these waits by allowing more data to be cached in memory and improving disk read speeds. This directly addresses the root cause of the performance issue.

Answer

Increase the allocated storage size for the DB instance.

Answer

Modify the DB parameter group to increase the max degree of parallelism (MAXDOP).

Answer

Enable Multi-AZ for the DB instance to offload read traffic.

Question 13

A database specialist is monitoring an Amazon RDS for SQL Server DB instance using Amazon CloudWatch. The specialist notices that the FreeStorageSpace metric is decreasing rapidly, and the instance is approaching its storage limit. The specialist needs to identify the cause of the rapid storage consumption. Which action should the specialist take to diagnose the issue?

Accepted Answer

Query the sys.dm_db_file_space_usage and sys.dm_db_log_space_usage DMVs to check space usage by file and log.. The DMVs sys.dm_db_file_space_usage and sys.dm_db_log_space_usage provide granular details about space usage within database files and transaction logs. They can pinpoint which database or log is growing, such as due to a large transaction or insufficient log backups. This is the most direct way to diagnose rapid storage consumption on RDS for SQL Server.

Answer

Check the CloudWatch metric DiskQueueDepth to see if there is a backlog of disk operations.

Answer

Review the RDS event log for messages about storage autoscaling being triggered.

Answer

Enable RDS Enhanced Monitoring and analyze the disk I/O metrics to identify high write activity.

Question 14

A company uses an Amazon Aurora MySQL cluster with a writer and a reader. They notice that the reader's replica lag is increasing, and the application is reading stale data. The database specialist needs to identify the cause of the replica lag. Which action should the specialist take first?

Accepted Answer

Check the 'AuroraReplicaLag' metric in Amazon CloudWatch for the reader instance.. AuroraReplicaLag is the primary CloudWatch metric for monitoring lag between the writer and a reader in Aurora. It directly shows the lag in milliseconds. Other metrics like VolumeReadIOPs or CPUUtilization can indicate causes but are not direct measures. Using 'SHOW REPLICA STATUS' is invalid for Aurora. Therefore, checking AuroraReplicaLag is the correct first step.

Answer

Query the 'SHOW REPLICA STATUS' command on the reader instance.

Answer

Review the 'VolumeReadIOPs' metric for the reader instance.

Answer

Inspect the 'CPUUtilization' metric for the reader instance.

Question 15

A database specialist manages an Amazon Aurora MySQL DB cluster with a single writer and two reader instances. During peak hours, the application experiences intermittent connection timeouts when connecting to the cluster writer endpoint. CloudWatch metrics show that the writer's CPU is at 45%, freeable memory is stable, and there are no long-running queries. The specialist needs to identify the cause of the connection timeouts. Which action should the specialist take to diagnose the issue?

Accepted Answer

Check the Aurora cluster's parameter group for the max_connections setting and compare it to the number of active connections.. Intermittent connection timeouts to an Aurora MySQL writer with low CPU and stable memory frequently point to the max_connections limit being reached. The max_connections parameter in Aurora MySQL is tied to the instance class, and when the number of concurrent connections hits that ceiling, new connection attempts are refused or time out. Checking this parameter against the current connection count is the most direct way to confirm the cause.

Answer

Enable Performance Insights on the writer instance and analyze the database load by wait events.

Answer

Increase the instance size of the writer to a larger class to provide more CPU and memory resources.

Answer

Review the Aurora cluster's error log for messages about aborted connections and restart the writer instance.