DBS-C01 Monitoring and Troubleshooting Practice Test 14 — 15 Questions

Question 1

A company has an Amazon Aurora MySQL DB cluster with one writer and two readers. The application is experiencing high read latency. CloudWatch shows that the 'AuroraBinlogReplicaLag' metric is high for one of the reader instances. What is the most likely cause?

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

Accepted Answer

The reader instance is not keeping up with the write workload from the writer. The 'AuroraBinlogReplicaLag' metric measures the lag between the writer and a reader when using binary log replication. A high value indicates that the reader is not applying changes from the writer quickly enough, causing read latency. This is typically because the reader instance is not keeping up with the write workload from the writer. Option A is incorrect because Aurora storage is shared and not the cause of replication lag. Option C is incorrect; while an undersized reader can contribute to lag, the primary cause is the reader not keeping pace with writes, not necessarily size. Option D is incorrect because parameter groups affect settings but not replication lag directly.

Answer

The Aurora cluster storage is experiencing high I/O latency

Answer

The reader instance is undersized and needs to be scaled up

Answer

The DB cluster parameter group is misconfigured

Question 2

An application running on Amazon EC2 is unable to connect to an Amazon RDS for SQL Server DB instance. The security group for the RDS instance allows inbound traffic from the security group of the EC2 instance on port 1433. The network ACLs allow all traffic. What is a likely cause of the connectivity issue?

Accepted Answer

The RDS instance is in a private subnet and does not have a public IP address. If the RDS instance is in a private subnet without a public IP address, the EC2 instance cannot connect using the public DNS endpoint unless the EC2 is in the same VPC. Since the security group and network ACLs are correctly configured, the most likely cause is that the RDS instance is not publicly accessible and the EC2 instance is attempting to connect from outside the VPC or via the public endpoint. Option B is wrong because network ACLs allow all traffic. Option C is wrong because the security group inbound rule is correctly configured to allow traffic from the EC2 security group on port 1433. Option D is wrong because port 1433 is the default SQL Server port, and if it were not, the error message would indicate a timeout, not a connectivity issue.

Answer

The network ACL is blocking the traffic

Answer

The security group inbound rule is incorrectly configured

Answer

The database port is not 1433

Question 3

A company is running an Amazon DynamoDB table with on-demand capacity. The application is experiencing high latency for GetItem operations. CloudWatch shows that 'ThrottledRequests' is zero, but 'ConsumedReadCapacityUnits' is consistently below the provisioned limit. The table has a global secondary index (GSI) with a different partition key. What is the most likely cause of the high latency?

Accepted Answer

Throttling on the base table due to hot partitions. While throttling on a Global Secondary Index (GSI) can cause backpressure and affect writes to the base table, it does not directly impact read operations like GetItem. In this scenario, with zero ThrottledRequests, throttling is not occurring on the base table or GSI. The high latency is more likely caused by a hot partition on the base table, which can still result in increased response times even before throttling metrics are triggered. Option C is therefore incorrect; the correct answer is D.

Answer

High write activity on the base table causing read latency

Answer

Insufficient provisioned read capacity on the base table

Answer

Throttling on the global secondary index due to uneven access patterns

Question 4

A company's Amazon RDS for MySQL DB instance is experiencing high CPU utilization. The DB instance is a db.r5.large with 200 GB of General Purpose SSD (gp2) storage. The application is performing many complex queries. Which action would BEST reduce CPU utilization without changing the application code?

Accepted Answer

Scale up the DB instance to db.r5.xlarge. Scaling up the DB instance to db.r5.xlarge provides more CPU capacity, directly reducing CPU utilization. Option A is wrong because read replicas help with read scaling but do not reduce CPU on the writer instance. Option B is wrong because changing storage type to gp3 does not affect CPU. Option D is wrong because the query cache is deprecated in MySQL 8.0 and its impact on CPU is minimal for complex queries.

Answer

Create a read replica and route write queries to it

Answer

Modify the storage type to gp3

Answer

Enable the query cache parameter

Question 5

A company is using Amazon Redshift for data warehousing. The data engineering team notices that queries are running slower than expected. CloudWatch shows that 'CPUUtilization' is high and 'DiskSpaceUsage' is also high. The cluster has 4 dc2.large nodes. What is the most likely cause of the performance degradation?

Accepted Answer

Queries are spilling to disk due to insufficient memory. High CPU and high disk space usage on dc2.large nodes are classic signs of queries spilling to disk due to insufficient memory. When there isn't enough memory for query processing, Redshift resorts to writing intermediate results to disk, which increases disk space usage and also causes high CPU as the system manages the spill. Option A is insufficient network bandwidth: network bandwidth issues would typically manifest as increased network throughput or latency metrics, not high CPU and disk usage. Option B is CPU bottleneck: while CPU is high, the simultaneous high disk usage suggests the root cause is memory spilling, not CPU exhaustion alone. Adding compute nodes would not address the memory spilling if the workload is memory-intensive; instead, increasing the node size or using a different instance type with more memory per node would help. Option C is WLM queue: WLM queue waits would be visible in CloudWatch metrics like 'WLMQueueLength' or 'QueryWaitTime', not in CPU or disk usage.

