DBS-C01 Monitoring and Troubleshooting Practice Test 20 — 15 Questions

Question 1

A company is using Amazon DynamoDB with global tables. The application is experiencing high write latency in one region. Which THREE factors could contribute to this issue? (Choose three.)

Accepted Answer

Replication lag from global tables causing write conflicts.. Option A (network latency), Option C (throttling due to insufficient write capacity), and Option D (replication lag) are correct. Option B is wrong because auto scaling doesn't increase latency; it adds capacity. Option E is wrong because read capacity affects reads, not writes.

Answer

Insufficient read capacity units provisioned for the table.

Answer

The table's auto scaling configuration is set to increase write capacity too aggressively.

Question 2

A database administrator needs to monitor the free storage space on an Amazon RDS for SQL Server instance. Which TWO CloudWatch metrics should be used? (Choose two.)

Accepted Answer

FreeStorageSpaceInPercent. Option A (FreeStorageSpace) and Option D (FreeStorageSpaceInPercent) are correct. Option B is wrong because BinLogDiskUsage is for MySQL. Option C is wrong because DatabaseConnections is connections. Option E is wrong because ReadLatency is for read operations.

Answer

DatabaseConnections

Answer

ReadLatency

Answer

BinLogDiskUsage

Question 3

A company runs an e-commerce platform using Amazon Aurora MySQL with Multi-AZ deployment. The application has a read-heavy workload and uses a mix of SELECT and UPDATE queries. Recently, the company migrated from a db.r5.large to a db.r5.2xlarge instance class to handle increased traffic. However, after the migration, the CPU utilization remains high during peak hours, and the application's page load times have increased. The DBA notices that the 'Read IOPS' metric is high, but the 'Read Latency' metric is low. There is also a high number of 'Select' queries in the database. The application uses a single database endpoint. What should the DBA do to reduce CPU utilization and improve read performance?

Accepted Answer

Create one or more Aurora Replicas and modify the application to use read-only endpoints for SELECT queries.. Option C is correct because creating read replicas offloads SELECT queries from the primary, reducing CPU. Option A is wrong because increasing instance size again may not be cost-effective and the issue is read-heavy. Option B is wrong because enabling Performance Insights only helps monitoring, not performance. Option D is wrong because Multi-AZ is for failover, not read scaling.

Answer

Enable Multi-AZ with one standby replica.

Answer

Enable Performance Insights and analyze the top SQL.

Answer

Upgrade the instance class to db.r5.4xlarge.

Question 4

A startup is using Amazon DynamoDB for a gaming leaderboard. The table has a partition key of 'game_id' and a sort key of 'score'. The application frequently queries the top 10 scores for a given game. Recently, users have reported that the leaderboard is showing stale data. The DBA checks the CloudWatch metrics and sees no throttling. The table has auto scaling enabled. The application uses eventual consistent reads. The DBA suspects that the issue is related to write conflicts. What should the DBA do to ensure the leaderboard shows the most recent data?

Accepted Answer

Modify the application to use strongly consistent reads for leaderboard queries.. Option B is correct because using strongly consistent reads ensures the latest data is read. Option A is wrong because increasing WCU does not affect consistency. Option C is wrong because DAX caches data and may serve stale data. Option D is wrong because DynamoDB Streams are for change data capture, not consistency.

Answer

Enable DynamoDB Streams and process updates in near-real-time.

Answer

Enable DynamoDB Accelerator (DAX) for caching.

Answer

Increase the write capacity units to reduce write throttling.

Question 5

A company has an Amazon RDS for SQL Server database that stores customer orders. The database is running on a db.m5.large instance. Recently, the DBA noticed that the 'Write IOPS' metric is consistently high during business hours, and the 'Write Latency' metric is also elevated. The application is experiencing slow order placement. The DBA checks the disk queue depth and finds it to be high. The database uses General Purpose SSD (gp2) storage with 500 GB. What should the DBA do to improve write performance?

Accepted Answer

Migrate to Provisioned IOPS (io2) storage with appropriate IOPS.. Option C is correct because Provisioned IOPS (io2) provides consistent low latency. Option A is wrong because gp3 may not provide enough IOPS for the workload. Option B is wrong because increasing storage size increases baseline IOPS for gp2, but 500 GB already gives 1500 IOPS; more IOPS may be needed. Option D is wrong because Multi-AZ does not improve write performance; it may increase latency.

