DBS-C01 Management and Operations Practice Test 8 — 15 Questions

Question 1

A company is using Amazon ElastiCache for Redis as a caching layer for a high-traffic web application. The cache hit ratio has dropped from 95% to 70% after a recent deployment that changed the cache key structure. The application team wants to improve the hit ratio without increasing the cache memory. Which action should they take?

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

Accepted Answer

Implement a consistent hashing algorithm for key distribution.. A drop in cache hit ratio after changing the key structure indicates that the new keys are not being distributed evenly across the cluster nodes, causing some nodes to be overloaded with misses. Implementing a consistent hashing algorithm (e.g., using the Redis Cluster hash slot mechanism or a client-side library like libketama) ensures that keys are distributed uniformly across shards, minimizing cache misses and improving the hit ratio without adding memory.

Answer

Disable Cluster Mode and use a single node.

Answer

Increase the TTL (time-to-live) for all cache keys.

Answer

Use random TTLs to spread out expiration times.

Question 2

A company has an Amazon DynamoDB table that stores IoT sensor data. The table has a partition key of device_id and a sort key of timestamp. The team wants to efficiently retrieve the latest reading for each device. Which query pattern should be used?

Accepted Answer

Query with ScanIndexForward=false and Limit=1. Setting ScanIndexForward=false on a Query returns items in descending sort-key order. By querying with the device_id as the partition key and limiting results to 1, you retrieve the most recent timestamp for that device efficiently without scanning the entire table.

Answer

Scan with FilterExpression to get the latest timestamp for each device

Answer

Query with ScanIndexForward=true and Limit=1

Answer

GetItem with the device_id and timestamp values

Question 3

A company is migrating a PostgreSQL database to Amazon Aurora PostgreSQL. The database has a large table that is frequently accessed. The team wants to minimize downtime during the migration. Which TWO strategies should be used together?

Accepted Answer

Use AWS DMS to create a target Aurora DB cluster and replicate data.. AWS DMS can perform a full load of the source PostgreSQL database to Aurora and then set up ongoing change data capture (CDC) replication to apply incremental changes, minimizing downtime by allowing the source to remain operational until cutover. Option A is correct because DMS can create and manage the target Aurora cluster as part of the replication task, while option D is correct because the combination of full load plus ongoing replication is the standard approach for near-zero downtime migrations.

Answer

Take a manual snapshot of the source database and restore it to Aurora.

Answer

Use AWS Schema Conversion Tool (AWS SCT) to convert the schema.

Answer

Configure Aurora as a read replica of the PostgreSQL instance.

Question 4

A company is using Amazon DynamoDB with provisioned capacity. The table's read capacity is consistently underutilized, but the write capacity is frequently maxed out. The team wants to optimize costs while maintaining performance. Which TWO actions should be taken?

Accepted Answer

Use DynamoDB Auto Scaling for write capacity.. The correct answers are C and E. DynamoDB Auto Scaling for write capacity (C) dynamically adjusts the provisioned write capacity based on traffic, preventing throttling during spikes without over-provisioning. Reducing provisioned read capacity (E) to match actual usage saves costs because reads are underutilized. Option A (on-demand) can be more expensive for predictable workloads, and Auto Scaling is often more cost-effective. Option B (DAX) offloads reads, not writes, so it does not address the write bottleneck. Option D (increasing provisioned writes) would raise costs without dynamic scaling, as capacity would remain high even when not needed.

Answer

Switch the table to on-demand capacity mode.

Answer

Enable DynamoDB Accelerator (DAX) to offload reads.

Answer

Increase the provisioned write capacity to handle spikes.

Question 5

The exhibit shows the output of an AWS CLI command for an Amazon RDS DB instance. Based on the output, what is the current configuration of the DB instance?

Accepted Answer

It is a Single-AZ MySQL DB instance.. The output shows engine=mysql, MultiAZ=false, SecondaryAvailabilityZone=null, and DBInstanceStatus=available. This indicates a Single-AZ MySQL DB instance, not a Multi-AZ deployment, not Aurora, and not in a failed state. Therefore, option D is correct.

Answer

It is an Amazon Aurora MySQL-Compatible DB cluster.

Answer

It is a MySQL DB instance that is currently in a failed state.

Answer

It is a Multi-AZ DB instance with a standby in a different AZ.

Question 6

The exhibit shows an IAM policy attached to a user. The user needs to create a manual snapshot of an RDS DB instance named 'production-db'. Which action will the user be able to perform?

Accepted Answer

Create a manual snapshot of 'production-db' with the name 'mydb-production-snapshot'.. The IAM policy allows CreateDBSnapshot only on DB instances with names starting with 'mydb-', and the snapshot name must also match the pattern 'mydb-*'. The snapshot name 'mydb-production-snapshot' satisfies that pattern. Option A is wrong because 'production-db-snapshot' does not start with 'mydb-'. Option C is wrong because the question asks about creating a snapshot, not describing instances. Option D is wrong because the policy does not grant DeleteDBInstance permission.

