DBS-C01 Monitoring and Troubleshooting Practice Test 18 — 15 Questions

Question 1

A company uses Amazon RDS for MySQL with Multi-AZ deployment. The database experiences intermittent write latency spikes. CloudWatch shows elevated 'WriteLatency' and 'WriteIOPS' but normal 'CPUUtilization'. Which is the MOST likely cause?

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

Accepted Answer

The instance is exceeding the provisioned IOPS burst balance. Intermittent write latency spikes with high WriteIOPS and normal CPU utilization indicate storage performance issues. For RDS MySQL using gp2 or io1 storage, exceeding the provisioned IOPS burst balance (for gp2) or provisioned IOPS (for io1) causes throttling and increased latency. Option A is incorrect because parameter group changes require a reboot and affect all operations, not just intermittent writes. Option C is incorrect because read replicas are read-only and cannot be used for write operations. Option D is incorrect because Multi-AZ replication uses synchronous standby replication, which typically does not cause noticeable write latency spikes; latency from replication is usually minimal.

Answer

A parameter group change was applied without rebooting

Answer

A read replica is being used for write operations

Answer

Multi-AZ replication is causing synchronous writes to the standby

Question 2

A DevOps engineer notices that an Amazon DynamoDB table's read capacity is frequently throttled during peak hours. The table has read-once, read-many workload. Which action is MOST cost-effective to reduce throttling?

Accepted Answer

Enable DynamoDB Accelerator (DAX). DynamoDB Accelerator (DAX) caches frequently read items, reducing the number of read requests to the table. For a read-once, read-many workload, this significantly lowers read capacity consumption, thus reducing throttling cost-effectively. Option A is incorrect: Enabling auto-scaling for read capacity would help reduce throttling by automatically adjusting capacity, but it does not reduce the number of reads; it increases capacity when needed, which can be more expensive than using DAX. Option C is incorrect: Switching to On-Demand capacity mode eliminates throttling by paying per request, but for a predictable, high-read workload, this is typically more expensive than provisioned capacity with DAX. Option D is incorrect: Increasing the provisioned read capacity units would reduce throttling, but it increases cost because you pay for higher capacity even during off-peak hours. DAX is more cost-effective as it reduces the required capacity.

Answer

Enable auto-scaling for read capacity

Answer

Switch to On-Demand capacity mode

Answer

Increase the provisioned read capacity units

Question 3

A database specialist is troubleshooting an Amazon Aurora MySQL cluster. The writer instance's CPU is at 90% and there are frequent 'Lock wait timeout exceeded' errors. The application uses many short-lived connections. What should the specialist do FIRST to reduce lock contention?

Accepted Answer

Enable RDS Proxy to pool database connections. Enabling RDS Proxy reduces connection churn by pooling database connections, which decreases the number of concurrent transactions competing for locks, thereby reducing lock contention. Option A is incorrect because adding read replicas does not address write lock contention on the writer instance. Option B is incorrect although increasing instance size can help with CPU, it does not directly reduce lock contention and may even exacerbate it by allowing more transactions. Option D is incorrect because reducing the maximum number of connections can actually increase contention per connection as the same workload is funneled through fewer connections.

Answer

Add additional read replicas to distribute read traffic

Answer

Increase the instance size to handle more concurrent transactions

Answer

Reduce the maximum number of connections in the application

Question 4

A developer reports that an Amazon ElastiCache for Redis cluster's memory usage is consistently above 90%. The application uses Redis for caching and session storage. Which configuration change would MOST effectively reduce memory pressure?

Accepted Answer

Enable eviction with volatile-LRU policy. Enabling eviction with the volatile-LRU policy automatically removes the least recently used keys that have a TTL set, freeing memory without manual intervention. Option B (scaling up) reduces memory pressure but at higher cost; it is not the most effective change since eviction addresses the root cause by discarding stale data. Option C (AOF persistence) writes data to disk, not freeing memory; it can actually increase memory usage during writes. Option D (disabling replication) may free some memory used for replica buffers but does not address the high memory utilization caused by cached data, and it impacts availability.

Answer

Scale up to a larger node type

Answer

Enable AOF persistence to free memory

Answer

Disable replication to reduce memory overhead

Question 5

A database specialist is monitoring an Amazon DynamoDB global table with two replicas in separate regions. The specialist notices that the 'ReplicatedWriteConflictCount' metric is increasing. What is the MOST likely cause?