Answer

Enable Multi-AZ to offload writes to standby.

Answer

Change the storage type to gp3 and increase the IOPS.

Answer

Increase the storage size to 1000 GB to get more baseline IOPS.

Question 6

A company is using Amazon DynamoDB with auto scaling for a social media application. The table has a partition key of 'user_id'. The application performs many small writes (update user profile) and reads (fetch user profile). Recently, the application's response time has increased. The DBA checks CloudWatch and sees that 'ConsumedWriteCapacityUnits' is close to 'ProvisionedWriteCapacityUnits', and 'WriteThrottleEvents' is low. However, 'ReadThrottleEvents' is high. The table has 1000 WCU and 1000 RCU provisioned. The auto scaling is configured to add capacity when utilization exceeds 70%. The DBA also notices that 'ReadThrottleEvents' spikes during peak hours. What should the DBA do to reduce read throttling?

Accepted Answer

Increase the provisioned read capacity to 2000 RCU or implement DAX caching.. Option D is correct because increasing RCU or using DAX can reduce read throttling. Option A is wrong because auto scaling target should be 70%, not 90%. Option B is wrong because decreasing WCU doesn't help reads. Option C is wrong because GP2 is for RDS, not DynamoDB.

Answer

Decrease the provisioned write capacity to 500 WCU to free up resources.

Answer

Increase the auto scaling target utilization to 90% to allow more headroom.

Answer

Change the storage type to General Purpose SSD (gp2) to improve I/O.

Question 7

A company has an Amazon RDS for PostgreSQL database that is experiencing intermittent connection timeouts. The application logs show 'FATAL: remaining connection slots are reserved for non-replication superuser connections'. The database has a max_connections parameter set to 200. The application uses a connection pool. The DBA checks the CloudWatch metric 'DatabaseConnections' and sees it at 195 during peak hours. The application is deployed on AWS Lambda with a provisioned concurrency of 100. The Lambda function creates a new connection for each invocation. What should the DBA do to resolve the issue?

Accepted Answer

Set up Amazon RDS Proxy to manage the database connections from Lambda.. Option A is correct because the Lambda function creates new connections, exhausting the pool. Using RDS Proxy manages connections efficiently. Option B is wrong because increasing max_connections may cause resource contention. Option C is wrong because reducing provisioned concurrency may not solve the root cause. Option D is wrong because decreasing max_connections would worsen the issue.

Answer

Reduce the Lambda provisioned concurrency to 50.

Answer

Increase max_connections to 500 to accommodate more connections.

Answer

Decrease max_connections to 100 to reserve more slots.

Question 8

A company runs a production Amazon RDS for PostgreSQL Multi-AZ DB instance (db.r5.large) with 500 GB of General Purpose SSD (gp2) storage. The application experiences intermittent latency spikes every 15 minutes. Monitoring shows that during these spikes, the ReadIOPS metric on the primary instance spikes to 5,000 IOPS (the baseline is 1,500 IOPS), and the BurstBalance drops from 100% to 20% then recovers. There is no increase in CPU or connections. The application uses connection pooling with pgBouncer on an EC2 instance. The team has verified that no long-running queries or index scans are causing the spikes. Which action is MOST likely to resolve the intermittent latency?

Accepted Answer

Migrate the storage to gp3 with a baseline of 3,000 IOPS and 125 MB/s throughput.. Option B is correct because the burst balance dropping indicates the gp2 volume is exhausting its burst credits. The baseline IOPS for a 500 GB gp2 volume is 1,500 IOPS, but the spikes reach 5,000 IOPS, burning credits. Converting to gp3 provides a baseline of 3,000 IOPS (or more) without burst credits, eliminating the burst balance issue. Option A increases volume size but does not change the burst behavior (larger gp2 still uses credits and needs even more IOPS). Option C adds read replicas but the issue is on the primary write instance. Option D increases instance size but the metric shows no CPU or connection bottleneck; the bottleneck is storage IOPS credit exhaustion.

Answer

Create a read replica and redirect read traffic to it.

Answer

Increase the DB instance to db.r5.xlarge to improve CPU and network performance.

Answer

Scale the storage to 1,000 GB to increase baseline IOPS and burst credits.