Answer

Create a manual snapshot of 'production-db' with the name 'production-db-snapshot'.

Answer

Describe the 'production-db' DB instance.

Answer

Delete the 'production-db' DB instance.

Question 7

The exhibit shows the output of a MySQL command run on an Amazon RDS for MySQL DB instance. The database is experiencing frequent checkpointing that is causing I/O spikes. The parameter innodb_log_file_size is currently 256 MB. Which change should be made to reduce checkpoint frequency?

Accepted Answer

Increase the value of innodb_log_file_size to 1 GB.. Increasing innodb_log_file_size reduces checkpoint frequency by allowing more transactions to be logged before a checkpoint is forced. Option A is wrong because decreasing the log file size would increase checkpoint frequency. Option B is wrong because innodb_flush_log_at_trx_commit controls write-ahead logging durability, not checkpoint frequency. Option D is wrong because innodb_buffer_pool_size affects caching and memory, but does not directly reduce checkpoint frequency.

Answer

Decrease the value of innodb_log_file_size to 128 MB.

Answer

Set innodb_flush_log_at_trx_commit to 0.

Answer

Increase the value of innodb_buffer_pool_size.

Question 8

A company is running an Amazon RDS for PostgreSQL DB instance with Multi-AZ. The database experiences a failover during a maintenance window. After the failover, the application connection pool continues to use the old primary endpoint, causing connection errors. What is the BEST way to ensure application connections automatically redirect to the new primary after a failover?

Accepted Answer

Use the RDS endpoint (CNAME) provided by RDS, which automatically points to the primary instance.. The RDS endpoint (CNAME) provided by Amazon RDS automatically points to the current primary instance. After a failover, RDS updates the CNAME record to point to the new primary, so application connections using the endpoint are seamlessly redirected without manual intervention. This is the simplest and most reliable approach. Option B (Custom Route 53 failover routing) is unnecessary because RDS already provides a managed DNS endpoint. Option C (modifying connection string manually) is not automated and prone to human error. Option D (static IP) is not practical as RDS instances do not have static IPs; the DNS endpoint handles failover transparently.

Answer

Create a custom Route 53 failover routing policy pointing to both DB instances.

Answer

Modify the application connection string to point to the new primary IP address after each failover.

Answer

Configure the application to use a static IP address of the primary instance.

Question 9

A company uses Amazon DynamoDB with on-demand capacity for a mobile application. During a marketing campaign, write traffic spikes to 10,000 writes per second for 5 minutes. The application experiences throttling after the first minute. The DynamoDB table has a single partition key. What should be done to prevent throttling in future campaigns?

Accepted Answer

Redesign the partition key to ensure write traffic is evenly distributed across partitions.. Throttling with on-demand capacity often results from a hot partition caused by a single partition key. On-demand capacity handles total throughput but still has per-partition throughput limits. Redesigning the partition key to distribute writes evenly across partitions resolves the hotspot. Option B is wrong because DAX is an in-memory cache for reads, not writes. Option C is wrong because switching to provisioned capacity with 10,000 WCUs would still hit partition-level limits if the partition key design is poor. Option D is wrong because pre-warming does not affect per-partition throughput ceilings.

Answer

Enable DynamoDB Accelerator (DAX) to cache write requests.

Answer

Switch to provisioned capacity and increase write capacity units to 10,000.

Answer

Pre-warm the table by writing dummy data before the campaign.

Question 10

A company is migrating an on-premises Oracle database to Amazon RDS for Oracle. The database is 2 TB in size and has a 100 Mbps internet connection. The migration must be completed within 3 days with minimal downtime. Which approach is MOST suitable?

Accepted Answer

Use AWS Database Migration Service (DMS) with a full load from an AWS Snowball device, then ongoing replication.. The 2 TB database cannot be fully loaded over a 100 Mbps internet connection within 3 days (theoretical max transfer ~2.6 TB in 3 days, but real-world throughput is lower due to overhead and contention). AWS Snowball provides a physical appliance to transfer the full load offline, bypassing bandwidth constraints, and then AWS DMS ongoing replication captures and applies changes with minimal downtime.

Answer

Export the database as a dump file, upload to S3, and restore to RDS.

Answer

Use AWS DMS with full load over the internet, then ongoing replication.

Answer

Create a VPN connection to AWS and use Oracle Data Pump over the VPN.

Question 11

A company runs an Amazon Redshift cluster with three nodes. The data warehouse team notices that some queries are slow due to high disk usage. The cluster has reached 80% storage capacity. What is the MOST cost-effective way to increase storage without interrupting operations?