Answer

Insufficient network bandwidth between nodes

Answer

CPU is the bottleneck and needs more compute nodes

Answer

Workload management (WLM) queue is causing query waits

Question 6

A company is running an Amazon DynamoDB table with provisioned capacity. The table has a partition key of 'user_id' and a sort key of 'timestamp'. The application performs frequent Query operations using the partition key and a range of sort keys. Recently, the 'ThrottledRequests' metric has spiked. The read and write capacity units are consistently at 80% utilization. What is the most effective way to resolve the throttling?

Accepted Answer

Change the partition key to a more uniformly distributed attribute. The throttling is likely due to uneven access patterns creating hot partitions. By changing the partition key to a more uniformly distributed attribute, the load is spread evenly across partitions, reducing throttling without needing to increase capacity. Option D is incorrect because enabling Auto Scaling with a higher target utilization delays scaling and can worsen throttling on hot partitions; it does not address the root cause. Option A is incorrect because increasing capacity may not help if a hot partition is throttled, and it increases costs. Option B is incorrect because adding a GSI does not reduce throttling on the base table; it only provides an alternative access pattern.

Answer

Increase the provisioned read and write capacity units

Answer

Add a global secondary index with a different partition key

Answer

Enable DynamoDB Auto Scaling with a higher target utilization

Question 7

A company is using Amazon RDS for PostgreSQL and needs to monitor the database for performance issues. Which TWO metrics in Amazon CloudWatch are most useful for identifying I/O bottlenecks?

Accepted Answer

ReadIOPS. Options A and C are correct. ReadIOPS (Option A) shows the actual number of read I/O operations per second, which is a direct indicator of I/O load. DiskQueueDepth (Option C) measures the number of pending I/O requests, indicating I/O contention or bottlenecks when the queue depth is high. Option B (FreeStorageSpace) is about storage capacity, not performance. Option D (DatabaseConnections) reflects connection count, not I/O. Option E (CPUUtilization) relates to compute, not I/O.

Answer

FreeStorageSpace

Answer

DatabaseConnections

Answer

CPUUtilization

Question 8

A company's Amazon Aurora MySQL DB cluster is experiencing a failover event. Which THREE metrics in CloudWatch should be examined to understand the cause of the failover?

Accepted Answer

ACUUtilization. (ACUUtilization) is correct because high ACU utilization can indicate resource exhaustion (CPU/memory pressure) that may trigger a failover in Aurora. Option D (DatabaseConnections) is correct because a sudden spike or drop in connections could signal issues like connection exhaustion or application failures that lead to failover. Option E (FailoverCount) is correct because this metric directly tracks the number of failover events; examining the timestamp of the last increment helps correlate with the incident. Option B (ReadLatency) is wrong because while high read latency can be a symptom, it is not a direct cause of failover; Aurora uses different mechanisms for read scaling. Option C (BinLogDiskUsage) is wrong because it relates to binary log storage for replication, not a direct trigger for failover.

Answer

ReadLatency

Answer

BinLogDiskUsage

Question 9

A company is troubleshooting an Amazon DynamoDB table that is experiencing high latency. The table uses on-demand capacity. Which TWO steps should be taken to diagnose the issue?

Accepted Answer

Examine CloudWatch metrics for throttling and latency patterns. CloudWatch metrics for DynamoDB can show throttling events, latency patterns, and consumed throughput, which help diagnose high latency issues. Option C is correct because DynamoDB Accelerator (DAX) provides an in-memory cache that can significantly reduce read latency for frequently accessed items. Option A is incorrect because the table uses on-demand capacity, so adjusting provisioned capacity is not applicable. Option D is incorrect because disabling TTL does not directly reduce write overhead or latency. Option E is incorrect because DynamoDB handles partitions automatically and manual splitting is not supported.

Answer

Increase the provisioned read capacity

Answer

Disable TTL to reduce write overhead

Answer

Split the table into multiple partitions manually

Question 10

A company's Amazon Redshift cluster is experiencing slow query performance. Which THREE diagnostic steps should be taken to identify the bottleneck?

Accepted Answer

Query SVL_QUERY_REPORT to see step-level performance. To diagnose slow query performance in Amazon Redshift, you should query SVL_QUERY_REPORT to view step-level execution details (Option B), STL_QUERY to analyze query execution times (Option C), and STL_WLM_QUERY to check for WLM queue waits (Option D). Option A is incorrect because STL_LOAD_ERRORS is used for data load errors, not performance. Option E is incorrect because STV_BLOCKLIST shows disk block allocation, which is not directly related to query performance.

Answer

Query STL_LOAD_ERRORS to check for data load errors

Answer

Query STV_BLOCKLIST to check disk allocation

Question 11

A company is experiencing slow query performance on an Amazon RDS for PostgreSQL DB instance. The DB instance is a db.r5.large with 16 GB RAM and 500 GB gp2 storage. Which metric in Amazon CloudWatch would most directly help identify if the performance issue is due to memory pressure?