Accepted Answer

The same item is being written concurrently in multiple regions. Concurrent writes to the same item in different regions cause conflicts. Option A is wrong because provisioned throughput affects throttling, not conflicts. Option B is wrong because network latency does not cause conflicts. Option C is wrong because eventual consistency does not cause conflicts.

Answer

Insufficient write capacity in one of the regions

Answer

High network latency between the regions

Answer

The application is using strongly consistent reads

Question 6

A company uses Amazon RDS for PostgreSQL with logical replication to a downstream system. The replication slot grows unbounded and causes storage full issues. Which action resolves this without data loss?

Accepted Answer

Monitor the replication slot and advance it using pg_replication_slot_advance. Monitoring and advancing the replication slot prevents WAL accumulation. Option A is wrong because disabling replication causes data loss. Option B is wrong because increasing storage is a temporary fix, not a resolution. Option D is wrong because deleting old WAL logs may break replication.

Answer

Disable logical replication and use DMS instead

Answer

Increase the allocated storage size of the RDS instance

Answer

Delete the replication slot and recreate it

Question 7

A developer is troubleshooting slow queries in Amazon RDS for MySQL. The 'Threads_running' status variable is consistently above 200. The application uses connection pooling. Which metric should be monitored to identify the root cause?

Accepted Answer

Innodb_row_lock_current_waits. High 'Threads_running' consistently above 200 often indicates queries waiting on locks or I/O. 'Innodb_row_lock_current_waits' directly measures the number of row lock waits, which is a common cause of blocked queries when connection pooling is used. Option B is wrong because 'Queries_per_second' measures throughput, not concurrent active queries. Option C is wrong because 'Slow_queries' counts only queries exceeding a time threshold, not all concurrent queries. Option D is wrong because 'Threads_connected' shows the number of open connections, not necessarily active queries; with connection pooling, many connections may be idle.

Answer

Queries_per_second

Answer

Slow_queries

Answer

Threads_connected

Question 8

A company uses Amazon Redshift for data warehousing. A nightly ETL job fails with 'Disk full' error on some nodes. The cluster has 8 dc2.large nodes. Which action will MOST efficiently resolve the issue without increasing costs?

Accepted Answer

Run a VACUUM command to reclaim space. Running a VACUUM command on Amazon Redshift reclaims storage space from deleted or updated rows without incurring additional costs. Option A is wrong because increasing the number of slices per node is not possible with dc2.large nodes; slice count is fixed per node type. Option B is wrong because adding more nodes would increase costs and is not the most efficient solution. Option C is wrong although enabling compression reduces storage usage over time, it requires a table redesign and does not immediately free space to resolve the immediate 'Disk full' error.

Answer

Increase the number of slices per node

Answer

Add more nodes to the cluster

Answer

Enable compression on all tables

Question 9

A database specialist is troubleshooting an Amazon RDS for SQL Server instance that is experiencing high CPU utilization. The instance has multiple databases. Which TWO actions should the specialist take to identify the cause?

Accepted Answer

Use Performance Insights to identify top SQL queries. Options B and E are correct because Performance Insights helps identify top SQL queries causing high CPU, and Enhanced Monitoring provides OS-level metrics (like CPU utilization per database process) to pinpoint the source. Option A is wrong: read replicas offload read traffic but do not diagnose CPU issues. Option C is wrong: increasing instance size is a remediation, not a diagnostic step. Option D is wrong: changing to a burstable instance class is also a remediation, not diagnostic.

Answer

Create a read replica to offload read traffic

Answer

Increase the instance size to handle the load

Answer

Modify the DB instance class to a burstable type

Question 10

An Amazon DynamoDB table is experiencing throttled write requests. The table uses provisioned capacity with auto-scaling enabled. Which THREE factors could contribute to throttling despite auto-scaling?

Accepted Answer

Auto-scaling maximum capacity is set too low. Auto-scaling can prevent throttling only if the maximum capacity is set appropriately and traffic patterns are predictable. Option B is correct because if the auto-scaling maximum capacity is set too low, the table cannot scale enough to handle the write demand. Option C is correct because auto-scaling reacts to sustained traffic but cannot instantly accommodate a sudden traffic spike that exceeds the maximum capacity. Option E is correct because even with auto-scaling, an uneven partition key distribution can cause a single partition to exceed its throughput capacity, leading to throttling. Option A is incorrect; a global secondary index with the same partition key does not inherently cause throttling on the base table. Option D is incorrect because eventually consistent reads affect read capacity, not write capacity, and do not cause write throttling.