Question 9

A company uses Amazon DynamoDB to store sensor data from IoT devices. The table has a partition key of DeviceID (String) and a sort key of Timestamp (Number). The table is configured with provisioned capacity of 1000 read capacity units (RCUs) and 500 write capacity units (WCUs). Auto Scaling is enabled with target utilization of 70% and is working correctly. Recently, a new batch job was introduced that performs Scan operations on the entire table every hour. The Scan consumes many read capacity units and causes throttling of the sensor write requests. The team wants to minimize the impact on the write-heavy sensor ingestion. Which approach is BEST?

Accepted Answer

Enable DAX (DynamoDB Accelerator) to cache Scan results and reduce read consumption on the table.. Option C is correct because enabling DynamoDB Accelerator (DAX) provides an in-memory cache for reads, which reduces the read load on the table itself. Since the Scan still consumes read capacity, caching can absorb some of the read traffic and free up RCUs for other operations, but more importantly, the team should also consider other measures. However, among the options, DAX is the best to reduce read load on the table. Option A is incorrect because increasing write capacity does not address the read throttling; it just increases cost. Option B is incorrect because reducing Scan frequency may not be acceptable for the batch job. Option D is incorrect because changing to on-demand may eliminate throttling but will be more expensive for this predictable workload and does not leverage existing provisioned capacity.

Answer

Increase the provisioned write capacity to 2000 WCUs to handle bursts.

Answer

Schedule the Scan to run during off-peak hours when sensor writes are lower.

Answer

Switch the table to on-demand capacity mode to eliminate throttling.

Question 10

A company runs a self-managed Redis cluster on Amazon EC2 for caching. The cluster has one primary and two replicas, each on c5.large instances. The application experiences high latency during peak hours. CloudWatch metrics show that the primary node's CPU utilization is consistently above 80% and the network bandwidth is near the instance limit. The replicas show moderate CPU usage. The team wants to reduce latency without increasing cost significantly. Which combination of actions should the team take? (Choose two.)

Accepted Answer

Enable Redis Cluster Mode and distribute data across multiple shards.. Option A and Option C are correct. Option A: Enabling Cluster Mode allows sharding data across multiple nodes, reducing load on each node. Option C: Using an ElastiCache Redis cluster with Cluster Mode enabled provides managed scaling and reduces the operational burden. Option B is incorrect because it increases cost (more instances) and does not address vertical scaling limits. Option D is incorrect because using larger instances (vertical scaling) increases cost significantly and may still hit network limits. Option E is incorrect because read replicas help with read scaling, but the primary is the bottleneck for writes and CPU.

Answer

Add more EC2 instances as additional replicas to offload reads.

Answer

Configure the application to read from replica nodes.

Answer

Upgrade the primary to a c5.2xlarge instance type.

Question 11

A company uses Amazon Aurora MySQL for its e-commerce platform. The DB cluster has one writer and two readers. Recently, the application started showing occasional deadlock errors during order processing. The error logs show: 'Transaction (Process ID 123) was deadlocked on lock resources with another process and has been chosen as the deadlock victim. Rerun the transaction.' The application retries three times before failing. The development team wants to reduce the likelihood of deadlocks. Which three actions should the team take? (Choose three.)

Accepted Answer

Shorten the duration of transactions by committing frequently.. Options A, C, and D are correct. Option A: Reducing transaction duration minimizes the window for lock conflicts. Option C: Accessing tables in a consistent order avoids cycle dependencies. Option D: Using READ COMMITTED reduces shared locks for reads. Option B is incorrect because increasing retries does not prevent deadlocks; it only delays failure. Option E is incorrect because lowering isolation level to READ UNCOMMITTED can cause dirty reads and is not recommended for e-commerce.

Answer

Switch to READ UNCOMMITTED isolation level to reduce locking.

Answer

Increase the number of retry attempts to 10.

Question 12

A company uses Amazon DocumentDB (with MongoDB compatibility) for its content management system. The application runs on EC2 instances and connects to a DocumentDB cluster with one instance (db.r5.large). Recently, users reported that retrieving documents takes longer than usual. CloudWatch metrics show that the CPU utilization of the DocumentDB instance is at 90% and the freeable memory is below 100 MB. The team has verified that no query optimization is possible. Which action should the team take FIRST to improve performance?