Accepted Answer

Monitor FreeableMemory to see if available memory is low.. FreeableMemory shows the amount of available RAM. Low FreeableMemory indicates memory pressure, which can cause swapping and slow queries. Option B is wrong because ReadIOPS measures I/O operations, not memory. Option C is wrong because DatabaseConnections tracks connections, not memory. Option D is wrong because CPUUtilization measures CPU, not memory.

Answer

Monitor ReadIOPS to see if there is a high I/O rate due to swapping.

Answer

Monitor DatabaseConnections to check for a high number of connections consuming memory.

Answer

Monitor CPUUtilization to check for high CPU usage.

Question 12

A developer reports that an application is unable to connect to an Amazon RDS for MySQL DB instance. The security group for the DB instance allows inbound traffic on port 3306 from the application server's security group. The DB instance is in a VPC with both public and private subnets. The application server is in a private subnet. What is the most likely cause of the connection failure?

Accepted Answer

The network ACL for the private subnet is blocking outbound traffic to the DB instance.. The most likely cause is that the network ACL (NACL) for the private subnet is blocking outbound traffic to the DB instance. Security groups are stateful and allow return traffic automatically, but NACLs are stateless and require explicit rules for both inbound and outbound. If the private subnet's NACL does not allow outbound traffic to the DB instance's subnet on port 3306, the application server cannot initiate the connection. Options A and B are incorrect because the security group already allows inbound traffic, and instances in public and private subnets within the same VPC can communicate via private IPs. Option D is incorrect; while a DB subnet group is required for RDS, it does not directly affect connectivity once the instance is running.

Answer

The DB instance is in a public subnet and the application server is in a private subnet, so they cannot communicate.

Answer

The security group for the DB instance does not allow inbound traffic from the application server's security group.

Answer

The DB instance is not part of a DB subnet group that includes the private subnet.

Question 13

A company uses Amazon DynamoDB with auto scaling enabled. The application experiences increased latency during peak hours. The DynamoDB table has a read capacity of 10,000 RCU and write capacity of 5,000 WCU. The auto scaling target utilization is 70%. During peak hours, the consumed read capacity reaches 8,000 RCU, but auto scaling does not increase capacity. What is the most likely reason?

Accepted Answer

The auto scaling configuration has a maximum capacity that prevents scaling beyond a certain limit.. Auto scaling in DynamoDB adjusts capacity based on consumed capacity relative to provisioned capacity. With a target utilization of 70%, the expected consumed capacity for 10,000 RCU is 7,000 RCU. However, the actual consumed capacity is 8,000 RCU, which is 80% utilization, above the target. Auto scaling should normally increase capacity to bring utilization back to 70%. But if the auto scaling configuration has a maximum read capacity limit (e.g., 8,000 RCU), scaling cannot exceed that limit, explaining why capacity does not increase. Option A is incorrect because auto scaling can trigger even before throttling occurs. Option C is incorrect because auto scaling can increase both read and write capacity. Option D is incorrect because auto scaling scales based on sustained consumption above target utilization, not necessarily exceeding provisioned capacity.

Answer

The consumed capacity is still below the provisioned capacity, so no throttling occurs, and auto scaling does not trigger.

Answer

Auto scaling for DynamoDB does not support increasing read capacity; it only decreases capacity.

Answer

Auto scaling only scales out when the consumed capacity exceeds the provisioned capacity.

Question 14

A database administrator is troubleshooting a failover event for an Amazon RDS for SQL Server Multi-AZ DB instance. The failover occurred automatically. Which AWS service or feature should the administrator use to view the failover history and the reason for the failover?

Accepted Answer

The Amazon RDS console Events page.. The Amazon RDS console Events page stores RDS events, including failover events with reasons. This is the best place to view failover history and reason. CloudTrail records API calls but not internal failover reasons. CloudWatch Logs does not automatically log failover reasons. The AWS Status Dashboard shows service health, not instance-specific failover history.

Answer

Amazon CloudWatch Logs for the DB instance.

Answer

AWS CloudTrail logs to view the failover API call.

Answer

The AWS Status Dashboard.

Question 15

A company notices that its Amazon DynamoDB table is consuming more read capacity than expected. The table has a global secondary index (GSI) with a different sort key. Which action would most likely reduce the read consumption?

Accepted Answer

Enable DAX (DynamoDB Accelerator) to cache read results.. Enabling DynamoDB Accelerator (DAX) caches read results from the DynamoDB table, reducing the number of reads that consume read capacity units (RCUs). When the table has a GSI, reads that use the GSI also consume RCUs from the index. DAX can cache both base table and index reads, thereby lowering overall read consumption. Option A is incorrect because increasing write capacity does not affect read consumption. Option C is incorrect because changing the sort key does not directly reduce read capacity usage. Option D is incorrect because a local secondary index (LSI) uses the same partition key and does not help reduce read consumption from a GSI.

Answer

Increase the write capacity of the table.

Answer

Change the sort key of the base table to match the GSI sort key.

Answer

Create a local secondary index (LSI) with the same sort key as the GSI.