DBS-C01 Practice Test 41 — 15 Questions

Question 1

A gaming company uses Amazon DynamoDB to store player profiles. Each profile is about 5 KB and is accessed frequently. The access pattern is mostly point reads by player ID. The company wants to reduce read costs while maintaining low latency. Currently, the table uses provisioned capacity with 3000 RCU. Which change would be MOST effective?

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

Accepted Answer

Use DynamoDB Accelerator (DAX) to cache frequently accessed items.. DynamoDB Accelerator (DAX) provides an in-memory cache that can serve frequently accessed items (like player profiles) with microsecond latency, reducing the number of read requests that hit the underlying table. Since each profile is 5 KB and accessed via point reads, DAX can absorb a significant portion of the read traffic, allowing you to lower provisioned RCU without sacrificing performance. This directly reduces read costs while maintaining low latency, making it the most effective solution.

Answer

Use strongly consistent reads instead of eventually consistent reads.

Answer

Switch from provisioned capacity to on-demand capacity mode.

Answer

Decrease the provisioned RCU to 2000 and rely on adaptive capacity.

Question 2

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.

Question 3

A company is using Amazon DynamoDB with auto scaling. The application is experiencing increased read latency. The monitoring shows that the ReadThrottleEvents metric is high. Which action should the company take to reduce read throttling?

Accepted Answer

Implement DynamoDB Accelerator (DAX) for caching.. DynamoDB Accelerator (DAX) provides an in-memory cache that reduces read latency and alleviates read throttling by serving frequently accessed items from cache, reducing the load on the underlying table. Option B is incorrect because switching to on-demand capacity mode may help with unpredictable traffic patterns but does not specifically address read throttling caused by high read demand; it can also increase costs. Option C is incorrect because enabling DynamoDB Streams does not directly reduce read throttling and may add overhead. Option D is incorrect because increasing write capacity units does not affect read throttling since read and write capacities are separate.

Answer

Switch the table to on-demand capacity mode.

Answer

Enable DynamoDB Streams on the table.

Answer

Increase the write capacity units.

Question 4

Which TWO metrics should be monitored together to detect a memory leak in an Amazon RDS for Oracle DB instance? (Choose TWO.)

Accepted Answer

FreeableMemory. Options A and B are correct. FreeableMemory shows the amount of available memory, and SwapUsage indicates the amount of swap space used. A memory leak causes increasing memory consumption, leading to swapping when free memory is exhausted. Monitoring both metrics together helps detect this pattern. Option C (ReadIOPS) is an I/O metric, not directly memory-related. Option D (DatabaseConnections) is a connection metric, unrelated to memory leak detection. Option E (NetworkThroughput) is a network metric, also not relevant.

Answer

ReadIOPS

Answer

DatabaseConnections

Answer

NetworkThroughput

Question 5

Which TWO of the following are valid methods to secure data at rest for an Amazon RDS for MySQL DB instance?

Accepted Answer

Enable encryption at rest using AWS KMS.. (encryption at rest using AWS KMS) is correct because Amazon RDS for MySQL supports encryption at rest using AWS KMS, which encrypts the underlying storage and automated backups. Option C is incorrect because there is no '--enable-encryption' flag in the AWS CLI; the correct parameter to enable encryption during instance creation is '--storage-encrypted'. Therefore, option C does not represent a valid method. Option A is incorrect because SSL/TLS secures data in transit, not at rest. Option D is incorrect because Transparent Data Encryption (TDE) is not supported for MySQL on RDS; it is available for Oracle and SQL Server. Option E is incorrect because Amazon RDS encryption is applied at the storage level, not the table level.

Answer

Enable SSL/TLS for connections to the DB instance.

Answer

Use the '--enable-encryption' flag when creating the DB instance.

Answer

Implement Transparent Data Encryption (TDE) using Oracle-compatible settings.

Answer

Use Amazon RDS encryption at the table level using the ENCRYPT option.

Question 6

A database administrator needs to audit all SQL queries executed on an Amazon RDS for PostgreSQL instance, including SELECT statements. Which two most efficient ways to achieve this?

Accepted Answer

Install the pgAudit extension and configure it to log all statements.. The pgAudit extension for PostgreSQL can be installed on RDS and configured to log all SQL statements, including SELECT queries. Option C is also correct because configuring the DB instance to export logs to Amazon CloudWatch Logs, when combined with enabling statement logging via the RDS parameter group (e.g., setting log_statement = 'all'), allows centralized log management and analysis, effectively auditing all queries. Option A is wrong because AWS CloudTrail does not capture SQL query content; it logs API actions on the RDS instance itself. Option D is wrong because Enhanced Monitoring provides OS-level metrics, not SQL query logs. Therefore, both B and C are correct.