Answer

Global secondary index is defined with same partition key

Answer

Use of eventually consistent reads

Question 11

A company uses Amazon RDS for PostgreSQL with Multi-AZ. The primary instance fails and a failover occurs. After failover, the application reports elevated write latency. Which TWO are possible causes?

Accepted Answer

The buffer pool is not warm on the new primary. After a Multi-AZ failover, the new primary instance starts with a cold buffer pool (no cached data blocks). PostgreSQL relies on shared buffers to cache frequently accessed data; without a warm cache, every read request must fetch data from disk, which increases I/O and write latency because writes often require reading the affected pages first. This is a known behavior in RDS for PostgreSQL after failover, and it resolves as the buffer pool warms up over time.

Answer

A read replica is now promoting to primary

Answer

The new primary has a smaller instance size

Answer

Automated backups are running on the new primary

Question 12

A company is running a production Amazon RDS for PostgreSQL database. The database has experienced a sudden spike in CPU utilization, causing application timeouts. The monitoring team needs to identify the root cause. Which AWS service or feature should be used to analyze the database load and identify the specific queries causing the high CPU?

Accepted Answer

Amazon RDS Performance Insights. (Amazon RDS Performance Insights) is correct because it provides a database performance tuning and monitoring feature that helps quickly assess the load on your database and identify specific queries causing high CPU utilization. Option A (Enhanced Monitoring) is wrong because it provides OS-level metrics, not database query details. Option B (Amazon CloudWatch Logs) is wrong because it captures database logs, not real-time performance data. Option D (AWS Trusted Advisor) is wrong because it provides best practice checks but not query-level analysis.

Answer

Enhanced Monitoring

Answer

Amazon CloudWatch Logs

Answer

AWS Trusted Advisor

Question 13

A company is using Amazon DynamoDB for a high-traffic application. The application is experiencing intermittent `ProvisionedThroughputExceededException` errors. The team has already increased the read and write capacity units multiple times but the errors persist. Which of the following is the MOST likely cause of the issue?

Accepted Answer

A hot key or uneven partition access pattern is causing throttling. Hot keys or uneven partition access patterns can cause throttling even if overall provisioned capacity appears sufficient. Option A is wrong because DynamoDB Accelerator (DAX) is an in-memory cache that reduces read load, but it does not directly fix capacity exceeded errors; misconfiguration might cause cache misses but not ProvisionedThroughputExceededException. Option B is wrong because Global Tables replication does not cause throttling on the source table; conflicts are handled by last-writer-wins. Option C is wrong because increasing capacity units multiple times without resolving the underlying access pattern suggests the issue is not simply insufficient capacity.

Answer

DynamoDB Accelerator (DAX) is not properly configured

Answer

The table is part of a DynamoDB Global Table and replication is causing conflicts

Answer

The provisioned capacity is not increased enough

Question 14

A database administrator notices that an Amazon RDS for MySQL instance's storage is filling up unexpectedly. The administrator has enabled automated backups and retains them for 7 days. Which of the following actions would help reduce storage consumption without losing the ability to perform point-in-time recovery?

Accepted Answer

Reduce the backup retention period to 1 day. Reducing the backup retention period reduces the amount of storage consumed by automated backup data, while still allowing point-in-time recovery for the duration of the retention period. Option A is incorrect because changing the instance class does not affect storage consumption. Option C is incorrect because deleting manual snapshots does not reduce the automated backup storage that is likely causing the unexpected filling, and manual snapshots are not necessary for point-in-time recovery. Option D is incorrect because disabling automated backups eliminates point-in-time recovery capability.

Answer

Modify the DB instance to a smaller instance class

Answer

Delete manual DB snapshots

Answer

Disable automated backups

Question 15

A company is using Amazon Redshift for data warehousing. The operations team notices that queries are running slower than usual. Which Amazon Redshift system view should be used to identify the queries that are consuming the most resources?

Accepted Answer

STL_QUERY. STL_QUERY (option B) is the correct system view because it stores detailed information about query execution, including resource consumption. This allows the operations team to identify which queries are consuming the most resources. The other options are incorrect: SVV_VACUUM_PROGRESS (option A) shows the progress of vacuum operations, not query performance. PG_TABLE_DEF (option C) shows table definitions. STV_TBL_PERM (option D) shows table permissions, not query resource usage.

Answer

SVV_VACUUM_PROGRESS

Answer

PG_TABLE_DEF

Answer

STV_TBL_PERM