Accepted Answer

Perform an elastic resize to change to a node type with larger storage per node.. Amazon Redshift's elastic resize operation allows you to change the node type to one with larger storage per node without downtime, and it completes in minutes. This is the most cost-effective approach for a cluster at 80% capacity, as it avoids the overhead of provisioning additional nodes or the longer downtime associated with classic resize, while directly addressing the high disk usage by increasing per-node storage.

Answer

Add one more node of the same type to the cluster.

Answer

Use classic resize to change to a node type with larger storage.

Answer

Create a second cluster and use Redshift Spectrum to offload queries.

Question 12

A company has an Amazon RDS for MySQL DB instance with automated backups enabled. The database is 500 GB in size. The company wants to create a new test database from the current state with minimal impact on production. Which approach meets these requirements?

Accepted Answer

Take a snapshot of the DB instance and restore it to a new instance.. Taking a snapshot of the RDS DB instance and restoring it to a new instance creates an independent copy of the database with minimal performance impact on the source. Snapshots are asynchronous and capture a consistent state without blocking writes, making this the most efficient method for creating a test database from the current production state.

Answer

Create a read replica and promote it to a standalone instance.

Answer

Use mysqldump to export the database and import into a new instance.

Answer

Create a manual DB snapshot from the automated backup and restore.

Question 13

A developer accidentally deleted a table in an Amazon RDS for PostgreSQL DB instance. The instance has automated backups enabled with a retention period of 7 days. The deletion occurred 2 hours ago. What is the quickest way to recover the table?

Accepted Answer

Perform a point-in-time recovery to a time just before the deletion.. Point-in-time recovery (PITR) allows restoring the RDS for PostgreSQL DB instance to any time within the 7-day backup retention period. Since the deletion occurred 2 hours ago, you can restore the instance to a time just before the deletion, then connect to the restored instance and extract the deleted table using pg_dump or similar tools. This is the quickest method because it does not require restoring a full snapshot and then applying transaction logs manually. Option B is incorrect because pg_dump cannot export a table that has already been deleted from the current instance. Option C is incorrect because automated backup files are not directly accessible as downloadable files from S3; they are used internally by RDS for PITR. Option D is incorrect because restoring from the latest automated snapshot would not recover the table if the snapshot was taken after the deletion, or if the snapshot includes the deletion state.

Answer

Use PostgreSQL pg_dump to connect and dump the table from the current instance.

Answer

Download the automated backup file from S3 and restore the table.

Answer

Restore the DB instance from the latest automated snapshot.

Question 14

A company uses Amazon DynamoDB with provisioned capacity for a gaming application. During a new game launch, write traffic spikes to 2x the provisioned write capacity for 30 minutes. Some writes are throttled. The company wants to handle these predictable spikes without manual intervention. What is the MOST cost-effective solution?

Accepted Answer

Enable DynamoDB auto scaling with a target utilization of 70%.. DynamoDB auto scaling automatically adjusts provisioned capacity based on actual usage, handling predictable spikes without manual intervention while minimizing cost by scaling down when demand drops. Option A is wrong because permanently doubling capacity leads to wasted resources and higher costs. Option B is wrong because on-demand mode can be more expensive for predictable workloads with consistent baseline traffic. Option D is wrong because SQS buffers writes but does not directly address DynamoDB write throttling; it adds latency and complexity without solving the capacity issue.

Answer

Increase the provisioned write capacity to 2x the baseline permanently.

Answer

Change the table to on-demand capacity mode.

Answer

Use Amazon SQS to buffer writes and process them later.

Question 15

An e-commerce company runs a multi-AZ deployment of Amazon RDS for MySQL. During a recent failover test, the application experienced a 30-second write outage. The application uses a connection pooling library. The DB instance has a 60-second TTL for DNS records. What is the MOST likely cause of the outage?

Accepted Answer

The connection pool had open connections to the old primary, and DNS TTL caused a delay in reconnecting to the new primary.. During a Multi-AZ failover, the RDS DNS record is automatically updated to point to the new primary. However, the application's connection pool may still have open connections to the old primary IP. Because the DNS TTL is 60 seconds, the client may continue to resolve to the old (cached) IP for up to 60 seconds, causing a write outage until connections are re-established to the new primary. Option B is incorrect because a cold start typically refers to an application starting from scratch, which is not the case here. Option C is incorrect because the DNS record is indeed updated after failover; the issue is client-side caching. Option D is incorrect because Multi-AZ failover usually completes within 1-2 minutes, but the outage duration is determined by DNS TTL and connection pooling behavior, not the failover time itself.

Answer

The application experienced a cold start after the failover.

Answer

The DNS record for the RDS endpoint was not updated after the failover.

Answer

The Multi-AZ failover took longer than 30 seconds to complete.