Answer

Enable AWS CloudTrail for the RDS instance.

Answer

Enable Enhanced Monitoring for the DB instance.

Question 7

A company is using Amazon DynamoDB with on-demand capacity mode. The application experiences occasional throttling during peak hours. The operations team wants to reduce throttling without changing the application code. What should they do?

Accepted Answer

Switch to provisioned capacity mode and configure auto scaling.. DynamoDB on-demand capacity mode does not allow manual adjustment of capacity units; it scales automatically but can still throttle if traffic exceeds the previous peak by a large margin. Switching to provisioned capacity mode with auto scaling allows you to set a higher minimum capacity and scale proactively based on actual usage patterns, reducing throttling without code changes. This approach gives more control over capacity limits while still automating adjustments.

Answer

Increase the read and write capacity units in the on-demand mode.

Answer

Enable DynamoDB Accelerator (DAX) to cache reads.

Answer

Use DynamoDB global tables to distribute traffic across regions.

Question 8

A company runs an Amazon Aurora MySQL database cluster with one writer and one reader instance. The application experiences intermittent connection timeouts during peak traffic. The DB cluster parameter group has 'connect_timeout' set to 5 seconds. What should a database specialist recommend to reduce connection timeouts?

Accepted Answer

Enable RDS Proxy for the cluster.. Enabling RDS Proxy reduces connection overhead and provides a connection pool, mitigating timeouts. Option A is incorrect because adding readers does not help with writer connection timeouts; the issue is with the writer instance. Option C is incorrect because increasing connect_timeout only delays the timeout, not the root cause. Option D is incorrect because the issue is not related to TLS.

Answer

Add additional reader instances to distribute the load.

Answer

Increase the 'connect_timeout' parameter to 10 seconds.

Answer

Enable IAM database authentication and require TLS.

Question 9

A startup is using Amazon ElastiCache for Redis to cache session data. They deployed a single Redis node (cache.t3.micro) in us-west-2. The application reports high latency when reading session data. CloudWatch metrics show CPUUtilization at 90% and Evictions at 100 per minute. The cache hit ratio is 80%. The database specialist suspects the node is overloaded. What should the specialist do to improve performance?

Accepted Answer

Scale up to a larger node type, such as cache.m5.large.. Scale up to a larger node type, such as cache.m5.large. The current node (cache.t3.micro) is overloaded, as indicated by high CPU utilization (90%) and frequent evictions (100/min). Scaling up provides more CPU and memory resources, reducing evictions and lowering latency. Option B (add a read replica) does not help because the issue is on the primary node; read replicas are for scaling read-heavy workloads on a primary, but here the primary is overloaded. Option C (enable cluster mode) is not suitable for a single-node setup and adds complexity; it is intended for partitioning data across multiple shards. Option D (decrease TTL) would reduce memory usage but may increase cache misses and does not address the CPU bottleneck; it could actually worsen performance by requiring more database reads.

Answer

Add a read replica to offload read traffic.

Answer

Enable cluster mode and add more shards.

Answer

Decrease the TTL for session keys to reduce memory usage.

Question 10

A data warehouse team is migrating from Amazon Redshift to Amazon Redshift RA3 nodes. The current cluster uses 10 DC2.large nodes. The new cluster will use 4 RA3.xlarge nodes. After the migration, the team notices that query performance is significantly slower. Which factor is the MOST likely cause of the performance degradation?

Accepted Answer

The cluster has fewer nodes, reducing parallelism.. Reducing the number of nodes from 10 to 4 decreases the parallelism, even though RA3 nodes have more compute capacity per node. Redshift distributes data across slices, and each node has multiple slices. With fewer nodes, the total number of slices is lower, reducing the degree of parallelism for query execution, which can lead to slower performance for large queries. Option A is incorrect because the distribution style (EVEN vs KEY) affects data distribution but is not the most likely cause here; the question does not indicate a change in distribution style. Option B is incorrect because RA3 nodes use managed storage with ample capacity; disk space is not constrained. Option D is incorrect because RA3 nodes are optimized for large datasets; the issue is not the node type but the reduction in parallelism due to fewer nodes.

Answer

The data distribution style is set to EVEN instead of KEY.

Answer

The cluster does not have enough disk space for the workload.

Answer

RA3 nodes are not optimized for large datasets.

Question 11

A retail company uses Amazon RDS for PostgreSQL as the backend for its e-commerce platform. During a flash sale, the database experienced high CPU utilization and increased the number of active connections. The application team reported that some queries timed out. The database specialist reviewed the slow query log and found that several queries were performing sequential scans on large tables due to missing indexes. The specialist created the necessary indexes, but the issue persists for some queries. Upon further investigation, the specialist notices that the query planner is still choosing sequential scans for some queries. What should the database specialist do to ensure the query planner uses the indexes?