Accepted Answer

Scale up the instance to db.r5.xlarge.. Option B is correct because the high CPU and low memory indicate the instance is overworked. Scaling up to a larger instance provides more CPU and memory resources. Option A is incorrect because adding a reader instance helps with read scaling but does not reduce CPU/memory pressure on the primary writer. Option C is incorrect because creating an index may improve query performance but the team already ruled out query optimization. Option D is incorrect because increasing storage does not directly affect CPU or memory.

Answer

Add a read replica instance to offload read traffic.

Answer

Create additional indexes on frequently queried fields.

Answer

Increase the storage volume size to improve I/O performance.

Question 13

A company runs a critical MySQL database on Amazon RDS Single-AZ (db.m5.large) with 200 GB of Provisioned IOPS (io1) storage set to 3000 IOPS. The application team reports that write operations are occasionally slow. CloudWatch metrics show that the Write IOPS metric peaks at 3500 IOPS during the slowdowns, but the average is 2000 IOPS. The Read IOPS average is 500 IOPS. The queue depth metric occasionally spikes to 20. The storage configuration includes a 50 GB General Purpose SSD (gp2) log volume attached to the same RDS instance. Which change will MOST effectively resolve the write latency?

Accepted Answer

Increase the provisioned IOPS on the io1 volume to 4000.. Option C is correct because the io1 volume is provisioned at 3000 IOPS, but the workload bursts to 3500 IOPS, causing queue depth to spike. Increasing the provisioned IOPS to 4000 ensures that the volume can handle the peak without queuing. Option A is incorrect because enabling Multi-AZ provides high availability but does not increase IOPS capacity. Option B is incorrect because moving to gp3 does not guarantee better performance; gp3 baseline is 3000 IOPS (same as current provisioned) but can burst to higher, but the issue is consistent peaks. However, the most direct fix is to increase io1 provisioned IOPS. Option D is incorrect because the log volume is separate and not the source of write IOPS contention.

Answer

Change the storage type to gp3 with 3000 baseline IOPS.

Answer

Move the log volume to the same io1 volume to reduce I/O overhead.

Answer

Enable Multi-AZ for failover protection.

Question 14

A company uses Amazon DynamoDB Global Tables for a multi-region application. The table is configured with on-demand capacity. The application writes data in the us-east-1 region and reads from us-west-2. Users in us-west-2 report that data written in us-east-1 is not appearing in us-west-2 within the expected replication latency of under 5 seconds. Instead, replication sometimes takes up to 30 seconds. Which two factors could be causing this increased replication latency? (Choose two.)

Accepted Answer

High network latency or packet loss between us-east-1 and us-west-2.. Options B and C are correct. Option B: Network latency between regions directly affects replication time. Option C: Large write volumes can cause backpressure on the replication stream. Option A is incorrect because on-demand capacity does not throttle writes; it scales automatically. Option D is incorrect because Global Tables replicate all data to all regions; us-west-2 must receive all writes. Option E is incorrect because read capacity on a replica does not affect replication; replication uses write capacity in the replica region.

Answer

The application is reading from the us-west-2 table before replication completes.

Answer

The read capacity in us-west-2 is insufficient, causing read throttling.

Answer

The on-demand capacity mode is causing write throttling in us-east-1.

Question 15

A company runs a PostgreSQL database on an Amazon RDS DB instance (db.t3.medium) with 100 GB of General Purpose SSD (gp2) storage. The database is used by a web application that experiences occasional slowdowns. CloudWatch metrics show that the BurstBalance metric for the storage volume drops to 0% during peak usage and then recovers. The average IOPS during peak is 600, and the baseline IOPS for the volume is 300. The team needs a cost-effective solution to eliminate the performance issues. What should the team do?

Accepted Answer

Migrate the storage to gp3 with 3000 baseline IOPS.. Option B is correct because converting to gp3 provides a consistent baseline of 3000 IOPS (or 3000 if using the default 3000 IOPS, though for 100 GB the baseline is 3000) without burst credits, eliminating the burst balance problem. Option A is incorrect because increasing gp2 volume size to 200 GB increases baseline to 600 IOPS and burst credits, but still relies on credits; the workload may still exceed baseline. Option C is incorrect because increasing instance size does not affect storage performance. Option D is incorrect because enabling Performance Insights does not improve performance.

Answer

Upgrade the DB instance to db.t3.large.

Answer

Increase the gp2 volume size to 200 GB.

Answer

Enable Performance Insights to monitor database load.