Accepted Answer

Run the ANALYZE command to update table statistics.. Running ANALYZE updates the table statistics used by the query planner, allowing it to make informed decisions about index usage. Without updated statistics, the planner may still choose sequential scans even after indexes are created. Option A is incorrect because increasing maintenance_work_mem speeds up index creation but does not affect query planning. Option B is incorrect because decreasing random_page_cost might make indexes more attractive, but it is a global setting that could have unintended consequences and does not address the root cause of stale statistics. Option D is incorrect because disabling sequential scans (enable_seqscan=off) forces index usage but can lead to suboptimal plans, especially if the index is not the most efficient access method.

Answer

Increase maintenance_work_mem to speed up index creation.

Answer

Decrease the random_page_cost to make indexes more attractive.

Answer

Set enable_seqscan to off to force index usage.

Question 12

A company is running an Amazon RDS for MySQL DB instance. The database performance has degraded over time, and the company suspects that slow queries are the cause. Which AWS service should the company use to identify the slow queries and analyze the database performance?

Accepted Answer

Amazon RDS Performance Insights. Performance Insights provides a dashboard to analyze database performance and identify slow queries. AWS Trusted Advisor (A) provides best-practice checks, not query analysis. Amazon RDS Enhanced Monitoring (B) provides OS metrics, not query details. Amazon CloudWatch Logs (C) is for logs, not query analysis.

Answer

AWS Trusted Advisor

Answer

Amazon RDS Enhanced Monitoring

Answer

Amazon CloudWatch Logs

Question 13

A company uses Amazon DynamoDB with provisioned capacity for a critical application. During a traffic spike, the table experiences throttling on write requests. The DBA needs to resolve the issue quickly. Which THREE actions should the DBA take? (Choose THREE.)

Accepted Answer

Implement exponential backoff in the application's write requests.. Uses exponential backoff to handle throttling by retrying requests with increasing delays. Option C temporarily increases write capacity units (WCU) to handle the spike. Option D enables auto scaling to automatically adjust capacity. Option A is incorrect because switching to on-demand may resolve throttling but is not one of the three correct actions; the question asks for three specific actions, and B, C, D are the correct combination. Option E is wrong because DAX is a caching layer for reads, not writes, and does not resolve write throttling.

Answer

Switch the table to on-demand capacity mode.

Answer

Enable DynamoDB Accelerator (DAX) to cache writes.

Question 14

A company uses Amazon DynamoDB for a highly transactional application. The application is experiencing increased latency and throttled requests. The operations team notices that the DynamoDB table's read and write capacity utilization is consistently near 100%. The table uses on-demand capacity mode. What is the MOST likely cause of the throttling?

Accepted Answer

The table has reached the per-table throughput limit for on-demand mode.. On-demand DynamoDB tables have a per-table throughput limit (e.g., 40,000 read/write units per second). When sustained traffic exceeds this limit, requests are throttled. Option B is incorrect because global table replication does not cause throttling; it replicates writes asynchronously. Option C is incorrect because DynamoDB Accelerator (DAX) is a read cache that reduces latency, but throttling still occurs if the table itself reaches its throughput limit. Option D is incorrect because adaptive capacity automatically handles hot partitions by splitting them; however, the primary cause here is hitting the on-demand throughput limit, not a partition design issue.

Answer

The table is configured as a global table and cross-region replication is causing write conflicts.

Answer

The application is not using DynamoDB Accelerator (DAX) to cache reads.

Answer

The table's partition key design is causing hot partitions, and adaptive capacity is not enabled.

Question 15

An RDS DB instance has two security groups attached. Security group sg-12345678 allows inbound traffic on port 3306 from 0.0.0.0/0. Security group sg-87654321 allows inbound traffic on port 3306 from 10.0.0.0/16. What is the effective inbound access to the DB instance?

Accepted Answer

All IP addresses (0.0.0.0/0) are allowed to connect.. When multiple security groups are attached to an RDS instance, the rules are combined, and the most permissive inbound rule applies. Security group sg-12345678 allows all IP addresses (0.0.0.0/0), so the effective inbound access is from all IPs. Option A is wrong because the rules do not conflict; they are additive. Option B is wrong because the more restrictive rule does not override the more permissive one. Option C is wrong because the less restrictive rule (0.0.0.0/0) applies, not just the 10.0.0.0/16 range.

Answer

No IP addresses are allowed because the rules conflict.

Answer

Only the 0.0.0.0/0 range is allowed because sg-12345678 is more permissive.

Answer

Only the 10.0.0.0/16 range is allowed because sg-87654321 is more restrictive.